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*As Featured on NI.com Original Authors: Anthony Afonso, Thales UK Edited by Cyth Systems The Challenge Upgrading traditional methods of testing the rails used in the London underground system, which has traditionally been costly to revenue and time. The Solution Automating the testing of rails used in the London underground system and automating the communication of rail health and integrity with the use of virtual test trains (VTTs) created by using NI CompactRIO hardware and NI LabVIEW system design software. This is used to mimic an actual passenger train while saving vast amounts of time and money. History Traditional methods of testing railway systems require the use of a fully operational train and full closure of the track, usually for days at a time. The process is expensive, time-consuming to arrange, and inconvenient to the public. The automatic signaling system upgrade project for the Jubilee and Northern lines promised to boost capacity by 33 percent (the equivalent of carrying approximately 5,000 extra passengers each hour) and cut journey times by 22 percent, according to the Transport for London website. This massive upgrade offered an opportunity to revolutionize testing within the rail industry. The challenge was to generate an alternative testing solution that could alleviate many of the burdens of this traditional method and ultimately lead to a less costly and more time-efficient means of testing new technologies that is in line with the Underground’s highly stringent health and safety policy. Left: VTT in Use, Right: London Underground Our Approach Thales UK is a world leader in transportation solutions, and we were commissioned to install the automatic signaling solution for the Jubilee and Northern lines. The project involved installing a Thales S40 SelTrac Transmission-Based Train Control (TBTC) system on both the track and the entire rolling stock fleet of trains. Before these retrofitted trains could use this new system in service, the track installation needed to be tested. The engineering team devised an innovative test rig that could mimic a passenger train fitted with a Thales TBTC system. It needed to be portable and quickly assembled in almost any location along the Underground. Another goal was to reduce the quantity of test staff and test time so that standard engineering hours could be followed instead of requiring costly weekend closures. From an environmental perspective, the system needed to run reliably in any environment that could be experienced on the Underground network. This can vary from snow and rain to deep, dark, and dusty tunnels. Additionally, the solution needed to be bidirectional to offer a massive advantage during testing/fault finding, thus increasing efficiency and optimizing track time. Finally, the software needed to be intuitive to reduce the impact on test engineers during the transition from real trains to the new design. Implementation The solution was to create several VTTs with CompactRIO at the heart of each VTT system. The VTT system operates as a portable, battery-powered railway trolley that carries a testing staff and the Thales communications equipment used to test the SelTrac TBTC system. It is already installed on the Jubilee line and installation on the Northern line (the busiest on the Underground network) is due for completion in 2014, per the Transport for London website. The VTT runs with the CompactRIO control system interfaced to custom hardware. We used a CompactRIO real-time controller, an FPGA-equipped chassis, and flexible modular signal interfaces to implement the system, all of which were programmed with LabVIEW system design software. We perform both control and monitoring simultaneously with CompactRIO. For the control we use simulated signals from the interactive dials and switches on the front panel and preset values to imitate a real train. The monitoring portion of the system consists of several assigned test points, signal communication antennas, and CPU serial data, which we record from the VOBC. This platform provides the onboard SelTrac TBTC signaling equipment with the appropriate signals to mimic an actual passenger train, hence the term “virtual test train.” Additionally, gathering of all this data allows us to view how a train's VOBC would react to its surroundings. The reaction of the VOBC is imperative to us since it is this data that allows us to have confidence that the systems were installed and commissioned correctly. We also programmed data-logging functions in the LabVIEW application to easily record technical data on an SD memory card. We did this in case the data was required for the testing and commissioning of the SelTrac TBTC system. To review the test data, a VTT viewer program was also developed using LabVIEW. This VTT viewer program means that the testers on-site can review data immediately to make necessary corrections and ensure the appropriate signals are monitored. Success of the New Solution While initial trials on the Jubilee line were promising, VTTs that are now being used for routine programmed testing on the Northern line have surpassed our expectations. Use of the VTT has dramatically increased and diversified. In addition to serving as a testing tool, the VTT is a useful fault-finding tool. Another major advantage is the VTT’s bidirectional ability: A normal test train is only permitted to travel forward, but the VTT can reverse, and retest missed track, rather than loop around the line, which inevitably takes time. Another bonus is that the VTT can perform testing whilst other work is being performed in parallel. This is not possible using traditional methods because a train requires that power be available on the trackside. Besides providing the control element, CompactRIO can automate data capture. The user can test, gather data, and analyze it all in a short amount of time, which speeds up testing and commissioning. The use of the VTT has already proven to be invaluable. Traditional methods that normally take days have now been reduced to hours and require around half the manpower to operate. Our solution, powered by CompactRIO and LabVIEW, has saved vast amounts of time and money, increased productivity, and helped us take a huge leap forward in signaling testing innovation. Impact of Using National Instruments Hardware and Software A key factor in the success of this project was the use of LabVIEW. The software offered several benefits, such as graphical programming, easy-to-read code, maintainability, and scalability, that all proved essential for a large project. It also featured built-in tools that reduced development time by providing proven sections of code. Finally, the user interface design, which is usually every programmer’s nightmare, was simple because LabVIEW offered tools for quick customization. We chose NI hardware due to the versatile, reliable, and high-performance CompactRIO platform. The platform incorporates an accessible FPGA built directly into the backplane of the chassis, which was one of the most valuable features. NI hardware, coupled with the simplicity of programming the PC, real-time processor, and even the FPGA—all with LabVIEW—made us choose the NI platform. From a software point of view, LabVIEW was the ideal environment to use because of its graphical and intuitive approach to programming. It was simple enough to demonstrate sections of code to someone who had no programming experience, which helped greatly with instilling confidence in our customers and bidding to get approval. The choice of a modular signal interface meant that specification changes and revisions were accommodated by swapping the relevant interfaces, rather than abandoning the entire system. The graphical system design approach not only met our needs but also helped us remain flexible in our methodology while developing a prototype. NI customer care has always been first-class, and we highly recommend them to potential customers. Overall, from start to finish, NI provided an excellent, complete platform so that we could intuitively and easily create programs to control reliable, versatile, and modern NI hardware. Original Authors: Anthony Afonso, Thales UK Edited by Cyth Systems

*As Featured on NI.com Original Authors: Bipin Adaki, Varroc Engineering Ltd. Edited by Cyth Systems The Challenge We needed to develop a prototyped controller to validate the algorithms with the physical assembly of the integrated starter generator (ISG) while the actual controller was designed and developed. The Solution We used the modular CompactRIO platform, which gave the flexibility of changing the input and output signals, along with LabVIEW and the LabVIEW Model Interface Toolkit to import custom simulation models and tune the algorithms by advanced signal processing. A key segment of Varroc group is the electrical-electronics business. Its key electrical-electronics products include magneto, lighting, starter motors, CDI, handlebar assemblies, RR, and instrument clusters. Varroc group works on the design and development of the integrated starter generator assemblies and its controller. Internal combustion engines rely on the inertia of each cycle (or stroke) for its next stroke. For a typical four-stroke engine, the power for the movement of the piston comes through the power or combustion stroke, which is one of the four strokes of a four-stroke engine. An ISG is a device used to rotate or crank an internal combustion engine to compress the charge for the first combustion. This combustion process then generates enough inertia for the engine to run on its own. After the engine is started, the same ISG works as the generator and supplies power to the vehicle auxiliary and to charge the battery. Although this system can be used in conventional engine-powered vehicles, one of the key contributors to the hybrid’s fuel efficiency is its ability to automatically stop and restart the engine under different operating conditions. A typical hybrid vehicle uses an ISG on the engine crank shaft. The ISG performs functions such as fast, quiet starting, automatic engine stops/starts to conserve fuel. It also recharges the vehicle batteries. Our team is responsible for the testing of ISG assembly. In the past, once the ECU and its low-level driver software were developed, the high-level algorithm needed to be integrated with the ECU. It was only after this integration, that the process of algorithm validation was initiated, leading to a longer time to market. For this project, our strategy was to quickly validate our high-level algorithm on a prototyping platform while the design and development of the actual ECU happened in parallel. Left: The ISG Assembly Connected to the Drive Board Being Controlled by the Prototyped ECU, Right: Integrated Starter Generator Validating the Control Algorithm on a Prototyping Platform Our control algorithms were written in The MathWorks, Inc. MATLAB® and Simulink® software. We wanted to accelerate the process of validation of these algorithms by moving forward from software simulations to hardware implementation without waiting on the actual controller development cycle. The challenge was to look for a prototyping platform that was flexible and scalable to allow integration of additional I/Os during the process of validation but at the same time allows us the ease of programming and signal processing to tune our control algorithms. We used the CompactRIO platform to prototype our controller. We used the LabVIEW FPGA Module to write the low-level driver IP without going into HDL programming languages. Our FPGA IP allowed us to generate PWM signals for the inverter or motor drive, acquire speed sensor pulses and calculate RPM, control relays, and so on. Using the LabVIEW Model Interface Toolkit, we were able to compile our control algorithm from The MathWorks, Inc. Simulink® software and seamlessly integrate it into our LabVIEW code and run it deterministically on an ARM Cortex-A9 processor (Xilinx Zynq-7000 SOC) on the CompactRIO running the NI Linux Real-Time OS. This model communicates with the FPGA to generate PWMs according to the set point as well as capture the feedback from the system. The NI-9401 module allowed us to provide high-speed switching signals of 5 kHz to 10 kHz to our power inverter board. We used NI-9403 to capture feedback using a Hall effect sensor for motor position sensing as well as to capture other signals like the wheel speed, ignition, clutch, and so on. We also monitored parameters like the three-phase motor voltages and current and the battery voltage through the NI-9229. With the inherent UI capabilities of LabVIEW, developed the user interface for our project without putting in any additional efforts. The UI allowed us to visualize the signals in real time and proved handy for debugging as well. Digital Signal Processing to Improve Effectiveness of Algorithm The development of such a system that needs to be deployed in a noisy environment requires additional signal-conditioning and signal-processing techniques like adaptive filtering and averaging of samples. With the ready-to-use libraries within LabVIEW along with the signal processing toolkit, we easily designed and tuned our filtering parameters like windowing, averaging, and so on to enhance the quality of the signal before providing it to the control algorithms. Real-Time Parameter Logging A major challenge in control algorithm development is to have the insight of how various parameters in the control algorithm are changing according to the stimulus as well as the real-world conditions. The Technical Data Management Streaming (TDMS) file writing capability in LabVIEW gave us the ease to implement parameter logging. We could derive insights from this data that helped us tune or modify our control algorithms. Results By following this approach of rapid prototyping and using the NI platform, we validated our control algorithms within a time span of four to six months. Using LabVIEW and user-programmable FPGA-based hardware, we quickly prototyped our controller and validated the control algorithm without waiting for the design and development of the actual controller. The ease of use of the NI platform helped us reduce the development and validation time of our control algorithms by 50 percent and gave us insights to modify them. We are looking to build on this approach and continue using our expertise on the CompactRIO platform and LabVIEW for our future projects as well. Original Authors: Bipin Adaki, Varroc Engineering Ltd. Edited by Cyth Systems

Left: NI cRIO-9038 8 slot chassis featured in the Hotbar fixture control system, Right: NI 9152 C Series Features Soldering tips contain zero-crossing solid state relays that apply 120V, controlled by the cRIO

*As Featured on NI.com Original Authors: Ryan Parkinson, Siemens Edited by Cyth Systems The Challenge Determining the source of electrical high-voltage transients to prevent light-rail car failure. The Solution Combining the benefits of the field-programmable gate array (FPGA) and processor in NI CompactRIO hardware to create a rugged, semipermanent monitoring system that records multiple data formats and rates, synchronizes the data, and performs real-time analysis to remotely monitor sensors in an industrial environment for extended durations. Governing subsystem interactions is a fundamental challenge for system integrators. Despite defining exhaustive I/O limits, sometimes failures occur and it is not clear which subsystem interaction generated the destructive element. It is difficult to request subsystem vendor's resources to troubleshoot a problem that did not clearly originate from their equipment, and testing each system in isolation may not account for all interactions. In these cases, the system integrator may be best positioned to monitor the relevant parts of the overall system, isolate the problem source, and assign the appropriate resources to resolve the issue. The Siemens Rail Systems Division recently successfully performed this system integrator's task. Over the past three years, one of our customers faced a recurring issue with our SD160 light-rail transit vehicles. Denver RTD, a bus and light-rail service operating in Denver, Colorado, has 170 Siemens vehicles in operation. These vehicles receive power from an overhead catenary system (OCS), which in turn receives power from RTD's power distribution network. The auxiliary power supplies (APS) on board each vehicle receive power from the OCS and condition it for use by most of the other onboard vehicle subsystems. This APS had a high failure rate, which caused a critical failure for the vehicle. The failure log reported a high-voltage transient on the power input to the APS, which led the vendor to believe that either Denver RTD or the onboard propulsion subsystem (which provides power to the APS during electro-dynamic braking) were providing power outside the acceptable transient limit. However, both RTD and the propulsion unit supplier confirmed that their systems should not generate such a transient. Each light-rail vehicle failure was extremely expensive and time-consuming for Siemens and our supplier, and the failures caused operating delays for our customer. We needed to monitor the situation, establish the root cause, and find a solution as quickly as possible. Preliminary Diagnostic Efforts Initially, engineers at RTD verified OCS voltage levels met specifications. Subsequently, engineers from the APS vendor confirmed voltage transients that could contribute to the equipment failures, although when inducing these transients through various test routines, the APS always performed as designed. This testing required removing the vehicle from passenger service so personnel could monitor portable scopes. This method was inconclusive because high-voltage transients don’t occur very frequently and it is unlikely that a rare, damaging transient would occur during a short test period. It became clear that more comprehensive testing on vehicles in transit was needed to accurately characterize actual operating conditions. The APS vendor built its own remote data logger to permanently install on an SD160 vehicle. It could obtain snapshots of system-level voltage data, but the data was insufficient to understand the surrounding environment and what was causing the transients. These approaches helped us realize that we needed to see the complete picture to diagnose the issue. We decided to build on these earlier efforts and design a rugged, remote system to monitor the trains for long periods of time to find and correct the problem. System Definition We needed a highly flexible, yet powerful monitoring system to accommodate the variety of sensors and communication protocols from the different subsystems. We defined the following requirements: Continuous multichannel voltage sampling at >10,000 Hz to monitor six inputs for high-voltage transients At least three different configurable sampling rates to optimize each signal class data rate and minimize storage requirements A serial input using standard protocols to interface with the GPS antenna and provide location information for events Real-time calculations to provide output responses to interact with the sensors Pre- and posttrigger (event) data recording without saving nontrigger data to optimize analysis and minimize storage needs Large storage capacity Video management Automatically synchronize all inputs regardless of data rate or format Automatic downloads for extended operation with minimal personnel interactions Vibration and temperature operating ranges acceptable for installation on a rail vehicle Small footprint for installation in an electrical compartment Left: Permanent CompactRIO Installation, Right: High-Voltage Transducers and Fuse Installation Programming With LabVIEW We programmed our system exclusively with NI LabVIEW system design software, using the LabVIEW Real-Time and LabVIEW FPGA modules. We programmed the FPGA to acquire high voltages, currents, and vehicle diagnostics. We programmed the processor to acquire GPS locations and vehicle speeds, to perform daily housekeeping, and to perform postprocessing which allowed us to erase nontrigger data and minimize storage requirements since we were recording about 1 GB of data every 30 minutes. With automated postprocessing, we stored only about 5 GB per day. NI has a great database of prewritten code. Plugging in GPS software modules and general templates for the FPGA and processor software layout saved us a significant amount of time. After attending LabVIEW Core 1 and Core 2 classes in San Diego, we progressed from first-time users to advanced programmers in only a few months. Due to the intuitive nature of LabVIEW and previous programming experience, we completed and tested the software in less than six months. Benefits of CompactRIO FPGA and Processor Perhaps the greatest benefit of CompactRIO is the FPGA/processor combination. Because the FPGA is reconfigurable, the achievable data rates and sampling accuracy are comparable to most state-of-the-art scopes. We can perform real-time calculations and outputs with no processor delays. Once the data is timestamped and buffered, the processor advantages come into play. Software engineers can take advantage of the full breadth of the processor’s flexibility to achieve extended and remote FPGA operation and manage large data sets. The buffered data can be retrieved and written to a USB drive, making its storage capabilities comparable to a laptop. The GPS signal is monitored and recorded. Scripts are run to postprocess, erase nontrigger data, and prepare the data for analysis. Daily tasks are performed and automated FTP uploads to a server can be executed each evening. Rugged and Reconfigurable The CompactRIO exceeded all our environmental requirements. It handles a temperature range of -40 °C to 80 °C, so we mounted the unit externally in an electrical compartment. Its small footprint and excellent vibration/shock resistance allowed for easy, semipermanent installation. CompactRIO is highly customizable. We knew we needed to conduct multiple phases of investigation, and the ability to reconfigure the system to hone in on potential problem areas was a significant benefit. After performing preliminary voltage analysis, we discovered that it would be beneficial to monitor two current signals. Adding these two signals was a very simple task. Using a CompactRIO with swappable input modules, we could monitor almost any conceivable input. Original Authors: Ryan Parkinson, Siemens Edited by Cyth Systems

Left: Complete Single Line Diagram of an SMG System, Center: NI cRIO-9022 and C Series Modules Used in

Due to these requirements, we chose the NI cRIO-9022 controller and NI cRIO-9114 chassis for our system

Controllers (PLCs) have long been the workhorse of the industry, but newer technologies like CompactRIO (cRIO Furthermore, the cRIO includes an FPGA, which can be programmed with algorithms and logic that execute This makes cRIO an excellent choice for applications requiring high-speed data processing and advanced However, the cRIO's microprocessor can be particularly advantageous when integrating with industrial Yet cRIO is also designed to work with industrial buses such as Modbus, Fieldbus, EtherCAT, DeviceNET

Hardware We based the system on cRIO-9035 to meet the following requirements: 6 C Series slots (PROFINET

We designed a very flexible, programmable motor management system using the CompactRIO (cRIO) programmable With the FPGA, the CRIO’s high-speed data acquisition allows for our motor’s sensor data to be tracked Left: NI cRIO-9038, Right: NI cDAQ-9178 Engine Sensor Simulation Before connecting our ECU system based on cRIO to our test bench engine, we verified the module’s function using Hardware in the Loop simulation

Hardware On the front end, 25 remote stations deployed in the field run on cRIO-9075 real-time controllers

sensor picking up pump speed and phase, a discharge pressure sensor, an embedded monitoring system (NI cRIO data), signal processing software and alarm logics implemented using LabVIEW software running on the cRIO

An NI cRIO-9074 integrated chassis/controller is the core component of the data acquisition system. The cRIO-9074 features a field-programmable gate array (FPGA) that allows for customizable access to The cRIO-9074 uses the LabVIEW Real-Time OS. Communication with the cRIO-9074 occurs over the Tufts University wireless-G network. The cRIO-9074 controller connects to the campus network through a wireless bridge.

155, which combines cutting-edge mechanical, electrical, and software systems based on the LabVIEW RIO LabVIEW RIO Architecture Using the LabVIEW and CompactRIO platform, we combined traditional fluid power

*As Featured on NI.com Original Authors: Jason Spyromilio, European Southern Observatory Edited by Cyth Systems The Challenge Using commercial off-the-shelf (COTS) solutions for high-performance computing (HPC) in active and adaptive optics real-time control in extremely large telescopes. The Solution Combining the NI LabVIEW graphical programming environment with multicore processors to develop a real-time control system and prove that COTS technology can control the optics in the European Extremely Large Telescope (E-ELT), which is currently under design, construction, and deployment/ and prototyping phases. The European Southern Observatory (ESO) is an astronomical research organization supported by 13 European countries. We have experience developing and deploying some of the world’s most advanced telescopes. Our organization currently operates at three sites in the Chilean Andes – the La Silla, Paranal, and Chajnantor observatories. We have always commanded highly innovative technology, from the first common-user adaptive optics systems at the 3.6 m telescope on La Silla to the deployment of active optics at La Silla’s 3.5 m New Technology Telescope (NTT) to the integrated operation of the Very Large Telescope (VLT) and the associated interferometer at Paranal. In addition, we are collaborating with our North American and East Asian partners in constructing the Atacama Large Millimeter Array (ALMA), a $1 billion (USD) 66-antenna submillimeter telescope scheduled for completion at the Llano de Chajnantor in 2012. The next project on our design board is the E-ELT. The design for this 42 m primary mirror diameter telescope is in phase B and received $100 million (USD) in funding for preliminary design and prototyping. After phase B, operations are expected to begin in 2025. Left: For a size comparison, two humans and a car stand next to the E-ELT. The M1 primary mirror, which is 42 m in diameter, features segmented mirror construction. Right: The E-ELT features a total of five mirrors. Grand-Scale Active and Adaptive Optics The 42 m telescope draws on the ESO and astronomical community experience with active and adaptive optics and segmented mirrors. Active optics incorporates a combination of sensors, actuators, and a control system so that the telescope can maintain the correct mirror shape or collimation. We actively maintain the correct configuration for the telescope to reduce any residual aberrations in the optical design and increase efficiency and fault tolerance. These telescopes require active optics corrections every minute of the night, so the images are limited only by atmospheric effects. Adaptive optics uses a similar methodology to monitor the atmospheric effects at frequencies of hundreds of hertz and corrects them using a deformed, suitably configured thin mirror. Turbulence scale length determines the number of actuators on these deformable mirrors. The wavefront sensors run fast to sample the atmosphere and transform any aberrations to mirror commands. This requires extremely fast and precise hardware and software. Controlling the complex system requires an extreme amount of processing capability. To control systems deployed in the past, we developed proprietary control systems based on virtual machine environment (VME) real-time control, which were expensive and time-consuming. We are working with NI’s engineers to benchmark the control system for the E-ELT primary segmented mirror, called M1, using COTS software and hardware. Together we are also exploring possible COTS-based solutions to the telescope’s adaptive mirror real-time control, called M4. M1 is a segmented mirror that consists of 984 hexagonal mirrors (Figure 1), each weighing nearly 330 lb with diameters between 1.5 and 2 m, for a total 42 m diameter. In comparison, the primary mirror of the Hubble Space Telescope has a 2.4 m diameter. The single primary mirror of the E-ELT alone will measure four times the size of any optical telescope on the earth and incorporate five mirrors (Figure 2). Defining the Extreme Computational Requirements of the Control System In the M1 operation, adjacent mirror segments may tilt with respect to the other segments. We monitor this deviation using edge sensors and actuator legs that can move the segment 3 degrees in any direction when needed. The 984 mirror segments comprise 3,000 actuators and 6,000 sensors (Figure 3). The system, controlled by LabVIEW software, must read the sensors to determine the mirror segment locations and, if the segments move, use the actuators to realign them. LabVIEW computes a 3,000 by 6,000 matrix by 6,000 vector product and must complete this computation up to 1,000 times per second to produce effective mirror adjustments. Sensors and actuators also control the M4 adaptive mirror. However, M4 is a thin deformable mirror – 2.5 m in diameter and spread over 8,000 actuators (Figure 4). This problem is similar to the M1 active control, but instead of retaining the shape, we must adapt the shape based on measured wavefront image data. The wavefront data maps to a 14,000 value vector, and we must update the 8,000 actuators every few milliseconds, creating a matrix vector multiply of an 8 by 14 k control matrix by a 14 k vector. Rounding up the computational challenge to 9 by 15 k, this requires about 15 times the large segmented M1 control computation. Left: A thin, flexible mirror spread across 8,000 actuators, the M4 can be deformed every few milliseconds to compensate for atmospheric interference. Right: LabVIEW software controls the M1 system comprised of 984 segments at 1.5 m each with six sensors and three actuator legs that provide 3 degrees of freedom for movement deviation. NI engineers are simulating the layout and designing the high-channel-count data acquisition, synchronization system, and control loop. At the heart of all these operations is a very large LabVIEW matrix-vector function that executes the bulk of the computation. M1 and M4 control requires enormous computational ability, which we approached with multiple multicore systems. Because M4 control represents a15 by 3 k submatrix problems, we require 15 machines that must contain as many cores as possible. Therefore, the control system must command multicore processing. This is a capability that LabVIEW offers using COTS solutions, making a very attractive proposition for this problem. Addressing the Problem with LabVIEW in Multicore HPC Functionality Because we required the control system to be engineered before the E-ELT’s construction began, the system configuration could have an effect on the construction characteristics of the telescope. It was critical to thoroughly test the solution as if it were running the actual telescope. To meet this challenge, NI engineers not only implemented the control system but also a system that runs a real-time simulation of the M1 mirror to perform a hardware-in-the-loop (HIL) control system test. HIL is a testing method commonly used in automotive and aerospace control design to validate a controller using an accurate, real-time system simulator. NI engineers created an M1 mirror simulator that responds to the control system outputs and validates its performance. The NI team developed the control system and mirror simulation using LabVIEW and deployed it to a multicore PC running the LabVIEW Real-Time Module for deterministic execution. In similar real-time HPC applications, communication and computation tasks are closely related. Failures in the communication system result in whole system failures. Therefore, the entire application development process includes the communication and computation interplay design. NI engineers needed a fast, deterministic data exchange at the core of the system and immediately determined that this application cannot rely on standard Ethernet for communication because the underlying network protocol is nondeterministic. They used the LabVIEW Real-Time Module time-triggered network feature to exchange data between the control system and the M1 mirror simulator, resulting in a network that moves 36 MB/s deterministically. NI developed the full M1 solution that incorporates two Dell Precision T7400 Workstations, each with eight cores, and a notebook that provides an operator interface. It also includes two networks – a standard network that connects both real-time targets to the notebook and a 1 GB time-triggered Ethernet network between the real-time targets for exchanging I/O data (Figure 5). As for system performance, we learned that the controller receives 6,000 sensor values, executes the control algorithm to align the segments, and outputs 3,000 actuator values during each loop. The NI team created this control system to achieve these results and produced a telescope real-time simulation in an actual operation called “the mirror.” The mirror receives the 3,000 actuator outputs, adds a variable representative of atmospheric disturbances such as wind, executes the mirror algorithm to simulate M1, and outputs 6,000 sensor values to complete the loop. The entire control loop is completed in less than 1 ms to adequately control the mirror (Figure 6). The benchmarks NI engineers established for their matrix-vector multiplications include the following: LabVIEW Real-Time Module with a machine with two quad-core processors, using four cores and single precision at 0.7 ms LabVIEW Real-Time Module with a machine with two quad-core processors, using eight cores and single precision at 0.5 ms The M4 compensates for measured atmospheric waveform aberrations, and NI engineers determined the problem could only be solved using a state-of-the-art, multicore blade system. Dell invited the team to test the solution on its M1000, a 16-blade system (Figure 7), and the test results were encouraging. Each of the M1000 blade machines features eight cores, which translates into the fact that engineers distributed the LabVIEW control problem onto 128 cores. NI engineers proved that we can, in fact, use LabVIEW and the LabVIEW Real-Time Module to implement a COTS-based solution and control multicore computation for real-time results. Because of this performance breakthrough, our team continues to set benchmarks for both computer science and astronomy in E-ELT implementation, which will further scientific advancements in space and atmospheric observation. Left: NI engineers validated the mirror control system (right) with the M1 mirror HIL simulation (left). Right: To achieve required loop rates, NI engineers set up a highly deterministic network and called it from an application using timed sequences and timed loops. Bottom: This illustrates the current NI approach to implement M4. The problem is approximately 15 times more demanding than the M1 controller. Original Authors: Jason Spyromilio, European Southern Observatory Edited by Cyth Systems

We used a 2-port, high-speed CAN module to connect to the CAN bus so the cRIO could receive information We connected a telemetry radio to the serial port on the cRIO module and the control program simply sends

The system can work with both NI cRIO-9073 and NI cRIO-9074 controllers, depending on the customer’s Left: The CPS Automation System Setup with the NI cRIO-9074, Right: System Architecture The software We selected NI cRIO-9073 and NI cRIO-9074 controllers, an NI 9871 serial interface module, an NI 9208

Left: Frame of automated circuit breaker testing system with DUT (Devices Under Test) Right: NI cRIO- 9063 & cRIO 9038 Controller Chassis Application Overview The test machine consists of two sections.

*As Featured on NI.com Original Authors: Stijn Schacht, Test & Measurement Solutions Edited by Cyth Systems The Challenge Lifting 20-metric-ton unbalanced trays containing uncured concrete more than 6 meters, using 4 hydraulic cylinders while maintaining a strict accuracy of two millimeters. The Solution Implementing a custom control algorithm in CompactRIO to control the four hydraulic cylinders to move the unbalanced load. Custom Hydraulics and Hydraulic Control At Test & Measurement Solutions, we specialize in custom industrial hydraulics. We manufacture a series of custom and special cylinders including large hydraulic cylinders with strokes of up to 8 m in length and cylinders with bores with internal diameters of up to 700 mm. Recently, customers started to request complete mechanical control of these custom hydraulic systems. For this reason, we wanted to further develop our expertise in precision positioning and control systems. For relatively simple hydraulic systems, such as systems where one or two cylinders need to be controlled, custom control mechanisms can usually be developed using off-the-shelf controllers and programmable logic controllers (PLCs). Communication with these systems is typically established with industrial field buses and digital I/O lines. To control more complex machines, however, we apply NI CompactRIO. These systems are useful for applications that need additional custom requirements, such as precise position control over the whole stroke, or high velocity and synchronized motion of multiple cylinders. While adding these requirements to off-the-shelf PID controllers is usually not possible, CompactRIO provided a rugged and reliable industrial solution for custom control. A Heavy Task Our customer manufactures prefab concrete slabs, which need to be dried for 24 hours before they can be taken out of their trays and stored vertically. To save space in the factory, a storage system was built that includes 10 shelves positioned around a central elevator. The concrete at this point is still fluid and needs to be stored perfectly horizontally. Each filled tray weighs 20 tons (12m x 2.5 m size; 10 cm thick prefab concrete, 10 tons, on a 10-ton steel tray). To store on the shelf, the tray needs to be lifted to an equal height as the shelf and then moved onto it. For lifting this much weight, we use 4 hydraulic cylinders that each have a 3 m stroke and use a chain to lift the shelf over 6 m. While the position of each cylinder during this movement must stay accurate to within 2 mm, our measurements showed that we could actually achieve 0.1 mm accuracy. Each cylinder is actively controlled to compensate for slight weight abnormalities; it’s common that some concrete slabs have an uneven weight distribution due to holes that accommodate staircases or windows. Since such heavyweight cannot be stopped or moved instantly, PID control loops are used within software to create a gradual velocity profile that ramps up to the maximum velocity of 45 mm/s (cylinder shaft) and 90 mm/s (table) and to ramps down to stop moving as well. Position feedback is obtained by a magnetostructive encoder that is built in a hollow shaft inside the cylinder. This helps protect the system against damage. The accuracy of this position sensor is 5-10 µm and communicates over SSI (Synchronized Serial Interface) protocol. CompactRIO for Hydraulic Control Hydraulic control is often seen as an easy control system. But to position hydraulic cylinders accurately over a whole stroke requires extensive control intelligence since hydraulic systems are non-linear by nature. The dynamic behavior of a cylinder that is at its initial position is not comparable to the dynamic behavior when the cylinder is at its middle or end position. The resonance stiffness and frequency vary as a function of the shaft position, caused by the compressibility of the hydraulic fluid. We needed to take this resonance frequency into account to meet the accuracy requirements of the heavy-weight system. To accurately control the movement, a PID controller would need to continuously adapt to control parameters depending on the shaft position. This is something that is not possible to realize with PLCs. Also, we needed to include analog measurements in our control system. PLCs often contain considerable amounts of noise since they are not measurement-class hardware. To accurately control our hydraulic cylinders, we needed a non-linear control algorithm based on the linear quadratic regulator (LQR) model based controllers (MBCS). These control algorithms provide tighter process tolerance, faster settling, less overshoot, and more efficient tuning capabilities. After evaluation, we found that a full-state feedback control algorithm proved to give the best results. System Setup The system setup consists of an operator interface and a CompactRIO controller. The operator interface is realized using a Touch Panel and communicates over Ethernet with CompactRIO. CompactRIO combines a Real-Time processor, a reconfigurable field-programmable gate array (FPGA) and industrial I/O modules. All parts have been programmed using LabVIEW graphical programming software. Parallel processing in FPGA The FPGA on the CompactRIO is used in our application as a fast-working custom parallel processing unit. With the FPGA, we read the digital signals from each cylinder-encoder over a synchronous serial interface (SSI), convert this to an actual position, and transfer it to the real-time processor. In parallel, the FPGA uses several digital I/O lines for gracefully handling emergency stops. To prevent equipment damage, the cylinders must be halted safely within a short time. If an emergency stop occurs this is fed directly to the RT controller to calculate a controlled stop of the system (using a steep velocity ramp down). The FPGA keeps track of the time so that if the system is not completely stopped within a short period, the FPGA stops any movement directly. In addition, we use the FPGA to sample 16 analog input sensors that measure the pressures of the cylinders and other states. This is all converted to measurement units and transferred to our Real-Time control loop. Control Loop Implemented in a Real-Time Controller All acquired sensor data, such as pressure, positions, and velocity, is fed to the LabVIEW Real-Time control algorithm. The control loop is based on a full-state feedback control algorithm. The FPGA sends a clock signal (interrupt) every 5 ms to the real-time controller to start its control calculation for all four cylinders. The reason for this is that the clock signal on the FPGA is more accurate and the most recent data is used, so the control loop is in the same state as the mechanical system. Current data is used to determine the actual state, and adjust settings accordingly. The controller then calculates new values for the regulated flow, as the steerable unit. The real-time controller also checks if the system is working within tolerance. Pressures, valve positions and reference positions are read. If these values do not meet preset tolerances, we can compensate in software for mechanical wear, or detect when a sensor or actuator wears or fails. This error management and diagnosis is active during usage and pre-startup. Touch Panel The operator controls the elevator using a touch panel. Communication with the CompactRIO system is implemented using Ethernet over TCP/IP communications. The touch panel application is written in LabVIEW, using the Touch Panel module, and based on command-based communication. The application uses a clear menu and runs a state machine (with states like start lifting, diagnose, and stop). The current state and error conditions and diagnosis information are displayed on the panel when needed. After installation, we discovered that our hydraulic system was capable of lifting a concrete slab with an accuracy of 0.1 mm at 45mm/s (cylinder shafts). We developed this application in just two months. Since we developed the software modularly, we can reuse most of the content and adapt the software for future systems. Original Authors: Stijn Schacht, Test & Measurement Solutions Edited by Cyth Systems

*As Featured on NI.com Original Authors: Paul Riley, Computer Controlled Solutions Limited Edited by Cyth Systems The Challenge Creating an end-of-line test system to provide a traceable quality standard of clutch drive plates for supplying original equipment (OE) parts to the automotive industry. The Solution Using LabVIEW software and NI hardware, including the NI CompactRIO expansion chassis and associated modules, to configure and implement a test system that delivers accuracy, repeatability, high throughput, and reliability in the production environment. The drive plate component of a typical clutch transmits torque from the engine to the driveshaft. The component consists of a friction plate bound to a central spline with springs of varying stiffness. The springs absorb torsional vibration, which provides a solution for driveline noise, vibration, and harshness (NVH) problems. cTo ensure this component works as specified, technicians have to test each one by rotating the central spline relative to the fixed friction plate and analyzing the spring rate and hysteresis characteristics to very fine tolerances. System Hardware Overview We based the system on a high-torque jig (800 Nm) and a low-torque jig (50 Nm) placed on each side of a floor-standing cabinet. Each jig uses a pneumatic actuator to clamp the drive plate, combined with a servo motor that provides a controlled angular deflection. We used a torque cell and encoder to acquire the hysteresis data. The central cabinet contains the following control and acquisition electronics: Intel dual-core Pentium 3.2 GHz processor NI 7811R field-programmable gate array (FPGA) device NI CompactRIO expansion chassis NI quad-core strain gage module NI 32-channel digital outputs (sourcing) NI 32-channel digital inputs (sinking) Baldor drives The jigs contain the following hardware: Baldor brushless servo motor Alpha 220:1 gearboxes Pneumatic actuators to clamp the parts Applied Measurements torque cells We needed to use hardware based on CompactRIO so we could develop a highly accurate machine within our budget. This gave us 24-bit resolution in the acquisition of the torque cell readings plus noise-free digital acquisition and angle control to a resolution of 0.0004 degrees. Software Design We wrote the complete software using NI LabVIEW software algorithms and the LabVIEW FPGA Module. Because the software was for a piece of production equipment, we included multiple features in our design. For example, with minimal operator computer use, the operator can simply load the part and press the start button after powering the system. Also, because our system uses encoders and does not require angle calibration, we built torque calibration into the software and hardware so we can check the torque readings against third-party load cells and displays. Then we can send these units for annual laboratory calibration. With simple test accumulation, the supervisor can create or edit a test, thereby providing a library of tests for all drive plate variations. Also, we saved all of the resultant data in the well-structured and searchable NI DIAdem Technical Data Management Streaming (TDMS) format. This facilitates up to 800 tests per file per day with high-speed search capabilities using the XML-based parameter headers. In addition, we designed the run screen to include historic traces of any measured parameter. This gives the operator/supervisor the ability to spot potential trends in the change of any result for predictive fault detection. We can also acquire data using FPGA hardware, which enables the acquisition of data against angle rather than time, providing a noise-free, ultrahigh resolution of data capture with no wasted data. Using LabVIEW and Associated Hardware for Efficient Development Several LabVIEW features were key in the smooth development cycle of this machine. With the LabVIEW 8.0 project environment, we can contain all PC code, subroutines, and input/output information in one place. We can also put all FPGA-related code, project documentation, data sheets, and specifications in one environment, making future servicing and maintenance easier. Also, the CompactRIO digital input and output modules saved a complete level of intermediate wiring. Normally we convert the computer signals to/from 24 V for operating various solenoids and reading inputs via an intermediate rail of clip-on solid-state relays. Because we used CompactRIO 24 V-rated modules, we eliminated all of this wiring. Using the CompactRIO strain gage module, we achieved a direct connection from the torque cells to the acquisition hardware, thus reducing wiring and minimizing noise. In the software, it provided simple calibration of the transducer with self-checking offset corrections down to a resolution of 100 fV. With the FPGA architecture, we acquired data from each rig independently. This is normally difficult to achieve in a PC-based architecture and usually results in the extra expense of a second PC or a slower synchronous throughput of parts. Furthermore, we used the FPGA for firmware high-speed trip monitoring. The FPGA monitors torque levels at a very high rate and directly cuts power if a level above 95 percent is reached. This saves on external analog hardware and has absolute deterministic response not achievable on a PC. Original Authors: Paul Riley, Computer Controlled Solutions Limited Edited by Cyth Systems

*As Featured on NI.com Original Authors: Masatsugu Shiraishi, (The Zenitaka Corporation) Edited by Cyth Systems The Challenge Building a system to better secure the safety of work crews in the construction of mountain tunnels and reduce construction site energy consumption. The Solution Developing an IoT ('Internet of Things') system using CompactRIO that actively tracks the location of workers and their construction vehicles using RFID tags. As well, using CompactRIO hardware and LabVIEW software to develop a system to actively measure and monitor construction site energy consumption to provide data logging and active energy reduction. Background Our corporation has two major business areas: architectural construction focused on structures such as government buildings, office buildings, and commercial facilities, while our civil engineering construction sector is targeted at structures such as tunnels, bridges and dams. Within these areas, there have two persistent issues in regard to the construction These issues are improving safety and reducing energy consumption. Mountain tunnels construction requires a massive amount of electricity. This is because there are many kinds of electrical equipment being used day and night, including construction machinery, construction lighting, and ventilating fan. Despite this, the amount of power consumption is generally not tightly managed and measured. In many cases, the exact amount of power consumption is only ascertained when the bill from the power company becomes available. Sometimes, corporations install demand-monitoring equipment to help curb the maximum power demanded. However, even in these cases, the devices only allow the total volume of power consumption to be ascertained, or they may issue warnings to prevent the contracted volume of power from being exceeded. In order to tackle the issue of reducing power consumption, it was first necessary to obtain an accurate breakdown of how much power was being used in each particular area. In other words, we needed to be able to visualize the amount of power being consumed. In order to tackle the challenges mentioned above, Zenitaka decided to build a system that could improve the safety of tunnel construction as well as reduce the amount of power consumed. In other words, this new system would facilitate a clear picture of which workers were working in each location at the mountain tunnel construction site, as well as which processes were being carried out at those respective locations at any given time. The system would maintain the safety of all workers while also carefully controlling the electrical equipment to reduce unnecessary power consumption. Having decided on the concept, our next concern was whether there existed any kind of robust hardware that would not break down at the construction work site, that could move freely in response to changes in the working environment, and that could accurately detect workers and vehicles using radio frequency identification (RFID). Given that this system would involve many components that were new to Zenitaka, we decided to enlist a joint development partner, as they had provided us with a highly practical proposal. Left: Control terminal built using CompactRIO, Center: Screen displaying information on workers and the onsite environment, Right: LabVIEW user interface visualizing the power consumption breakdown. This system is composed of a server located on site, such as in the office at the construction work site, and multiple control terminals with allocated IP addresses. CompactRIO worked as the control terminals, and the required functionality has been developed using LabVIEW. Each control terminal is fitted with components such as an RFID reader for detecting workers and construction vehicles entering the tunnel, a densitometer for measuring the concentration of substances such as dust and combustible gases, and a wattmeter monitoring the operational status of the construction lighting, ventilating fan, and tunnel excavating machinery. These terminals are attached to each piece of electrical equipment that will be controlled, as well as to the electrical distribution boards that are positioned every 100 m within the tunnel, and all are linked to the server via the network. Each control terminal collects data on the position of workers and vehicles within the tunnel, as well as on the concentrations of various gases, and sends this information to the server. Data received by the server is analyzed and processed, and instructions for controlling the lighting and ventilating fan are then issued to the terminals based on the data results. This mechanism correlates the various kinds of measurement data with the electrical equipment, and utilizes the IoT for intercommunication to control and automatically reduce power consumption. CompactRIO-based distributed measurement systems use CompactRIO to perform measurements and process data. In most cases, these results are only sent in a single direction: upstream to the server. However, the TUNNEL EYE system is also able to send data downstream from the server to CompactRIO. This two-way data transfer is one of the special features of the TUNNEL EYE system. By building the system in this way, we have been able to achieve improvements in safety and reduced power consumption. The respective benefits are described in further detail below. Firstly, we have improved safety by ensuring that all people entering the work site carry a portable RFID tag. This has enabled us to manage work site entry electronically. In addition, we can now determine the location of each person working on site, and record their movements within the site. This means that we can track a person's location based on their previous movements if an emergency occurs in the tunnel work site, such as a fire or cave-in. Although there have been similar other types of tunnel entry management systems in the past, the major distinguishing feature of the TUNNEL EYE system is that data on the workers can be linked to the operation of the automatic controls for the lighting and ventilating fan. In other words, the energy saving feature is linked to the safety confirmation feature and operates accordingly once confirmation of worker safety has been assured. Let us illustrate this functionality using the example of transporting excavated earth. Huge dump trucks must make return trips into the tunnel as part of this process. The TUNNEL EYE system detects he movement of these trucks and triggers the lighting to make it brighter than usual. At the same time, the speed of the ventilating fan is automatically increased to cope with the exhaust fumes from the entering truck, as well as the dust particles from the excavated earth that will be blown around by the movement of the truck. As another example, take the case of workers located at the face of the tunnel excavation while electrical equipment such as a drill jumbo is being operated. In this scenario, no vehicles are making return trips, so exhaust fumes and dust particles are less of an issue. The system automatically controls the lights to dim the brightness elsewhere in the tunnel and reduce the speed of the ventilating fan. Unnecessary power consumption can be reduced, thanks to the ability to automatically control the lighting and ventilating fan to suit any combination of various situations, such as whether workers or construction vehicles are present, the operating status of construction machinery, and the concentration of various gases. If safety in the tunnel has been confirmed, the lighting and fan may also be switched off using a tablet device. In addition, a breakdown of the volume of power used on site can now be visualized. This is an essential step towards achieving reduced energy consumption. In particular, the ability to control the ventilating fan contributes greatly to reducing energy consumption. Ordinarily, the fan would be operated continuously at maximum speeds. However, the reality is that high speeds are not required when there is minimal dust. Accordingly, the concentration of dust is measured by a densitometer and then the speed of the fan is adjusted based on these results to prevent power from being wasted unnecessarily. This is a method that has been used previously. However, there is one important difference with the TUNNEL EYE technique. Under the previous method, the tunnel face environment might already be covered in high concentrations of dust by the time dust is detected by the densitometer. This is because the densitometer is positioned approximately 50m away from the tunnel face to prevent faults that could be caused by contact with the construction machinery or by explosive blasts. By the time the dust is detected, it is already too late to start increasing the speed of the ventilating fan. In contrast, the TUNNEL EYE system detects workers and construction vehicles, measures the power consumption of each piece of equipment, and measures the concentration of substances in the air. Based on this collective information, the kind of activity being conducted within the tunnel can be recognized automatically. If the system then predicts that this activity will cause the volume of dust to increase, it can automatically configure the ventilating fan to operate at maximum speed in preparation, rather than wait until the densitometer actually detects a high concentration of dust. This achieves enhanced reliability of the continued safety of workers in comparison to previous methods. The program for this kind of control flow has been revised countless times for optimization, resulting in smooth operation and efficient energy conservation. The design and implementation of the TUNNEL EYE system was able to be completed in just two months. Following this, it was repeatedly tested and revised, and even this latter process was concluded in one month. The reason we were able to achieve the full system in the short time of just three months was largely thanks to our use of CompactRIO, which allows reconfiguring, and LabVIEW, which facilitates graphical development. Original Authors: Masatsugu Shiraishi, (The Zenitaka Corporation) Edited by Cyth Systems

*As Featured on NI.com Original Authors: Paulo Carvalho, Worcester Polytechnic Institute Edited by Cyth Systems The Challenge By combining MRI 3D intraoperative imaging with robotics, we have been able to create healthcare professionals can create guiding interventions with precise closed-loop instrument delivery. But because MRI is highly sensitive to electromagnetic interference (EMI), healthcare professionals need a low-noise, modular control system for use with MRI-safe surgical robots. The Solution By combining MRI 3D intraoperative imaging with robotics, we have been able to create a surgical guide robot that assists surgeons during minimally invasive brain surgery. This has been made possible by creating an NI CompactRIO-based multi-axis piezoelectric motion control system. The Story The Automation and Interventional Medicine Robotics Research Laboratory (AIM Lab) at Worcester Polytechnic Institute (WPI), was founded to enhance healthcare through smart medical robotic systems. The lab supports a wide array of projects related to healthcare cyber-physical systems. The AIM Lab’s core capabilities range from low-level embedded system hardware to robot design and high-level control software. A primary focus area is an image-guided intervention, for which primarily MRI is used to provide “closed loop” surgical interventions. Left: Left: NeuroRobot Inside the MRI Bore Right: A Closeup of the CompactRIO SOM in the Top Left Corner of the Completed Control System Prototyping Challenges Our surgical robots operate inside the bore of an MRI machine. The MRI both injects noise into electrical sensors and is sensitive to electrical noise. The machine’s intense and fast-changing magnetic fields require carefully designed systems that operate in or near it. The sensitivity to electrical noise in the megahertz range also requires the drive systems to produce clean signals that do not overlap the frequency band used by the MRI for imaging. Furthermore, a surgical robot requires precise coordination among all its motion axes so that paths are followed precisely as the surgeon intends. Our first prototypes used a SOM that contained the Xilinx Zynq-7030 system on a chip and met most of our needs. However, the lack of an integrated programming environment significantly increased prototyping time. As a result, we redesigned our system to incorporate the NI CompactRIO SOM that uses a developer-friendly FPGA hardware description visual programming language in NI LabVIEW and exports a C API in easy-to-use header files. This enabled faster software development so our team could focus on our core value proposition instead of infrastructure work. An established development environment and commercial off-the-shelf (COTS) hardware also enhance our ability to validate the system as we move towards scale-up and commercialization. How It Works The control system is composed of five different types of boards: backplane, daughtercard, power input, power distribution, and breakout (Figure 1). This architecture ensures we meet the system’s modularity requirement while maintaining all the required safety features of a medical device. The backplane connects the entire system and provides a gateway to external control. It is the largest circuit board in the system. The backplane interfaces the CompactRIO SOM to each one of the up to 10 daughtercards with individual sets of LVDS SPI lines, a heartbeat, a card detect line, and a card reset line. Gigabit Ethernet over a fiber-optic connection jack serves as the primary connection between the backplane and external entity (Figure 4). The CompactRIO SOM runs the NI Linux Real-Time OS on which our custom control software runs. A LabVIEW implementation of hardware SPI blocks and a packet parser for each daughtercard connection offloads processing from the ARM core. The use of the LabVIEW FPGA Compile Cloud Service reduced our FPGA image creation time by approximately 25 percent. Each daughtercard attaches to the backplane via PCI Express-style connectors and handles the low-level control of one robot axis. This includes motor actuation, sensing, and encoder-counting functionalities. The number and type of daughtercards can vary depending on the system. The power input board receives raw power from the power supplies, measures current usage, and switches on and off power for the motor supply rails. This board is a key member of the safety chain. It analyzes the state of each of the heartbeat signals, detects which slots have daughtercards physically present, emergency stops the system, and independently determines whether the switched rails should be powered. The power distribution board provides voltage rails to the daughtercards. The robot-dependent breakout board connects one or more daughtercards to the cable that connects to the robot inside the MRI. The Application This motion control system is the first to be modular enough to work with multiple MRI surgical robots; operators simply replace the daughtercards that drive each axis to match the motor and sensor types of that specific robot. The control system is currently used as a controller for two different MRI-compatible surgical robots: the NeuroRobot (in preclinical trials) to ablate deep brain tumors and the ProstateRobot (a previous variation was used in a clinical trial) to conduct targeted biopsies. See figures 2 and 3, respectively. Stereotactic neurosurgery is a form of minimally invasive surgery that uses a 3D coordinate frame to target locations inside the brain through a single burr hole. However, the requirement to use preoperative images for surgical planning can lead to errors of up to 20 mm due to brain shift when the actual procedure takes place. The NeuroRobot addresses this issue by remaining in the bore with the patient during MR imaging and aligning itself with the target locations based on interactively updated intraoperative image feedback. The robot has a total of 7 degrees of freedom including insertion and probe rotation. We are experimenting with using the robot to ablate brain tumors using interstitial needle-based high-intensity focused ultrasound transducers; it can also be used for other procedures such as biopsy, electrical stimulation, gene therapy delivery, and brachytherapy, which involves implanting small radioactive seeds near or inside a tumor. Accurate prostate biopsies are an important step towards the diagnosis of prostate cancer, which is the second leading cause of cancer-related deaths among men in the United States. Although intraoperative imaging is sometimes used in clinical prostate biopsies, manual open-loop insertions suffer from decreased targeting accuracy due to unmodeled needle deflection and target shift. The use of real-time MRI alongside a robot for closed-loop active compensation to steer the needle towards the target can help address this issue. We are also experimenting with virtual fixturing as a way to program the robot to guide the needle around sensitive structures. This adds an extra layer of safety to the procedure. The strong magnetic fields in the MRI do not allow for the use of common electrical actuators such as DC motors. Instead, these robots use piezoelectric resonant motors. These actuators have a thin lead zirconate titanate (PZT) ring attached to a copper stator that when vibrating at resonance creates a traveling wave that leads to the rotation of the rotor through frictional coupling. To properly control these motors, the control system needs to identify the resonance point and tune the drive frequency around it based on the desired velocity. Original Authors: Paulo Carvalho, Worcester Polytechnic Institute Edited by Cyth Systems

A cRIO and an HMI were used to create a remote power switch that does not put operators in potentially

Specifically, the cRIO-9030 controllers offered great advantages while running Linux Real-Time. The high-end cRIO-9030 products include Gigabit Ethernet, IP, and USB camera support, an in-demand feature

After we configure the test and initialize the CompactRIO controller, the NI cRIO-9014 controller collects Data Logger We used an 8-slot NI cRIO-9104 chassis that we can configure to meet any test requirement

*As Featured on NI.com Original Authors: Johnathon Williams, National Physical Laboratory Edited by Cyth Systems The Challenge Developing a high-precision quantum waveform synthesizer to use in the characterization of analog-to-digital converters (ADCs) that is reliable and maintains high accuracy during repetitive testing through direct traceability to the Josephson quantum voltage. The Solution Using NI LabVIEW software and NI CompactRIO hardware to develop a low-jitter system for high-frequency data transfer and control of the bespoke synthesizer hardware. LabVIEW simplified the production of a fully integrated system, serial peripheral interface (SPI) communications, and an intuitive user interface, which enabled operators to configure the synthesizing process and required reference voltages. The National Physical Laboratory (NPL) is the United Kingdom’s national measurement institute. NPL is a world-leading center of excellence in developing and applying the most accurate measurement standards, science, and technology available. For more than a century, NPL has developed and maintained the nation’s primary measurement standards. These standards underpin an infrastructure of traceability throughout the UK and the world that ensures the accuracy and consistency of measurement. Based in southwest London and employing more than 500 scientists, the NPL facility is internationally regarded as one of the most extensive and sophisticated measurement science facilities. Figure 3. CompactRIO and the Serial Optical Interface Board Electrical Standards For more than 20 years, the electrical standards of voltage, current, and resistance have been based on highly reproducible quantum effects. For example, the Josephson effect relates voltage to frequency and is now used in measurement laboratories worldwide to provide the highest accuracy voltage measurements currently possible. NPL has achieved its level of quality research by designing bespoke hardware and software that interfaces with delicate quantum devices. These prototype systems form the basis of future measurement infrastructure at NPL and are regularly used by other laboratories. However, to carry out our research in a timely and competitive manner, we need to develop solutions using as many commercially available tools and systems as possible, and we need to ensure these systems can be easily maintained and supported into the future. Quantum Waveform Synthesizer Our application is a waveform synthesizer with direct traceability to the Josephson quantum voltage reference. Digital electrical measurement is now the method of choice in the instrumentation sector since signal processing is much easier to realize in digital circuits than in analog filters. The performance of the ADCs is crucial to the success of digital instruments, and our synthesizer is designed to generate waveforms with high spectral purity and a high level of amplitude stability. These reference waveforms are used to characterize ADCs represented by the device under test (DUT) in Figure 2. Figure 2. Schematic Diagram of the Synthesizer Design The synthesizer is based on a digital-to-analog converter (DAC) with 20-bit resolution and linearity. The output of the DAC is passed through an anti-imaging, multipole lowpass filter. The output of the filter is compared with the Josephson quantum voltage reference by measuring a voltage difference using an amplifier with a gain of 100 and an 18-bit ADC. A waveform is typically sampled 100 times per period to generate a 1 kHz reference sine wave (Figure 3). For ADC characterization, a sampling frequency of 100 kHz is required on the ADC. The DAC is similarly updated at 100 kHz. Figure 3. Oscilloscope Trace Showing the Voltage Difference Waveform with a Zoom-In on Two ADC Sample. Background Information on Our Chosen Technical Solution Our first synthesizer design used an FPGA along with a microprocessor to load data into the DAC and to read data from the ADC. This system delivered a sampling frequency of 5 kHz, which was determined by the speed of the microprocessor. This limited the synthesizer to applications at power line frequencies. An upgrade of this approach to a higher sampling frequency would have needed a complete redesign of the FPGA code. Therefore, we required the following levels of functionality from our system: A logic system based on an FPGA for fast data transfer to the DAC and from the ADC together with low-timing jitter. A real-time OS for the control loop, which stabilizes the synthesizer output against the Josephson reference. An Ethernet connection to a PC running LabVIEW for the user interface and data storage. This was comfortably achieved using CompactRIO-embedded hardware. Aside from providing the graphical user interface and data logging, LabVIEW simplified the sharing of data between the three architectural layers described above. That, along with the short development times, meant that LabVIEW was a real advantage to us. Our Experience with CompactRIO Our application required a high level of electrical isolation, so we chose to use optical fiber connections (Figure 3) between the CompactRIO hardware and the synthesizer. Each sample of the waveform consisted of three 8-bit data packets, enabling a data rate across this serial link of 2.4 MHz for a sampling frequency of 100 kHz. Two NI 9402 high-speed digital I/O modules were used to provide the digital I/O for the CompactRIO hardware. Three lines were used to implement the SPI interface to the DAC and the ADC. The built-in FPGA on the CompactRIO system continuously updated the DAC with data from memory and read data from the ADC to memory over the serial links. In addition, a timing signal was generated to synchronize the Josephson quantum voltage reference so that it was phase-locked to the synthesizer. The CompactRIO real-time processor transferred data to and from the memory and analyzed the ADC readings, which represented the difference between the synthesized voltage and the quantum reference. An algorithm on the real-time processor calculated corrections to the DAC values to adjust the synthesized voltage and stabilize it against the reference voltage. The real-time processor also averaged the data from the ADC before transferring it to the PC over Ethernet at a lower data rate. Software written in LabVIEW on the host PC provided the user interface for the whole measurement system including the configuration of the Josephson quantum voltage reference; choice of the amplitude, frequency, and number of samples in the synthesized waveform; and presentation of the data from the ADC. Original Authors: Johnathon Williams, National Physical Laboratory Edited by Cyth Systems

The NI cRIO provided a chassis to which we added modules supporting the I/O precision and flexibility The cRIO’s ability to handle over 80+ inputs and outputs (including flow, valve control, temperature,

The Challenge A biopharmaceutical research and development company approached us with the need for a system to automate the process of dispensing viral content onto test slides. The Solution By using hardware, software, and robotics, we created a solution that increased the customer’s throughput of available testing samples by over 300% and ensured greater safety protocols for their laboratory. The Story and The Cyth Process A biopharmaceutical company approached us with a process bottleneck they were facing in their research and development laboratories. They had operators dispensing samples of 8 various respiratory diseases (including rhinovirus and influenza) one by one, by hand, onto testing slides. This timely process was highly inefficient and held back their ability to scale up their testing volumes. Within Image, 1: A heated stirring plate. 2: A 16-channel peristaltic pump. 3: A stack of clean slides. 4: The Denso 6-axis robot with its custom fabricated gripper. 5: An indexing rotary table with a drying rack for slides. Our team began by designing a workflow that efficiently used hardware, software, and robotics to increase the client’s throughput of virus slides for testing. The workflow’s steps were as followed: A heated stirring plate (1) prepared viral content by keeping eight separate viruses suspended in a liquid medium. A 16-channel peristaltic pump (2) pumped the various viruses to the liquid dispensing nozzles. A Denso 6-axis robot arm (4) would pick up an available testing slide (3) from a stack, the robot arm would position the slide underneath nozzles for liquid dispensing at an accuracy of 5 to 30uL ±10%, and after viral content was dispensed the robot arm moved the slide to a drying rack to vaporize. After a drying rack of test slides was full an indexing rotary table (5) would rotate to an available rack which allowed for a total of 1000 testing slides to be created every 2-hour cycle, (approx. 1 slide every 7 secs). Developing a machine control architecture within LabVIEW required us to control and monitor several different inputs and outputs. These were the robot movements, sensor and camera I/O, and data acquisition hardware. Our team’s first step was programming a Denso 6-axis robot to dynamically follow a preset routine of positions. Several of the movements in its routine were fixed, such as the location of picking up new test slides, but several positions were dynamic or subject to changes in its environment. For example, when placing a dispensed test slide on a drying rack the robot had to dynamically sense the next available slot. This was made possible using Sick proximity sensors, and a high-definition camera mounted to the robot’s gripper manifold. The sensors gave the robot critical information about its positioning relative to surrounding objects, and a camera with machine vision software gave the robot the ability to make subjective decisions critical in a dynamic environment. The programming of the robot’s highly complex routine was made possible by using NI TestStand. TestStand was the supervisory sequencing software that ran LabVIEW executables, logic engines, and threads required for machine control and robot positioning. Partnered with TestStand was the NI PXI platform we used for the robot system’s data acquisition. The PXI chassis offered a built-in industrial computer and adjustable modules, giving us the high-speed I/O and capabilities required for Modbus and RS485 communication protocols. At Cyth we consider operational safety a critical component for any system that involves robotics. Our development team created a safety control loop that would instantly take over control of the system if any unsafe conditions were identified. A light curtain was installed surrounding the robot’s enclosure that would engage an emergency stop sequence if it tripped in any fashion. This was critical because if the robot was engaged in high-speed movements regardless of operator involvement all functions would cease in the case of an emergency. Adding to the enclosure’s safety was the use of a biological safety cabinet to contain the infectious diseases that were dispensed onto testing slides. According to our client’s guidance, we used a Biological Safety Level II hood which used laminar airflow to suction all molecules present outside the liquid medium, ensuring no escape or spread of the viruses under test. Respiratory viruses under test: · Rhinovirus (common cold) · Influenza (common flu) · SARS Delivering the Outcome Our engineering team was able to deliver a full turnkey solution for the creation of our client’s viral test slides. Using hardware, software, and robotics, we increased the customer’s throughput of test slide creation by over 300% while ensuring a high safety measure for their laboratory. The sequencing we were able to achieve in NI TestStand allowed us to provide the logic and threads necessary to run a LabVIEW machine control architecture and direct the robot’s complex routine. Overall, by collaborating with the client to provide a cost-effective solution within their budget and timeline Cyth was to deliver a tool that has assisted in furthering the efficiency of virus research. Technical Specifications 1 x 1300 Series Class II, Type A2 Biological Safety Cabinet (Thermofischer) 1 x 6-stop Indexing Rotary Table 1 x Denso 6 axis robot 1 x Watson Marlow 520Di Peristaltic Pump Drive (16 channel) 1 x Basler Camera 4 Megapixel Color 1 x Edmund Optics Telecentric Lens 1 x SONY Mini Pinhole Lens Camera 1 x PXI 8 Slot Chassis 1 x PXI 6514 1 x PXI 6225 8 x Sick Proximity Sensors 4 x Safety Light Curtain Sender and Photoelectric Sensor

As Featured on NI.com Original Authors: Scott Christensen, Collins Aerospace Edited by Cyth Systems The Challenge Collins Aerospace needed to create a “cradle to grave” test architecture for electromechanical systems that was flexible enough to use for a wide range of aerospace controller and component tests across the product development cycle on new and existing programs. The Solution We standardized on the NI PXI and CompactRIO hardware platforms and LabVIEW software to provide a modular test architecture that could be easily configured, customized, and maintained. We collaborated with NI Alliance Partners Wineman Technology on the software and Sierra Peaks on the instrumentation and actuation. Aerospace Test Needs Aerospace line replaceable units (LRUs), components, and controllers require rigorous test, and aerospace companies like Collins Aerospace must test a wide range of configurations and variants of one type of part for a variety of OEM vehicle programs, from business jets to commercial airliners to military aircraft. Collins Aerospace designs many of components used in aircraft flight systems. The actuation group designs systems that translate cockpit control commands into movement of all the leading and trailing edge control surfaces (flaps, slats). These systems are comprised of slat and flap electronic control units (SFECUs), central power drive units (PDUs) and associated power transmission elements like torque tubes and gear boxes. All these system components need to be tested individually and in combination at the system and aircraft levels. This test configuration and LabVIEW user interface (UI) management screen demonstrates the variety of devices under test that can be handled with this common architecture and how an application can be configured on the subsystem level. Challenges of a Traditional Test Approach The design and test methodology from component to component is relatively similar. However, those of us in the actuation group were operating many test stands for various types of LRU test, including development, qualification, production, and repair. Furthermore, we were operating with hydraulic loading on big test systems (both for internal use and for customers) that were time consuming and costly to reconfigure. We were losing time re-creating architectures and procedures to run different tests across the product development cycle. For example, existing stands used hydraulic loading for mechanical LRU test. We were seeing a lot of similar rework across tests; we needed to replumb hydraulic systems and rewire whenever we wanted to reconfigure our test setup. Even for electronic test, the test stands required actual flight hardware, which made the test solutions rigid and inflexible. Automated test was minimal, and support for multiple configurations was limited. The “traditional approach” to test was costly and time consuming. Our group faced aggressive schedule and resource constraints that simply did not allow us to adapt the fragmented existing architecture quickly enough to meet the growing requirements. Also, Collins Aerospace still needed a competitive advantage over other suppliers to reduce cost and schedule to win future programs, so were driven to develop a new test architecture. The Benefits of a Common Test Platform Across the Design Cycle The upfront work and investment we put into our new distributed, deterministic, and dynamic (D3) architecture was a forward-looking approach that will pay off in the years to come. We saw great potential to optimize tests by standardizing on a common test architecture for all tests across the design cycle for a component. We implemented the following test types with the D3 architecture: model-in-the-loop (MIL), software-in-the-loop (SIL), and hardware-in-the-loop (HIL) tests; hardware and software validation and verification (V&V) test (fault insertion); life-cycle durability test; system integration lab (iron bird) test; aircraft-level system integration test; high-lift system test rig (HLSTR) including aircraft-level physical system test; system test rig (STR) including performance, endurance, and fatigue tests; slat/flap controller rig (SFCR) including software development, fly-the-box, software functional, software regression, system, and automated production (acceptance test procedures or ATP) tests; and physical tests including single wing and “right side” emulating tests based on total loading on left side. We achieved several goals. First, we created a single common test platform that provides a “cradle to grave” test architecture and multipurpose tester. We used the same SFECU rig across the entire design “V” for development, ATP, iron bird test, system integration test stand (SITS) test, full production electronic controller test, and full production mechanical hardware test. Second, we incorporated modular hardware that is maintainable and reconfigurable. Now we can easily expand for larger system qualifications, reconfigure for different systems, and avoid hard wiring or plumbing to connect system components. Third, we have an open software architecture that is easy to integrate. The reflective memory architecture allows us to completely control our test stands with memory reads and writes. We can use this architecture separately or integrate it into larger test systems, and we can achieve distributed control that allows for more processing power as the system grows. Collins Aerospace Cost, Time, and Labor Savings By using NI’s distributed measurement and control products, we were able to cut test reconfiguration times from weeks to a day. Our D3 architecture is multipurpose (same load tables used for system, ATP, and iron bird; same SFECU rig used for development, ATP, iron bird, SITS, ESIM), modular (no hard wiring or plumbing to connect; software and hardware are built on designs common to multiple aircraft), easy to integrate (open software architecture; script writing in any language; proven RFM architecture that allows test stand to run in segregated or integrated mode), maintainable (eliminates traditional harness construction through extensive use of printed wiring boards), and forward looking (our team has patentable designs). By developing a common test platform to address our HIL, V&V, system integration, and production test needs across a variety of projects and even aircraft architectures, we were able to cut our test equipment development time while positioning ourselves to better address future needs including a more digital test lab. We’ve saved months of development time and hundreds of thousands of dollars on new platforms while operating with less test lab labor. We’ve perfected an architecture on which an entire test lab can run on a series of mobile common front ends, which eliminates the problem of aging, stationary electronics designed for a single function on a single mechanical test bed. Now we are striving to complete the integration of this new architecture into our daily technical and business systems to achieve a fully automated test lab where concerns over labor rates are a thing of the past, which frees investment for further innovation. Original Authors: Scott Christensen, Collins Aerospace Edited by Cyth Systems

The application includes three layers, which use the best of each of the three RIO computational domains—the

For this application, the NI Compact-RIO (cRIO) combined with our installation methodology was decided To migrate LabVIEW code from an obsolete cFP to a high-speed cRIO is not an easy task, especially when Our team was allotted 80 hours to modify their embedded code and deploy it onto the ROV's new Compact-RIO

The Challenge A company that supplies scientific instrumentation approached us with the need for a system to automate the hydrophobic coating of cartridges. The Solution Using NI CompactRIO hardware, precision motors, and a LabVIEW motor control architecture, we built the customer an industrial six-station assembly fixture to increase their manufacturing throughput and quality assurance. The Modularity of the System Stack Dispenser: The plastic cartridges were loaded in left and right stacks of 250. Escapement Mechanism: A mechanism that uses pneumatic actuators to give the controlled release of a left and right half to the plastic cartridge. Hydrophobic Coater: The machine used a custom brush attached to a pneumatic slide to evenly apply the plastic with a hydrophobic (water-resistant)resin coating. Oven & UV Curer: The left and right halves would travel on a conveyor through an oven and high-strength UV curing light. Camera Vision Inspection: The cartridge halves would be positioned via conveyor on a zebra-striped background. A camera conducting a vision inspection using machine vision algorithms to ensure the translucent coating was even and free of bubbles. Restacker: The left and right halves were restacked into hoppers. CompactRIO: 3 x NI-9145 8 Slot Chassis, EtherCAT bus connector, used to control the system I/O. Left: A variable frequency drive (VFD) sets the programmable speed of the conveyor carrying cartridges. Right: Stack dispensers using Sick proximity sensors to detect stack levels. System Highlights Stack Dispenser & Escapement Mechanism: Four pneumatic actuators that programmatically released cartridges one by one. Hydrophobic Coater: A two-part peristaltic pump released a precise amount of hydrophilic coating which was evenly applied using a brush attached to a pneumatic slide. Oven & UV Curer: UV Curer set the coating under high heat and the oven (500± ºF) vaporized any residual solvent leftover from the coating. Camera Vision Inspection: Used two Basler cameras with Edmund Optics lenses in two different positions. Spectral position, direct reflected light, which was used to spot potential defects, second camera positioning with zebra lines were used to determine imperfections (bubbles in coating, etc.) Restacker: Pneumatic restacker Left: A pneumatic on the assembly line pushes cartridges to the side that are determined rejects by the camera vision inspection. Right: A Vexta DC brushless motor powers the conveyor belt. Technical Specifications Stack Dispenser 4 x Neumatic Actuator Release Cylinder & Valve 4 x Custom Escapement Fitting Hydrophic Coater 2 x Watson Marlow Peristaltic Pump 2 x Custom Brush 2 x Pneumatic Linear Slide Oven & UV Curer Camera Vision Inspection System 2 x Basler Running Line Scan Camera 2 x 75 mm Focusable Double Gauss Lens Conveyor 4 x SICK Variable Frequency Drive 8 x Sick Proximity Sensor 4 x Solenoid Operated Pinch Valve 1 x Acer Operator Monitor 4 x CompactRIO NI-9145 8 Slot Chassis, EtherCAT bus connector 1 x LabVIEW 2020

We have used several versions of CompactRIO and Single-Board RIO devices to develop the technology both ERS controller contains a custom daughterboard that sits on top of the NI CompactRIO modules and a NI cRIO Our first NI controller was an 8-slot cRIO-9024. We later transitioned to a 4-slot cRIO-9075 as our second-generation controller.

Using the NI LabVIEW Real-Time Module, the NI LabVIEW FPGA Module, and NI CompactRIO, NI Single-Board RIO To perform these applications, we programmed an NI cRIO-9076 real-time processor with an FPGA-based system In this case, the control of one of the test benches is based on an NI cRIO-9022 embedded real-time controller

Compared to PC-based systems cRIO offers a more compact and rugged built chassis, better temperature field-programmable gate array (FPGA) within the same chassis (ENA450.EB, ENA450.NB) NI Single-Board RIO

The NI cRIO-9014 embedded controller receives wind speed data from a GILL WindMaster sonic anemometer

We adopted the cRIO-9030 for our project due to its powerful dual-core Intel Atom E3825, its high-value We also reduced the number of controllers since we used one cRIO-9030 for all test benches instead of

this article, we'll explore how to control a stepper motor using National Instruments' Single-Board RIO Role of sbRIO and CircaFlex™ in Stepper Control National Instruments' Single-Board RIO (sbRIO) and CircaFlex

result of these studies with NI technologies, we have developed a system architecture that includes a cRIO

Circaflex is a circuit board that interfaces the NI Single-Board RIO with all the sensor controls the Technical Specifications 1 x Circaflex 577 1 x NI Single-Board RIO 9603 1 x Peristaltic Pump 1 x Stepper

The Solution Using our embedded control system Circaflex paired with the NI Single-Board RIO, we designed provide high-speed I/O for device control using Cyth’s Circaflex platform paired with the Single-Board RIO Delivering the Outcome Our engineering team designed Circaflex paired with the NI Single-Board RIO to Technical Specifications 1 x Circaflex Board 1 x Client Mezzanine Board 1 x NI SingleBoard RIO – 9641

The Challenge A pharmaceutical test and validation company approached us, requiring a tradeshow demonstration capable of showcasing their test and measurement process for the inspection of silicon lubricant utilized in self-administering syringes.   The Syringe Lubrication Inspection Solution We paired the NI Single-Board 9651 (sbRIO) SOM with our Circaflex embedded control board to showcase the control and monitoring of a machine vision solution that captures images of Syringe Lubrication Inspection for improved and measured quality assurance.   The Story EpiPens are devices used to administer medication to an individual experiencing a severe allergic reaction, also known as anaphylaxis. Blocking the body’s response to an allergen, the importance of the EpiPen administering itself correctly in critical situations could not be higher. The product’s success depends on its ability to administer a predetermined drug dosage every time.   Our clients ensure that this occurs through the test and measurement of the silicon lubrication located in the interior of the self-administering syringes. Their system captures images (using cameras) of syringes individually used for inspection and analysis to meet strict FDA medical standards and detect defective syringes along their line. They asked us to create a fully capable demonstration system that they could use to showcase their processes. The Process An operator places a syringe in the rotating holder, located in the system housing. The system's gripper holds the syringe in a vertical position while the first stepper motor rotates the syringe at a predefined rate. A custom LED array casts and reflects light from the syringe towards a camera. The light reflected off the syringe is then gathered by our camera to recreate a two-dimensional image of the lubrication located in the syringe’s interior. A programmable logic controller (PLC) strobes the lighting in tandem with the camera’s capture sequence. Use of Circaflex and the sbRIO’s deterministic nature enabled the synchronization of the camera and lighting together for a predefined exposure time ensuring consistent lighting and improved camera imaging consistency. Using software to stitch together a high-definition image, we can accurately quantify the coating of the syringe’s interior lubricant. All of this is controlled and synchronized using the NI sbRIO 9651 SOM and the Cyth Circaflex platform. The LabVIEW motor control architectures measuring inputs and outputs (pulse and steps) are controlled by the pairing of the NI Single-Board 9651(sbRIO) SOM with our Circaflex embedded control board for high-speed data acquisition and measurement. The system's enclosure houses the stepper motors, camera, and hardware required to image the syringe.   Delivering the Outcome Throughout the project Power Syringe Lubrication Inspection, our sales and engineering teams collaborated closely with the client to ensure their timeline and project requirements. We were able to provide the client with a high-quality inspection system with additional tradeshow demonstration features that fulfilled their needs and met their budgetary requirements. This included the system’s ability to scan and render a 2D image of a syringe’s interior lubricant for comparison and analysis and to give this data readout live using their test and measurement software. Our improved system and high-quality inspection processes now ensures the ability of our customer to showcase their improved silicon lubricant inspection technology.   Technical Specifications 2 x Applied Motion NEMA 17 Integrated Drive + Motor with Encoder 1 x Applied Motion NEMA 23 Integrated Drive + Motor with Encoder 1 x 20 - Megapixel CMOS Global Shutter Camera 1 x Telecentric, HP Illuminator (beam diameter 60 mm), White 1 x RC Series LED Strobe Controller 1 x NI sbRIO-9651 SOM (System on Module) 1 x Circaflex 315

Solution Implementing intensity-modulated pencil beam scanning in the ProNova SC360 by using Single-Board RIO approach lends itself nicely to the design of a distributed control system with NI reconfigurable I/O (RIO Consequently, we used CompactRIO and Single-Board RIO solutions extensively throughout the SC360 for We used the Single-Board RIO FPGA and LabVIEW FPGA Module for each of these applications to meet the The Single-Board RIO device dedicated to beam control is responsible for controlling the magnetic fields

Our engineers decided to use a National Instruments’ 9651 RIO SOM, (System on Module), in conjunction The Circaflex 304 is a custom-built board designed to the exact dimensions of the RIO SOM and contains

Illuminator (beam diameter 60 mm), White · 1 x RC Series LED Strobe Controller · 1 x NI RIO

The Solution Using the NI Single-Board RIO control platform, Promethean Power Systems built a thermal tasks, yet provide a very simple operating interface for the farmers, so they used the NI Single-Board RIO

Left: Electronics Control Cabinet, Right: NI-9038 & NI-9063 cRIO Controllers Why CompactRIO?