Industrial PC Research Articles

Model Predictive Control and Service Life Monitoring for Molten Salt Solar Power Towers

A two-component system for control and monitoring of solar power towers with molten salt receivers is proposed. The control component consists of a model predictive control application (MPC) with a flexible objective function and on-line tunable weights, which runs on a Industrial PC and uses a reduced order dynamic model of the receiver’s thermal and flow dynamics. The second component consists of a service-life monitoring unit, which estimates the service-life consumption of the absorber tubes depending on the current mode of operation based on thermal stresses and creep fatigue in the high temperature regime. The calculation of stresses is done based on a detailed finite element study, in which a digital twin of the receiver was developed. By parallelising the model solver, the estimation of service-life consumption became capable of real-time operation. The system has been implemented at a test facility in Jülich, Germany, and awaits field experiments. In this paper, the modeling and architecture are presented along simulation results, which were validated on a hardware-in-the-loop test bench. The MPC showed good disturbance rejection while respecting process variable constraints during the simulation studies.

A Machine Vision Method for Identifying Blade Tip Clearance in Wind Turbines.

This paper introduces a machine vision method for measuring the blade tip clearance in a wind turbine. An industrial personal computer (IPC) is installed in the nacelle of the wind turbine to continuously receive video data from a digital camera mounted at the bottom of the nacelle. Using the open-source computer vision (OpenCV) digital image processing library data base, the real-time trajectory of the turbine blades is determined from the video data. Furthermore, fast Fourier transform (FFT) analysis is performed for determining the operating frequency of the blades in the images. The amplitude analysis performed at this operating frequency reveals the pixel-based blade tip clearance, which is then used to calculate the actual clearance of the wind turbine. This value is subsequently transmitted to the main controller of the wind turbine. The main controller can enhance the operational safety of the wind turbine by implementing appropriate pitch control strategies to restrict and safeguard the blade tip clearance. The results obtained by conducting experiments on a 2.0 MW wind turbine unit validate the effectiveness of the proposed identification method. In this method, the blade tip clearance can be calculated effectively in real time, and both the video sampling rate and communication speed meet the requirements for controlling the blade pitch.

Production System for Industrial PCs with 10-Year Long-Term Supply

Production System for Industrial PCs with 10-Year Long-Term Supply

Dreaming of seamless interfaces: media and friction from the feuilleton to personal computing

Dreaming of seamless interfaces: media and friction from the feuilleton to personal computing

Design of an Enhanced Dynamic Regulation Controller Considering the State of Charge of Battery Energy Storage Systems

In recent years, the escalating electricity demand in Taiwan has heightened the prominence and discourse surrounding the issue of power supply. With the enactment of the European climate law, global commitment to achieving net-zero emissions has gained momentum. Concurrently, the Taiwanese government has articulated the Taiwan 2050 net-zero emissions policy. To realize this objective, Taiwan has vigorously promoted renewable energy in recent years, increasing the proportion of renewable energy in its energy mix. However, confronted with the intermittent and unpredictable nature of renewable energy generation, challenges arise concerning the stability and quality of power supply. In response to the impact of integrating renewable energy into the grid, the Taiwan Power Company (Taipower) has introduced the day-ahead ancillary service market. Through this platform, power generation and battery energy storage systems (BESSs) engage in competitive bidding, fostering the integration of diverse distributed energy resources into the system. These resources serve as dispatchable assets for Taipower, contributing to grid stability by providing ancillary services. This study has developed an advanced dynamic regulation reserve controller by employing an industrial PC (IPC) in conjunction with a multifunctional power meter. Through real-time measurement of the power grid frequency by the multifunctional power meter, a sophisticated dynamic frequency reserve control strategy has been devised, taking into account the charging state of energy storage systems. This strategy exhibits high operational quality, effectively regulating the charging and discharging of energy storage systems. In addition to swiftly adjusting the current grid frequency, it encompasses the capability to facilitate the transfer of peak electrical energy. This effectively stabilizes the power grid, alleviating supply pressures during nighttime peaks and enhancing the overall supply stability of the power system.

Fast state transfer for updates and live migration of industrial controller runtimes in container orchestration systems

Many industrial processes (e.g., steel, fertilizer, paper production) utilize programmable logic controllers or distributed control systems, which cyclically execute control applications. Dynamic updates of such applications at runtime are desirable for optimizing the production while avoiding production stops. However, such updates are challenging since they require fast switching to an updated instance and executing an internal state transfer within the control cycle times. Existing dynamic update approaches for industrial applications can for example not update controller runtimes or operating systems, since they do not utilize modern container virtualization technologies. Furthermore, existing state transfer methods for container orchestration systems do not support fast cyclic applications. We propose a novel state transfer method for industrial control applications deployed as containerized Kubernetes microservices on server hosts or resource-rich industrial personal computers. The method enables dynamic updates and live migration of applications to others hosts without interrupting the underlying production facilities, which avoids costly downtimes. We have implemented our method as a Kubernetes extension and found that it can transfer large application states (i.e. 100.000 variables) via OPC UA in less than 42 ms across different hosts, which can fit into the available cycle slack time, therefore enabling a wide range of bumpless updates at runtime.

Hardware-in-the-loop testing of control of a precooled desiccant air-cooling system

Increasing the energy efficiency of cooling in buildings is an important component of the management of global energy consumption. A super-efficient cooling system based on the evaporation concept has been developed, and initial simulation results using the MATLAB/Simulink software tool have already been published by our team. In this paper, we present the results of hardware-in-the-loop (HIL) testing of the real-time controller for the cooler. HIL testing is an engineering process in which the actual controller hardware and software are implemented and interfaced with a real-time simulated model of the controlled system. Using HIL testing, many real-world problems can be fixed before testing on the actual prototype. The controller design is implemented on a small-footprint industrial PC with CODESYS RTE and application code, while control software is implemented using IEC 61131-3 programming languages. Similarly, a real-time thermodynamic and input–output variable-based model of the room, environment, and cooler and its mechanical components (sensors and actuators) are modeled using another industrial PC with the same software tools. HIL test results show very good agreement with the offline simulations.

Research on the design of mechanical robot control system for industrial PC in the context of big data

Abstract In the digitalization of big data information, how to use big data technology to design and study the mechanical robot control system of industrial PC has become a key topic of concern in today’s society. In this paper, robot kinematic modeling is mainly used to analyze and study the robot motion equations and control system operation mechanism, and the motion controller of the industrial robot control system is selected from the CLIPPERPMAC controller of the PMAC motion controller series. The approach to reducing the operation error of the industrial robot system from the control perspective is discussed. The error is reduced by adjusting the PID parameters of the PMAC motion controller in automatic and manual ways, and the error is further reduced by introducing fuzzy control algorithms. By comparing the original curve, the curve after the PID adjustment of PMAC itself and the curve after the introduction of the fuzzy controller, the curve error is kept below 5%, which is determined to be an effective method to reduce the error. This study can precisely realize the design and research of mechanical robot control systems, thus providing a guiding reference value for the research of industrial robot mechanization.

METU-DBL: a cost effective proton irradiation facility

The Middle East Technical University Defocusing Beamline (METU-DBL) is designed to deliver protons with selectable kinetic energies between 15–30 MeV, and proton flux between 106–1010 protons/cm2/s, on a maximum 21.55 to 15.40 cm target region with a beam uniformity within ±6%, in accordance with the ESA ESCC No. 25100 specification for single event effects (SEEs) tests in the low energy range. The achieved high proton fluences, allow users to test space-grade materials; electronic circuits, ASICs, FPGAs, optical lenses, structural elements, and coating layers for LEO, GEO, and interplanetary missions.The total received dose on the Device-Under-Test (DUT) from secondary particles created during proton-material interactions at the first beam collimator and the beam dump never exceed 0.1% of the dose from primary protons. The METU-DBL is equiped with several measurement stations and services to the user teams. A secondary measurement station in a rotating drum that can hold multiple samples has been constructed next to the first collimator which provides neutrons for transmission experiments. At the target region, a robotic table is located, which provides mechanical and electrical mounting points to the samples and allows multiple samples to be tested in a row. A modular vacuum box can also be attached on the robotic table for any test that may require a vacuum environment. Power rails on the robotic table provide various outputs for the DUT. For the data acquisition, high-speed networking and a modular industrial PC are available at the target station. The design of the METU-DBL control software enables test users to integrate and optimize the data acquisition and controlling of the DUT.The beam properties at the target region are measured with the diamond, Timepix3, and fiber scintillator detectors mounted on the robotic table. With diamond and Timepix3 detectors, measurements are taken from the five different points (center and the four corners) of the test area to measure the proton flux and ensure that it is uniform across the full test area. Fiber scintillators on both axes (X and Y) scan the target area to cross-check the beam profile's uniformity. Secondary doses during the irradiation are measured by a Geiger-Müller tube sensitive to electrons and gammas above 0.1 MeV and by a neutron detector located at the entrance of the R&D room. The room cools down relatively fast after any irradiation (<1 hour).Accurate linear energy deposition rates and absorbed doses on the samples are calculated using MCNP6, FLUKA and Geant4 Monte Carlo simulations. Alanine dosimetry measurements that are calibrated against these simulations are also used to estimate the absorbed dose on the sample.

An Integrated Off-Line Echo Signal Acquisition System Implemented in SoC-FPGA for High Repetition Rate Lidar

High repetition rate lidar is typically equipped with a low-energy, high repetition rate laser, and small aperture telescopes. Therefore, it is small, compact, low-cost, and can be networked for observation. However, its data acquisition and control functions are generally not specially designed, and the data acquisition, storage, and control programs need to be implemented on an IPC (Industrial Personal Computer), which increases the complexity and instability of the lidar system. Therefore, this paper designs an integrated off-line echo signal acquisition system (IOESAS) for lidar developed based on SoC FPGA (System-On-Chip Field Programmable Gate Array). Using a hardware–software co-design approach, the system is implemented in a heterogeneous multi-core chip ZYNQ-7020 (integrated FPGA and ARM). The FPGA implements dual-channel echo data acquisition (gated counting and hardware accumulation). At the same time, the ARM performs laser control and monitoring, laser pointing control, pulse energy monitoring, data storage, and wireless transmission. Offline data acquisition and control software was developed based on LabVIEW, which can remotely control the status of the lidar and download the echo data stored in IOESAS. To verify the performance of the data acquisition system, IOESAS was compared with the photon counting card P7882 and MCS-PCI, respectively. The test results show that they are in good agreement; the linear correlation coefficients were 0.99967 and 0.99884, respectively. IOESAS was installed on lidar outdoors for continuous detection, and the system was able to work independently and stably in different weather conditions, and control functions were tested normally. The gating delay and gating width time jitter error are ±5 ns and ±2 ns, respectively. The IOESAS is now used in several small lidars for networked observations.

NeuTHOR Station-A Novel Integrated Platform for Monitoring BNCT Clinical Treatment, Animal and Cell Irradiation Study at THOR.

(1) Background: A well-established Boron Neutron Capture Therapy (BNCT) facility includes many essential systems, which are the epithermal neutron beam system, on-line monitoring system (OMS), QA/QC (quality assurance or quality control) system, boron concentration (BC) measurement system, and treatment planning system (TPS). Accurate data transmission, monitoring, and deposition among these systems are of vital importance before, during, and after clinical, animal, and cell BNCT irradiation. This work developed a novel integrated platform NeuTHOR Station (NeuTHORS) for BNCT at Tsing Hua Open-pool Reactor (THOR). Apart from the data of the OMS and QA/QC system, the data of BC and TPS can be loaded on NeuTHORS before BNCT clinical, animal, and cell irradiation. (2) Methods: A multi-paradigm computer programming language c# (c sharp) was used to develop the integrated platform NeuTHORS. The design of NeuTHORS is based on the standard procedures of BNCT treatment or experiment at THOR. Moreover, parallel testing with OMS-BNCT (the former OMS) and QA/QC of THOR was also performed for more than 70 times to verify the validation of NeuTHORS. (3) Results: According to the comparisons of the output, NeuTHORS and OMS-BNCT and QA/QC of THOR show very good consistency. NeuTHORS is now installed on an industrial PC (IPC) and successfully performs the monitoring of BNCT Treatment at THOR. Patients' f BC and TPS data are also input into NeuTHORS and stored on IPC through an internal network from BC measurement room and TPS physicist. Therefore, the treatment data of each patient can be instantaneously established after each BNCT treatment for further study on BNCT. NeuTHORS can also be applied on data acquisition for a BNCT-related study, especially for animal or cell irradiation experiments. (4) Conclusions: A novel integrated platform NeuTHOR Station for monitoring BNCT clinical treatment and animal and cell irradiation study has been successfully established at THOR. With this platform, BNCT radiobiology investigations will be efficiently performed and a thorough data storage and analysis system of BNCT treatments or experiments can thus be systematically built up for the further investigation of BNCT at THOR.

ID Asks/Kenneth Werner

ID Asks/Kenneth Werner

Review: Whole Earth: The Many Lives of Stewart Brand, by John Markoff

Review: <i>Whole Earth: The Many Lives of Stewart Brand</i>, by John Markoff

TDPPL-Net: A Lightweight Real-Time Tomato Detection and Picking Point Localization Model for Harvesting Robots

Existing target detection models are large and have multiple network parameters, which can severely slow down the detection speed when deployed on small, low-cost GPU-free Industrial Personal Computers (IPC). As a result, this study proposes a lightweight real-time tomato detection and point-picking integrated network model based on YOLOv5 (TDPPL-Net). Firstly, the algorithm replaces the YOLOv5 backbone with a four-group lightweight downsampling model consisting of Ghost Conv and Ghost Bottleneck to reduce the model size, while adding the attention mechanism SimAM module to improve detection accuracy after each scale’s feature map. Secondly, the Spatial Pyramid Pooling-Fast(SPPF) network structure is used and the convolutional layers in the (Feature Pyramid Network and Path Aggregation Network)FPN+PAN structure are replaced with a depth-separable convolution to reduce the computational effort. Finally, the center of the bounding box is used as the picking point, and the corresponding depth information is obtained in combination with the Intel RealSense D435 camera, which is converted into 3D coordinates under the robot arm coordinate system after hand-eye calibration. The experimental results show that TDPPL-Net reduces the number of parameters by 59.84% compared with the original YOLOv5, the model volume is only 40% of the original, the mAP is 93.36, and the real-time detection speed on the IPC without GPU acceleration is 31.41 FPS, which is 170.31% higher than YOLOv5. The TDPPL-Net increases detection speed on low-performance equipment without compromising detection accuracy. It can detect and locate tomato picking points in real-time in the complex natural environment, which can meet the working requirements of harvesting robots.

Differential drive kinematics and odometry for a mobile robot using TwinCAT

&lt;abstract&gt;&lt;p&gt;In this paper, we propose a motion control system for a low-cost differential drive mobile robot. The robotic platform is equipped with two driven wheels powered by Beckhoff motors, instrumented with incremental encoders. The control system is designed and implemented using Beckhoff's TwinCAT 3 automation software, running on an industrial PC. The system is tested and experimentally tuned to achieve optimal performance. The method allows addressing both odometry motion accuracy and motion correction in order to obtain minimum trajectory errors. Test results on linear and angular robot trajectories show errors below 0.02 and 0.03%, respectively, after tuning of the motion parameters. The proposed approach can be expanded, tweaked and applied to other differential drive TwinCAT 3 based robotic solutions. This will contribute to expanding mobile robot applications to a variety of fields, such as industrial automation, logistics, warehouse management, health care, ocean and space exploration and a variety of other industrial and non-industrial activities.&lt;/p&gt;&lt;/abstract&gt;

KUKA KR3 Industrial Robot Unit HMI Design and Control with Universal Industrial PC in Sipy Development Environment

The challenges presented by Industry 4.0 require an innovative, new type of thinking from the engineers. Connecting old machines into a network presents significant problems, as the switch cabinets for these are obsolete and non-upgradeable. This has made developing a solution necessary, that is later universally applicable for scrapped, but mechanically intact robot arms. During the realization of the project such an IoT compatible graphical interface was developed, which can control a KUKA KR3 industrial robot unit and can also Real-Time simulate it in virtual reality. The security functions of the robot are provided by a Pycom SiPy developer panel.

Studying the Communication Possibilities Between a Collaborative Robot and an Industrial Computer

Abstract This project is based on the study of collaborative robots (hereafter: Cobot) and industrial PCs, including the communication possibilities between them. In the course of the project, a number of possibilities were studied in order to solve the problem and then summarised to select a collaborative robot and an industrial PC. After that, the focus of the project was on the communication options between the two systems: communication via I/O ports and net-work communication (TCP/IP, Modbus/TCP). Finally, the possible solutions were analysed from different points of view (complexity, flexibility, technical aspects, etc.) and communication between the chosen devices was implemented. The implementation was mainly carried out in a simulation environment, but as the project progressed a communication solution was tested on real industrial devices.

Data-driven fault monitoring for spacecraft control moment gyro with slice residual attention network

This paper studies the fault monitoring problem of a spacecraft control moment gyro (CMG) in complex environments based on the data-driven method. First, the wavelet denoising method and short-time Fourier transform (STFT) are utilized to preprocess the signal measured by an industrial personal computer (IPC) to obtain the frequency spectrum of each failure mode. Then, a slice residual attention network (SRAN) based on the ResNeXt model, attention mechanism, and random slice idea is proposed, which can fully capture the edge features of images while satisfying the learning efficiency. Furthermore, a set of comparative experiments are carried out to validate the ability of the proposed method, and the performance of SRAN is further verified under different datasets. Finally, based on the confusion matrix and t-SNE dimension reduction technique, the monitoring ability of SRAN for various faults is analyzed. Experimental results show that SRAN processes good fault monitoring capability and ideal robustness and can identify different fault degrees under the real-time fault monitoring scenario.

Design and Test of the Seedling Cavitation and Lodging Monitoring System for the Rape Blanket Seedling Transplanter

To realize the real-time monitoring of the lodging and cavitation state of the rape blanket seedling transplanter, a real-time online monitoring system set for cavitation and lodging based on machine vision was designed. The system was mainly composed of an image acquisition module, a height sensor, and an IPC (Industrial Personal Computer). When the system starts to work, the height of the lens from the ground and the collected images are saved in real time, and the operating status of the equipment is judged according to the height of the lens from the ground, and the actual corresponding size of the image pixels is corrected. We proposed a calculation method for judging the cavitation and lodging state of the seedlings based on the comparison between the actual planting position and the theoretical planting position of the seedlings. The processing and analysis software for the cavitation and lodging monitoring system of the rape blanket transplanter was compiled, and the monitoring system was developed. The dynamic test showed that the maximum absolute error of the cavitation recognition rate was 1.23%, and the maximum absolute error of the lodging recognition rate was 3.80%. The total time consumed of a 1 m image collected in real time from the collection, image processing and stitching, to seedling status recognition of the rape blanket seedling field was about 1 s. The accuracy and system processing time of the seedling cavitation and lodging state judgment can meet the accuracy and real-time requirements of cavitation and lodging state recognition for field transfer of rape blanket seedlings.

Will artificial intelligence help us in predicting outcomes in cardiac surgery?

Will artificial intelligence help us in predicting outcomes in cardiac surgery?