Data Acquisition Control Research Articles

Low cost circulatory pressure acquisition and fluid infusion rate measurement system for clinical research

Acquiring patient physiological waveforms is useful for studying hemodynamic management and developing medical monitoring systems. A low cost, Arduino controlled data acquisition system acquires arterial pressure waveforms (Edwards Lifesciences TruWave compatible) and measures fluid infusion rate using hanging scales. This system can be used at the same time as a clinical monitor, enabling recording of patient arterial pressure and fluid delivery for clinical research. The system is powered via a USB connection, which additionally provides serial output, aiding compatibility and customisation. A simple software user interface, developed in Python, shows outputs. Each data acquisition system, including all necessary connection cables costs ̃US$90 and is multiple-use.

RF Acquisition System Based on μTCA for Testing of High-Gradient Acceleration Cavities

The radio frequency (RF) laboratory hosted in the Corpuscular Physics Institute (IFIC) of the University of Valencia is designed to house a high-power and high-repetition-rate facility to test normal conduction RF accelerator cavities in the S-Band (2.9985 GHz) in order to perform R&D activities related to particle accelerator cavities. The system, which manages the entire process of RF signal generation, data acquisition and closed-loop control of the laboratory, is currently based on a modular and compact PXI platform system. This contribution details the development of a platform with similar features, but which is based on open architecture standards at both the hardware and software level. For this purpose, a complete system based on the μTCA platform has been developed. This new system must be able to work with accelerator cavities at other operating frequencies, such as 750 MHz, as well as to explore different options at firmware and software levels based on open-source codes.

Embedded Machine Learning Using a Multi-Thread Algorithm on a Raspberry Pi Platform to Improve Prosthetic Hand Performance.

High accuracy and a real-time system are priorities in the development of a prosthetic hand. This study aimed to develop and evaluate a real-time embedded time-domain feature extraction and machine learning on a system on chip (SoC) Raspberry platform using a multi-thread algorithm to operate a prosthetic hand device. The contribution of this study is that the implementation of the multi-thread in the pattern recognition improves the accuracy and decreases the computation time in the SoC. In this study, ten healthy volunteers were involved. The EMG signal was collected by using two dry electrodes placed on the wrist flexor and wrist extensor muscles. To reduce the complexity, four time-domain features were applied to extract the EMG signal. Furthermore, these features were used as the input of the machine learning. The machine learning evaluated in this study were k-nearest neighbor (k-NN), Naive Bayes (NB), decision tree (DT), and support vector machine (SVM). In the SoC implementation, the data acquisition, feature extraction, machine learning, and motor control process were implemented using a multi-thread algorithm. After the evaluation, the result showed that the pairing of the MAV feature and machine learning DT resulted in higher accuracy among other combinations (98.41%) with a computation time of ~1 ms. The implementation of the multi-thread algorithm in the pattern recognition system resulted in significant impact on the time processing.

Neural network-based optimization model for sprint data collection

Sprint data has the characteristics of quality and continuity, but due to the limitations of optimization algorithm, the existing sprint data acquisition optimization model has the problem of low optimization performance parameters. Therefore, a data acquisition control optimization model based on neural network is proposed. This paper analyzes the advantages and disadvantages of neural network algorithm, combined with the sprint data collection optimization requirements, introduces BP neural network algorithm, based on this, uses multiple sensors, based on baud interval balance control to collect sprint data, applies BP neural network algorithm to compress, integrate and classify sprint data, realizes the sprint data collection and optimization. The experimental results show that the optimization performance parameters of the model are large, which fully shows that the model has good data acquisition optimization performance.

Experimental analysis of centrifugal downhole separators in boosting artificial lift performance

Gas evolution and expansion is a natural phenomenon in most oil and gas wells. However, gas is detrimental to pumping artificial lift systems, causing incomplete pump fillage and reduced pump efficiency. This makes it essential to separate the gas before a pump's intake. Various downhole separators with questionable efficiencies are available today. In this study, an automated experimental separation facility is presented, and efficiency of a novel centrifugal separator is tested. The setup includes a 31-ft horizontal section followed by a 27-ft vertical section that contains the centrifugal separator. The performance of the separator is evaluated at different air (34–215 Mscf/d) and water rates (17–867 bpd). The multiphase-flow loop is equipped with pressure transducers and control valves for effective flow control. Data acquisition and process control are performed using Labview™.A newly designed packer-type centrifugal downhole separator is used for all the tests. It takes an average of 5 min to establish steady-state flow in tubing return line. Liquid separation efficiency is a measure of the ratio of the inlet liquid produced at the tubing return line. Separation efficiency is close to ideal (100%) for liquid rates up to 500 bpd. The efficiency slightly reduces at higher liquid rates, but stays above 80%. The decline in efficiency is sharper for higher gas rates (over 300 SCF/STB). The effects of liquid level in casing on separation are also tested. The flow pattern in the tubing is intermittent for all the tests, while various flow patterns in casing are also visualized and recorded. With declining rates of production from oil fields, efficient artificial lift is necessary. This system provides a unique and novel tool to simulate the dynamics of flow in wellbores.

Ultrasonic methods for determining flows and velocity fields

This paper introduces research and development of a modern non-invasive device for determining flows and velocity fields. This device is based on the ultrasonic method. The measured fluid flow is surrounded by appropriate ultrasonic transmitters and receivers, which communicate with each other. A physical principle of this method consists in an interaction of sound waves with a flow, which generates a certain delay in sound waves transmission. The found quantity is thus time delay. The device is being designed as a flowmeter and with advanced and extended postprocessing as a tomograph, which reconstructs a 3D vector field for big volumes. This whole process requires the following: development of an appropriate design of the ultrasonic flowmeter and tomograph, testing the signal transfer and also various postprocessing methods on a measurement accuracy, building of a special verification experimental equipment and building of an electronic device as a control unit and data acquisition system.

System Design and SVM Identification Algorithm for the Ultrasonically Catalyzed Single-Sensor E-Nose

In this article, a system design method and Support Vector Machine (SVM) gas identification algorithm for the ultrasonically catalyzed single-sensor E-nose is proposed and investigated for the first time. In the aspect of hardware, the E-nose system consists of an ultrasonic module, sensing module, data processing module, personal computer, and power supply module. In the aspect of software, a microcontroller in the data processing module is coded by C programming language for data acquisition and operational control, and a user interface is made on the PC by C# programming language for display and sending commands. Performance of the integrated E-nose is tested and evaluated by methanol, ethanol, acetone, and hydrogen gases, respectively. The experimental results show that the integrated E-nose can achieve up to 100% gas identification success rate in the concentration range greater than 10% LEL (LEL = lower explosive limit), with a concentration measurement error less than 10%, and the SVM algorithm can effectively improve the gas identification ability in the low-concentration range (1%–10% LEL). For 1% LEL methanol target gas, it raises the gas identification success rate from 0% to 90%.

Data acquisition and monitoring system for KSTAR VUV spectrometer systems

To facilitate the stable monitoring of impurity species, an I&C system has been developed for the automated data acquisition and remote control of KSTAR VUV spectrometer systems, which provide the monitoring of impurity species of plasmas with regards to the machine protection and the plasma control. All controller computers for VUV cameras were relocated from the KSTAR main torus hall to the diagnostics room far from the tokamak, and optical converters were utilized to overcome the short communication length of USB interface for VUV cameras. An automated data acquisition code for Andor cameras was developed using C++ which runs on Linux, and an additional Windows-based GUI code using C# and .Net platform was developed for a legacy PI(Princeton Instruments) camera. The EPICS process variables are monitored and the data acquisition codes execute necessary actions based on the values of process variables. EPICS IOC, as well as OPI for the data acquisition parameters, were implemented, which enables the monitoring and configuring of the data acquisition parameters of VUV spectrometers over the network. These data acquisition codes store the acquired VUV spectrum into the KSTAR MDSplus server as the central data repository. The vacuum and power components of VUV spectrometers are controlled by PLC, and the EPICS IOC, as well as EPICS OPI as an HMI, was built for the remote control of PLC from the control room. Several interlocks were implemented on PLC to protect KSTAR main vacuum from the failure of the local vacuum system of VUV spectrometers as well as to protect VUV spectrometers from an incident of the KSTAR main vacuum.

LABORATORY SCALE PLANT FACTORY ARTIFICIAL LIGHT: PRIMARY EVALUATION OF THE LIGHT ENVIRONMENT, RESOURCES CONSUMPTION AND YIELDS

Plant factory artificial light (PEAL) is an attractive technology for producing high-value plants and medical-grade herbs. The PFAL research and development in Thailand are in their early stages. This article aims to design and construct the lab-scale PFAL, which includes several key features such as the lighting quality, the controls of the environment, and the embedded technology monitoring system. The lab-scale PEAL must evaluate the preliminary results of the artificial light parameters, resources consumption, the plant production yield, and the correlation between LED artificial light and the plant yields. The results demonstrated that our lab-scale PFAL consists of 27 m3 cultivation volumes. White-LED T8 (4091K) artificial light emitted, on average, the PPFD of 187±23 µmol m-2 s-1 with an R:B ratio of 1.8. The lettuce production yields show a strong positive correlation with the PPFD. The lettuce production yield is 76.23 g plant-1 under the temperature of 24.05℃, RH of 79.3%, and 923 ppm of CO2 concentration with a light period of 16/8 h. The PC-based monitoring and data acquisition control worked well during the crop experiments. The environmental parameters indicated that the results did not differ from the other PFALs. Electrical energy consumption data were also reasonable at 45%, 37%, and 17% of LED artificial light, air condition units, and other types of equipment, respectively. The artificial light sources have to improve the light uniformity and increase intensity. The lab-scale PFAL is very helpful in developing students’ skills in education and disseminating the knowledge and technical design of our PFAL to academic services. For future studies, efforts will be put in developing this PFAL to achieve higher productivity by balancing the resources consumption with the cloud-based control and monitor system.

Data acquisition and slow control interface for the Mu2e experiment

The Mu2e experiment at the Fermilab Muon Campus will search for the coherent neutrinoless conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement by a factor of 10000 over existing limits. The Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates both the artdaq DAQ and the art analysis frameworks for event transfer, filtering, and processing. otsdaq is an online DAQ software suite with a focus on flexibility and scalability and provides a multi-user, web-based, interface accessible through a web browser. The data stream from the detector subsystems is read by a software filter algorithm that selects events which are combined with the data flux coming from a cosmic ray veto system. The Detector Control System (DCS) has been developed using the Experimental Physics and Industrial Control System (EPICS) open source platform for monitoring, controlling, alarming, and archiving. The DCS system has been integrated into otsdaq. A prototype of the TDAQ and the DCS systems has been built at Fermilab’s Feynman Computing Center. In this paper, we report on the progress of the integration of this prototype in the online otsdaq software.

Detecting the Causal Structure of Risk in Industrial Systems by Using Dynamic Bayesian Networks

Our study deals with detecting the causal structure of risk in industrial systems. We focus on the prioritization of risks in the form of correlated events sequences. To improve existing prioritization methods, we propose a new methodology using Dynamic Bayesian networks (DBN). We explore a new user interface for industrial control systems and data acquisition, known as Supervisory Control and Data Acquisition (SCADA), to demonstrate the analysis method of risk causal structure. Our results show that: (1) the network of variables before and after the failure is represented by a limited and distinct number of factors;(2) the network of variables before and after the failure can be graphically represented dynamically in a user interface to assist in fault prevention and diagnosis;(3) variables related to the sequence of events at the time of failure can be used as a model to predict its occurrence, and find the main cause of it, thus making it possible to prioritize the requirements of the production system on the right variables to be monitored and manage in the event of a breakdown

Daiquiri: a web-based user interface framework for beamline control and data acquisition.

Daiquiri is a web-based user interface (UI) framework for control system monitoring and data acquisition designed for synchrotron beamlines. It provides simple, intuitive and responsive interfaces to control and monitor hardware, launch acquisition sequences and manage associated metadata. Daiquiri concerns itself only with the UI layer; it does not provide a scan engine or controls system but can be easily integrated with existing systems.

Development and application of cutterhead vibration monitoring system for TBM tunnelling

During TBM tunnelling, the rock breaking by cutters usually induces vibration. The cutterhead vibration is composed of all cutter vibrations. On the one hand, cutterhead vibration directly affects the life of the cutter, cutterhead and main gear. On the other hand, cutterhead vibration reflects the TBM excavation performance. In this paper, a cutterhead vibration monitoring system for TBM tunnelling was developed. The system consisted of the data acquisition module, communication and control module, as well as data processing and display module. Acceleration sensor, gyroscope and clock chip were integrated into a sensor board to acquire triaxial vibration data, cutterhead rotating status and acquisition time. The installation structure with anti-hit and water-proof functions was designed to ensure the stable operation of the system. Three types of data acquisition modes were proposed to meet the different monitoring scenarios. The system was applied in a TBM tunnelling project. Based on the normal monitored data in TBM tunnelling and penetration tests data, the differences in amplitude and frequency of triaxial vibration, as well as the effect of geological conditions and operating parameters on cutterhead vibration characteristics were analyzed. The engineering application showed that this system can reflect the changes of the geological conditions and operating parameters, providing guidance for the TBM tunnelling.

에너지 프로슈머 설비 복합진단장비 개발

초록·키워드 목차 오류제보하기 The need for safe management of energy prosumer electronic components is increasing as the energy prosumer market is revitalized and disseminated in accordance with the government"s new and renewable energy supply policy following the implementation of the Convention on High Oil Prices and Climate Change. Currently, the safety diagnosis of energy prosumer facilities is a measurement system for single elements of electrical, environmental, and mechanical properties, and it is difficult to study the correlation between the properties of each facility. In this paper, we intend to develop a complex diagnostic equipment for energy prosumer facilities that simultaneously collects electrical, mechanical, and environmental factor data. By analyzing standards related to prosumer facilities, we want to define measurement elements and develop diagnostic equipment mainframes, analog data acquisition modules, and control and monitoring programs for diagnostic equipment development. #Energy Prosumer #Electrical Safety Diagnosis #Complex Diagnostic Equipment #Power Quality Analyzer #Analog DAQ module Abstract1. 서론2. 에너지 프로슈머 설비 복합진단장비 설계3. 시제품 제작4. 실증시험센터 구축5. 결론References

Wind Turbine Concept for Educational Purposes

The environmental awareness of modern society is changing regard to the use of electrical sources. Change of climatic conditions, as a consequence of fossil fuel energy use, increases the need for renewable energy research. Consequently, a wind turbine will be installed on the premises of the University Department of Professional Studies at the University of Split, for educational purposes. Based on an annual assessment of energy production and consumption a wind turbine project is developed. This paper explains the main concept of wind turbine operation. The system is controlled manually or remotely by programmable logic controller (PLC) and supervisory control and data acquisition (SCADA), with the possibility to measure and monitor all relevant points in the system. The purpose of this system is to be used to perform laboratory exercises and to educate students of the Department. It also describes the possibility of integrating the system into an internal electric power system.

Control and Real-Time Data Acquisition of an Experimental Platform for Stored Grain Aeration Study.

Aeration is one of the most important methods to keep stored grain safe and maintain its quality. Experimental platforms are used for stored grain aeration study in a laboratory-scale. The purpose of this paper was to provide the real-time data acquisition and control system design of a new experimental platform with multifunction for stored grain study. Requirements of the aeration experiments were analyzed, and multi running modes were designed. The aeration inlet air conditions were designed to be adjustable and multi variables need to be controlled simultaneously, which was a key problem to be solved for the platform. An ON/OFF-PID based multivariable cooperative control method was proposed, and two control loops were formed where inlet air temperature and humidity were considered separately while could be controlled simultaneously with a logic judgement strategy. Real-time data needed to be monitored was acquired with different sensors and displayed intuitively. Experiments were carried out to test the static and dynamic characteristics of the control method and three inlet air flow rates of 0.03, 0.08 and 0.13 m·s−1were used. Performance of the data acquisition system was also tested. The results showed that, the inlet air conditions control error was within ±1 °C and 10% for temperature and relative humidity, respectively. The real-time data acquisition of multi parameters during aeration process was realized. The experimental platform can be used for studies of different aeration objectives.

Ultra-short-term Wind Power Prediction Model Based on VMD Decomposition and LSTM

With the rising demand for environmental protection, wind energy has made considerable progress as a clean energy source. Due to the uncertainty of wind power generation, accurate forecasting of wind power is conducive to achieving stable grid-connected control of wind turbines. This paper proposes an ultra-short-term wind power forecasting model composed of variational modal decomposition (VMD) and long short-term memory (LSTM) networks. Obtain the recorded historical wind speed and historical power from the wind field data acquisition and monitoring control system (SCADA), and use VMD to decompose and reconstruct the historical wind speed of the wind field to form 5 training data sets. Using historical power, historical wind speed, and predicted wind speed as input, wind power forecasts for the next 4 hours (15 minutes apart) are made. In order to evaluate the prediction ability of the proposed model, two algorithms, LSTM and XGBoost, are used for prediction. Taking root mean square error (RMSE) and mean absolute error (MAE) as evaluation indicators, the results show that the prediction accuracy of wind power is significantly improved after VMD processing, and the performance of LSTM is better than XGBoost in the two evaluation indicators.

Adevelopment of an Advanced Pressure Signal Acquisition Card for a Modular Turbojet Fadec System

Gas turbine engines are very important in aviation. Pressure is one of the key thermodynamic parameters which, first of all, suffers radical change within the flow passage of a gas turbine, on the other hand, there are several accessories like fuel and oil supply, in which the pressure of the working medium is essential. The measurement of this variable is therefore inevitable in data acquisition or engine control systems. The author shows the process of development of an advanced pressure signal acquisition card that fits into a modular electronic control system of a turbojet engine. The unit incorporates numerous experiences gathered with the previous generation of this module regarding power supply and integrated sensors as well. Furthermore, there are several innovations that enable a more efficient installation, data acquisition and built-in test possibilities. The most important difference is the 32-bit ARM Cortex-M0+ microcontroller which allows faster operation which allows the acquisition of more signals, including additional functions as thrust measurement, digital input/output handling and many others. The unit operation was thoroughly assessed using simulated and real operating conditions as well.

The upgrade to the EAST poloidal field power supply monitoring system

This paper presents the architecture and the implementation of the upgraded Experimental Advanced Superconducting Tokamak (EAST) Poloidal Field Power Supply (PFPS) monitoring system. To meet the requirements of EAST long pulse discharge, the monitoring system has been upgraded based on experimental physics and industrial control system (EPICS) and MDSplus. It provides an integrated management of supervision, data acquisition and real-time control. The program is flexible and portable, which improves the system performance. The I/O interrupt mechanism of the device support module is used to read the updated data, which reduces the network communication load. Asynchronous Driver Support (AsynDriver) is used to develop the device's specific interfacing code for the DAQ card driver, simplify writing of drivers and make the program more reliable. The HMI is developed using Control System Studio (CSS). During the experiment, the collect data is stored in the archiving system from PFPS system and sent to the MDSplus data server at the same time, so that the operator can view and analyze the online data and offline data. The upgraded monitoring system provides a general design scheme, which can be well integrated into the control system. The experimental results show the system realizes the remote operation and monitoring of equipment of PFPS and provides a friendly human-machine interface, supports multiuser operation.

Embedded system for ultrasonic imaging of under-water concrete structures

Many of the modern concrete structures such as sea-links and bridges are built in water. They require structural health monitoring (SHM) and audit to ascertain the quality and estimation of remaining useful life. To meet these requirements, a single-channel ultrasonic imaging system has been designed and developed to detect defects, porosities and rebar locations inside the Concrete/ Reinforced Cement Concrete (RCC) structures. This real-time and reconfigurable embedded system whas evaluated by carrying out under-water imaging of Concrete and RCC test blocks. Conventionally, Ultrasonic Pulse Velocity (UPV) method is being utilized over three decades in Transmit-Receive (T-R) mode to estimate the density and strength of the concrete structure under test. UPV method requires a skill to interpret the data provided by the UPV instrument. The novelty of the single-channel system discussed in this paper is that it is capable of inspecting Concrete/ RCC structures both in Pulse Echo (PE) as well as in T-R mode. An application software has been developed using C# in a visual environment for image acquisition and the control of Data Acquisition (DAQ) hardware has been interfaced to the computer via USB. The imaging system performs data acquisition and coherent averaging of the RF bipolar data to achieve Signal-to-Noise Ratio (SNR) higher than 20 dB. The performance of the system was evaluated by acquiring B-Scan images of the water submerged concrete test blocks having Side Drilled Hole (SDH) and RCC blocks with one as well as two steel rebars, using 54 kHz water immersion transducer in PE mode. The acquired B-Scan images have revealed the internal details of the sample test blocks, resembling the defects generated in the test blocks. High voltage tone burst bipolar pulser with maximum output of (± 350 V) has been specifically designed for this system to inspect highly attenuative porous and non-homogeneous Concrete/ RCC materials for the detection of SDH and reinforced steel bars in the concrete test blocks, using B-Scan imaging technique.