Data Acquisition Control Research Articles

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.

Design of a Laboratory Scale Solar Microgrid Cyber-Physical System for Education

Renewable energy sources such as solar and wind provide an effective solution for reducing dependency on conventional power generation and increasing the reliability and quality of power systems. Presented in this paper are design and implementation of a laboratory scale solar microgrid cyber-physical system (CPS) with wireless data monitoring as a teaching tool in the engineering technology curriculum. In the system, the solar panel, battery, charge controller, and loads form the physical layer, while the sensors, communication networks, supervisory control and data acquisition systems (SCADA) and control systems form the cyber layer. The physical layer was seamlessly integrated with the cyber layer consisting of control and communication. The objective was to create a robust CPS platform and to use the system to promote interest in and knowledge of renewable energy among university students. Experimental results showed that the maximum power point tracking (MPPT) charge controller provided the loads with power from the solar panel and used additional power to charge the rechargeable battery. Through the system, students learned and mastered key concepts and knowledge of multi-disciplinary areas including data sampling and acquisition, analog to digital conversion, solar power, battery charging, control, embedded systems and software programing. It is a valuable teaching resource for students to study renewable energy in CPS.

Time dependent network resource optimization in cyber–physical systems using game theory

The social and economic stability of a country is dependent on critical infrastructures (CIs) whose services range from financial to healthcare and power to transportation and communications. Most of these CIs are cyber–physical systems (CPSs), which integrate the network’s computational and communication capabilities to facilitate the monitoring and controlling of physical processes. Such systems are vulnerable to damage due to natural disasters, physical incidents, or cyber-attacks impacting the CPS organizations managing complex industrial control systems and data acquisition systems. When these CPSs are exposed to systemic cyber risks and cascaded network failures, network administrators need to recover from the compromise under limited resources. This is formulated as an attacker-defender game model to emulate the decision-making process in choosing an appropriate attack/defence mechanism in response to cybersecurity incidents using game theory. To further improve the assumptions made in the pure game-theoretic model, we relax the constraints on the rationality of the players, monetary payoff, and completeness of information by incorporating learning in games using reinforcement learning technique and compute the expected payoff using linguistic fuzzy variables.

The Application of a Data Acquisition System and Airflow Control System in an Air Dehumidified Drying Machine

There are various possible drying methods used in seed drying. The tray dryer with an air dehumidifying system was used to produce various agricultural seeds. Seed drying by using an optimal air temperature requirement with low relative humidity can accelerate the drying process. To meet the specific drying requirement for agricultural products, air dehumidifying process, measurement data record, and airflow control were conducted in the drying machine. The objective of this research was to apply the data acquisition system and airflow control for seeds drying. The drying machine consisted of an air dehumidifying unit, data acquisition and airflow control unit, and a tray dryer unit. The air dehumidifying system was used to minimize the moisture in the drying air. The data acquisition system was used to monitor temperature and relative humidity distribution along with the drying machine. While the airflow control system was used to confirm that the requirement of air dehumidifying process was reached. A tray dryer used dehumidified air as the air input for the seed drying process. The drying machine was successfully reaching the optimal condition for drying with the temperature and relative humidity distribution were recorded. The optimal condition for the seed drying was reached by using this air dehumidified drying machine.

DEVELOPMENT OF A LOW-COST OPEN-SOURCE PLATFORM CONNECTED TO THE INTERNET FOR ACQUISITION OF ENVIRONMENTAL PARAMETERS AND SOIL MOISTURE

The development of the Internet and the technologies associated with it has allowed disseminating and cheapening of communication equipment, prototyping services, electronic sensors, and all types of devices. Agriculture has benefited from these technological advances to boost its productivity and profitability. This study presents the development of a data acquisition and device control platform to obtain, in real-time and remotely, information from the field for decision-making and process automation. All electronic components are low-cost and “open hardware”, and the software is “open-source”. The developed platform was validated during a development cycle of two lettuce varieties (Japanese and crisp), in which the soil water matric potential was monitored at two depths (10 and 25 cm), while solar irradiation, air temperature, and soil temperature were evaluated only to monitor the cycle. The platform automatically and satisfactorily controlled the applied irrigation depths using only the data of matric potential by activating a solenoid valve and made the information from the sensors available on the ThingSpeak Internet of Things (IoT) platform.