Parameters Acquisition System Research Articles

Neural Network-Based Body Weight Prediction in Pelibuey Sheep through Biometric Measurements

This paper presents an intelligent system for the dynamic estimation of sheep body weight (BW). The methodology used to estimate body weight is based on measuring seven biometric parameters: height at withers, rump height, body length, body diagonal length, total body length, semicircumference of the abdomen, and semicircumference of the girth. A biometric parameter acquisition system was developed using a Kinect as a sensor. The results were contrasted with measurements obtained manually with a flexometer. The comparison gives an average root mean square error (RMSE) of 9.91 and a mean R2 of 0.81. Subsequently, the parameters were used as input in a back-propagation artificial neural network. Performance tests were performed with different combinations to make the best choice of architecture. In this way, an intelligent body weight estimation system was obtained from biometric parameters, with a 5.8% RMSE in the weight estimations for the best architecture. This approach represents an innovative, feasible, and economical alternative to contribute to decision-making in livestock production systems.

Design of Wearable Human Physiological Parameter Acquisition System Based on Fiber Bragg Grating Sensors

Design of Wearable Human Physiological Parameter Acquisition System Based on Fiber Bragg Grating Sensors

Design and research of digital twin system for multi-environmental variable mapping in plant factory

Internet of Things (IoT) technology develops rapidly and is increasingly used in the field of facility agriculture, the emergence of digital twin technology provides a possibility for the intelligent management of facility agriculture. In this study, IoT and digital twin technologies are combined to design a digital twin system for mapping multiple environmental variables in plant factories to realize the intelligent management and help plant factory managers make intelligent decision-making management schemes. The system includes a multi-environmental variable parameter acquisition system and an environment variable control system based on Arduino, a multi-environmental variable data monitoring and remote environment control system based on Android, and a multi-environmental variable mapping digital twin model. IoT and computer development technologies are used to monitor environmental parameters and control the state of various equipment in plant factories and realize the connection between things and networks. Digital twin technology maps the multi-environmental variables of plant factories to digital twin and intuitively feeds back the parameters of the multi-environmental variables to the plant factory managers, completing the connection between people and things. By combining the IoT technology with digital twin technology, a digital twin system based on multi-environmental variable mapping in plant factory is established, so that the parameters of environmental variables such as CO2, temperature and humidity in plant factory can be accurately adjusted according to the different needs of different stages of plant growth, and it can help plant factory managers to realize intelligent decision-making.

Fault Diagnosis Method and Application of ESP Well Based on SPC Rules and Real-Time Data Fusion

Aiming at the popularization and application of a real-time monitoring parameter acquisition system of the electric submersible pump (ESP) well, this paper proposes a fault diagnosis method of ESP well operation based on the SPC rule and prior knowledge fusion. Based on the study of parameter variation rules of ESP well, the SPC expansion rule model is established; by analyzing the variation of some typical characteristic parameters of ESP well, combined with SPC expansion rules and expert experience, a priori knowledge of fault diagnosis of ESP well is formed, that is, multiparameter fault analysis table and weight factor; the SPC extended rule model and prior knowledge are fused to establish the fault probability model of ESP well, form the fault diagnosis method of ESP well, develop the online fault diagnosis software of ESP well, and deploy it in 425 ESP wells in a block. Taking five types of tubing leakage, pump wear, shaft breakage, gas influence, and pump plugging as examples, the application process of fault diagnosis method is analyzed. The research and application show that compared with other fault diagnosis methods, this method needs a smaller time window and higher diagnosis accuracy. By setting multiple time windows, this diagnosis method is applied to calculate the fault probability of ESP well in real time, solve the real time and accurate identification of 14 sudden faults and gradual faults, and significantly improve the intelligent diagnosis level of production faults of ESP well.

Design of multi-parameter real-time acquisition system of human movement based on nanosensor

Aiming at the problems of low accuracy of parameter collection in traditional systems, low comprehensiveness of collection results, and poor system robustness, a Nanosensors-based multi-parameter real-time collection system of human body motion is designed in this work. According to the overall frame structure of the parameter acquisition system, the system hardware design is realized by using Nanosensors and nodes, radiofrequency chip MC13201, and a multi-parameter acquisition circuit. Based on hardware design, the time synchronization algorithm based on virtual time stamp is used to realize the time synchronization among sub-nodes of the sensor, and the COPS algorithm is used to identify the bad parameters and control the parameter acquisition error, to realize the effective collection of multiple parameters of human motion. The experimental results show that the system has an 80% higher accuracy rate, 83% higher degree of comprehensiveness, better robustness, and higher practical application value.

The parameter acquisition system of oil drill’s bit in working process

In the process of oil drilling, it is often required to improve the drilling efficiency and to be able to analyze the faults in the drilling process, so it is of great significance to study the parameter acquisition system of the oil drill bit working process[1]. Aiming at this situation, this paper designs a device for downhole data acquisition, vibration detection, temperature detection and rotational speed detection of deep well drill bits. In this paper, an overall scheme is designed, and the acceleration[2], on-board temperature [3]and rotational speed[4] of the three axes of X, Y, and Z are selected as the main measurement objects. The working parameters of the drill bit can not only reflect the entire working condition of the drill bit, but also can be used for failure analysis during the drilling process. Provide strong evidence. First of all, components need to have high temperature resistance characteristics. At the same time, the selected components can meet the detailed parameters of technical requirements, including measurement range, measurement accuracy, resolution, etc. Secondly, design the hardware circuit, including acceleration acquisition circuit, temperature measurement circuit, rotational speed measurement circuit and data storage circuit. Finally, the software is designed, including the data acquisition, the A/D conversion and the Flash stored program design.

Development of a virtual shapemeter based on a shape control model for continuous annealing

Purpose Continuous annealing (CA) units usually lack a physical shapemeter; consequently, real-time display and closed-loop control of the strip shape are impossible to achieve. Design/methodology/approach A shape model for the CA process is established in this study. Specifically, a virtual shapemeter and closed-loop control system based on the advanced parameter acquisition system and information transmission of CA units are developed in C++ programming language. This system realises real-time dynamic shape display, closed-loop control and shape prediction by collecting raw data of steel coils and parameters during CA. Findings Field test results show that the shape predicted by the virtual shapemeter coincides with the measured shape by over 90 per cent, which fully meets the precision requirement of industrial applications. Originality/value Moreover, shape quality is effectively improved without increasing hardware investments.

Construction of operation parameters data acquisition system for 300 keV/20 mA EBM BATAN yogyakarta

Construction of components operating system and operation data parameters acquisition system for 300 keV/20 mA EBM PSTA-BATAN Yogyakarta has been done. The system is used for operating and monitoring of operation data parameters of 300 keV/20 mA EBM such as input oscillator power voltage, high voltage, high voltage current, coloumn current, regulated voltage of electron gun, electron beam current and vacuum pressure. The system consists of a hardware and a software. The hardware consisted of the SuperPLC FX2424 Module, L-Relay 51 module, voltage power supply, while the software as created using the LabVIEW version 2018 and i-TRiLOGI programs version 7.01. The construction of the system was started with the making of an operating program at i-TRiLOGI, making PLC and LabVIEW communications, programming the operating system in LabVIEW, making a data acquisition system in LabVIEW. The system was functioned to operate will operate EBM components via a computer device by pressing the operation buttons on the computer screen, while the operating parameters was displayed in the form of continuous graphics, digital tables and numbers. The system was equipped with operating data storage facilities that can be opened or printed at any time. The test results of communication testing between SuperPLC and LabVIEW was done with serial communication. The operation of the LabVIEW software was able to operate the programming function on PLC FX2424. From the ADC PLC test the linear graph results showed with a correlation value of 1. In the data appearance testing in HMI LabVIEW it was appropriate and the data presentation function could be performed in the form of tables and graphs and the data could be displayed in Ms. Excel for data tables and in Ms. format Word for graphical data.

Development and implementation of EPICS application program of HL-2A host engineering parameters acquisition system

Abstact In order to meet the increasing experimental requirements of HL-2A tokamak device discharge and improve the integration of HL-2A host centralized control system, this paper designs a high-speed data acquisition system based on PXI Express. In order to enable the fast acquisition system to be integrated into the HL-2A host centralized control system under the EPICS platform for centralized control and management, it mainly describes how to realize the communication between fast acquisition signal system based on C# and the upper layer OPI through the PON network under the EPICS platform. The data acquisition system hardware adopts PXIe-based chassis, embedded controller and high-speed synchronous acquisition card, which has the advantages of good mechanical encapsulation, high modularity and high sampling rate. The software adopts a measurement and control system development platform based on Microsoft. NET platform, Visual Studio development environment and Visual C# language. In this paper, the Epics C# library was studied, the EPICS Server application was developed and the remote control of the state and parameters in HL-2A host engineering system was realized. The system runs stably in the HL-2A device 2018 experiment. The result shows that the system can work stably at 10KSps sampling rate, which can better meet the needs of the device operation. This work completed the basic framework of the HL-2A Tokamak host centralized control system. And the technology and method can provide reference for the design of the next-generation device HL-2 M host centralized control system of the, laying a good foundation.

Identification of the stroke type of hemorrhage and ischemic based on microwave measurement technique

Objective To establish a microwave scattering parameter acquisition system to detect cerebral hemorrhage and cerebral ischemia animal models, and to study the non-contact rapid identification methods for the two stroke types. Methods Rabbits were selected for modeling. Eight rabbits in the cerebral hemorrhage group were injected with autologous blood. Six rabbits in the cerebral ischemia group were treated with bilateral common carotid artery clamping and femoral artery bleeding. The measurement excitation source has a scanning frequency range of 300 kHz to 3 GHz and an intermediate frequency bandwidth of 30 kHz. The signal of the S21 phase was acquired. The collected microwave scattering signals were subjected to mean filtering, principal component analysis dimension reduction, and mean clustering and nearest neighbor analysis to realize the identification of stroke types. Results The microwave scattering measurement method can reflect the changes of cerebral hemorrhage and cerebral ischemia. The phase of S21 decreases with the increase of blood loss and increases with the increase of ischemic duration. The results of the differential experiment showed that all 14 models were correctly identified. Conclusions The stroke identification system based on microwave scattering measurement can effectively distinguish rabbit cerebral hemorrhage model and ischemic model. This technology is low cost, portable non-invasive, simple operation and fast, which make it be a promising method for identifying pre-hospital stroke types. Key words: Stroke types diagnosis; Cerebral hemorrhage; Cerebral ischemia; Microwave detection; Non-contact diagnosis

The analysis of “more electric engine” technology to improve the environmental performance of aircraft jet engine

In aviation, there is now a dynamic development of aircraft equipment related to the implementation of “more electric aircraft” technology. This concept offers the ability to improve the use of on-board systems, e.g. environmental operating conditions of aircraft jet engine. This technology is named “more electric engine”. It allows the use of magnetic levitation technology at engine turbine shaft bearing. The development of this technology relates to the dynamic change of electronic power systems for civilian transport aircraft, the use of adaptive control methods and new materials in aviation technology. All technologies are improved the environmental operating conditions of the on-board system, e.g. operational flexibility, technological potential growth. [1] In the paper will be presented the TS-21 aircraft jet engine. This engine is modernized in the Jet Engine Laboratory of the Military University of Technology. The paper is presented a digital engine control system, the operating parameters acquisition system and magnetic bearing system. It is described the concept of active magnetic suspension of the turbine engine shaft support. The magnetic suspension technology allows eliminate mechanical bearing arrangements with an oil installation, friction forces and classical, mechanical bearings. The paper contains the simulation and experimental results of a modernized jet engine TS-21.

Design of a Remote Health Monitoring System Based on Wireless Sensor Networks

A multi physiological parameter acquisition system is designed through the research of telemedicine application and wireless communication technology in this paper. The sensors installed on the ZigBee terminal nodes collect the physiological parameters of the human body without delay and transmit information to the sensor gateway; the gateway sends the collected information to the system server and eventually displays the results in real time. When the physical condition of the monitored person has problems, the system starts the alarm display. Experiments show that the effect is good.

Research and Implementation of High Precision Power Parameter Acquisition Technology Based on LabVIEW

On the analysis of function requirements of the power parameter acquisition system during the test for intelligent low-voltage electrical apparatus, a high precision power parameter acquisition system based on LabVIEW was proposed. The hardware platform of the acquisition system was made up of industrial control computer, high precision sensors and high speed data acquisition card. According to the measuring principles and calculation methods of different power parameters, corresponding data acquisition, analysis and processing software is developed by LabVIEW software. Finally, the application example shows that the acquisition can carry out real-time and accurate acquisition and processing on related power parameters.

Research on Test System for Disease Aided Diagnosis

A real-time multi parameter acquisition system is designed in this paper. Sensors collect physiological parameter data. The parameters are transmitted to the main processor module via a wireless sensor network. The main processor processes the data. The results reflect the current physiological condition of the monitored person.If the physiological condition is abnormal, alarm measures will be initiated to inform the monitor. Wavelet analysis method is used to denoise data. The wavelet transform and least squares support vector machines are used to predict the information, and the model is corrected by the statistical results of the measured data. Experiments show that the modified method is effective.

Moving train loads and parameters identification on a steel truss girder model

This paper presents a new system for moving train loads and its parameters identification. A model of simply supported truss girder is constructed according to a side span of Poyang Lake continuous steel truss girder. The moving train loads are simulated by a model train with three coaches. In this system, time history displacements of measurement stations on bridge are simultaneously measured by using displacement image monitoring system when the model train moves across the bridge. Basic parameters of the model train, including moving speed, axle numbers and axle spacing, are identified with a parameter acquisition system. Finally moving train loads are identified by using multi-axle moving loads identification system. A series of experiments have been conducted. Effects of a few main parameters on the proposed system are investigated. The result shows that this system is a feasible and accurate method for the identification and makes preparations for the practical practice in engineering.

Online Parameter Identification of Synchronous Machine under Small Disturbance

The paper studies the online parameter identification technique of a synchronous machine, constructs its online parameter acquisition system, establishes its proper circuit model and state equation, uses maximum likelihood algorithm to identify the linear parameters of the machine under light load and low excitation, recognizes and modifies the saturation parameters with the magnetic circuit in saturation, inspects and revises the parameters and model in the big disturbance, and verifies the validity of the proposed method by the experiment and simulation.

Multi-Parameter Monitoring System Design of Modern Facility Agriculture

According to the request of the facility agriculture, the parameters acquisition system is designed, into which the temperature, humidity, CO2 concentration and illumination have been integrated. The light source control system for adjusting LED spectrum is designed together with relation of the plants and LED optic character, used as the supplementary lighting source of plant environment. The monitoring system replaces of traditional manual monitoring mode, so the automation has been improved greatly. Based on the different plants, different LED spectrum is employed to irradiate the plants, which is benefit to the plant growth. Experiments show that whole system works stably, temperature error is ±2.4%, humidity error is ±3.1%, CO2 concentration error is ±0.7%, illumination error is ±1.9%, and the LED spectrum can be adjusted in 255 grades automatically or manually.

A time-dependent parameter acquisition system for the characterization of MOS transistors and SONOS memory devices

An inexpensive and fully automated test station is described for the dynamic characterization of MOS and SONOS devices. The system incorporates a novel circuit which monitors the extrapolated threshold, transconductance, and subthreshold slope over time; onboard circuitry to place the system into one of several different modes of operation; an IEEE-488 interface to a controlling desktop computer; and a control program which performs several different measurement functions. Nonvolatile memory transistors are evaluated by the use of memory retention, programming, and endurance measurements, while short-channel MOS transistor reliability under DC and AC voltage stress is evaluated by monitoring the degradation in threshold and transconductance over time. >