bluuebunny/crossref_metadata_2025 huggingface dataset:
A coordinated control strategy for energy storage stations to suppress overvoltage in sending-end AC grid caused by DC blocking
Authors: Ma Runsheng , Han Dong , Li Yuyang , Zhang Wei , Lu Mengyu
Published: December 2024

A DC blocking event will cause a substantial quantity of reactive power injection into the sending-end AC grid, leading to overvoltage, which severely affects the secure and reliable functioning of the system. Synchronous condensers (SCs) offer the dual advantages of substantial capacity and rapid response speed, but their output target reactive power requires about 200-500 ms, much slower than energy storage stations. Therefore, this article introduces a coordinated control strategy for energy storage stations, grounded in the Karush-Kuhn-Tucker (KKT) conditions. The strategy in question is designed to optimize the reactive power margin, ensuring that the energy storage station’s total active power output remains steady while maximizing the reactive power it can absorb, as defined by the objective function. By solving the Lagrange equation in MATLAB, the objective value for the optimized energy storage unit’s output power is ascertained and subsequently allocated to individual energy storage units. In addition, the energy storage station, in conjunction with the SCs, jointly absorbs reactive power to mitigate overvoltage in the sending-end AC grid during DC blockages. Finally, simulations confirm the efficacy of the proposed coordinated control strategy.
Deadbeat predictive current control for high-speed permanent magnet synchronous motor based on extended state observer
Authors: Hua Qingyang , Mi Qianbao , Zhang Yi , Chen Fang
Published: December 2024

Addressing the serious issue of delays in the high-speed controlling area and the impact of motor parameter mismatches on current loop performance, this paper proposes a high-speed PMSM current control method based on an extended state observer (ESO). To improve the angle delay, a leading phase angle is introduced for compensation. Additionally, a one-step-ahead predictive compensation for time delay is included in the control method to reduce the time delay. The ESO is also employed to estimate electrical parameters and compensate for control errors, enhancing the robustness. The simulation validates the effectiveness of the method.
Automatic observation system for polar multi-parameter buoys based on SAILOR 4300
Authors: Zhao Jianglong , Dou Yinke
Published: December 2024

In recent years, with the gradual rise of global sea levels, the Arctic and Antarctic, as the largest freshwater reserves, have attracted increasing attention from scholars in various research fields. Among them, the melting of sea ice in the Arctic and subarctic regions is the most significant annual cycle change in the world. To monitor seawater quality, biological activity traces, and sea ice drift trajectories, an automatic monitoring device for multi-parameter observation of seawater was designed. The server and buoy processor programs are written in Python and can measure chlorophyll, dissolved oxygen, temperature, and salinity at a fixed horizontal depth for a long time. Meanwhile, we observe the activity status of underwater organisms at that point. We observe the movement trajectory of the sea ice where it is located throughout the entire work cycle. Due to the large amount of data transmission, SAILOR 4300 was used as the communication terminal for the system. A reliable transmission strategy was designed. In January 2024, the system underwent a one-week ice lake test. The interval between collection and transmission is 60 minutes. Based on the daily aging experiments of sensors and ice lake test data, it is shown that the system can be used for a long time in extremely low-temperature polar regions.
An improved fast filtering method based on target indication pre-calculation
Authors: Wang Baobao , Wan Shuaishuai
Published: December 2024

In order to improve the ability to track and monitor high-speed targets, an improved fast filtering method is proposed. Based on the traditional fast filtering of target indication pre-calculation, this paper makes full use of the target speed information in target indication data and constructs a non-stationary variable period extended dimension filtering method based on target indication pre-calculation, which enhances the fast-solving ability of high-speed maneuvering targets. Simulation results show that this method has better filtering performance compared with the traditional method.
Research on the application of load balancing strategy in IEC61850 communication of large-scale new energy monitoring system
Authors: Li Shaopeng , Zhang Ting , Hua Shuo , Pan Hongxiang , Zhang Xie , Shen Jian
Published: December 2024

This paper proposes an optimization scheme to achieve high throughput and stability of the system through efficient thread management and load-balancing strategies. Firstly, based on the IEC 61850 standard framework, a distributed architecture is constructed, which uses the advantages of multi-core processors for task distribution to improve data processing capabilities and system response speed. Secondly, in terms of thread management, prioritizing key operations ensures the timely processing of important data and reduces latency. At the same time, an asynchronous processing mechanism is introduced, so that the control and data can work in parallel, avoiding the occurrence of blockage. Then, the load-balancing strategy reasonably distributes the tasks to different processing nodes, avoiding the problem of single-point overload. Finally, the data caching mechanism and high-speed data bus are specially strengthened in the design to support the efficient transmission of large amounts of real-time data.
Optimization strategy for load demand response of microgrid clusters based on improved artificial hummingbird algorithm
Authors: Wang Zhenshang , Zhao Yuming , Wang Jing , He Shan , Tang Wenjun
Published: December 2024

As an emerging power system structure, microgrid clusters face significant challenges due to the increasing penetration rate of new energy sources such as photovoltaics, as well as intermittency and uncertainty in the distribution network system. This article proposes an optimization strategy for microgrid group load demand response based on an improved artificial hummingbird algorithm. Firstly, taking the interconnected microgrid group as the object, a load demand response model is established for the microgrid group, and the objective function and constraints of the microgrid group are determined. Then, an improved artificial hummingbird algorithm (mAHA) is proposed to solve the constructed model. Local Avoidance Operator (LEO) and Oppositional Learning (OBL) techniques are integrated to improve the basic Artificial Hummingbird Algorithm (AHA), accelerating convergence speed, enhancing solution quality, avoiding algorithm getting stuck in local optima, and thus better exploring the solution space. Ultimately, the improved artificial hummingbird algorithm is used to solve the load demand response model of microgrid clusters, to achieve lower economic costs for microgrid cluster operation.
Optimal DG hosting capacity evaluation method based on energy storage configuration and network reconfiguration strategy in power supply unit cluster
Authors: Li Hongjun , Ma Liang , Jiang Shigong , Qian Ruixin , Zhang Mingze , Shi Fangdi
Published: December 2024

For a single node in the power supply unit cluster, the effect of the node’s energy storage configuration capacity on improving the capacity of distributed power supply (DG) is analyzed, considering the energy storage access. Network reconfiguration is performed during operation to enhance DG capacity further. Firstly, a DG capacity evaluation model is constructed. The model maximizes DG capacity under various energy storage capacities for a single node, transforming it into a MILP model. Secondly, corresponding points of total cost and DG capacity under different storage capacities are obtained, and a piecewise linear interpolation method is used to plot the relationship curve. Thirdly, the optimal energy storage configuration and corresponding optimal DG capacity are determined by calculating the slope of the curve. Finally, the proposed model and method are verified on the IEEE-33 node system.
Analysis of the effect of active power threshold on dynamic metering of energy meters
Authors: Zhang Xinhui , Lu Da , Wang Chunyan , Li Helong
Published: December 2024

With the high proportion of new energy and power electronic equipment access in the construction of new power systems, the dynamic volatility of the grid signal is stronger, which poses a serious challenge to accurate metering. To address this problem, this paper starts with the analysis of the electric energy metering algorithm principle. Firstly, the measurement characteristics of the Moving average algorithm and the Non-overlapping algorithm are compared. Secondly, on the basis of studying the steady-state signal metrology power metering error of the two algorithms when there is an active power threshold, the metrology ability of the two algorithms to dynamic signal is further analyzed. The conclusion is drawn that the threshold will cause the metrology power metering error of the moving average algorithm. The non-overlapping algorithm has a certain probability of power metering error. Finally, by designing different input signals, the moving average and non-overlapping algorithms are tested, respectively, to verify the effectiveness of the analysis. The research results of this paper can provide ideas for the research and analysis of dynamic metering algorithms of energy meters.
Development and testing of a remote calibration device for the temperature field of environmental testing equipment
Authors: Xiong Zhichun , Ling Yancui , Chen Xu
Published: December 2024

Temperature is one of the important parameters for the calibration of environmental testing equipment. Due to its special working requirements and large volume and weight, the demand for on-site inspection and calibration of environmental testing equipment has always been high. Conducting research on remote calibration devices for temperature fields in environmental testing equipment is beneficial for improving the testing efficiency of environmental temperature and humidity, reducing the workload of testing personnel, and further reducing customer testing costs. By using ANT Wireless technology and using SHT3X temperature and humidity sensors to create a temperature field calibration device for environmental testing equipment, the above functions can be achieved. After testing, the maximum transmission distance of a single node can reach 70 meters, and the maximum networking distance between multiple nodes can exceed 1,000 meters. It can adapt to high and low-temperature impact tests at -20°C~60°C, and the response speed of temperature and humidity sensors is slightly slower than traditional temperature measurement thermocouples. It is suitable for calibration and detection of environmental testing equipment with good insulation performance.
A small variable rate underwater CAN-fiber data transmission system
Authors: Chen Zerui , Cheng Yanyan , Zhao Shijie
Published: December 2024

Currently, the primary data transmission methods underwater include optical fibers, radio waves, blue-green light, underwater acoustics, electric fields, and inductive coupling electric fields. Optical fibers are extensively utilized for underwater data transmission due to their benefits, such as long transmission distances, strong anti-interference capabilities, good environmental adaptability, and minimal limitations from navigating carriers. However, optical fibers face challenges in meeting high-speed transmission requirements beyond 10km due to communication distance constraints. As a result, optical fibers are often used as a replacement for the CAN communication system, but they come with drawbacks such as large volume and fixed speed. They lack dynamic testing and release-length experiments, supporting only one-time use. To tackle these issues, this paper presents a comprehensive design of a variable (adaptive) baud rate optoelectronic data transmission system for underwater applications with limited space. Lake trials were conducted under various conditions, demonstrating the system’s excellent performance. It ensures high-speed data transmission without interference and extends communication distances. This system holds significant reference value for the engineering implementation of composite data transmission systems constrained by space.
Design and implementation of wheel speed simulation system for civil aircraft
Authors: Li Xuesong
Published: December 2024

In the ground simulation test of civil aircraft braking systems, a number of functional, performance, and fault tests need to be carried out, and wheel speed is an important input parameter of the brake control box in the test. To meet the demand of the aircraft to provide wheel speed to the brake control box, a wheel speed simulation system was developed in this paper. The system can simulate the wheel speed state of the aircraft when the aircraft is sliding and braking, and transmit the wheel speed signal to the brake control box, which features portability and versatility, and the system is reliable and stable, which well meets the test needs of the brake system.
Pt100 temperature measurement sensors design and transducer simulation
Authors: Li Haoran
Published: December 2024

Temperature measurement (thermometry) is indispensable in industrial operations, aiding engineers in monitoring and evaluating temperatures. This study focuses on the utilization of Platinum Resistance Temperature Detectors (Pt100 RTDs) for precise thermal measurements, operating within an input simulation range of 0-10 V and tailored for measuring temperatures from 10°C to 90°C in chemical processes. Using the Siemens PLC300 simulation system as the power supply, the experiment involved connecting a Pt100 RTD to a DC balance Wheatstone bridge to assess thermal conductivity characteristics. The experiment in this research setup included a simulation of the circuit diagram using Multisim software, comprising a bridge configuration, amplifier circuitry, and voltage display. Results based on the Coefficient of Determination and Mean Squared Error demonstrated the sensor’s high accuracy and reliability. The experiment also underscored the importance of calibration and the impact of ambient conditions on measurement accuracy. The findings affirm the Pt100 RTD’s potential in industrial applications, offering valuable insights into its performance and areas for improvement in circuit design and component selection.
Research on the traceability method of direct current electrical energy value based on quantum voltage
Authors: Xu Xitong , Jia Fuquan , Bai Jingfen
Published: December 2024

After the redefinition of the International System of Units (SI), China has affirmed the establishment of a voltage primary standard based on the Josephson effect and a resistance primary standard based on the quantum Hall effect. Despite this, the derived measure of direct current (DC) energy has yet to fully realize its re-realization in physical constants. As the regulations and systems for DC energy measurement are newly established, the gradual adaptation to quantum changes and the enhancement of DC energy value capabilities are crucial. Integrating natural physical constants into the DC system is essential for establishing a foundation for a more streamlined future. This paper introduces two strategies for developing DC energy standards based on quantum voltage. Through theoretical analysis, the paper substantiates the viability of tracing DC energy to fundamental physical constants.
Design of high-precision multi-channel ice detection system
Authors: Zhou Nianpeng , Song Pan , Zhang Yang , Zhu Chunling
Published: December 2024

Effectively detecting aircraft icing caused by supercooled water is essential for ensuring safe flight. This paper utilizes ultrasonic pulse-echo technology to measure ice thickness. Unlike traditional ultrasonic detection devices, which are widely used for flaw detection but are bulky, inconvenient, and have low detection accuracy, this study develops a multichannel, high-resolution pulse-echo wireless detection system with a field-programmable gate array (FPGA) as the central processing unit. The system primarily involves the design of ultrasonic pulse-echo hardware, high-speed data processing, and wireless transmission. Ice detection experiments were conducted on an ice-aluminum double-layer structure. The test results indicate that this system can effectively detect the thickness of ice layers with a resolution of 1 mm.
Reliability and maintainability design of the micro ammeter
Authors: Chen Hongliang , Han Lin , Guo Jiaxin , Wen Xingxi
Published: December 2024

The reliability design and maintainability design of the micro ammeter were made in the paper. Firstly, reliability and maintainability models for the micro ammeter were established, and corresponding predictions and allocations were made. Secondly, this paper developed an analysis tool to improve the efficiency of reliability calculations greatly. Then, three micro ammeters participated in the 612-hour reliability test, and all successfully passed the reliability assessment.
Effect of multiple scattering on ultrasonic imaging detection for titanium alloy
Authors: Zhao Yang , Zhang Xinyue , Huang Yufeng , Yang Pinghua
Published: December 2024

Ultrasonic imaging for the micro-pores can evaluate the performance state of the parts. Wave multiple scattering caused by the micro-pores is significant for ultrasonic imaging. This paper provides an ultrasonic imaging method combined with a total focusing method (TFM) to inspect the micro-pores in additive manufacturing titanium alloys. Initially, a geometric model of the titanium alloy containing micro-pores was created using k-wave software for Phased Array Ultrasonic Testing (PAUT) detection simulations. Subsequently, the time-domain TFM algorithms were developed to generate defect images based on the simulation data. Finally, the influence of wave multiple scattering on TFM imaging has been analyzed.
Research on calibration method for flange-type apparatus to Measure Water Permeability of Concrete
Authors: Deng Xiaodong , Fu Yanxiang , Yuan Jing , Xu Yang , Ren Tingting
Published: December 2024

The water permeability of concrete is a crucial indicator to evaluate its ability to resist the infiltration of water or other liquids under pressure, which is vital for ensuring the stability and durability of building structures. The flange-type apparatuses are commonly used for detecting concrete’s impermeability and determining its impermeability rating. This article proposes a novel calibration method specifically designed for the flange-type apparatus to measure the water permeability of concrete, according to which the standard pressure measuring device is connected to the calibrated apparatus by a connection device designed and presented in this article in order to ensure sealing performance and operational safety during the experiment. Additionally, a host computer software is presented in this article for data recording and analysis to realize real-time recording and saving of experimental data, as well as generating pressure curves. The flange-type apparatus is calibrated mainly through the measurement of two metrological parameters, which are indication error and set pressure retention error. Experimental verification has confirmed that this method can simultaneously calibrate both parameters, which can significantly improve the accuracy and efficiency of on-site calibration of flange-type apparatus to measure the water permeability of concrete.
Research on static calibration method of wind tunnel balance based on CNN
Authors: Fu Huawei , Jin Feng , Xu Yue , Tao Aihua , Qiao Liyan , Liu Wang
Published: December 2024

A wind tunnel balance is an important device for force measurement experiments in vehicle wind tunnel experiments and is used to measure the aerodynamic loads acting on the model. The static calibration of the balance is a critical step to ensure measurement accuracy. The traditional calibration method uses a fitting method based on the least squares method, which could be better for dealing with the nonlinear errors of the balance. In order to further improve the calibration performance of wind tunnel balance, this paper proposes a fitting method based on the Convolutional Neural Network (CNN). The mapping relationship between input and output is established for a six-component balance. The optimal parameters of the network model are explored. Through the analysis of the prediction results of the network model, it is found that the CNN balance calibration method is generally better than the traditional least squares fitting method in suppressing the error caused by system nonlinearity. The prediction accuracy of its components reaches the advanced index of the national military standard, which improves the fitting accuracy of the balance formula.
Experimental study of ARtag-based indoor localization techniques
Authors: Chen Chaoda , Chen Ziyang , Li Kangxing , Guo Junrong , Huang Zhixing , Lu Xuan
Published: December 2024

To address the limitations of traditional indoor localization techniques in indoor environments, the ARtag indoor localization technique is proposed to determine the optimal recognition distance to optimize the robot’s localization performance in indoor environments. The performance of the robot at different distances is evaluated by setting up an ARtag at different distances in an indoor environment, testing and comparing the robot’s recognition accuracy and response time at these distances. The experimental results show that at a distance of 25 cm, the robot has the fastest response speed and the highest stability, with a recognition accuracy of 100% and a response time of only 0.39 ms. The ARtag indoor localization technique can significantly improve the robot’s localization performance at specific distances, which can provide a basis for optimizing the performance of indoor robotic applications.
Research on dynamic swing experiment of atomic gravimeter based on the inertially stabilized platform
Authors: Che Hao , Li An , Ma Jinxiu , Han Yu , Qin Fangjun
Published: December 2024

Based on the principle of quantum interference, with excellent accuracy, sensitivity, and stability, miniaturized and portable atomic gravimeters are gradually exploring the possibility of applying them to mobile platforms such as ships. However, the vibration noise brought by the dynamic environment has a great influence on it. To explore the stability and reliability of the atomic gravimeter in the mobile platform, we built a dynamic measurement system of the atomic gravimeter in the laboratory. With the help of the swing test bench, the swing of the roll and pitch directions was added to the system to simulate the wave environment, and the dynamic swing experiment was carried out. By changing different swing levels, the system can work in different vibration environments and measure the gravity value. The experimental results show that the atomic gravimeter can work normally in various swing environments, and the internal coincidence accuracy of 1.861 mGal is achieved. The measurement standard deviation of 2.194 mGal and the resolution of 1.160 mGal@48 s are obtained under static conditions. The measurement standard deviation of 34.200 mGal and the resolution of 9.538 mGal@48s are obtained under mixed swing conditions. Under the condition of mixed rolling, the standard deviation of the interference phase noise of the atomic gravimeter and its contribution to the resolution of gravity measurement reach 23.121 π mrad and 2.045×10−6 g/shot, respectively. Our work provides a new reference for the research of high-precision atomic gravimeters based on quantum sensing technology in the field of gravity measurement in ship-borne environments.
Detection of concrete reinforcement condition based on Decay Time Constant
Authors: Ren Xiao , Wu Haitao , Li Yong , Wu Zhaoguo , Bao Jiankang , Zhou Xiaolong , Zhou Qing
Published: December 2024

Reinforced concrete (RC) is widely used in all kinds of building facilities and electric power infrastructure. When its internal reinforcement structure is unreasonable or the quality of reinforcement is not up to standard, the performance of RC will be greatly reduced, resulting in a huge safety hazard. In this paper, a non-destructive testing method based on pulsed eddy current (PEC) for the state of internal reinforcement in concrete is proposed with concrete poles as the research object. The relationship between PEC response and the multiple parameters of the reinforcement has been analyzed, the decay time constant (DTC) is obtained, and a simulation model is built to demonstrate the connection between the DTC and the electrical conductivity, relative magnetic permeability, and thickness. Finally, a simulation model is constructed to verify the effectiveness of the proposed method for rebar condition detection.
Real-time 3D human pose estimation system based on multi-views
Authors: Cai Huiqi , Han Peng
Published: December 2024

Multi-view-based real-time 3D human pose estimation systems have seen widespread application across various domains, including sports, virtual reality, film production, and video surveillance. Despite significant advancements at the algorithmic level, the challenge of real-time performance remains a critical factor that restricts the full application potential of these systems. The synchronization and fusion of data from multiple cameras, high computational complexity, and the rigidity of system architecture contribute to the difficulty in balancing speed and accuracy within existing systems. In response to these challenges, a real-time 3D human pose estimation system based on multiple views has been proposed. This system achieves synchronization of data from multi-views, incorporates a lightweight model design, and implements parallel processing within its architecture. As a result, it is capable of outputting high-precision 3D human poses at a real-time speed of 25.56 FPS.
Innovation in nitrogen concentration measurement method based on TRIZ
Authors: Zhu Huibo , Song Wei , Xing Chunhua , Wang Lixin
Published: December 2024

The current UV curing (Ultra-Violet Ray Curing) process necessitates the absence of oxygen, and the industrial standard often achieves this by replacing air with nitrogen to attain a nitrogen concentration of 99.97%, thereby fulfilling process requirements. However, the existing nitrogen concentration measuring instruments with a response time of 30 s are incapable of directly ascertaining whether the nitrogen concentration within the chamber has already reached 99.97% prior to those 30 s. This paper systematically analyzes the issues in the current measurement system through the application of the Theory of Inventive Problem Solving (TRIZ), encompassing Function Analysis, Cause -Effect Chain Analysis, Engineering Contradiction and Inventive Principles [1, 2]. Furthermore, a novel nitrogen measurement scheme is proposed to clarify the temporal profile of nitrogen concentration during the displacement process, thereby providing a basis for accurately setting the nitrogen displacement time. This approach can lead to a reduction in nitrogen wastage and shorten production cycles.
Intelligent recognition of atomic saturated absorption spectra based on 1D Convolution Neural Network
Authors: Zhu Yuchen , Liang Changwen , Huang Yihang , Zhu Lingxiao
Published: December 2024

Laser frequency locking technology is widely used in quantum precision measurement, quantum simulation, quantum information, etc. The conventional frequency locking process based on the saturated absorption spectrum needs to find the target peak corresponding to a specific frequency manually. However, due to the complexity of atomic energy level structure and drifts caused by the parameters of semiconductor lasers in different environments, it is usually time-consuming and related to the experience of operators. To solve the above problems, a new approach based on machine learning has been proposed. Using the one-dimensional convolution neural network combined with the gradient analysis method, the recognition accuracy of 0.9784 and high precision of feature extraction have been achieved. The approach presented in this paper combines laser frequency locking in the quantum field with AI and addresses the bottleneck issue in intelligent frequency locking of semiconductor lasers, which holds significant reference value.
GRU-based anomaly monitoring method for injection molding equipment
Authors: Xie Xiaobo , Zhang Zilin , Hu Mingxue , Liao Jige , Zheng Gengzhe
Published: December 2024

For the prediction of abnormal states in the overall injection molding equipment, this paper proposes a novel idea of GRU-based anomaly monitoring for injection molding equipment, thereby enriching research in this field. Firstly, the existing multimodal data of injection molding equipment is mined, and a prediction model is trained using GRU as the benchmark model for simulating the prediction of abnormal states. Finally, practical examples are used for verification. Experimental results show that this method can effectively monitor the abnormal states of injection molding equipment. Currently, there are relatively few studies on the prediction of abnormal states in the overall injection molding equipment. The method proposed in this paper enriches research in this area and has practical significance.
Research on multi-scale defect detection methods based on image segmentation and multi-model parallel inference
Authors: Liu Xiali , Wu Guangdong , Wei Long , Cao Jialun , Deng Yaohua
Published: December 2024

To address the problem of insufficient extraction of tiny chipping features and low detection accuracy due to large-scale differences in photovoltaic (PV) silicon wafers defect detection, this paper proposes a detection strategy based on image segmentation and multi-model parallel inference. By segmenting the image and independently detecting the sub-images, we enhance the capture of local features and enlarge the receptive field. Furthermore, we utilize differentiated models for parallel inference, employing separate models for edge-chipping sub-images and full broken wafer images. With 10 parallel threads processing concurrently, this approach not only accelerates the detection process but also effectively improves the detection rate of small edge-chipping defects. The experimental results show that the proposed method in this paper is able to detect both broken wafer and edge-chipping defects, and the detection rate of edge-chipping defects is dramatically improved compared to the single model detection. The mAP of the YOLOv8m and YOLOv8m-p2 models are 0.704 and 0.771, respectively, which are improved by 30% compared to that before the unsegmentation.
Research on multi-sensor data fusion fault diagnosis method for rotating parts of injection molding machine
Authors: Liao Jige , Xie Xiaobo , Deng Yaohua
Published: December 2024

In the field of fault diagnosis of rotating parts of injection molding machines, traditional methods often rely on single sensor data, which makes it difficult to comprehensively capture the complex dynamic characteristics of the system operation, limiting the accuracy and reliability of diagnosis. To overcome this challenge, this paper proposes a multi-sensor data fusion fault diagnosis method combining graph convolution and Transformer neural network. A constraint-based Bayesian network structure learning algorithm is adopted to fuse vibration and current multi-sensor data, and a graph structure reflecting the basic dependency relationship between sensor data is constructed; a multi-head self-attention mechanism for weight allocation of the basic dependency relationship between multi-sensor data is investigated; and a model architecture taking into account the global and local features of multi-sensor data is constructed by combining graph convolution and Transformer neural network. Experiments show that the fault diagnosis accuracy of the method proposed in this paper reaches 99.20%, which is 5.4% higher than that of single sensor data, proving the effectiveness and accuracy of the method proposed in this paper. Finally, it is applied in the actual scenario of an injection molding machine, and the experimental effect is good.
Intrusion sound and light alarm method for radiation detection operation site based on infrared induction radar
Authors: Fan Yi , Hua Xiongfei , Ji Hui , Zeng Zhikun
Published: December 2024

A method based on infrared induction radar is proposed for intrusion sound and light alarms in radiation detection operation sites. We will use infrared sensors to sense the thermal radiation of human bodies or objects within the work site, and monitor specific areas through the constructed infrared light “wall”. When someone or an object enters the preset alert area and blocks the infrared beam, the sensor will quickly detect changes in thermal radiation and monitor and track potential intruders in real time, then trigger the alarm system. The alarm system emits strong sound and light signals through sound and light alarms to deter intruders and notify relevant personnel, ensuring the safety of the work site. The experimental results show that this method has the characteristics of high efficiency, sensitivity, and reliability, and is suitable for radiation detection operation sites and other places that require high safety requirements, effectively improving the level of safety protection.
Fault diagnosis of pneumatic control valve based on Bat Optimization algorithm and BP neural network
Authors: Xu Bing , Fei Dongyi
Published: December 2024

This article proposes a fault diagnosis model for pneumatic control valves based on a bat optimization (BA) algorithm and backpropagation (BP) neural network. The DAMADICS platform simulates the pneumatic industrial process control valve failures, and the fault signals are collected to construct the data set. A fault diagnosis model combining the Bat Optimization algorithm and Back Propagation neural network (BA-BP) is built, and four common faults are injected for experiments. The method is compared with Support Vector Machine (SVM), BP, and Bayesian optimized BP (BO-BP). Experimental results indicate that BA-BP has high diagnostic precision in the diagnosis of malfunctions in pneumatic valves.
Defect detection for polyethylene pipelines based on ultrasonic-guided waves
Authors: Liu Yang , Mai Huaming , Cheng Mengfei , Li Hongzhao , Zhang Weiwei , Lin Rong
Published: December 2024

The identification of small non-penetrating defects in polyethylene (PE) pipes, utilizing ultrasonic-guided waves, serves as the cornerstone for ensuring the safe operation of these pipes. However, owing to the PE pipe material characteristics, the guided wave has high attenuation in PE pipe, which seriously limits the detection range and accuracy of the guided wave. To address this problem, the dispersion and dissipation characteristics of ultrasonic-guided waves in PE pipes were derived, and the results indicated that the excitation frequency was the important parameter affecting the propagation distance. Then, an experimental platform for PE pipe testing was built using macro fiber composites. The acoustic attenuation coefficient and dispersion were calculated. After considering the effects of dissipation and dispersion on the guided wave, the optimal excitation frequency was selected to extend the guided wave detection distance to 4 m. Finally, an experimental study on ultrasonic-guided wave detection of defects in PE pipes was conducted. The experimental results showed that non-penetrating small defects with a section loss rate of 8% could be effectively identified and located using ultrasonic-guided waves.
Wind turbine gearbox bearings fault detection based on TCN-Attention-MTBO
Authors: Zhang Tianjie , Cheng Xiangheng
Published: December 2024

In recent years, the new wind turbine gearbox, as the key to promoting wind power generation technology, is regarded as the future direction to alleviate the energy crisis, so the detection of gearbox-bearing faults has become a research hotspot. Based on this, this paper proposes a new wind turbine gearbox-bearing fault detection method based on the improved TCN-Attention-MTBO model. First, a temporal convolutional network (TCN) is used to effectively capture and extract the key features in the gearbox-bearing signal. Secondly, the key features are given weights by combining the self-attention mechanism, to increase the weight proportion of effective features. Finally, the MTBO algorithm is used to automatically search the three key parameters in the TCN network. The results show that the proposed model achieves a classification accuracy of 98.75% on the public data test set. Meanwhile, compared with other classical classification models, the accuracy is improved by up to 12.92%, and the Recall, Precision, and F1 values are also improved, which realizes the accurate detection of wind turbine gearbox bearing faults.
Flexible arc suppression control method for single-phase grounding fault current in distribution network
Authors: Liu Delin , Liu Baowen , Cai Jiamin , Yu Baoqi
Published: December 2024

This research presents a closed-loop control technique grounded in multi-proportional (MPR) resonance to improve the stability of the output waveform of the arc suppression device and achieve precise arc suppression, in response to the problem of incomplete arc suppression caused by external interference in the distribution network grounding current. Firstly, we calculate the optimal injection current required for arc suppression before the fault occurs and use it as the reference current for closed-loop control. Secondly, after a fault occurs, the injected current is monitored in real-time, the reference current is subtracted from the actual injected current, and the difference is input into the current closed loop as a feedback parameter to adjust the injected current to approach the reference current and improve its controllability. After simulation verification, the arc suppression control method described in this piece can achieve a current control accuracy of 97%, effectively regulating injection as a reference value and suppressing fault currents.
Study on induced voltage of DC transmission lines and its influencing factors
Authors: Wen Junyi , Yu Haisheng , Liu Yang , Jin Guoliang
Published: December 2024

To address the issue of induced voltage that may occur during the maintenance and repair of intersecting lines below ultra-high voltage ±800 kV DC transmission lines, which poses a threat to the safety of maintenance personnel, this paper analyzes the formation mechanism of induced voltage based on the principles of electrostatic fields. By modeling an actual ±800 kV transmission line and using EMTP simulation software, the variations in induced voltage were simulated under various factors such as voltage level, parallel line length, and soil resistivity. The simulation analysis results indicate that the electrostatic-induced voltage of DC lines increases with the voltage level, parallel running length, sag, soil resistivity, and the number of split conductors; it decreases with the increase of the distance from the center and the crossing angle; and it is essentially unaffected by the operating current. Therefore, the findings of this paper have significant practical value for the protection against induced voltage in future DC high-voltage transmission lines.
Maximum power point tracking control and power distribution of marine current power system based on hybrid energy storage
Authors: Wang Ruiwang
Published: December 2024

With the development of industry in modern society leading to the energy crisis and the problem of the earth’s environmental pollution, it is especially important to generate electricity from renewable and clean energy sources. Marine current power generation, as a form of marine energy use, is also the object of widespread concern at home and abroad. A system consisting of supercapacitors and batteries can smooth out the fluctuations of the generating power. Power distribution is a necessary step to achieve smooth grid-connected power fluctuation by using the hybrid energy storage system (HESS). In the article, low-pass filter (LPF) and empirical mode decomposition (EMD) algorithms are used to distribute the marine current power generation, and the simulation experimental model of the present system is constructed in the Matlab/Simulink environment. Results of the simulation experiments show that the power curve of the generator side is obtained, and the generation power distribution is realized. Power signals of different frequencies are separated through the power distribution, so as to obtain the reference power of supercapacitors and the batteries.
Design and implementation of terminal power information collection and control system based on low-code platform
Authors: Qin Weiming , Guo Wenjing , Lin Jingwen , Chen Xuerui , Li Jiahao , Ming Meng
Published: December 2024

As the number of power consumption collection terminals continues to increase, the business needs for remote signaling and telemetry data collection through interface services continue to expand. Different professional collection front-end openness levels and open standards are not unified, and each professional terminal can only be managed in a decentralized manner. As a result, the current power consumption information data collection capabilities are scattered. In general, active data collection and sensing in enterprises must rely on various collection services to carry out applications. The lack of unified operation and management mechanisms and tools leads to difficulties in the development of interfaces and the management of terminal equipment. A set of power consumption information collection service integration systems developed based on a low-code platform is proposed. In view of the different communication protocols of power terminals and the need to develop different interfaces, etc., the command issuance and message encapsulation of different power collection protocols is carried out, to provide customized collection services and improve unified access and management capabilities of terminals.
Transformers partial discharge pattern recognition based on Vision Transform
Authors: He Shifang
Published: December 2024

The secure and stable operation of modern electricity systems depends on the reliable performance of transformers. Partial discharge (PD), as a common fault phenomenon in transformers, has a significant impact on its performance and lifetime. Traditional PD identification methods rely on manual feature extraction and lack generalization capability. In addition, this paper proposes a partial discharge recognition method based on Vision Transformer (ViT), which utilizes the self-attention mechanism of the visual transformer to accurately recognize partial discharges in transformers. Through the training and testing of the transformer partial discharge mapping dataset, the results show that the method in the present paper outperforms the traditional method in terms of recognition accuracy and stability, and the accuracy is maintained between 96.24% and 97.08%, which has a good prospect for engineering applications.
Optimization control of distribution network voltage based on voltage level and power factor segmentation
Authors: Ma Xiang , Shen Xi , Fang Xuan , Lv Leiyan , Song Xin , Mao Huibao
Published: December 2024

This article deeply analyses the model and calculation method of distributed energy in reactive power generation and absorption operation modes. It proposes an optimized control model and optimization method based on the segmented power factor of the distribution network voltage level. Simulation calculations were conducted. The results showed the effectiveness, economy, and balance of the reactive power optimization model and algorithm considering voltage level and power factor segmentation.
Risk assessment of belt conveyor belt in thermal power plant based on Bow-tie model and uncertainty Fuzzy Dynamic Bayesian Network
Authors: Liu Xin , Zhou Chongbo , Jiang Wen , He Hui , Liu Hao
Published: December 2024

In thermal power plants, coal conveyor belts pose significant risks that jeopardize the stability of the energy supply, underscoring the need for effective risk management. To address the complexity, uncertainty, and polymorphism issues in belt conveyor systems, we introduce a BT-UFDBN risk analysis method specifically for coal conveyor belts. This method develops a typical Bow-tie model, identifies potential risk factors for unplanned stoppages, and utilizes fuzzy evaluation methods and an improved SAM method to determine prior probabilities. The Bow-tie (BT) model is then mapped into a Dynamic Bayesian Network (DBN). To manage uncertainties within the DBN, the Leaky Noisy-OR gate model, stationarity, and first-order Markov assumptions are employed to ensure the model’s validity and practical relevance. This paper uses a belt conveyor system from a thermal power plant as a case study to validate the model’s effectiveness in predicting accident consequences, diagnosing fault causes, and proposing targeted preventive measures for identified weak points. The study provides theoretical guidance for risk management of coal conveyor belts in power plants.
Polynomial fitting calibration method for K-type thermo-couples based on the least squares method
Authors: Li Xingyu
Published: December 2024

Thin-film thermocouples, a crucial technology for accurate temperature measurement, have attracted considerable attention in energy utilization, environmental monitoring, and advanced manufacturing. This paper provides an overview of the evolution of thin-film thermocouples, with a focus on the calibration methods and experimental performance of K-type thermocouples. Utilizing a five-layer film structure that includes a polyimide substrate, aluminum oxide insulation layer, nickel-chromium and nickel-silicon metal films, and a silicon oxide protective layer, we have designed and implemented a new thin-film thermocouple temperature measurement system, which has been experimentally validated for stability and repeatability under high-temperature conditions. The results indicate that the system demonstrates excellent thermoelectric potential output and good repeatability in temperature measurement within the range of 50°C to 250°C. Although the long-term stability in extremely high-temperature environments requires further study, this research provides theoretical and experimental support for the future development of thin-film thermocouple technology.
Fault Detection selection method for distribution network based on regional amplification of grounding current and double closed-loop feedback control
Authors: Yu Baoqi , Liu Baowen , Liu Delin , Cai Jiamin
Published: December 2024

The susceptibility of high-resistivity ground faults in power systems, coupled with systemic imbalances, can result in the distortion of fault characteristics, leading to erroneous fault line selection. In addition, the full compensation of fault arc suppression conceals the fault characteristics, which brings difficulties to fault detection. In order to take into account the needs between fault arc suppression and fault detection, and tackle the issue of high-impedance fault line discrimination with a comprehensive and innovative approach, this paper studies the approach to line selection based on double closed-loop feedback control and amplification of the grounding current region. It enables adaptable grounding of the neutral point when a transient ground fault arises, and priority is given to ensuring fast and reliable arc suppression. In the event of a persistent grounding fault, the flexible grounding of the neutral point through the current source serves to mitigate the deleterious effects of fault deterioration, and the fault current is flexibly modulated within a relatively safe range until the requirements of fault arc suppression and fault detection are met.