Table of Content

30 October 2023, Volume 0 Issue 10

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Overview

Review of Research on Remaining Useful Life Prediction of Relays Based on Deep Learning

LI Shaofei, WANG Zhaobin, ZHANG Wenhang

2023, 0(10):  1-7.  doi:10.16628/j.cnki.2095-8188.2023.10.001

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Studying the reliability of individual relays is of great significance. Therefore, it is necessary to predict the lifespan of relays. Due to the excessive reliance of traditional prediction methods on the equipment domain knowledge, the deep learning is applied to the field of life prediction. Firstly, the storage failure mechanism of relays is summarized. Secondly, the current research status of relay remaining useful life prediction is introduced. Then, several common model methods and their characteristics of deep learning are analyzed. Finally, the application of deep learning in the remaining useful life prediction is prospected.

Research & Analysis

Analysis of Dynamic Characteristics Influencing Factors of Rapid Repulsion Mechanism in Demagnetization Switch

DONG Li, MA Shaohua

2023, 0(10):  8-13.  doi:10.16628/j.cnki.2095-8188.2023.10.002

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In order to improve the breaking speed of the rapid repulsion mechanism and meet the requirements of demagnetization switch applications, the finite element method is used to establish a two-dimensional axisymmetric model of the rapid repulsion mechanism with Maxwell electromagnetic simulation software according to the dynamic characteristics requirements of the demagnetization switch for the rapid repulsion mechanism. The effects of the thickness, radius, material, spacing, coil turns, capacitance, and voltage of the repulsive disk on the dynamic characteristics of the rapid repulsion mechanism are analyzed through simulation. The results show that the optimizing relevant parameters can improve the dynamic characteristics of the fast repulsion mechanism, and the simulation results provide guidance for the prototype design of the fast repulsion mechanism.

Research on Backflow Power Optimization Strategy for Dual-Active-Bridge DC-DC Converter

KANG Zhiwei, XU Yuzhen

2023, 0(10):  14-20.  doi:10.16628/j.cnki.2095-8188.2023.10.003

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Aiming at the value of the backflow power of dual-active-bridge DC-DC converter is too large during power transmission, based on the dual-phase-shift control, the segmented optimization control strategy is proposed to optimize the backflow power. In the control strategy, the whole output power is divided by defining the power segmentation point. When the output power is lower than the power segmentation point, zero backflow power operation is realized.When the output power is higher than the power segmentation point, the minimum backflow power operation is realized. Finally, a 250 W experimental prototype is built. The experimental results show that compared with the traditional phase shift control method, the segmented optimization control strategy can effectively reduce the backflow power of the dual-active-bridge DC-DC converter and improve the efficiency of the circuit.

Primary Frequency Control Strategy for Inverter Air Conditioner Considering User Behavior

LIU Meiyan, WANG Juanjuan

2023, 0(10):  21-27.  doi:10.16628/j.cnki.2095-8188.2023.10.004

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With the development of power system, the stable operation of frequency is facing great challenges, and the cost of generation side is also increasing rapidly. In order to address the many adverse effeds faced by the power grid and involve the load side in power grid frequeney regulation, a hierarchical control strategy of inverter air conditioner participating in primary frequency modulation based on improved droop control is proposed. According to the characteristics of inverter air conditioner, the aggregation model based on the first-order physical model is established, and the droop control model is improved.Considering the state of indoor temperature with air-conditioner (SOA) and the comfort of users, an orderly participation response control strategy of inverter air conditioners based on SOA priority list is established. It can efficiently dispatch inverter air conditioners and adjust the frequency.

Research on Decomposition of Influencing Factors and Prediction Methods of Carbon Emissions in Industrial Sector

CHU Linlin, ZONG Ming, LI Qinyu, CHEN Yanjun, ZHU Xia, LIU Yiting, GU Jie

2023, 0(10):  28-35.  doi:10.16628/j.cnki.2095-8188.2023.10.005

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The industrial sector is one of the main sources of global carbon dioxide emissions. Understanding the factors that affect carbon emissions in the industrial sector can help to develop the targeted optimization measures to reduce carbon emissions. Meanwhile, predicting carbon emissions can achieve to control and adjust future carbon emissions, and formulate the corresponding policy measures to guide and regulate the development of the industrial sector. Firstly, a calculation model of the industry's carbon emission contribution is coustructed through the logarithmic mean Divisia index (LMDI) decomposition method, and the contribution of various influencing factors to carbon emissions is analyzed. Further combining the analysis results of factor decomposition method, a stochastic impacts by regression on population, affluence and technology (STIRPAT) model is constructed to predict the carbon emissions of various industries in the industrial sector. Finally, a study is conducted on an industrial sector in a certain region of China, and the results verify the feasibility of the proposed model.

Short-Term Photovoltaic Output Prediction Based on CEEMDAN and Improved LSTM

HUANG Junzhe, YIN Yuhan, TANG Mingxuan, MEI Fei

2023, 0(10):  36-43.  doi:10.16628/j.cnki.2095-8188.2023.10.006

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In order to improve the accuracy of photovoltaic output power prediction, a model that combines complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm with improved long short-term memory (LSTM) neural network is proposed to predict short-term photovoltaic power. Firstly, the photovoltaic power sequence is decomposed by CEEMDAN algorithm and the subsequence components are obtained. Then, improved LSTM neural network is used to predict each subsequence component. Particle swarm optimization (PSO) algorithm is used to optimize the number of hidden layer neurons, learning rate and training times of LSTM neural network. The attention mechanism is used to optimize the probability distribution in the process of training LSTM neural network. Finally, the final predicted value is obtained by adding the predicted results of each subsequence component. Example analysis shows that prediction evaluation indexes of the proposed model MAE, RMSE and R²are all the best by comparison with other algorithms, which can verify the superiority of the proposed model.

Detection & Experiment

Design on Testing System for Pull-in Characteristics of AC Electromagnet

GU Zhihao, GUO Jing, ZHANG Chao, DU Qingfeng, REN Wanbin

2023, 0(10):  44-48.  doi:10.16628/j.cnki.2095-8188.2023.10.007

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The pull-in action of AC electromagnet directly determines its work performance and electrical on-off control performance.The novel testing system for the pull-in characteristics of AC electromagnet is designed. The highlights include the adjustable magnetic gap, the controllable closing phase angle and the simultaneous measurement of coil voltage, coil current and dynamic force. Finally, taking the electromagnetic system of AC contactor as an example, the typical waveforms of the pull-in process of AC electromagnet are recorded and analyzed, and the effects of the point-on-wave on collision force and pull-in time are investigated.

Short Circuit Testing System for DC Circuit Breaker Used in Communication

HUANG Fang, ZHANG Liqian, ZHANG Yan

2023, 0(10):  49-53.  doi:10.16628/j.cnki.2095-8188.2023.10.008

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Based on the rated DC operating voltage characteristics of communication DC circuit breakers, a short-circuit testing system for communication DC circuit breakers is designed using a large capacity multi magnetic circuit transformer. The system adopts the built-in rectifier circuit and the regulating impedance nearby, the independent control systems and mobile measurement systems to test a maximum short-circuit current capacity of 25 kA for rated voltage DC 100 V and below, which can be suitable for short-circuit testing of communication DC circuit breakers.

Design of Automatic Testing System for Contact Parameters of 1/2 Crystal Cover Sealed Relay

MA Hangyu, LIANG Huimin, CHEN Hao, LUO Fubiao, ZHOU Zhefeng, FENG Keyun

2023, 0(10):  54-60.  doi:10.16628/j.cnki.2095-8188.2023.10.009

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To address the shortcomings of poor accuracy, low efficiency, time-consuming and labor-intensive testing, as well as damage to the contact spring of the 1/2 crystal cover sealed relay contact spring system when using traditional manual methods for contact parameter testing, a contact parameter automatic testing system is designed and implemented using a certain type of 1/2 crystal cover sealed relay contact spring system as the testing object. The system uses machine vision detection technology to automatically test the contact gap, and uses an electric sliding table combined with a acrylic meter to automatically test the initial pressure of the contact. The automatic testing is conducted on the contact spring samples of the same type of relay. The experimental results show that the testing accuracy of the system's contact gap is higher than 1 μm, and the test accuracy of the contact initial pressure is 1 mN, which can ensure the consistency of contact parameters during relay assembly.

Series Arc Fault Detection Method for Photovoltaic System Based on Improved Singular Value Decomposition Denoising Algorithm

CHEN Xinkai, BAO Guanghai

2023, 0(10):  61-69.  doi:10.16628/j.cnki.2095-8188.2023.10.010

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Aiming at the problem that the calculation speed of the singular value decomposition denoising algorithm for constructing Hankel matrix is slow, an improved singular value decomposition denoising algorithm is proposed. The algorithm increases the delay step of data points between rows of Hankel matrix to reduce the attractor track matrix andaccelerate the calculation speed. Besides, the effective order of singular values is obtained by combining the difference spectrum method of singular value energy and the mean value method of singular value energy to ensure good denoising effect. On this basis, a series arc fault detection method of photovoltaic system based on improved singular value decomposition denoising algorithm is proposed. Firstly, the improved singular value decomposition denoising algorithm is used to remove the noise. Secondly, the FFT and wavelet transform are used to analyze the signal. The sum of harmonic amplitude values and the energy of wavelet detail coefficients d₂ and d₃ are selected as the feature vectors. Finally, the linear support vector machine (LSVM) is used to realize arc detection. The experimental results show that the propsed method has high accuracy.

Analysis of Overload Breaking Testing System and Testing Method for Fuses

LI Saisai, MIAO Benjian, ZHANG Dafen, ZHOU Xiaomeng, LIN Zhili, GUO Xiangrong

2023, 0(10):  70-75.  doi:10.16628/j.cnki.2095-8188.2023.10.011

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In order to solve the problem that the fuse breaks in advance in the preheating stage or takes a long time to break in the full-voltage circuit due to the inaccurate judgment of the preheating transition time during the fuse breaking capability test using the existing fuse overload breaking test system in the laboratory, the fusing process of the fuse and the changing trend of the port voltage are analyzed. A testing method using the voltage slope of the fuse port as the criterion is proposed. The voltage fitting formula and control program are designed and verified by the simulation and experiment. The simulation and testing results show that the curve fitted by the formula is perfectly consistent with the actual testing waveform. The control program determines the preheating conversion time and performs the preheating conversion operation. After switching to the full voltage loop, the flow passing time is controlled within 3 seconds, and the ideal testing results are obtained. The testing system and control method mentioned are suitable for different types and voltage levels of fuses, and have high application value.

1D Simulation and Experiment for Dynamic Characteristic of Magnetic Latching Relay

ZHAO Yong, WU Duanjian, LIU Lei

2023, 0(10):  76-80.  doi:10.16628/j.cnki.2095-8188.2023.10.012

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To study the dynamic characteristics of the magnetic latching relay, the 1D mechanical-electrical-magnetic coupling model is built based on Modelica. Firstly, the magnetic circuit simulation is conducted in Maxwell to obtain the static characteristic data such as electromagnetic torque and inductance, and coupled with the mechanical and circuit systems built on the Modelica platform to achieve the simulation and solution of relay dynamic characteristics. Finally, the high speed camera is used to test the dynamic characteristics for the electrical mechanism to validate the previous simulation model. The conclusions are valuable for optimizing the product.