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Abnormal State Detection of OLTC Based on Improved Fuzzy C-means Clustering

Chinese Journal of Electrical engineering 2023年第1期9卷 129-141页

作者： Hongwei Li Lilong Dou Shuaibing Li Yongqiang Kang Xingzu Yang Haiying Dong School of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou 730070China School of New Energy and Power Engineering Lanzhou Jiaotong UniversityLanzhou 730070China

An accurate extraction of vibration signal characteristics of an on-load tap changer(OLTC)during contact switching can effectively help detect its abnormal ***,an improved fuzzy C-means clustering method for abnormal state detection of the OLTC contact is ***,the wavelet packet and singular spectrum analysis are used to denoise the vibration signal generated by the moving and static contacts of the ***,the Hilbert-Huang transform that is optimized by the ensemble empirical mode decomposition(EEMD)is used to decompose the vibration signal and extract the boundary spectrum ***,the gray wolf algorithm-based fuzzy C-means clustering is used to denoise the signal and determine the abnormal states of the OLTC *** analysis of the experimental data shows that the proposed secondary denoising method has a better denoising effect compared to the single denoising *** EEMD can improve the modal aliasing effect,and the improved fuzzy C-means clustering can effectively identify the abnormal state of the OLTC *** analysis results of field measured data further verify the effectiveness of the proposed method and provide a reference for the abnormal state detection of the OLTC.

关键词： On-load tap changer singular spectrum analysis Hilbert-Huang transform gray wolf optimization algorithm fuzzy C-means clustering

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On-Policy and Off-Policy Value Iteration Algorithms for Stochastic Zero-Sum Dynamic Games

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Journal of Systems Science & Complexity 2025年第1期38卷 421-435页

作者： GUO Liangyuan WANG Bing-Chang ZHANG Ji-Feng School of Control Science and Engineering Shandong UniversityJinan 250063China School of Automation and Electrical Engineering Zhongyuan University of TechnologyZhengzhou 450007China Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China

This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown ***-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games,where the system dynamics is not *** analyzing the value function iterations,the convergence of the model-based algorithm is *** equivalence of several types of value iteration algorithms is *** effectiveness of model-free algorithms is demonstrated by a numerical example.

关键词： Approximate dynamic programming on-policy off-policy stochastic zero-sum games valueiteration

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New Results in Cooperative Adaptive Optimal Output Regulation

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Journal of Systems Science & Complexity 2024年第1期37卷 253-272页

作者： DONG Yuchen GAO Weinan JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China Department of Electrical and Computer Engineering Tandon School of EngineeringNew York UniversityBrooklynNY 11201USA

This paper investigates the cooperative adaptive optimal output regulation problem of continuous-time linear multi-agent *** the multi-agent system dynamics are uncertain,solving regulator equations and the corresponding algebraic Riccati equations is challenging,especially for high-order *** this paper,a novel method is proposed to approximate the solution of regulator equations,i.e.,gradient descent *** is worth noting that this method obtains gradients through online data rather than model information.A data-driven distributed adaptive suboptimal controller is developed by adaptive dynamic programming,so that each follower can achieve asymptotic tracking and disturbance ***,the effectiveness of the proposed control method is validated by simulations.

关键词： Adaptive dynamic programming cooperative output regulation gradient descent method multi-agent systems.

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Quality-Oriented Dynamic Sparse Latent Variable Detection Approach for Industrial IoT Based on Joint Spatial and Temporal Decomposition

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IEEE Internet of Things Journal 2025年第11期12卷 17558-17568页

作者： Ma, Hao Wang, Yan Liu, Xiang Yuan, Jie Ji, Zhicheng Jiangnan University Engineering Research Center of Internet of Things Technology Applications Ministry of Education School of Internet of Things Engineering Wuxi214122 China Wuxi University School of Automation Wuxi214122 China

Quality-oriented fault detection facilitates intelligent inspection, operation optimization, and product quality improvement in the industrial Internet of Things. Data-driven latent variable-based approaches are among the mainstream methods in this field. However, traditional latent variable methods establish static relational models, which are less suited to the dynamic characteristics of industrial processes. To address this issue, dynamic latent variable methods, such as dynamic inner partial least squares (DiPLS), have been proposed. Despite this, the DiPLS method only enhances the descriptive capability of the partial least squares (PLS) method for dynamic characterization and does not overcome the inherent limitations of the PLS method in quality-oriented fault detection. Specifically, the residual subspace obtained by the PLS still contains quality-related information, which undoubtedly increases the false alarm rates and missed alarm rates in subsequent detection. Additionally, the DiPLS method does not address the problem of overfitting during the modeling process. To deal with the above issues, this article proposes a quality-oriented dynamic sparse latent variable method for efficient fault detection with respect to quality indicators. This method introduces a weight matrix to sparsity the coefficient matrix, enhancing the interpretability of the model while addressing the overfitting problem that may occur during the DiPLS modeling process. Furthermore, an alternating direction method of multipliers-based technology is studied to solve the corresponding optimization problem. To further refine the orthogonal decomposition of the process variable space, a joint temporal and spatial decomposition strategy is presented. This strategy accomplishes the orthogonal decomposition of the process variable space based on latent variable and time lag components, extracting the latent variables accordingly. Subsequently, the detection statistics and logic are derived

关键词： Least squares approximations

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Design of control system for solar power generation based on an improved bat algorithm for an island operation

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Energy Harvesting and Systems 2023年第2期10卷 199-212页

作者： Mensah Akwasi, Amoh Wei, Xie School of Automation Science and Engineering South China University of Technology Guangzhou China

Solar energy is sustained using the principle of photovoltaic effect through a solar photovoltaic (PV) system as the main receiver of sunlight for the island. The use of photovoltaic (PV) systems to generate power from solar energy has increased in recent years due to its availability and sustainability. The proposed bat algorithm provides a very quick confluence and high accuracy since it interactively merges with the exploration advancements with the substantial distinctive signal search during the maximum power point tracking process from the PV array. The improved bat algorithm proposes a signal search method to increase the speed and tracks more power at a longer distance by using the signal between the bat and its prey. An energy storage system (ESS) stores solar energy and releases it into the system for use when energy generation from the source is low. DC to DC converter controls and regulates the output generated voltage from the PV array. DC to AC converter converts DC power produced to AC power to be supplied to the island for use. The design and simulation were performed in MATLAB Simulink and the result shows the effectiveness of the proposed design. & amp;copy;2022 Walter de Gruyter GmbH, Berlin/Boston. © 2023 Walter de Gruyter GmbH. All rights reserved.

关键词： Solar energy

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Bearing Fault Numerical Model for the Closed-slot Rotor Submersible Motor

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Chinese Journal of Electrical engineering 2023年第2期9卷 84-93页

作者： Zhe Ke Bokai Guan Chong Di Jingwen Yan Xiaohua Bao School of Electrical Engineering and Automation Hefei University of TechnologyHefei 230009China School of Electrical and Computer Engineering The Ohio State UniversityColumbus OH 43210USA

A numerical model of the bearing fault of a motor with a closed-slot rotor using the finite element method(FEM)is *** rotor’s radial motion can be regarded as static eccentric at the defect time points and healthy at other time *** frequency of the harmonic component is analyzed corresponding to bearing fault in stator current according to the radial movement of the motor ***,the relative permeability variation region is established to achieve the radial motion of the rotor with bearing ***,the relative permeability variation region is established in the health and static eccentric ***,the defect time points are estimated and the static eccentricity model by transient field is ***,the relative permeability of the variable region in the static eccentric model is imported into the variable region of the health model at the defect time *** simulation results show that the air gap flux density of the bearing fault model is different from that of the health model and static eccentric *** addition,the stator current contains harmonic components of the bearing *** analysis results prove the applicability of the proposed model.

关键词： Bearing fault finite element method relative permeability variation region closed-slot rotor stator current

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Preconditioning for Accurate Threshold Voltage Extraction of SiC MOSFETs after AC Bias Temperature Instability in Reliability Tests 10

Preconditioning for Accurate Threshold Voltage Extraction of...

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10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia

作者： Chen, Cen Wang, Zicheng Zhang, Ruyue Ye, Xuerong Zhang, Xiaosheng Pan, Yanchen Lai, Yaokang Du, Jiangyuan Harbin Institute of Technology School of Electrical Engineering and Automation Harbin China China Jiliang University School of Electrical Engineering and Automation Hangzhou China

ISBN: (纸本)9798350351330

Due to their significant reliability issues, SiC MOS-FETs have faced limitations in their widespread adoption. One of the critical reliability concerns is related to the gate oxide layer of SiC MOSFETs, known as Bias Temperature Instability (BTI). This phenomenon describes the drift in the threshold voltage of SiC MOSFETs under gate bias and high-temperature. This reliability issue poses challenges for the design, manufacturing, and application of SiC MOSFETs. To accurately measure the drift, necessary preconditioning procedures and carefully designed test sequences are crucial. In this paper, the drift in the threshold voltage of SiC MOSFETs under AC gate stress was discussed through accelerated degradation tests, and the significance of preconditioning operation before analyzing the results was emphasized. © 2024 IEEE.

关键词： Threshold voltage

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Synthetical Thermal Modeling and Optimization Design for High Power Density Inverter Heat Dissipation

CPSS Transactions on Power Electronics and Applications

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CPSS Transactions on Power Electronics and Applications 2023年第1期8卷 3-12页

作者： Dai, Kemin Gong, Jinwu Lin, Wenqiang Pan, Shangzhi Zha, Xiaoming School of Electrical Engineering and Automation Wuhan University Hubei Wuhan430072 China

Demanding accuracy and reliability of thermal design for high efficiency and high-power density inverter devices. Integrating heat conduction, convection heat transfer and fluid dynamics theories, a synthetical thermal model based on the characteristic length as the square root of the cross-sectional area and a multi-objective optimization method based on entropy yield minimization theory and electrothermal coupling are proposed for a typical forced air-cooling heatsink system to improve the efficiency of design optimizations in the structure and cost. The fin thickness, fin length, number of fins, and air velocity of the heatsink are used as design variables, and the NSGA-III algorithm applying a prophet population is used to obtain the pareto fronts with minimum thermal resistance, cost and pressure loss as optimization objectives. Enhanced airflow through the heatsink by arranging the columns in a phyllotactic pattern. A temperature rise test by a 100 V/10 kW prototype was designed to prove the accuracy of the model proposed and heatsink optimized. At rated power, the surface temperature of power devices and heatsink has 10°C reduction. © 2017 CPSS.

关键词： Multiobjective optimization

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Analysis and Research on Mechanical Stress and Multiobjective Optimization of Synchronous Reluctance Motor

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CES Transactions on Electrical Machines and Systems 2024年第3期8卷 274-283页

作者： Han Zhou Xiuhe Wang Lixin Xiong Xin Zhang School of Electrical Engineering Shandong UniversityJinan 250061China School of Electrical and Electronic Engineering Shandong University of TechnologyZibo 255000China Shandong Kehui Power Automation Co. Zibo 255000China

The mechanical strength of the synchronous reluctance motor(SynRM)has always been a great *** paper presents an analysis method for assessing stress equivalence and magnetic bridge stress interaction,along with a multiobjective optimization *** the complex flux barrier structure and inevitable stress concentration at the bridge,the finite element model suitable for SynRM is ***,a neural network structure with two inputs,one output,and three layers is *** functions are constructed to enhance ***,the equivalent stress can be converted into a contour distribution of a three-dimensional stress *** contour line distribution illustrates the matching scheme for magnetic bridge lengths under equivalent ***,the paper explores the analysis of magnetic bridge interaction *** optimization levels corresponding to the length of each magnetic bridge are defined,and each level is analyzed by the finite element *** Taguchi method is used to determine the specific gravity of the stress source on each magnetic *** on this,a multiobjective optimization employing the Multiobjective Particle Swarm Optimization(MOPSO)technique is *** taking the rotor magnetic bridge as the design parameter,ten optimization objectives including air-gap flux density,sinusoidal property,average torque,torque ripple,and mechanical stress are *** relationship between the optimization objectives and the design parameters can be obtained based on the response surface method(RSM)to avoid too many experimental *** optimized model is compared with the initial model,and the optimized effect is ***,the temperature distribution of under rated working conditions is analyzed,providing support for addressing thermal stress as mentioned earlier.

关键词： Multiobjective optimization Neural network Stress equivalence Synchronous reluctance motor Taguchi method

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Identification of nonlinear process described by neural fuzzy Hammerstein-Wiener model using multi-signal processing

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Advances in Manufacturing 2023年第4期11卷 694-707页

作者： Feng Li Li Jia Ya Gu College of Electrical and Information Engineering Jiangsu University of TechnologyChangzhou213001JiangsuPeople’s Republic of China School of Mechatronics Engineering and Automation Shanghai UniversityShanghai200444People’s Republic of China School of Electrical Engineering and Automation Changshu Institute of TechnologyChangshu215500JiangsuPeople’s Republic of China

In this study,a novel approach for nonlinear process identification via neural fuzzy-based Hammerstein-Wiener model with process disturbance by means of multi-signal processing is *** Hammerstein-Wiener model consists of three blocks where a dynamic linear block is sandwiched between two static nonlinear ***-signal sources are designed for achieving identification separation of the Hammerstein-Wiener *** correlation analysis theory is utilized for estimating unknown parameters of output nonlinearity and linear block using separable signals,thus the interference of process disturbance is ***,the immeasurable intermediate variable and immeasurable noise term in identification model is taken over by auxiliary model output and estimate residuals,and then auxiliary model-based recursive extended least squares parameter estimation algorithm is derived to calculate parameters of the input nonlinearity and noise ***,convergence analysis of the suggested identification scheme is derived using stochastic process *** simulation results indicate that proposed identification approach yields high identification accuracy and has good robustness.

关键词： Nonlinear process Parameter identification Hammerstein-Wiener model Neural fuzzy model Multiple signal processing

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