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Research on state monitoring system of high-pressure servo motor based on SVDD and SVM

Zhendong yu Chongji/Journal of Vibration and Shock 2025年第12期44卷 238-248页

作者： Ma, Liqiang Jiang, Anqi Jiang, Wanlu Zheng, Yunfei Wu, Fenghe Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control Yanshan University Qinhuangdao066004 China Key Laboratory of Advanced Forging & Stamping Technology and Science Ministry of Education Yanshan University Qinhuangdao066004 China School of Electrical Engineering Yanshan University Qinhuangdao066004 China School of Mechanical Engineering Yanshan University Qinhuangdao066004 China

In the monitoring of high-pressure servo motor, the number of normal samples far exceeds that of fault ones. Fault data are scarce and relatively difficult to collect. In addition, with the uncertain of fault occurrence, traditional monitoring methods are difficult to apply effectively. To address these issues, a state monitoring system for high-pressure servo motor was proposed based on support vector data description (SVDD) for anomaly detection and support vector machine (SVM) for fault diagnosis. Initially, time-domain (T), frequency-domain (F), and wavelet packet subband energy (W) features were extracted from raw data. These features were then fused and normalized to form a new multidimensional feature vector, TFW. Subsequently, a convolutional neural network (CNN) was employed to deeply mine the TFW, generating more expressive features, TFWCNN, which served as inputs to the SVDD and SVM models. An experimental platform for simulating high-pressure servo motor faults was constructed to collect data and validate the proposed method. The results indicate that on three dynamic datasets with different valve opening positions, the Fl scores for SVDD anomaly detection are 0. 999 1, 0. 997 8, and 0. 976 0, and for SVM fault diagnosis, the Fl scores are 0.998 8, 0.995 0, and 0. 986 7, respectively. These findings demonstrate the superior performance of the proposed method in the state monitoring of high-pressure servo motor and highlight the efficacy and accuracy of deep TFWCNN features. Furthermore, this study provides an effective technical solution for similar turbine state monitoring and diagnostic systems. © 2025 Chinese Vibration Engineering Society. All rights reserved.

关键词： Frequency domain analysis

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WCFormer: An interpretable deep learning framework for heart sound signal analysis and automated diagnosis of cardiovascular diseases

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Expert Systems with Applications 2025年 276卷

作者： Wang, Suiyan Hu, Junhui Du, Yanwei Yuan, Xiaoming Xie, Zhongliang Liang, Pengfei Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control Qinhuangdao066004 China School of Mechanical Engineering Yanshan University Qinhuangdao066004 China Department of Engineering Mechanics Northwestern Polytechnical University Xi'an710072 China

In recent years, there has been a surge focusing on advanced heart sound (HS) signal analysis and automated diagnosis based on deep learning (DL) for cardiovascular diseases (CVDs). However, the untrust of users in decision-making caused by the complex nonlinear transformation within the model and unclear feature extraction mechanism remains a huge challenge. For the diagnosis issue of CVDs involving human life and health, if the reasons why the model obtains the final conclusion cannot be known in advance, taking actions rashly will conceal significant risks. In this paper, an interpretable wavelet convolution transformer, named WCFormer, is proposed for HS signal analysis and automated diagnosis of CVDs. This method aims to enhance the interpretability of the traditional transformer and realize the high-accuracy diagnosis of CVDs by embedding wavelet knowledge information and improving its structure. Specifically, a wavelet convolution kernel is first designed to capture disease-related information with a clear physical meaning. Then, a global–local feature extractor is designed by removing the position encoding of the transformer and combining it with the convolution module. Two case studies involving HS signals are implemented to validate the efficacy of the proposed WCFormer and the results are compared with several widely used approaches, revealing that the WCFormer can achieve more excellent performance than other comparison methods. © 2025 Elsevier Ltd

关键词： Automated diagnosis Cardiovascular diseases Heart signal analysis Interpretable

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Complementary Operations of Multi-renewable Energy Systems with Pumped Storage

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CSEE Journal of power and Energy Systems 2023年第5期9卷 1866-1880页

作者： Zean Zhu Lingling Wang Xu Wang Chuanwen Jiang Shichao Zhou Kai Gong Key Laboratory of Control of Power Transmission and conversion Shanghai Jiao Tong UniversityShanghai 200240China

Complementarity is an important attribute among different renewable energy sources(RESs).A multi-renewable energy system(MRES)offers an alternative to aggregate diverse RESs and can ensure the best attributes of their mutual ***,few papers conduct convincing research into the complementary operation of a *** paper investigates the complementarities in a MRES that contains wind,photovoltaic,run-off hydro,pumped storage power plants and incorporates complementarity into the optimal operation of a *** complementarity is theoretically summarized and first classified into two categories:natural and *** effectively capture the uncertainty and complementarity of RESs,the time-dependent clustering simulation technique is employed to generate their *** equivalent runoff hydropower plant index is proposed,based on which a novel complementary operation model,that considers volatility and self-sufficient adequacy,is *** are presented and compared in a case study,which demonstrate the validity and scalability of the proposed methodology,reveals the complementarities under multiple time-scales,and illustrates the significance of complementary operations.

关键词： Complementarity multi-renewable energy system optimal operation multi time-scale fuzzy-c means clustering

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FPGA-based real-time simulation for EV station with multiple high-frequency chargers based on C-EMTP algorithm

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Protection and control of Modern power Systems 2020年第1期5卷 303-313页

作者： Zirun Li Jin Xu keyou Wang Pan Wu Guojie Li Key Laboratory of Control of Power Transmission and Conversion(SJTU) Ministry of EducationShanghaiChina

The electric vehicle(EV)charging station is a critical part of the infrastructure for the wide adoption of *** simulation of an EV station plays an essential role in testing its operation under different operating ***,the large numbers of high-frequency power electronic switches contained in EV chargers pose great challenges for real-time *** paper proposes a compact electromagnetic transient program(C-EMTP)algorithm for FPGA-based real-time simulation of an EV station with multiple high-frequency *** C-EMTP algorithm transforms the traditional EMTP algorithm into two parallel sub-tasks only consisting of simple matrix operations,to fully utilize the high parallelism of *** simulation time step can be greatly reduced compared with that of the traditional EMTP algorithm,and so the simulation accuracy for high-frequency power electronics is *** EV chargers can be decoupled with each other and simulated in parallel.A CPU-FPGA-based realtime simulation platform is developed and the proposed simulation of the EV station is *** control strategy is simulated in a CPU with 100μs time-step,while the EV station circuit topology is simulated in a single FPGA with a 250 ns *** the case studies,the EV station consists of a two-level rectifier and five dual-active bridge(DAB)EV *** is tested under different scenarios,and the real-time simulation results are validated using PSCAD/EMTDC.

关键词： Dual-active bridge(DAB) Electromagnetic transient program(EMTP) Field-programmable gate arrays(FPGA) EV charger Real-time simulation

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Demand-side Response Strategy of Multi-microgrids Based on an Improved Co-evolution Algorithm

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CSEE Journal of power and Energy Systems 2021年第5期7卷 903-910页

作者： Yang Gao Qian Ai Key Laboratory of Control of Power Transmission and Conversion Shanghai Jiao Tong UniversityShanghai 200240China

An effective modeling and optimization method,which takes into account source-load-storage coordination,and full-time collaborative optimization within and outside micro-grids,is *** the operational conditions of various resources and their interactions,an energy management model for microgrids is proposed aiming at maximization of renewable energy utilization and minimization of overall system *** model is suitable for both real-time pricing and time-of-use *** microgrids,demand response and economic energy storage dispatch are introduced to enhance selfcoordination and self-balancing ability among different *** on whether there is still an imbalance between supply and demand after coordination within a niicrogrid,trade between it and external microgrids are optimized in a orderly manner by considering different transaction prices and usage ***,three different schemes are designed,where the Lagrangian multiplier method as well as a co-evolution algorithm are used to solve and analyze different examples,verifying the reliability and validity of the method proposed in this paper.

关键词： Terms—Co-evolution demand-side response multi-microgrids source-load-storage coordination.

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Electrical control strategy for an ocean energy conversion system

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Protection and control of Modern power Systems 2021年第1期6卷 160-177页

作者： Muhammad Noman Guojie Li keyou Wang Bei Han Key Laboratory of Control of Power Transmission and Conversion(SJTU) Ministry of EducationShanghaiChina

Globally abundant wave energy for power generation attracts ever increasing attention. Because of non-linear dynamics and potential uncertainties in ocean energy conversion systems, generation productivity needs to be increased by applying robust control algorithms. This paper focuses on control strategies for a small ocean energy conversion system based on a direct driven permanent magnet synchronous generator (PMSG). It evaluates the performance of two kinds of control strategies, i.e., traditional field-oriented control (FOC) and robust adaptive control. The proposed adaptive control successfully achieves maximum velocity and stable power production, with reduced speed tracking error and system response time. The adaptive control also guarantees global system stability and its superiority over FOC by using a non-linear back-stepping control technique offering a better optimization solution. The robustness of the ocean energy conversion system is further enhanced by investigating the Lyapunov method and the use of a DC-DC boost converter. To overcome system complexity, turbine-generator based power take-off (PTO) is considered. A Matlab/Simulink study verifies the advantages of a non-linear control strategy for an Oscillating Water Column (OWC) based power generation system.

关键词： OWC Ocean wave power generation Robust adaptive control FOC PMSG Wells turbine

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A Two-stage Autonomous EV Charging Coordination Method Enabled by Blockchain

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Journal of Modern power Systems and Clean Energy 2021年第1期9卷 104-113页

作者： Jian Ping Zheng Yan Sijie Chen Key Laboratory of Control of Power Transmission and Conversion Ministry of Education(Shanghai Jiao Tong University)ShanghaiChina

Increasing electric vehicle(EV) penetration in distribution networks necessitate EV charging coordination. This paper proposes a two-stage EV charging coordination mechanism that frees the distribution system operator(DSO) from extra burdens of EV charging coordination. The first stage ensures that the total charging demand meets facility constraints,and the second stage ensures fair charging welfare allocation while maximizing the total charging welfare via Nash-bargaining trading. A decentralized algorithm based on the alternating direction method of multipliers(ADMM) is proposed to protect individual privacy. The proposed mechanism is implemented on the blockchain to enable trustworthy EV charging coordination in case a third-party coordinator is absent. Simulation results demonstrate the effectiveness and efficiency of the proposed approach.

关键词： Electric vehicle(EV)charging coordination Nash bargaining alternating direction method of multipliers(ADMM) blockchain

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Unsupervised and controllable synthesizing for imbalanced energy dataset based on AC-InfoGAN

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Applied Energy 2025年 393卷

作者： Zhenghao Zhou Yiyan Li Runlong Liu Xiaoyuan Xu Zheng Yan The Key Laboratory of Control of Power Transmission and Conversion Ministry of Education Shanghai Jiao Tong University Shanghai 200240 China

Generating synthetic data has become a popular alternative solution to deal with the difficulties in accessing and sharing field measurement data in power systems. However, to make the generation results controllable, existing methods (e.g., Conditional Generative Adversarial Nets, cGAN) require labeled dataset to train the model, which is demanding in practice because many field measurement data lack descriptive labels. Meanwhile, real-world datasets are naturally imbalanced, causing bias in neural network training. In this paper, we introduce the Adaptive and Contrastive Information Maximizing Generative Adversarial Nets (AC-InfoGAN) to achieve controllable synthesizing for the unlabeled and imbalanced energy dataset. Features with physical meanings can be automatically extracted by maximizing the mutual information between the input latent code and the classifier output. Then the extracted features are used to control the generation results similar to a vanilla cGAN framework. We employ the Gumbel-Softmax distribution and frequency-based contrastive learning techniques to dynamically adapt to the imbalanced dataset to avoid the model training bias. Meanwhile, frequency-domain neural network modules are introduced to the AC-InfoGAN framework to enhance the model performances. Case study is based on the unlabeled and imbalanced energy datasets of power load and renewable energy output. Results demonstrate that AC-InfoGAN can extract both discrete and continuous features with certain physical meanings, as well as generating realistic synthetic energy data that satisfy given features

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Density-based Global Sensitivity Analysis of Islanded Microgrid Loadability Considering Distributed Energy Resource Integration

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Journal of Modern power Systems and Clean Energy 2020年第1期8卷 94-101页

作者： Zhuoxin Lu Xiaoyuan Xu Zheng Yan Han Wang Key Laboratory of Control of Power Transmission and Conversion of Ministry of Education Shanghai Jiao Tong UniversityShanghaiChina

With the proliferation of renewable energy and electric vehicles(EVs),there have been increasing uncertainties in power *** the influencing random variables will reduce the effort in uncertainty modeling and improve the controllability of power *** this paper,a density-based global sensitivity analysis(GSA)method is proposed to evaluate the influence of uncertainties on islanded microgrids(IMGs).Firstly,the maximum IMG loadability evaluation model is established to assess the distance from the current operation point to the critical operation ***,the Borgonovo method,which is a density-based GSA method,is used to evaluate the influence of input variables on IMG ***,to improve GSA efficiency,a modified Kriging model is used to obtain a surrogate model of IMG loadability,and Borgonovo indices are calculated based on the surrogate ***,the proposed method is tested on a 38-bus IMG *** results are compared with those considering other methods to validate the effectiveness of the proposed *** storage systems are considered to diminish the influence of critical uncertainties on IMG operation.

关键词： Islanded microgrids(IMGs) renewable energy global sensitivity analysis uncertainty

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The staged optimal scheduling method for a multi-source industrial park with wind, solar, thermal, and energy storage

The staged optimal scheduling method for a multi-source indu...

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3rd International Conference on Smart Energy and Electrical Engineering, SEEE 2024

作者： Hao, Ling Xu, Hui Tan, Zhenlong Zheng, Zhibao Xu, Fei Yang, Ruixuan Xu, Zhenyu Dai, Xuhui State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Co. Ltd. Beijing101199 China School of Economics and Management Tsinghua University Beijing100084 China State Key Laboratory of Power Transmission Equipment Technology Chongqing University Chongqing400044 China

The increase in the proportion of renewable energy generation capacity has placed significant pressure on thermal power operations. Constructing energy storage facilities within the metering output of thermal power plants, allowing them to participate in peak load regulation with generating units jointly, is one effective way to alleviate the operational pressure on thermal power. To achieve comprehensive scheduling of thermal power plants with energy storage, this paper first establishes an overall output model for the coupling operation of thermal power and energy storage. Secondly, a staged optimal scheduling method for a multi-source industrial park with wind, solar, thermal, and energy storage is proposed to solve the optimization scheduling problem for the industrial park involving thermal power plants with energy storage participation. Finally, the simulation results based on a specific regional power grid in Inner Mongolia validate the feasibility of the proposed method. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Thermoelectric power plants

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