LS-SVM based capacitor anomaly identification method-Reference-Cited by-同舟云学术

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LS-SVM based capacitor anomaly identification method

Published:2024-05-17 Issue: Volume:3 Page:4542-4546
ISSN:
Container-title:2024 IEEE 10th International Power Electronics and Motion Control Conference (IPEMC2024-ECCE Asia)
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Author:

Lv Chunlin¹,Deng Yuxi²,Liu Jinjun¹,Zhang Xiaotong³,Zhang Yan¹,Chang Fei⁴

Affiliation:

1. Xi’an Jiaotong University,School of Electrical Engineering,China

2. Chinese Academy of Sciences,Institute of Automation,China

3. Xi'an University of Technology,School of Electrical Engineering,China

4. State Grid Shaanxi Electric Power Company,Electric Power Research Institute,China

Funder

Research and Development

Science and Technology Project of State Grid

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10567049/10567050/10567650.pdf?arnumber=10567650

Reference10 articles.

1. Reliability of Capacitors for DC-Link Applications in Power Electronic Converters—An Overview

2. Real-Time Fault Detection and Identification for MMC Using 1-D Convolutional Neural Networks

3. Performance of a Classifier Based on Time-Domain Features for Incipient Fault Detection in Inverter Drives

4. Cascaded H-Bridge Multilevel Inverter System Fault Diagnosis Using a PCA and Multiclass Relevance Vector Machine Approach

5. Fault detection and diagnosis of grid-connected power inverters using PCA and current mean value

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