摘要详情

ID / 提交时间

88 / 2021-10-22 09:16:24

标题

Fault Diagnosis Method of Three-phase Inverter Based on Time Convolutional Neural Network

关键字

Inverter fault,TCN,Fault diagnosis

主题及专题

Power electronics technology and application > Power converter topologies and design

状态

全文被拒

作者

Gang Li / Jilin University

Jing Li / Jilin University

Jinru Song / Jilin University

Yizhuo He / Jilin University

Qun Guo / Jilin University

摘要

Power electronics converter is widely used in various applications. When the converter failure occurs, the system will be damaged, so it is of great significance to timely detect the fault and apply effective protection. In this paper, the open-circuit fault of the three-phase inverter is taken as the main object. The time convolutional neural network (TCN) model is designed to realize the fault diagnosis strategy of the inverter based on feature extraction. The simulated experimental results show that the neural network model can realize high accuracy fault diagnosis for different inverter circuits. The overall classification performance is good, and the loss is small. It is shown that the time convolutional neural network method can diagnose different IGBT fault intelligently in the inverter. It is proved that the neural network model is effective and feasible for inverter circuit fault diagnosis.

重要日期

会议日期

07月11日

2023

至

08月18日

2023
11月10日 2021

初稿截稿日期
12月10日 2021

注册截止日期
12月11日 2021

报告提交截止日期

主办单位

IEEE IAS

承办单位

IEEE IAS Student Chapter of Southwest Jiaotong University (SWJTU)
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
IEEE PELS (Power Electronics Society) Student Chapter of HUST