摘要详情

ID / 提交时间

130 / 2021-10-27 11:03:08

标题

Data-Driven IGBT Open-Circuit Fault Diagnosis Method for the Modular Multilevel Converter

关键字

MMC,data-driven,Fault Diagnosis

主题及专题

AI-driven technology > Intelligent Anomaly Detection, Fault Diagnosis and Prognostics

状态

全文被拒

作者

Yang An / Xi'an University of Technology School of Electrical Engineering

Xiangdong Sun / Xi'an University of Technology

Hui Li / Xi'an University of Technology

Mengnan Zhang / Xi'an University of Technology

摘要

With the wide application of the modular multilevel converter topology in different electric power transmission fields, the key technology is to ensure its normal operation. It is composed of a large number of IGBTs, and it is and it is difficult to detect the open-circuit fault of one or more IGBTs. With regard to this problem, a data-driven IGBT open-circuit fault diagnosis method is proposed based on the Elman neural network. The principle of fault detection is to quickly detect the fault by comparing the distance between the predicted value of bridge arm current and actual value. The Elman neural network model is established by using Matlab and the modular multilevel converter circuit model is built by using PSIM circuit model. The simulation results denote that the proposed method can detect IGBT open-circuit fault accurately, and it is proved that the data-driven method is suitable for fault diagnosis of the modular multilevel converter.

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