WANG F Z, QIAO S S, TIAN G Q.A fault prediction method of Vienna rectifier based on LSTM[J].Journal of Henan Polytechnic University(Natural Science) ,2023,42(3):111-117.

doi:10.16186/j.cnki.1673-9787.2021070011

Received:2021/07/02

Revised:2021/12/10

Published:2023/05/25

A fault prediction method of Vienna rectifier based on LSTM

WANG Fuzhong1, QIAO Shanshan1, TIAN Guangqiang2

1.School of Electrical Engineering and Automation，Henan Polytechnic University，Jiaozuo  454000，Henan，China;2.School of Intelligent Engineering，Huanghe Jiaotong University，Jiaozuo  454950，Henan，China

Abstract:In order to grasp the health status of the Vienna rectifier，a fault prediction model of the Vienna rectifier was proposed based on LSTM network.By analyzing the degradation and fault characteristics of capacitor and power MOSFET，a relationship was established between the circuit performance of the Vienna rectifier and the degradation of key components，so the output voltage variation value ω was selected as the fault characteristic parameter of the rectifier.On this basis，the fault prediction model of Vienna rectifier based on LSTM was constructed，and the Adam optimization algorithm was used to train the prediction model to realize the prediction of the characteristic parameters of the Vienna rectifier.The simulation results showed that，the RMSE of the prediction results of the model was 0.123 3，and the MAPE was 0.101 8.The prediction accuracy of the model was high，and the fault prediction of the Vienna rectifier could be achieved better.

Key words:Vienna rectifier;long and short-term memory network;component degradation;fault prediction

基于长短期记忆网络的Vienna整流器故障预测_王福忠.pdf