Research on Fault Prediction Method of Electronic Equipment Based on Bi-LSTM

In order to improve the accuracy of electronic equipment fault prediction results, a fault prediction method based on bi-directional long short term memory (Bi-LSTM) is proposed. Firstly, the research of long short term memory(LSTM) is carried out, and Bi-LSTM is proposed for fault prediction of electronic equipment, and a fault prediction method based on Bi-LSTM is given. Secondly, the extraction method of analog circuit health index is studied, and a fault prediction example based on the simulation data of a radar bandpass filter amplifier analog circuit is taken. Finally, the fault prediction method based on Bi-LSTM is applied to three groups of status monitoring data of radar transmitter to develop fault prediction research based on actual data. Through the comparative analysis of electronic equipment simulation data case and actual data case, it shows that the fault prediction method based on Bi-LSTM is obviously superior to the recurrent neural network (RNN) and LSTM, and Bi-LSTM can be used to improve the accuracy of electronic equipment fault prediction.

Abstract licence: CC BY

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.