In order to improve the accuracy and rapidity of power electronic circuit fault prediction

In this paper

the fault characteristic performance parameters used are processed according to the LIFT fidelity denoising method

and divides multiple data windows according to data characteristics

using Long Short-Term Memory（LSTM） to adaptively predict the characteristic performance parameters of DC-DC circuits.The size of the window can be adjusted automatically during prediction

finds the optimal number of training sets

makes the prediction accuracy the highest.Taking the boost circuit in the DC-DC circuit as an example

Use the output voltage as the monitoring signal

calculates the characteristic parameters U

pp

and U

ave

to set the vol

tage threshold according to the circuit performance

and establish the LSTM fault prediction model based on the adaptive data window and the LITF-LSTM fault prediction model based on the adaptive data window

By comparing and analyzing the prediction results

explains the validity of the LITF-LSTM prediction model

Finally

analyzes whether the predicted data reaches the set threshold to determine whether the circuit is malfunctioning in the future.