Thermal fault diagnosis of marine diesel engine based on LSTM neural network algorithm

Abstract

As the power source of the ship sailing, diesel engine will inevitably produce some thermal faults in the course of sailing, which will affect the stability of the ship sailing, so the diagnosis of thermal faults becomes very important. This paper uses Simulink software platform to simulate the thermal failure of diesel engine, and selects seven thermal parameters as the source of data set. The data set is input into LSTM neural network algorithm diagnosis model, several typical fault modes of diesel engine are output, and the data processing and image drawing are carried out in Matlab. Compared with other algorithms, LSTM neural network algorithm solves the long time dependence problem and has a high interpretation of the predicted data. The results show that the fault diagnosis model based on LSTM neural network algorithm can diagnose the diesel engine fault mode well.