Optimization of BP Neural Network Based on Genetic Algorithm for Fault Diagnosis of Internal Combustion Engine Bearings
A bearing fault diagnosis method based on variational modal decomposition and genetic algorithm optimized BP neural network is proposed to address the high occurrence rate and difficult diagnosis of bearing faults in internal combustion engines.The bearing data set of Jiangnan University is used to verify the method.The results show that the diagnostic accuracy of this method can reach over 96%under various working condi-tions,and it can accurately identify various types of bearing faults,solving the problem of difficult bearing fault diagnosis in internal combustion engines to a certain extent.
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