2023
DOI: 10.1088/1742-6596/2549/1/012025
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Fault diagnosis of Rolling Bearing for Motor Based on LSTM-EEMD and Genetic Optimization

Abstract: In the process of ensemble empirical mode decomposition (EEMD) for motor rolling bearing time series, if the classifier is trained directly using the eigenvalues extracted from the pattern components, there are two shortcomings leading to the reduction of fault identification accuracy as follows: decomposition has serious endpoint effects; the correlation between extracted features lead to the confusion of the fault feature vector classification boundary. Aiming at the problems, in this paper, a fault diagnosi… Show more

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