Abstract:In order to avoid frequent unwarned shutdowns of motors, diagnosis and analysis of electromechanical equipment is a very important task. Aiming at a single motor fault in the roller motor, an intelligent motor fault diagnosis and analysis strategy based on deep learning was proposed according to the motor current data collected under normal operating conditions and fault conditions of all motors. Considering the current of other motors working in coordination to diagnose the fault of the monitored motor was proposed for the first time. In this scheme, the Lenet-5 model was used for classification prediction training to diagnose faults of the motor. In addition, the actual deployment and implementation of this program and the collection of experimental data showed that the proposed method was feasible and effective in motor fault diagnosis.
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