Electric Tractor Drive Motor System Fault Diagnosis Model Research
Failure of an electric tractor drive motor system can lead to loss of vehicle control or unexpected situations that can endanger the driver and the surrounding environment.Accurate fault diagnosis can help the driver to take timely ac-tion to avoid potential danger.In order to further improve the fault diagnosis accuracy of electric tractor drive motor sys-tem,based on the data characteristics and fault types of the drive motor system,this paper constructs the fault diagnosis model of electric tractor motor drive motor system based on BP artificial neural network model with PSO-BP optimized ar-tificial neural network model,optimizes the threshold and weights of the traditional BP neural network model,and faster convergence to the global optimal solution.The experimental validation of the PSO-BP fault diagnosis model based on the drive motor system by collecting data from the drive motor system shows that the model has a high accuracy in diagnosing five fault states,especially in the two complex fault types of demagnetization fault and IGBT fault.The research content can provide an effective method and technical support for the fault diagnosis of electric tractor drive motor system,improve the diagnosis accuracy,guarantee the safety of the driver and the surrounding environment,improve the efficiency and re-duce the maintenance cost.
electric tractordrive motor systemfault diagnosisaccuracyPSO-BP optimization algorithm
万方数据
维普
