基于工业互联网云平台的异步电机故障诊断

Asynchronous Motor Fault Diagnosis Based on Industrial Internet Cloud Platform

基于工业互联网云平台所搭载的数据驱动故障诊断技术是工业设备故障诊断行业发展的主流趋势,想要提升故障诊断效率,就要不断更新故障诊断算法,同时提升传感器数据精度。将三相异步电机故障诊断工作转移至互联网云平台,根据设备监测数据对故障诊断模型进行训练,提升模型精确性,再利用VMD-BP神经网络以及卷积神经网络,对三相异步电机的故障进行精准、高效的诊断。

The data-driven fault diagnosis technology based on the Industrial Internet cloud platform is the mainstream trend of the development of industrial equipment fault diagnosis industry.In order to improve the efficiency of fault diagnosis,it is necessary to constantly update the fault diagnosis algorithm,improve the accuracy of sensor data,transfer the fault diagnosis of three-phase asynchronous motor to the Internet cloud platform,train the fault diagnosis model according to the equipment monitoring data,and improve the accuracy of the model.Then VMD-BP neural network and convolution neural network are used to diagnose the fault of three-phase asynchronous motor accurately and efficiently.