高压电器2025，Vol.61Issue(5)：189-196,8.DOI:10.13296/j.1001-1609.hva.2025.05.020
基于变分模态分解和CNN-BiGRU-Attention神经网络的电机故障分类方法
Fault Classification Method of Motor Based on Variational Modal Decomposition and CNN-BiGRU-Attention Neural Network
司成志 1惠世贤 1邢超 2邓灿2
作者信息
- 1. 云南电网有限责任公司文山供电局,云南 文山 663000
- 2. 云南电网有限责任公司电力科学研究院,昆明 650217
- 折叠
摘要
Abstract
For solving the problem of low accuracy of fault classification results of motor,a kind of fault classification method for motor based on variational mode decomposition(VMD)and CNN-BiGRU-Attention neural network mod-el is proposed.Firstly,the motor data of Case Western Reserve University is preprocessed,and then the complex mo-tor signal is decomposed into multiple intrinsic mode function(IMF)components by VMD method and the fault fea-ture vector of motor is constructed.Finally,the feature training CNN-BiGRU-Attention neural network model is set up,and the specific types of faults of motor are diagnosed based on the iterative training of the model.The experimen-tal results show that after the application of the proposed diagnosis method,the number fault classification errors of motor is less and the accuracy of test set is up to 97%.The method has high robustness and accuracy.关键词
VMD/CNN-BiGRU-Attention/IMF/故障分类Key words
VMD/CNN-BiGRU-Attention/IMF/fault classification引用本文复制引用
司成志,惠世贤,邢超,邓灿..基于变分模态分解和CNN-BiGRU-Attention神经网络的电机故障分类方法[J].高压电器,2025,61(5):189-196,8.
