现代电子技术2024，Vol.47Issue(2)：115-120,6.DOI:10.16652/j.issn.1004-373x.2024.02.022
基于VMD-ESA和IPOA-XGBOOST相结合的异步电机故障诊断
Asynchronous motor fault diagnosis based on combination of VMD-ESA and IPOA-XGBOOST
高猛 1曾宪文1
作者信息
- 1. 上海电机学院 电子信息学院, 上海 201306
- 折叠
摘要
Abstract
In order to improve the accuracy of fault diagnosis of asynchronous motor,an intelligent diagnostic method is proposed that combines variational mode decomposition(VMD),envelope spectrum analysis(ESA),and improved Pelican optimization algorithm to optimize the limit gradient lifting model(IPOA-XGBOOST).VMD decomposition on the measured vibration signals of asynchronous motors is conducted,and ESA is used to calculate the instantaneous energy matrix of the intrinsic mode components(IMFs)obtained from VMD decomposition.Then,singular value decomposition(SVD)is used to extract features from the obtained instantaneous energy matrix.The extracted feature vectors are used to train the IPOA-XGBOOST model and obtain the accuracy of fault diagnosis of asynchronous motor.In order to solve the problems that the pelican optimization algorithm is easy to fall into the local optimal solution and the optimization speed is slow,the Circle mapping is used to improve the pelican optimization algorithm.The optimization analysis of improved pelican optimization algorithm,genetic algorithm(GA)and pelican optimization algorithm are conducted.The experimental results show that the improved pelican optimization algorithm has the best optimization effect.关键词
异步电机/故障诊断/鹈鹕优化算法/变分模态分解/包络谱分析法/瞬时能量矩阵/Circle映射Key words
asynchronous motor/fault diagnosis/pelican optimization algorithm/variational mode decomposition/envelope spectrum analysis/instantaneous energy matrix/Circle mapping分类
电子信息工程引用本文复制引用
高猛,曾宪文..基于VMD-ESA和IPOA-XGBOOST相结合的异步电机故障诊断[J].现代电子技术,2024,47(2):115-120,6.
