摘要
电机作是一种通过旋转传动实现动作的设备,其与转子系统的运行稳定性要求很高。为了提高对转子系统故障信号的特征提取效果,通过改进遗传方法(IGA)来优化变分模态分解(VMD)的方式设计了一种IGA-VMD方法,并成功应用于电机转子系统故障识别领域。研究结果表明,故障信号包络解调后表现出周期特征,具有明显的突出谱峰。IMF4模态分量位置的包络谱内未发现高倍频率信号,证明IGA-VMD方法能够成功用于转子系统故障特征提取方面。该研究能够有效实现转子系统故障特征的准确采集,为电机后续维修与故障诊断提供一定参考。
The electric motor is a kind of equipment that realizes the action through the rotary transmission,which has a high requirements on the operation stability of rotor system.In order to improve the feature extraction effect of rotor system fault signals,this paper designs a method of optimizing the Variational Mode Decomposition(VMD)by an Improved Genetic Algorithm(IGA).The IGA-VMD method has been designed and successfully applied in the fault identification field of motor rotor system.The research results show that the fault signal after envelope demodulation appears the periodic characteristics and has obvious prominent spectral peaks.The high-multiplier frequency signal wasn′t found out in the envelope spectrum of IMF4 modal component position,which proves that IGA-VMD method can be successfully used in fault feature extraction of rotor system.The research can effectively realize the accurate acquisition of rotor system fault characteristics,which provides a certain reference for the follow-up maintenance and fault diagnosis of the motor.
作者
杨林
高永杰
Yang Lin;Gao Yongjie(Department of Electrical Engineering,Luohe Technician College,Luohe 462300,China;Department of Mechanical Engineering,Luohe Technician College,Luohe 462300,China)
出处
《防爆电机》
2025年第4期39-42,共4页
Explosion-proof Electric Machine
基金
河南省高等学校重点科研项目(23B510012)。
关键词
电机转子系统
故障识别
遗传方法
变分模态分解
Motor rotor system
fault identification
genetic method
variational mode decomposition
