摘要
针对永磁同步电机(permanent magnet synchronous motor,PMSM)匝间短路故障振动信号易受噪声干扰导致故障特征难以准确提取的问题,提出一种改进鲸鱼优化算法(improved whale optimization algorithm,IWOA)优化变分模态分解(variational mode decomposition,VMD),并将其应用于PMSM匝间短路故障振动信号去噪。首先在传统鲸鱼优化算法中引入非线性收敛因子、自适应权重和柯西算子,利用IWOA算法对VMD参数进行寻优来实现信号的自适应分解。然后根据多尺度排列熵-方差贡献率最优模态分量选取原则将信号分量分为噪声主导分量和有效信号分量,对噪声主导分量进行非局部均值滤波(non-local mean filtering,NLM)去噪。最后将去噪分量与有效信号分量重构为去噪信号。使用ANSYS有限元软件建立了电机短路故障模型,并搭建了短路故障实验平台,利用该方法对仿真与实测信号进行去噪处理,并与小波阈值去噪等去噪方法进行对比分析,得出仿真信号的信噪比从8 dB提升至20.2738 dB,实测信号的信噪比相较于小波阈值去噪提高了77.01%,验证了所提方法的有效性和实用性。
Aiming at the problem that vibration signal of inter-turn short circuit fault in permanent magnet synchronous motor(PMSM)is easily affected by noise and it is difficult to accurately extract the fault feature of it,an improved whale optimization algorithm(IWOA)optimized variational mode decomposition(VMD)denoising method is proposed and applied to vibration signal of inter-turn short circuit fault in PMSM.Firstly,the nonlinear convergence factor,adaptive weight and the Cauchy operator are introduced into the traditional whale optimization algorithm,and the IWOA algorithm is used to optimize the VMD parameters to achieve adaptive signal decomposition.Secondly,according to the principle of selecting the optimal intrinsic mode function based on multi-scale permutation entropy and variance contribution rate,the signal components are divided into the noise-dominated components and effective signal components.The noise-dominated components are denoised by the non-local mean filtering(NLM).Finally,the denoised and effective signal components are reconstructed as denoised signal.A motor short circuit fault model is established using ANSYS finite element software,and a short circuit fault experimental platform is built.Using this method to denoise the simulated and measured signals,it is further compared with many denoising methods such as wavelet threshold denoising method.The signal to noise ratio of the simulated signal is improved from 8 dB to 20.2738 dB,and the signal to noise ratio of the measured signal is improved by 77.01%compared with wavelet threshold denoising method,which proved the effectiveness and practicality of the proposed method.
作者
夏焰坤
寇坚强
李欣洋
Xia Yankun;Kou Jianqiang;Li Xinyang(School of Electrical Engineering and Electronic Information,Xihua University,Chengdu 610039,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2024年第4期202-216,共15页
Journal of Electronic Measurement and Instrumentation
基金
四川省科技计划项目(2020YFG0184)资助。
关键词
永磁同步电机
匝间短路
振动信号
改进鲸鱼优化算法
变分模态分解
非局部均值滤波
permanent magnet synchronous motor
inter-turn short circuit
vibration signal
improved whale optimization algorithm
variational mode decomposition
non-local mean filtering
