改进VMD和阈值算法在局部放电去噪中的应用

Application of improved VMD and threshold algorithm in partial discharge denoising

为解决局部放电检测中存在白噪声和周期窄带干扰的问题,提出一种结合改进变分模态分解(VMD)和阈值算法的局部放电去噪法。针对VMD在实际应用中难以自适应选取分解参数的问题,提出以能量偏差最小为原则确定分解个数,通过天牛须搜索算法(BAS)优化各分量对应的惩罚因子,以峭度准则筛选出有效分量,从而去除掉窄带干扰噪声;利用3σ准则确定阈值,结合阈值函数进一步去除有效分量中残留的白噪声,重构有效分量。通过对仿真、实测信号去噪分析,并与提升db4小波法、集合经验模态分解(EEMD)阈值法对比。结果表明,该方法具有更好的去噪效果,去噪后波形相似度更高,噪声抑制比更高,能够保留更多的局部放电特征。

In order to solve the problems of white noise and periodical narrow-band interference in PD detection,a denoising method combining improved variational mode decomposition(VMD)and threshold denoising is proposed.Aiming at the problem that the VMD algorithm is difficult to choose the decomposition parameters adaptively in the practical application,the decomposition number is determined by the principle of minimum energy deviation,the penalty factor of each component was optimized by BAS,and the kurtosis criterion was used to screen the effective component,so as to eliminate the narrow-band interference noise.Threshold function combined with 3σcriterion was used to remove the residual white noise in the effective component and reconstruct the effective component.Through simulation and measured signal denoising analysis and compared with lifting db4 wavelet method and EEMD threshold method,the results show that this method has better denoising effect,the denoising waveform similarity coefficient is higher after denoising,the noise rejection ratio is higher and can retain more partial discharge characteristics.