针对高压电机局部放电(PD)在线检测中信号被高斯白噪声和窄带周期干扰淹没这一问题，应用基于改进变分模态分解（VMD）算法进行噪声滤除。为了克服常用的VMD算法可能会造成信号欠分解或过分解的问题，改用能量损失系数作为标准对分解模态数进行算法优化，优化分解后利用峭度值剔除无效模态，重构出PD信号。使用改进算法与现有方法进行了仿真数据对比，结果表明，使用改进的VMD算法可以更有效地滤除PD信号噪声。

In order to solve the problem that the signal in the online detection of high-voltage motor partial discharge (PD) is submerged by Gaussian white noise and narrow-band periodic interference, an algorithm based on improved variational mode decomposition (VMD) is used to filter out the noise. The common VMD algorithm may cause signal under-decomposition or over-decomposition. In order to overcome this shortcoming, the energy loss coefficient is used as the criterion to optimize the decomposition mode number. After the optimal decomposition, the kurtosis value is used to eliminate invalid modes and reconstruct the PD signal. The improved algorithm is compared with the existing methods in simulation. The results show that the improved VMD algorithm can filter out PD signal noise more effectively.