The invention discloses an urban medium-
voltage distribution cable
partial discharge signal denoising method. In order to suppress periodic
narrowband interference, a K-means clustering
algorithm is used to classify noisy
partial discharge signal spectrums. In order to suppress
white noise interference, an improved empirical
Wavelet Transform (EWT)
algorithm based on an Order Statistic Filter (OSF) is provided, and the method comprises the following steps: firstly, estimating an envelope line on a
signal frequency spectrum by using the OSF, reasonably segmenting the
signal frequency spectrum, then, carrying out adaptive
decomposition on a signal by using the EWT, introducing a kurtosis criterion to select a useful
modal component, and finally, carrying out adaptive
decomposition on the signal by using the EWT. And finally, reconstructing a
partial discharge signal through threshold denoising. In combination with the K-means clustering
algorithm and the empirical
wavelet transform, the method provided by the invention does not need to modify algorithm parameters, can perform
adaptive denoising on
white noise and periodic narrow-band interference at the same time, can effectively reserve signal details while having a high denoising signal-to-
noise ratio, and is relatively high in algorithm efficiency.