The detection process of partial discharge（PD） ultrahigh frequency（UHF） signals is severely susceptible to white noise and periodic narrowband noise. In order to extract PD UHF signals and suppress noise effectively

a denoising method based on singular value decomposition（SVD） and low rank radial basis function（RBF） neural network is proposed.Firstly

the noisy PD signals are constructed as a Hankel matrix and SVD matrix is decomposed into a feature matrix space. Then

the singular value mutation point in the feature matrix is set as a threshold to remove the narrowband noise.Finally

RBF neural network is used to approximate the denoised PD signals

and Gaussian window filtering is used to extract the PD signals. The proposed method is compared with reverse separation（RS） and morphology wavelet filter（MWF）. The simulation and field-detection results show that the method has a stronger inhibition effect on periodic narrowband noise and white noise

and the evaluation index is more significant.