Abstract
Due to electromagnetic interference in power substations, the partial discharge (PD) signals detected by ultrahigh frequency (UHF) antenna sensors often contain various background noises, which may hamper high voltage apparatus fault diagnosis and localization. This paper proposes a novel de-noising method based on the generalized S-transform and module time-frequency matrix to suppress noise in UHF PD signals. The sub-matrix maximum module value method is employed to calculate the frequencies and amplitudes of periodic narrowband noise, and suppress noise through the reverse phase cancellation technique. In addition, a singular value decomposition de-noising method is employed to suppress Gaussian white noise in UHF PD signals. Effective singular values are selected by employing the fuzzy c-means clustering method to recover the PD signals. De-noising results of simulated and field detected UHF PD signals prove the feasibility of the proposed method. Compared with four conventional de-noising methods, the results show that the proposed method can suppress background noise in the UHF PD signal effectively, with higher signal-to-noise ratio and less waveform distortion.
Highlights
Partial discharge (PD) is a major cause and manifestation of insulation degradation
The background noise interferes with the PD detection and causes PD pulse shapes to be distorted, which may negatively affect high voltage (HV) apparatus fault diagnosis and localization accuracy [5,6].noise suppression is a vital issue of field ultra-high frequency (UHF) PD signal testing
To suppress the periodic narrowband noise, the module time-frequency matrix (MTFM) based on the generalized S-transform is is applied as follows: applied as follows: Step 1: Use the generalized S-transform to obtain the MTFM SM×N and time-frequency distribution of noisy UHF PD signals, where SM×N is the matrix with M rows and N columns ; Step 1: Use the generalized S-transform to obtain the MTFM SMN and time-frequency distribution
Summary
Partial discharge (PD) is a major cause and manifestation of insulation degradation. PD detection has been utilized for insulation condition assessment of high voltage (HV) apparatus [1]. Methods based on adaptive filters have been proposed to effectively suppress the narrowband noise [9,10], when the frequencies of the interferences and the Sensors 2016, 16, 941; doi:10.3390/s16060941 www.mdpi.com/journal/sensors. The Gaussian white noise is generated by the heating effect of HV apparatus and will distort the UHF PD signals. A novel method based on singular value decomposition (SVD) has been utilized for Gaussian white noise suppression, and more accurate recovery of the original PD signal was obtained [17]. A novel de-noising method based on the module time-frequency matrix (MTFM) is proposed to suppress periodic narrowband noise and Gaussian white noise. The fuzzy c-means (FCM) clustering method is employed to select effective singular values for recovering the UHF PD signals without Gaussian white noise. The de-noising results of simulated and field test UHF PD signals demonstrate the validity of the proposed method
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