Abstract
The partial discharge signal measurement is a non-destructive diagnostics procedure to assess the status of insulation system in high voltage equipment. Due to the adverse measurement conditions, the PD signals are strongly influenced with external noise. In this paper, a new approach is presented for PD signal denoising, which combines the Variational Mode Decomposition and Group-Sparse Total Variation based denoising. The proposed method is applied to extract the simulated PD signal buried in white noise, discrete spectral interference and color noise. Simulation results show that the performance of the proposed VMD-GSTV method is superior to that of Wavelet and the recently introduced Wavelet Total Variation method, specifically when the SNR is low.
| Original language | English |
|---|---|
| Title of host publication | 2019 2nd International Conference on Signal Processing and Information Security (ICSPIS) |
| Publisher | IEEE |
| ISBN (Electronic) | 9781728138732 |
| ISBN (Print) | 9781728138749 |
| DOIs | |
| Publication status | Published - 26 Mar 2020 |
Documents and Links
- Dhandapani, R. et al (2020) Partial discharge signal denoising based on VMD and group-sparse TV denoising
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