An evaluation of total variation signal denoising methods for partial discharge signals

I. Mitiche, G. Morison, A. Nesbitt, M. H.-Narborough, P. Boreham, B.G. Stewart

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Abstract

In this paper, we investigated the application of modern signal denoising techniques for nonstationary signals to real PD signals. We also introduced a new method ALIF-TV based on signal decomposition and TV, inspired by WATV developments. The methods' performance was evaluated and compared on the basis of their MSE metric. It was found that ALIF-TV outperforms WATV when applied to PD signals. Both algorithms were successful in reducing AWGN noise observed in our data. Other than AWGN, impulsive noise may also be an issue in PD field. However, it is not present in our data. This may be investigated as future work. The work of this paper can be exploited in condition monitoring for EMI fault diagnosis as pre-processing which will clean the signal to aid interpretation of PD information.
Original languageEnglish
Title of host publication2017 INSUCON - 13th International Electrical Insulation Conference (INSUCON)
PublisherIEEE
Number of pages5
ISBN (Electronic)9781-999815691
DOIs
Publication statusPublished - 7 Nov 2017

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Keywords

  • partial discharges
  • noise reduction
  • corona
  • noise measurement
  • electromagnetic interference
  • wavelet transforms
  • signal denoising

Cite this

Mitiche, I., Morison, G., Nesbitt, A., H.-Narborough, M., Boreham, P., & Stewart, B. G. (2017). An evaluation of total variation signal denoising methods for partial discharge signals. In 2017 INSUCON - 13th International Electrical Insulation Conference (INSUCON) IEEE. https://doi.org/10.23919/INSUCON.2017.8097195