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

doi:10.23919/INSUCON.2017.8097195

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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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 language	English
Title of host publication	2017 INSUCON - 13th International Electrical Insulation Conference (INSUCON)
Publisher	IEEE
Number of pages	5
ISBN (Electronic)	9781-999815691
DOIs	https://doi.org/10.23919/INSUCON.2017.8097195
Publication status	Published - 7 Nov 2017

Keywords

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

Documents and Links

10.23919/INSUCON.2017.8097195

Mitiche, I. et al (2017) An evaluation of total variation signal denoising methods for partial discharge signals
Copyright © 2017 IEEE. This is a post-peer review, pre-copy edited version of the article and may differ slightly from the final published version of the work. This work is made available in line with the publisher policy. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Accepted author manuscript, 162 KB

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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

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title = "An evaluation of total variation signal denoising methods for partial discharge signals",

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.",

keywords = "partial discharges, noise reduction, corona, noise measurement, electromagnetic interference, wavelet transforms, signal denoising",

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

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AU - Mitiche, I.

AU - Morison, G.

AU - Nesbitt, A.

AU - H.-Narborough, M.

AU - Boreham, P.

AU - Stewart, B.G.

N1 - Acceptance in SAN AAM: no embargo

PY - 2017/11/7

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N2 - 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.

AB - 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.

KW - partial discharges

KW - noise reduction

KW - corona

KW - noise measurement

KW - electromagnetic interference

KW - wavelet transforms

KW - signal denoising

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