Open AccessImpulsive noise reduction for transient Earth voltage‐based partial discharge using Wavelet‐entropy
Author(s) -
Luo Guomin,
Zhang Daming,
Tseng King Jet,
He Jinghan
Publication year - 2016
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2014.0203
Subject(s) - partial discharge , wavelet , entropy (arrow of time) , noise reduction , wavelet transform , pattern recognition (psychology) , voltage , transient (computer programming) , computer science , materials science , artificial intelligence , electronic engineering , engineering , physics , electrical engineering , quantum mechanics , operating system
Partial discharge (PD) is caused by the localised electrical field intensification in insulating materials. Early detection and accurate measurement of PD are very important for preventing premature failure of the insulating material. Detection of PDs in metal‐clad apparatus through the transient Earth voltage method is a promising approach in non‐intrusive on‐line tests. However, the electrical interference from background environment remains the major barrier to improving its measurement accuracy. In this study, a wavelet‐entropy‐based PD de‐noising method has been proposed. The unique features of PD are characterised by combining wavelet analysis that reveals the local features and entropy that measures the disorder. With such features, a feed‐forward back‐propagation artificial neural network is adopted to recognise the actual PDs from noisy background. Comparing with other methods such as the energy‐based method and the similarity‐comparing method, the proposed wavelet‐entropy‐based method is more effective in PD signal de‐noising.