Open AccessSensitivity Improvement of Acoustic Partial Discharge Detection Measurements through Wavelet Analysis
Author(s) -
Demetres Evagorou,
Patrick Janus,
Mohamad Ghaffarian Niasar,
Hans Edin
Publication year - 2018
Publication title -
proceedings of the nordic insulation symposium
Language(s) - English
Resource type - Journals
ISSN - 2535-3969
DOI - 10.5324/nordis.v0i23.2480
Subject(s) - partial discharge , transformer , wavelet , sensitivity (control systems) , noise (video) , acoustic emission , computer science , wavelet transform , acoustics , automotive engineering , electronic engineering , reliability engineering , electrical engineering , engineering , voltage , artificial intelligence , physics , image (mathematics)
Condition monitoring of power equipment is a vital stepin extending the lifetime of existing equipment andreducing costs for utilities while minimizing the risk ofunscheduled outages. Partial discharge (PD) monitoringhas evolved as a reliable mean of determiningdeterioration in insulation systems. Acoustic emissiondetection techniques are usually utilized for PDdetection mainly in oil-filled transformers offering theadvantage of being immune to electrical noise and amethod to localize PDs. In this work it was attempted toimprove the sensitivity of acoustic measurementsthrough wavelet analysis and estimation of the thresholdvalue from actual measurements of the noise, whichproved to be more effective compared to otherestimation values. The analysis was performed onlaboratory measurements from a 36 kV condenserbushing known to exhibit PD activity acquired with alow cost PD acoustic sensor developed at KTH. As anext step the results have to be verified by onlinemeasurements, which can result in the addition of anCondition monitoring of power equipment is a vital step in extending the lifetime of existing equipment and reducing costs for utilities while minimizing the risk of unscheduled outages. Partial discharge (PD) monitoring has evolved as a reliable mean of determining deterioration in insulation systems. Acoustic emission detection techniques are usually utilized for PD detection mainly in oil-filled transformers offering the advantage of being immune to electrical noise and a method to localize PDs. In this work it was attempted to improve the sensitivity of acoustic measurements through wavelet analysis and estimation of the threshold value from actual measurements of the noise, which proved to be more effective compared to other estimation values. The analysis was performed on laboratory measurements from a 36 kV condenser bushing known to exhibit PD activity acquired with a low cost PD acoustic sensor developed at KTH. As a next step the results have to be verified by online measurements, which can result in the addition of an onboard signal-processing box for improved sensitivity.