Automatic Blind Equalization and Thresholding for Partial Discharge Measurement in Power Transformer

Partial discharge (PD) signals acquired from on-line measurements of power transformers are easily overwhelmed by various interference and noise. This paper proposes an automatic blind equalization (BE) and morphological thresholding method for PD signal de-noising. Firstly, BE automatically selects...

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Bibliographic Details
Published in:IEEE transactions on power delivery 2014-08, Vol.29 (4), p.1927-1938
Main Authors: Chan, Jeffery C., Hui Ma, Saha, Tapan Kumar
Format: Article
Language:English
Subjects:
Applied sciences
Automation
Blind equalization (BE)
Blind equalizers
Blinds
Boundary element method
de-noising
Discharge
Discharges (electric)
Electrical engineering. Electrical power engineering
Electrical power engineering
Equalization
Exact sciences and technology
Insulation
Mathematical analysis
mathematical morphology (MM)
Noise
partial discharge (PD)
Partial discharge measurement
Partial discharges
phase-resolved pulse sequence (PRPS)
Power electronics, power supplies
Power networks and lines
Sensors
Substations
Testing. Reliability. Quality control
transformer
Transformers
Transformers and inductors
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Summary:Partial discharge (PD) signals acquired from on-line measurements of power transformers are easily overwhelmed by various interference and noise. This paper proposes an automatic blind equalization (BE) and morphological thresholding method for PD signal de-noising. Firstly, BE automatically selects an equalized signal that reveals PD impulses from an acquired noise-corrupted signal. Then, automatic morphological thresholding (AMT) is adopted for determining thresholds on the equalized signal. After de-noising with BE and AMT, phase-resolved pulse sequence (PRPS) is constructed and used for analyzing the types of insulation defects that cause discharges. To verify the proposed method, PD measurements on experimental PD models and a distribution transformer have been conducted. The results show that PD impulses can be extracted from severely noise-corrupted signals by using the proposed method. Also, PRPS constructed from de-noised signals can achieve consistency in revealing the types of insulation defects even different types of PD sensors and measurement systems are used.
ISSN:0885-8977
1937-4208
DOI:10.1109/TPWRD.2014.2322114