Preprocessing of electrical partial discharge signals using autocorrelation function (ACF)

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Md Thayoob Y.H.
Ghosh P.S.
Ghani A.B.Abd.
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IEEE Computer Society
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Partial discharge (PD) measurement has always been a popular technique to detect the degradation in high voltage plant insulating systems. In this research work, an experiment has been carried out on an 11KV, single-core 240mm2 XLPE cable to acquire electrical partial discharge signals under several different operating conditions. Despite the advances in measuring instrumentation including special detection circuits to filter out various forms of noise, the sensitivity and validity of partial discharge data is often compromised by noise. This is because PD signals are random signals, which may represent wanted signals, mixed with unwanted noise. Hence the application of the autocorrelation function (ACF), which is a random process function, to process, characterize and validate the PD data from the experiment prior to further analysis is explored in this paper. The obtained results also confirmed the ability of the technique to process and analyze PD signals. � 2006 IEEE.
Autocorrelation function (ACF) and random signals , Partial discharge measurement , Partial discharge signals , Autocorrelation , Correlation detectors , Discharge (fluid mechanics) , Random processes , Signal processing , Autocorrelation functions , Detection circuits , Different operating conditions , High voltage plant , Insulating system , Partial discharge measurements , Partial discharge signal , Random signal , Partial discharges