Partial discharge (PD) diagnosis is essential to identify the nature of insulation defects causing discharge. The problem of PD signal recognition has been approached in a number of ways. Most of the approaches are based on laboratory experiments or on signals acquired during off-line tests of industrial apparatus. On-line testing is vastly preferable as the equipment can remain in service, and the operators can monitor the insulation condition continuously. Interferences from noise sources have been a persistent problem, which have increased with the advent of solid-state power switching electronics. Use of wavelet transform technique offers many advantages over conventional digital filters and is ideally suited to process nonstationary signals (transients) often encountered in high voltage testing and measurements. In this paper, an empirical waveletbased method is proposed to recover PD pulses mixed with excessive noise/interference. A critical assessment of the proposed method is carried out by processing simulated PD signals along with noise signals using MAT LAB software.
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