DETECTION AND DENOISING OF PARTIAL DISCHARGE SIGNALS IN POWER CABLES USING WAVELET TECHNIQUE

Abstract

In this thesis, the problem of partial discharges and their adverse effect on the lifetime of the insulation of high voltage cables is highlighted. Ways of detecting partial discharges inside shielded laboratories in the factory along with all the requirements to achieve successful detection are shown. Meanwhile, it is pointed out that partial discharge detection on installed live cables is necessary in many cases to diagnose cable defects and allow condition monitoring of the cable’s insulation. In such cases, the most prevalent problem preventing proper diagnosing and monitoring of partial discharges online is the fact that ambient noise normally exists on the site, which would then superimpose on the signal generated by the partial discharge. Such external noise may vary in magnitude, frequency, and shape. Therefore, this study presents a novel wavelet-based denoising algorithm, which is seen in the thesis to successfully differentiate between the noise and the signal, whereby it enables reducing the noise magnitude. Consequently, a better and realistic partial discharge signal is produced to serve cable condition monitoring and diagnosis.