A new adaptive technique for on-line partial discharge monitoring

Abstract

The insulation system of HV apparatus deteriorates due to partial discharges (PD). PD tests are carried out successfully in shielded laboratories to verify the insulation quality and to rectify defects left during the manufacturing process. A variety of techniques exists for this purpose. It is also desired to monitor the insulation when equipment is in operation. Unfortunately, the performance of PD test equipment is adversely affected by interference signals. The sinusoidal signals of low and high frequency, due to their correlation, make the measurement difficult and sometimes even impossible. This paper describes the design of an adaptive digital filtering technique and its successful application to the on-line/on-site detection of PD current pulses generated in HV insulation in the presence of sinusoidal noise signals. The technique is based on Wiener optimal filtering theory and its characteristics are investigated. The adaptive filter of this system has a time-varying response and is self-tuning to each low and high frequency noise component. The filter remains active until the signal-to-noise ratio is significantly increased and it can be used for weak PD pulse integration. Theoretical background of the technique and the results of laboratory and field tests are presented.The insulation of HV equipment in service is usually evaluated using off-line techniques which are expensive and time consuming. Therefore, it is desired to perform Conventional narrow band and wide band detectors are commonly used to reduce the interference caused by periodical signals. Their use during on-line conditions is 1070-9878/95/ $3.00

Comparing the trustworthiness of signal‐to‐noise ratio and peak signal‐to‐noise ratio in processing noisy partial discharge signals

“…In [7], a PD pulse polluted with sinusoidal noise, measured during an on‐line insulation evaluation of a power transformer has been de‐noised and it has been claimed that high SNR value has been obtained after de‐noising. Although the noise reduction strength can be visually verified from the figures given in that paper, it should be noted that there are many samples with zero magnitude in the selected data window.…”

A Review of Online Partial Discharge Measurement of Large Generators

“…Based on the power spectrum density (PSD) of detected signals obtained by FFT, in conjunction with threshold optimized by fuzzy C-mean (FCM) adaptively, Luo et al [72] proposed an extractive method by searching DSI frequencies in PSD and compensating these frequencies smoothly with a compression ratio, which outperforms the wavelet-based denoising methods. As regard to filtering, there are several filters have been employed to suppress the PD signals, such as infinite impulse response (IIR) filter, finite impulse response filter, notch filter [73] and adaptive filter [74]. In [73], Nagesh et al evaluated various types of digital filters based on pulse distortion and filtering time, and found the cascaded 2nd order IIR lattice notch filter outperformed the others in DSI removal.…”

A PRPD-Based UHF Filtering and Noise Reduction Algorithm for GIS Partial Discharge

“…Extensive research has been conducted to address the elimination and suppression of interference. In the literature [ 8 , 9 ], various digital filtering techniques such as high-pass and low-pass filters, adaptive filters, etc., have been explored. Filters are simple and widely used.…”