Partial Discharge Signal Processing Research Articles

Review of Partial Discharge Signal Processing and Monitoring System using Virtual Instrument Software

Most of Partial Discharge (PD) processing systems have been developed using virtual instrument to analyse raw measured PD signal. However, some of researchers had neglected the denoising or recognition technique and only focussed on PD location estimation and vice versa This paper reviews an overview of denoising recognition techniques, denoising analysis, PD sensors, location methods and type of virtual instruments in published PD signal processing signal system. A perfect PD analysis system is more beneficial if both PD denoising and locating are applied in the system. Based on this review, the new design of PD signal processing system based on DWT denoising technique and RC sensor using LabVIEW Software for underground power cable using SCTM as PD location algorithm is proposed.

Remote testing of high-voltage insulators

An integrated two-channel method has been suggested for remote testing of operating condition of high-voltage insulators. The method is based on concurrent registration and computer processing of partial-discharge signals that are detected by electromagnetic and acoustic sensors. Using the device that was created based on this method, diagnostic signs have been established that make it possible to distinguish between functional and faulty insulators under real service conditions.

A New Method for Partial Discharge Signal Processing

A partial discharge (PD) signal processing method based on dynamic measurement theory and wavelet transform is proposed in this paper. The deterministic component was separated by polynomial fitting, and the random component of the remaining residual after the separation was estimated using autoregressive (AR) model; The true value estimate and dynamic measurement uncertainty of noisy signal were obtained by the deterministic component and random component;Db8 wavelet and the soft threshold based on Stein’s Unbiased Estimate of Risk were used to smoothly denoise for better PD signal processing. Finally, the effectiveness of the method was verified by MATLAB simulation and experimental noisy PD signal extraction.

Recording and processing of partial discharge signals

Electromagnetic-activity signals that arise in an air discharge gap under the action of an alternating voltage at a frequency of 50 Hz were studied using an omnidirectional antenna, a measuring pulse transformer, and an oscilloscope. The frequency range with the maximum signal-to-noise ratio for partial discharge signals was determined. Partial discharges that cause a breakdown in the air discharge gap and that are identical in the apparent-discharge value to partial discharges in the polymer insulation were simulated using a system of surface-needle electrodes. Corona discharges were modeled. Amplitude-phase diagrams were constructed for distinguishing corona signals from partial-discharge signals. Model discharges made it possible to investigate the specific features of a polymer-insulation breakdown.