Partial discharge

About: Partial discharge is a research topic. Over the lifetime, 13997 publications have been published within this topic receiving 102058 citations. The topic is also known as: PD.

Partial discharges. XII. Partial discharge detection in rotating electrical machines

Abstract: For pt.XI see ibid., vol.8, no.2, p.14 et seq. (1992). Partial discharge (PD) phenomena in the windings of rotating machines are examined. PD measurements on rotating machines, both offline and online, are described. Data acquisition and analysis requirements are briefly considered. >

Effect of voltage and capacitance in nanosecond pulse discharge enhanced laser-induced breakdown spectroscopy

Abstract: The laser ablation fast pulse discharge plasma spectroscopy (LA-FPDPS) technique has demonstrated its validity to enhance the optical emission of laser-induced plasma. It has the potential to improve the performance of traditional LIBS measurement. Very recently, LA-FPDPS with a nanosecond pulse discharge circuit has been developed, which has a better capability to enhance the optical emission intensity of laser plasma compared with that using a microsecond pulse discharge circuit. In this paper, the effect of the discharge capacitance and discharge voltage on the optical emission of soil plasma generated by LA-FPDPS with a nanosecond pulse discharge circuit is evaluated in detail. In addition, the stability of the time delay between the laser firing and discharge, and between the discharge and optical emission, has been carefully investigated.

Partial discharge tests using CIGRE method II

Abstract: In this paper, the results of an experimental project on insulating material aging, performed in both Denmark and Italy, are reported. This study was concerned with partial discharge (PD) behavior at temperatures between 30 and 80/spl deg/C using CIGRE method II. The material tested was a commercial polymethylmethacrylate (PMMA) which was chosen not for its good dielectric properties but rather because much of its discharge resistance data at ambient temperature is already well documented. A description is given of the theoretical and experimental methodology followed in this work. Mixed Weibull analysis techniques in terms of the PD amplitude and phase distribution characteristics were employed to distinguish the presence of different aging mechanisms. Such a difference was observed at 30 and at 80/spl deg/C. At 30/spl deg/C the analysis inferred a single discharge aging process acting until breakdown, while at 80/spl deg/C the results suggested the predominance of a single PD aging mechanism for the first half of the insulation lifetime; however, for the remainder of the insulation life time, an additional degradation mechanism was evinced.

Degradation of epoxy resin by partial discharges

Abstract: Epoxy resins are used in the production of high-voltage insulation components. Partial discharges, inherent in high-voltage installations, degenerate the resinous material and cause degradation of the insulation thus reducing the working life of the component, An understanding of the nature of the chemical changes taking place under partial discharge stressing should allow the production of improved insulation systems and/or identification of diagnostic methods for monitoring the state of existing equipment. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) microspectroscopy is used to determine the chemical changes to the surface of a bisphenol-A based epoxy resin resulting from partial discharge stressing in an air environment. Differences in stressed resin surface chemistry are found to be dependent upon the humidity of the stressed air. The variation in degradation products occurring in dry and in moist air are discussed and possible reactions to explain these differences are presented.

Wavelet Kernel-Based Convolutional Neural Network for Localization of Partial Discharge Sources Within a Power Apparatus

Abstract: This article presents a new convolutional neural network (CNN) topology using wavelet kernels to detect and discriminate single or multiple partial discharge (PD) locations in high voltage power apparatus with increased accuracy. The method is tested on an electrical equipment model with acoustic PD sensors. A cubical tank has been emulated in the laboratory representing the equipment under test and partial discharge sources have been placed at different positions along with the required data acquisition hardware. The present scheme eliminates the requirement of separate algorithms for feature extraction and classification of the acquired PD signals. Wavelet kernels of the CNN play a crucial role in feature learning, and the proposed CNN architecture as a whole, can classify the features in a supervised manner. The performance of the proposed scheme is compared with other existing methods using the same data set . It is found that an overall accuracy of 97.64% is achieved by the proposed method, outperforming other existing methods by a significant margin of at least 5% in terms of accuracy. The developed module is a generic one and can be adapted for different high voltage electrical apparatus with similar topological structures; hence, it can be used in various ways in power industry.