A new approach to the diagnosis of solid insulation systems based on PD signal inference

Cavallini, A.; Montanari, G.C.; Contin, A.; Pulletti, F.

doi:10.1109/mei.2003.1192033

Cited by 162 publications

(70 citation statements)

References 16 publications

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“…The reason is that the pulse interference, especially the random pulse interference, has very similar characteristics to partial signals in time domain. With the development of high-speed acquisition technology, the interference suppression mean based pulse waveform characteristics is gradually applied [14][15][16][17]. In this paper, the phase correlation of partial charge pulses caused by typical defects within XLPE (cross-linked polyethylene) cable is studied.…”

Section: Introductionmentioning

confidence: 99%

Suppression of Pulse Interference in Partial Discharge Measurement Based on Phase Correlation and Waveform Characteristics

Gao¹,

Wang²,

Gui³

et al. 2015

JEPE

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Partial discharge measurement is one of the most effective methods to find insulation defects and early failure of high voltage power equipments. The accuracy is significantly reduced by the interference in the partial discharge on-site detection or on-line monitoring, especially by the pulse interference. This paper studies the phase correlation of some types of typical partial discharge pulses and their characteristics in time domain and frequency domain. By collecting enough partial discharge pulse data, the correlation coefficient can be calculated based on both phase correlation and waveform similarity. The type of pulse will be determined by the scope of the calculated correlation coefficient. The pulses with very strong correlation will be identified as periodic pulse interference. The pulses with very weak correlation will be identified as random pulse interference. Only the pulses whose correlation coefficients fall into a specific range will be identified as partial discharge signals. In laboratory, simulated pulse interference is injected into measurement circuit, and typical partial discharge pulses are sampled by a high-speed acquisition system. The pulse interference can be effectively separated from partial discharge signals by correlation coefficient.

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Section: Introductionmentioning

confidence: 99%

Suppression of Pulse Interference in Partial Discharge Measurement Based on Phase Correlation and Waveform Characteristics

Gao¹,

Wang²,

Gui³

et al. 2015

JEPE

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“…This is especially important in the case of using this technique with the machine in operation. Following this trend, the analysis of the waveform of the pulse PD is also used for separating partial discharges from electrical noise and even to classify different PD sources (Okubo & Hayakawa, 2005;Cavallini, Montanari, Contin & Pulletti, 2003;Robles, Martinez-Tarifa, Rojas-Moreno & Sanz-Feito 2009).…”

Section: Introductionmentioning

confidence: 99%

A new monitoring and characterization system of partial discharges based on the analysis of the spectral power

2015

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Partial Discharges (PD) are one of the possible causes for unexpected faults in power systems equipment, so that its measure is an essential tool for high-voltage electrical equipment maintenance. In order to characterize the PD activity, some statistic magnitudes are necessary. For this reason, the acquisition and processing of PD is very important when making critical decisions regarding disconnection or repairing assets in power systems. On the other hand, the measurement environments often present multiple sources of electrical noise, thus the proper interpretation of PD patterns is a challenge in the identification of sources of different nature. In this paper, the development of a PD monitoring system capable of displaying in real time the classic PD parameters, the PD waveform, its frequency spectrum and calculating statistical parameters of the acquisition, are presented. On the whole, a new method of identifying sources of PD and electrical noise, developed by the authors, which is based on measuring the relative spectral power of PD pulses, is shown. This method has proven effective in characterizing PD and electrical noise; a series of experiments conducted in several test objects are presented in order to validate the performance of the proposed system. Keywords:Partial discharges, electrical insulation, PD pulse waveform, spectral power, fast Fourier transform. RESUMENLas descargas parciales (PD) son responsables de las fallas inesperadas en los equipos de sistemas de potencia, por lo que su medida es una herramienta fundamental en el mantenimiento de equipos eléctricos de Alta Tensión. Con el fin de caracterizar la actividad de PD, algunas magnitudes estadísticas son necesarias. Por esta razón, la adquisición y procesamiento de PD es muy importante en el momento de tomar decisiones críticas en relación con la desconexión o reparación de los sistemas de potencia. Por otro lado, los entornos de medida suelen tener presentes múltiples focos de ruido eléctrico, por lo que la interpretación adecuada de patrones de PD es un reto al que se añade la identificación de fuentes de diferente naturaleza. En este artículo se presenta el desarrollo de un sistema de monitorización de descargas parciales, capaz de visualizar en tiempo real los parámetros clásicos de descargas parciales, la forma de onda de un pulso de PD, su espectro de frecuencia y calcular los parámetros estadísticos de la adquisición. Conjuntamente se presenta un nuevo método de identificación de fuentes de PD y ruido eléctrico que han desarrollado los autores, el cual se basa en la medida de la potencia espectral relativa de los pulsos de PD. Éste método ha probado ser eficiente en la caracterización de PD y ruido eléctrico, Una serie de experimentos realizados en varios objetos de ensayo son presentados, con el fin de validar el comportamiento del sistema propuesto.Palabras clave: Descargas parciales, aislamiento eléctrico, forma de onda de los pulsos de PD, potencia espectral, transformada rápida de Fourier. Received

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“…As PDs detection is usually made in industrial environments where electrical noise is present, advanced noise rejection techniques are necessary for PDs measurement and interpretation [8]. Following this trend, pulse waveforms analysis is recently used to help in noise separation and classification [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

“…Following this trend, pulse waveforms analysis is recently used to help in noise separation and classification [8]- [10]. These processes require the use of wider band acquisition data systems and sensors (up to 50 MHz).…”

Section: Introductionmentioning

confidence: 99%

A Partial Discharges acquisition and statistical analysis software

Ardila-Rey

Martínez-Tarifa

Robles

et al. 2012

2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings

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This document is published in:Ardila-Rey, J.A.; Martinez-Tarifa, J.M.; Robles, G.; Rojas-Moreno, M.; Albarracin, R.; , "A Partial Discharges acquisition and statistical analysis software," Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International , pp. 1670-1675 Abstract-Partial Discharges (PDs) are responsible for unexpected failures in power system equipment, so their measurement is a fundamental tool for electrical equipment maintenance. In order to characterize PDs activity, some statistical magnitudes are necessary. For this purpose, PDs acquisition and processing is an important tool for critical decisions related to power systems. In this paper, the main difficulties and challenges facing PDs detection, acquisition and processing are presented. Results will be compared to a commercial PDs detection system.

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A new approach to the diagnosis of solid insulation systems based on PD signal inference

Cited by 162 publications

References 16 publications

Suppression of Pulse Interference in Partial Discharge Measurement Based on Phase Correlation and Waveform Characteristics

Suppression of Pulse Interference in Partial Discharge Measurement Based on Phase Correlation and Waveform Characteristics

A new monitoring and characterization system of partial discharges based on the analysis of the spectral power

A Partial Discharges acquisition and statistical analysis software

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