On-line detection and measurement of partial discharge signals in a noisy environment

Gaouda, A.M.; El-Hag, Ayman H.; Abdel-Galil, T.K.; Salama, M.M.A.; Bartnikas, R.

doi:10.1109/tdei.2008.4591239

Cited by 72 publications

(42 citation statements)

References 28 publications

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“…Internal discharges are generated using a plane-to-plane oil-dipped electrode configuration within a sample of glass consisting of a cavity [14]. This is a typical void found in solid sheet material and some cast components.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Identification of Acoustic Signals of Internal Electric Discharges on Glass Insulator under Variable Applied Voltage

Al-geelani¹,

Piah²,

Saeh³

et al. 2016

IJECE

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A Partial Discharge (PD) is an unwanted phenomenon in electrical equipment. Therefore it is of great importance to identify different types of PD and assess their severity. This paper investigates the acoustic emissions associated with Internal Discharge (ID) from different types of sources in the time-domain. An experimental setup was arranged in the high voltage laboratory, a chamber with an electrode configuration attached to it was connected to a high voltage transformer for generating various types of PD. A laboratory experiment was done by making the models of these discharges. The test equipment including antennas as a means of detection and digital processing techniques for signal analysis were used. Wavelet signal processing was used to recover the internal discharge acoustic signal by eliminating the noises of many natures. Keyword:Acoustic INTRODUCTIONOutdoor insulation represents an important component of electric power transmission and distribution systems, given that a single insulator failure can result in an excessive outage of the power system. Different insulator designs and materials are employed by power corporations and their behaviours are investigated and tested in laboratories and field tests as well as during service conditions. Specimens (rods and plates) are also tested when researchers focus on investigating certain phenomena of surface activity or material performance without being influenced by the insulator design [1]. The performance of insulators is strongly linked to local conditions, especially to the accumulation of pollutants and the wetting mechanisms present.The weak parts of the insulation are the cavities, since the gas breakdown strength is lower than that of the solid insulation. On the other hand, the electric field in the cavities is much stronger than in the big insulation parts due to lower gas permittivity [2]. Hence, the PD is limited inside the cavities and does not penetrate through the solid material to reach the electrodes. Initiation of a PD in a cavity needs two major conditions; essentially the cavity electric field should be more than that of the gas, a condition called the inception voltage level. To start an electron avalanche, a free electron must be present in the cavity [3]. The extinction voltage level may depend on the actual voltage at which a discharge starts, since presumably a higher inception voltage yields a higher initial temperature in the streamer channel. In this study, the adaptability of the Daubechies wavelets of orders 2 has been evaluated, and results have shown the superiority. It is befitting to select a suitable number of breakup levels based on the nature of the signal.

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Section: Resultsmentioning

confidence: 99%

“…To generate a cavity or internal discharge, a plastic container was used to place the specimen inside it and the container was filled with transformer oil in order to avoid any other type of PDs and to focus exclusively on internal discharge [14]. Figure 4 reports the setup for generation of internal discharge in oil.…”

Section: Internal Discharge Generationmentioning

confidence: 99%

Identification of Acoustic Signals of Internal Electric Discharges on Glass Insulator under Variable Applied Voltage

Al-geelani¹,

Piah²,

Saeh³

et al. 2016

IJECE

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“…Many researches have been undertaken focusing on related areas [2][3][4]. Partial discharge in dielectric liquids is a very complex process that involves a succession of inter-correlated phenomena (electronic, mechanical, thermal, etc.).…”

Section: Introductionmentioning

confidence: 99%

Modeling of the Partial Discharge Process in a Liquid Dielectric: Effect of Applied Voltage, Gap Distance, and Electrode Type

et al. 2013

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Abstract:The partial discharge (PD) process in liquid dielectrics is influenced by several factors. Although the PD current contains the information representing the discharge process during the PD event, it is difficult to determine the detailed dynamics of what is happening in the bulk of the liquid. In this paper, a microscopic model describing the dynamics of the charge carriers is implemented. The model consists of drift-diffusion equations of electrons, positive and negative ions coupled with Poisson's equation. The stochastic feature of PD events is included in the equation. First the model is validated through comparison between the calculated PD current and experimental data. Then experiments are conducted to study the effects of the amplitude of the applied voltage, gap distance and electrode type on the PD process. The PD currents under each condition are recorded. Simulations based on the model have been conducted to analyze the dynamics of the PD events under each condition, and thus explain the mechanism of how these factors influence the PD events. The space charge generated in the PD process is revealed as the main reason affecting the microscopic process of the PD events.

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“…Although offline measurements can eliminate most noise by carefully arranging measurement setups, online measurements provide higher flexibility on continuously acquiring PD signals from operating transformers. Therefore, online PD measurement methods have been widely investigated for transformer insulation diagnostics over the past few decades [28][29][30][31][32][33][34][35][36][37][38][39][40][41]. PD is a localized electrical breakdown, which can be traced back to a tiny area of a discharge site inside insulation materials.…”

Section: Chemical-based Methods Electrical-based Methodsmentioning

confidence: 99%

“…The transformers under investigation are in the range from 1 MVA to 10 MVA. [34,[121][122][123][124][125]. In WT, a wavelet function is used to decompose an acquired signal (noise-corrupted PD signal) into a series of wavelet coefficients.…”

Section: Field Pd Measurement Setupmentioning

confidence: 99%

Advanced signal processing techniques for online power transformer insulation diagnosis

Chan¹

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Power transformer is one of the most important assets in an electric utility. However, a large number of existing power transformers worldwide have already approached or even exceeded their designed lifetimes. Any failure of a transformer can be disastrous. Therefore, the conditions of transformers need to be continuously monitored and evaluated. Since a transformer's condition is largely dependent on its insulation system, a number of diagnostic methods have been developed for assessing transformer insulation conditions over the past decades. Among these methods, partial discharge (PD) measurement is widely adopted due to its capability of providing continuously online monitoring and diagnosis of a transformer without disturbing its normal operation.PD is a rather complicated phenomenon and stochastic in nature. Properly performing online PD measurements of a transformer, effectively analysing the measured PD signals, and subsequently making an informed condition assessment on a transformer's insulation system are still challenging.This thesis is aimed at developing advanced signal processing techniques for online PD monitoring and diagnosis of power transformer insulation systems.PD signals acquired at substation environments are always coupled with extensive noise, which exhibits different distribution properties. Therefore, PD signal de-noising is an essential process for accurately extracting PD signals from the acquired noise-corrupted signals before further analysis. In this thesis, advanced signal processing techniques, such as wavelet transform (WT), empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), blind equalization (BE) and pre-whitening, have been investigated for removing discrete spectral interference (DSI) that exhibits sinusoidal behaviour at various frequencies. Mathematical morphology (MM) has also been investigated for suppressing white noise by adaptively selecting threshold values. To remove stochastic noise, fractal dimension and entropy analyses have been investigated. Based on these techniques, several adaptive PD signal de-noising methods have been proposed in this thesis for removing different types of noise. A number of case studies using PD signals acquired from both laboratory experiments and online PD measurements of field transformers are presented. These case studies demonstrate advantages of the proposed PD signal de-noising methods over conventional methods in PD signal de-noising.In this thesis, phase-resolved pulse sequence (PRPS) diagrams and kurtograms have also been proposed for consistent representations of PD patterns after the noise has been removed. Case studies have been provided to prove a PRPS diagram's capability for accurately and consistently ii representing PD patterns. This representation can minimize influences of different types of PD sensors and measurement systems on PD pattern construction. Results are presented to demonstrate that kurtograms can be used to represent PD patterns even in the presence of extensive w...

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On-line detection and measurement of partial discharge signals in a noisy environment

Cited by 72 publications

References 28 publications

Identification of Acoustic Signals of Internal Electric Discharges on Glass Insulator under Variable Applied Voltage

Identification of Acoustic Signals of Internal Electric Discharges on Glass Insulator under Variable Applied Voltage

Modeling of the Partial Discharge Process in a Liquid Dielectric: Effect of Applied Voltage, Gap Distance, and Electrode Type

Advanced signal processing techniques for online power transformer insulation diagnosis

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