Detection and location of partial discharge in cast-resin dry-type transformers using a waveguide and a new acoustic emission sensor pair design

Su, Ching Chau; Tang, Ya Wen; Tai, Cheng Chi; Chen, Jiann Fuh

doi:10.1631/jzus.c1000126

Cited by 6 publications

(5 citation statements)

References 12 publications

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“…To locate partial discharges in the insulation system of transformers, microphones with a frequency range above 200 kHz and beyond with a range of several MHz are used. It can also be supplemented by measuring the radiation of the electromagnetic field of the dry transformer in the frequency range of several tens of MHz [14], [15].…”

Section: A Analysis Of the Condition Of Dry Transformers Using Acoust...mentioning

confidence: 99%

Combination of Non-contact and Contact Measuring Methods for Analyzing Structural Conditions of Dry Transformers

Gutten,

Korenciak,

Karman

et al. 2023

Measurement Science Review

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The article describes the non-contact and contact analysis of 1-MVA dry power transformers with epoxy-resin insulation using an acoustic camera and frequency analyzer with automatic sweeping for low-middle frequency areas. Power transformers are most commonly used for construction component (core, windings, taps) analysis. The electrical, non-rotating machine generates electromagnetic and acoustic emissions that can be used to analyze dry transformers during their operation. Non-contact online diagnostic methods have many advantages over offline methods because it is not necessary to shut down the transformer, and also, the condition and behaviour of the machine are analyzed during its normal operation. The article presents the analysis and comparison of structural parts of the distribution dry transformers of the same type and power. The problem of insufficient or incorrect clamp-screw connection was identified using the SFRA (Sweep Frequency Response Analysis) method.

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Section: A Analysis Of the Condition Of Dry Transformers Using Acoust...mentioning

confidence: 99%

Combination of Non-contact and Contact Measuring Methods for Analyzing Structural Conditions of Dry Transformers

Gutten,

Korenciak,

Karman

et al. 2023

Measurement Science Review

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“…Acoustic emission technique has been utilized for partial discharge detection in different components of the electric network like cables [8] gas insulated substations [9] and power transformers [10]. Moreover, multiple acoustic sensors were used to precisely locate the partial discharge source in power transformers as in [11].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Where ρ represents the density of the medium and V is the velocity of acoustic signals in that medium [10].…”

Section: Proposed Researchmentioning

confidence: 99%

“…The results of the routine oil tests performed for the two oil samples are recorded in table 2: The acoustic emission sensor was used to detect PD signals created in the air and in the oil. In previous work, it was found that most of the acoustic PD signal energy is in the frequency range 23-80 KHz [10]. Based on that an acoustic sensor with frequency range 20-80 KHz was utilized in the measurements of PD signal.…”

Section: Oil Samplesmentioning

confidence: 99%

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Acoustic detection of partial discharge using signal processing and pattern recognition techniques

Swedan¹

2012

Insight

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Power transformers are one of the major components in electric network. The service area of power transformers is quite large which means that the failure of such equipment will cause huge losses for power companies. Therefore, continuous monitoring of power transformers and preventing such failures is of great importance.During operation, power transformers are affected by different stresses such as electrical, thermal and mechanical stresses. Also, the presence of some defects within the transformer insulation under the applied electrical stress may initiate internal partial discharges. Previous experience has shown that internal partial discharges can cause serious damages for the insulation. Different methods like acoustic, optical and RF sensors were proposed to detect the partial discharge activity. Compared to other techniques, acoustic detection methods are cost effective and less susceptible to noise and interference. In addition, partial discharge (PD) source can be located using multiple acoustic sensors. However, acoustic methods have some drawbacks such as low sensitivity and high attenuation of acoustic signals.In this thesis, artificial neural networks are utilized to enhance the acoustic PD detection under different insulation conditions. Experimental results have shown that high iv detection rates of PD can be obtained under different conditions. Also, classification of insulation condition based on the acquired acoustic PD signals was successful.

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“…The nonelectric measurements detect the phenomenon of acoustics, light and thermology when PD occurred. They can use to find the location of PD [2]. Acoustic emission (AE) is one of the nonelectric methods and it provides a low-cost measurement for PD.…”

Section: Introductionmentioning

confidence: 99%

Partial discharge signal extracting using the empirical mode decomposition with wavelet transform

Lin

Tai

Tang

et al. 2011

2011 7th Asia-Pacific International Conference on Lightning

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Empirical mode decomposition (EMD) has good adaptivity for non-stationary and nonlinear signal analysis. This paper uses the advantage of EMD and combines with the wavelet transform (EMD-WT) to extract partial discharge (PD) signals in noises. The wavelet transform is a common used method for PD signal denoising. However, once the signal to noise ratio (SNR) decreases seriously, the WT method will be failed. Compare to the WT method, the EMD-WT has better performance for noise reduction. It has been verified that the EMD-WT method can preserve more information even though the SNR is low. The results show that the EMD-WT is suitable for PD denoising in a noisy environment. Index Terms-Empirical mode decomposition (EMD), Partial discharge (PD), Wavelet transform (WT), Empirical mode decomposition with wavelet transform (EMD-WT), Signal to noise ratio (SNR)

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Detection and location of partial discharge in cast-resin dry-type transformers using a waveguide and a new acoustic emission sensor pair design

Cited by 6 publications

References 12 publications

Combination of Non-contact and Contact Measuring Methods for Analyzing Structural Conditions of Dry Transformers

Combination of Non-contact and Contact Measuring Methods for Analyzing Structural Conditions of Dry Transformers

Acoustic detection of partial discharge using signal processing and pattern recognition techniques

Partial discharge signal extracting using the empirical mode decomposition with wavelet transform

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