Mathematical Model and Numerical Analysis of AE Wave Generated by Partial Discharges

Wotzka, Daria; Boczar, T.; Frącz, Paweł

doi:10.12693/aphyspola.120.767

Cited by 29 publications

(10 citation statements)

References 4 publications

(5 reference statements)

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“…The typical frequency band for AE signals generated by PD under on-site conditions is expected to be in the range from 30 to 150 kHz. However, some researchers gave examples of PD signals where higher frequency components (300–400 kHz) were significantly presented [15,35,36]. Therefore, according to the current knowledge and authors’ experience, the upper frequency was set to 500 kHz.…”

Section: Methodsmentioning

confidence: 99%

A Classification Method for Select Defects in Power Transformers Based on the Acoustic Signals

Kunicki

Wotzka

2019

Sensors

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Effective, accurate and adequately early detection of any potential defects in power transformers is still a challenging issue. As the acoustic method is known as one of the noninvasive and nondestructive testing methods, this paper proposes a new approach of the classification method for defect identification in power transformers based on the acoustic measurements. Typical application of acoustic emission (AE) method is the detection of partial discharges (PD); however, during PD measurements other defects may also be identified in the transformer. In this research, a database of various signal sources recorded during acoustic PD measurements in real-life power transformers over several years was gathered. Furthermore, all of the signals are divided into two groups (PD/other) and in the second step into eight classes of various defects. Based on these, selected classification models including machine learning algorithms were applied to training and validation. Energy patterns based on the discrete wavelet transform (DWT) were used as model inputs. As a result, the presented method allows one to identify with high accuracy, not only the selected kind of PD (1st step), but other kinds of faults or anomalies within the transformer being tested (2nd step). The proposed two-step classification method may be applied as a supplementary part of a technical condition assessment system or decision support system for management of power transformers.

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Section: Methodsmentioning

confidence: 99%

A Classification Method for Select Defects in Power Transformers Based on the Acoustic Signals

Kunicki

Wotzka

2019

Sensors

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“…This understanding of the PD behavior can be very helpful to predict the actual frequency ranges of the generated PD based on the received one. An approach in [3] presented the PD as a multiple of different sine waves with different frequencies and attempted to understand the interaction between them as it happens in PD pulse. This approach considers that all these sine waves will travel with the same velocity which is not accurate because each frequency will travel with different velocity as discussed by reference [4].…”

Section: Introductionmentioning

confidence: 99%

Detection of partial discharge acoustic emission in power transformer

Shaker¹

2019

IJECE

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<span>Partial discharge is one the most important factor that leads to deteroration and failure of the power transformer transformer. Acoustic emission detection is effective method to evaluate the health index of the power transformer. Using acoustic emission (AE) sensors for partial discharge (PD) measurement is considered as one of the most promising techniques to detect and localize PD activities inside the transformer tank. On the other hand, AE waves suffer from high attenuation and reflections while traveling from the PD source to the AE sensor. The modeling of the AE wave can help to understand the behavior of the AE PD signal during its travel. In this paper, the AE PD signal is assumed to be composed of different frequencies. This work aims to investigate the influence of the frequency value on the attenuation and arrival time of the acoustic wave.</span>

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“…Parameters of the propagation path of AE signals aect the results of the analysis in time, frequency and time-frequency [5,10,11,16]. Therefore, an important problem is to determine the length and value parameters of prolongation path of the acoustic wave generated by PDs.…”

Section: Introductionmentioning

confidence: 99%

Solving a Set of Spherical Equations for Localization of Partial Discharges by Acoustic Emission Method

et al. 2015

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This article deals with the subject matter of improvement of the acoustic emission methods used for location of partial discharges, which may occur inside power transformer insulation systems. Analytical solutions of spherical equations for location of partial discharge generation using the acoustic method were shown in detail. Presented in the article method of solving the assumed equations is based on the analytical method and matrix notation. Theoretical considerations and later the measurement-based verication refer to the use of the triangulation method for location of the occurrence of partial discharges. The results of the scientic and research works that have been presented in this article are the next stage of research aimed at development of on-line diagnosis system for insulation systems of electrical equipment, allowing for detection, measurement and identication of forms and locations of partial discharges using the acoustic emission method.

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Mathematical Model and Numerical Analysis of AE Wave Generated by Partial Discharges

Cited by 29 publications

References 4 publications

A Classification Method for Select Defects in Power Transformers Based on the Acoustic Signals

A Classification Method for Select Defects in Power Transformers Based on the Acoustic Signals

Detection of partial discharge acoustic emission in power transformer

Solving a Set of Spherical Equations for Localization of Partial Discharges by Acoustic Emission Method

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