UHF Measurement in Power Transformers: An Algorithm to Optimize Accuracy of Arrival Time Detection and PD Localization

Ariannik, Mohamadreza; Azirani, Mohammad Akbari; Werle, Peter; Azirani, Asghar Akbari

doi:10.1109/tpwrd.2019.2909706

Cited by 33 publications

(8 citation statements)

References 21 publications

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“…In [111], an optimized algorithm was developed for the location of PD sources in power transformers. The authors evaluated three types of non-conventional techniques for extracting TDOA from signals obtained by four probe sensors, with an operating range of 150 MHz-1 GHz, inserted in a transformer specially modified for the realization of laboratory experiments.…”

Section: Location Of Pd Sources In High Voltage Equipmentmentioning

confidence: 99%

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Detection, Classification and Location of Sources of Partial Discharges Using the Radiometric Method: Trends, Challenges and Open Issues

et al. 2021

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In this article, we provide a comprehensive survey on the most relevant research in the area of detection, classification and location of partial discharge (PD) sources using the radiometric or ultra high frequency (UHF) method, focusing mainly on the works related to the use of antennas. To the best of the authors knowledge, this is the first review paper that focuses on the application of antennas based on UHF method in the complete diagnosis of PD. Specifically, we first present the main contributions to the development and optimization of UHF sensors for application in the detection of PD sources. Second, articles that used the UHF method to identify different types of PD in high voltage equipment are described. Finally, the main contributions regarding the location of sources of defects using the radiometric method are presented. Summary of works in the area of UHF detection sensors, PD classification and PD location, with their respective contributions, are shown. Finally, research trends, challenging and open issues are discussed. The purpose of this article is to provide important information about the complete diagnosis of PD, which could be used to guide the development of more efficient techniques in this research area.

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Section: Location Of Pd Sources In High Voltage Equipmentmentioning

confidence: 99%

“…Cumulative energy - [111] Developed an optimized algorithm for PD location in transformers using probe-type UHF sensors. TWCF 14,5 [112] Evaluated the impact of two filtering techniques, EMD and WT, on the results of PD location signals in a power transformer.…”

Section: Cross Correlation -[70]mentioning

confidence: 99%

Detection, Classification and Location of Sources of Partial Discharges Using the Radiometric Method: Trends, Challenges and Open Issues

et al. 2021

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“…The shortest route method [13][14][15][16][17] and the hyperbolic method [18][19][20][21][22] are two methodologies that can locate the PD source inside the power transformers utilizing the UHF measurements. The accuracy of the shortest route method is inherently better than the hyperbolic method because in the shortest route method all components inside the tank such as windings, tap-changer, EMWs velocity inside different insulations, which affect the localization accuracy, are considered, while in the hyperbolic method, these components are not considered and the entire space inside the transformer tank is considered homogeneous.…”

Section: Introductionmentioning

confidence: 99%

Ultra‐high frequency sensors positioning on the power transformer to mitigate the negative effects on the partial discharge localization accuracy

Jangjoo,

Allahbakhshi,

Mirzaei

2024

IET Generation Trans & Dist

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This paper proposes a new method for improving the partial discharge (PD) localization accuracy by detecting the best places of ultra‐high frequency (UHF) sensors on the power transformer tank. In this way, firstly, the critical sites inside the power transformer that can produce PD are determined. Then the sensors’ positioning is done in such a way that if the PD happens at each point of these critical sites, the distance between the estimated PD location obtained by solving the time difference of arrival (TDOA) equations and the actual PD location is laid in an acceptable range. For this purpose, the TDOA equations are linearized around the critical PD coordinates as a matrix form A.X = B. The configuration of the sensor positions that minimizes the condition number of the matrix A is the best configuration. To evaluate the effectiveness of the proposed method, several simulations and evaluations are performed on a power transformer in the CST software. The obtained results and comparing them with the previous method and also conventional arbitrary sensors positioning confirm the effectiveness of this method.

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“…PD is often difficult to detect and locate, and it can be a major cause of transformer failure [2][3][4][5]. Various diagnostic techniques have been developed to sense and detect PD in power transformers [5][6][7]. These techniques include time and frequency analysis.…”

Section: Introductionmentioning

confidence: 99%

Time Reversal vs. Integration of Time Reversal with Convolution Neural Network in Diagnosing Partial Discharge in Power Transformer

Sekatane,

Bokoro

2023

Energies

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Partial discharge (PD) is a common issue in power transformers that can lead to catastrophic failures if left undetected. Time reversal (TR) is a well-known technique in signal processing that can reconstruct signals by reversing the direction of time. The paper investigates the use of time reversal and the integration of time reversal with convolution neural networks (CNNs) for diagnosing PD in power transformers. We compare the performance of these techniques on a dataset of PD signals collected from power transformers. We propose a novel method of using time reversal as a pre-processing step to improve the accuracy of CNNs on noisy or distorted signals. Our experimental results demonstrate that this approach can significantly enhance the performance of CNNs on various datasets, including speech, audio, and image datasets. This paper provides a novel approach to signal processing and demonstrates the potential of time reversal as a pre-processing step in CNNs.

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UHF Measurement in Power Transformers: An Algorithm to Optimize Accuracy of Arrival Time Detection and PD Localization

Cited by 33 publications

References 21 publications

Detection, Classification and Location of Sources of Partial Discharges Using the Radiometric Method: Trends, Challenges and Open Issues

Detection, Classification and Location of Sources of Partial Discharges Using the Radiometric Method: Trends, Challenges and Open Issues

Ultra‐high frequency sensors positioning on the power transformer to mitigate the negative effects on the partial discharge localization accuracy

Time Reversal vs. Integration of Time Reversal with Convolution Neural Network in Diagnosing Partial Discharge in Power Transformer

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