Evaluation of transformer health condition using reduced number of tests

Abu-Elanien, Ahmed E. B.; Salama, M.M.A.

doi:10.1007/s00202-019-00785-x

Cited by 5 publications

(6 citation statements)

References 29 publications

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“…Unlike the dissolved gas analysis methods [2], the test results are instantaneous with the UHF method.…”

Section: Original Papermentioning

confidence: 99%

“…Reliable operation of power transformers is critical for the necessary security of electricity supply and mainly depends on the correct condition of electrical insulation. If the insulation damage is not detected [1,2] and repaired, the initial defects can lead to the transformer operating outside its nominal parameters, which can lead to a fatal failure [3]. This will not only damage the surrounding equipment and plant, but will also lead to appropriate payment of prescribed fines, loss of revenue and dissatisfaction of electricity users [4].…”

Section: Introductionmentioning

confidence: 99%

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Extraction of Partial Discharge Signal in Predominantly VHF Frequency Range in the Presence of Strong Noise in Power Transformer

Dukanac¹

2022

Preprint

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This paper provides a detailed analysis of the online detected partial discharge (PD) in the predominantly VHF range in the power transformer during normal operation in the thermal power plant. A standard UHF drain valve sensor is used with the ability to also capture VHF frequencies of received signals. If PD detection is performed during off-line testing, there are excessive costs proportional to the time during which the power transformers are disconnected from the network. For this economic reason, online PD detection techniques are more convenient. The UHF technique has a higher signal-to-noise ratio compared to IEC 60270 and the acoustic method. To accurately determine the strength and waveform of the PD signal, especially if the source position is far from the UHF sensor or if the signal is weak, it is necessary to properly separate the useful part of the recorded signal from the background noise. The criterion for this is that there are no time shifts of the first peaks of the most prominent PD. For that reason, the beginning and the approximate end of PD signal has to be determined. The results show some obvious similarities of PDs in the recorded signals, such as frequency range, duration, repetition rate and the same dominant frequency, which sufficiently indicates that it is the same type of PD.

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“…Unlike the dissolved gas analysis methods [2], the test results are instantaneous with the UHF method.…”

Section: Original Papermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extraction of Partial Discharge Signal in Predominantly VHF Frequency Range in the Presence of Strong Noise in Power Transformer

Dukanac¹

2022

Preprint

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“…MRMR ranks the importance features of the classification problem. The main objective of MRMR is to minimize the redundancy of a feature set and maximize the relevance of a feature set to classification output c by using mutual information I, as follows [18,19]:…”

Section: B Reduced-feature Scenariomentioning

confidence: 99%

“…where S is the optimal set of features that maximize relevance and minimize redundancy , | | is the number of features in S, are two features that belong to set S, denotes the output classes, and I is the mutual information that can be expressed as follows [18,20]:…”

Section: B Reduced-feature Scenariomentioning

confidence: 99%

“…The method's accuracy was investigated by using one case only, which was not enough to verify the model's prediction capability. The proposed model in [18] was used to estimate the linear relation between PTHI and transformer tests. The researchers concluded that DGA, FA, and breakdown voltage test are sufficient and can provide an acceptable indication of PTHI compared with other techniques that involve many tests.…”

Section: Introductionmentioning

confidence: 99%

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Comparative Study of Full and Reduced Feature Scenarios for Health Index Computation of Power Transformers

Ghoneim

Taha

2020

IEEE Access

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Power transformer health index (PTHI) computation is performed based on the results of different tests, such as dissolved gas analysis (DGA), oil quality (OQ) evaluation, and depolarization factor (DP) testing. In this study, PTHI computation is performed using 631 dataset samples from Malaysia and 730 samples from the Gulf Region. A new model is proposed to predict the PTHI state by adopting intelligent classification methods (e.g., decision tree, support vector machine, k-nearest neighbor, and ensemble methods). The model is built via two-stage data processing. The first stage separates the test results into three modules that represent DGA, OQ, and DP factor codes. In the second stage, the output of the three modules is processed to predict the PTHI state. The four classification methods are applied to the proposed model, and the prediction accuracy of the PTHI state is determined. Results indicate that the proposed model has superior classification accuracy for each AI method compared with recent work. Furthermore, feature reductions are applied to minimize the testing time, effort, and costs. The reduced-feature models reveal the effectiveness of the adopted feature reduction technique. A slight difference in accuracy is observed between the full-and reduced-feature scenarios. Thus, the reduced-feature scenario is considered to decrease the effort and time of the computation process and the experimental cost. The proposed model is validated against uncertain noise in features of up to ±20%.

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Evaluation of in-service power transformer health condition for Inspection, Repair, and Replacement (IRR) maintenance planning in electric utilities

Murugan

Ramesh

2021

Int J Syst Assur Eng Manag

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Evaluation of transformer health condition using reduced number of tests

Cited by 5 publications

References 29 publications

Extraction of Partial Discharge Signal in Predominantly VHF Frequency Range in the Presence of Strong Noise in Power Transformer

Extraction of Partial Discharge Signal in Predominantly VHF Frequency Range in the Presence of Strong Noise in Power Transformer

Comparative Study of Full and Reduced Feature Scenarios for Health Index Computation of Power Transformers

Evaluation of in-service power transformer health condition for Inspection, Repair, and Replacement (IRR) maintenance planning in electric utilities

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