Feature extraction and analysis of ultra-high-frequency signals for partial discharges in power transformers
Zeyu Cui
Chongqing University
DOI: https://doi.org/10.59429/esta.v12i1.9661
Keywords: Power transformer, local discharge, uHF signal, time-frequency analysis, machine learning
Abstract
In the power system, the local discharge of electrical signal of power transformer are rich and complex, easy to noise interference, and the traditional analysis method has obvious limitations. To this end, the author innovatively puts forward the time frequency analysis and machine learning technology fusion of local discharge electrical signal diagnosis method, through the short Fourier transform and wavelet transform capture high frequency signal component, reuse support vector machine machine learning methods, greatly improve detection accuracy and reliability, provide scientific basis for power equipment on-line monitoring and fault early warning.
References
[1] Rajamayil M ,Basharan V .A novel semi-supervised power transformer defect monitoring technique using unreliable pseudo-labels with highly imbalanced partial discharge signals[J].Electrical Engineering,2024,(prepublish):1-19.
[2] LiuH ,YangT ,ZhangZ , et al.Ultrasonic localization method based on Chan‐WLS algorithm for detecting power transformer partial discharge faults by fibre optic F‐P sensing array[J].High Voltage,2024,9(6):1234-1245.
[3] ShangH ,ZhaoZ ,ZhangR , et al.Transformer partial discharge fault diagnosis based on improved adaptive local iterative filtering‐bidirectional long short‐term memory[J].IET Electric Power Applications,2024,18(10):1214-1232.
[4] Thobejane T L ,Thango A B .Partial Discharge Source Classification in Power Transformers: A Systematic Literature Review[J].Applied Sciences,2024,14(14):6097-6097.
[5] Shang H ,Zhao Z ,Li J , et al.Partial Discharge Fault Diagnosis in Power Transformers Based on SGMD Approximate Entropy and Optimized BILSTM[J].Entropy,2024,26(7):551-551.
[6] Farzin K ,Hamidreza K ,Zarei M K , et al.Partial discharge localization in power transformer tanks using machine learning methods[J].Scientific Reports,2024,14(1):11785-11785.
[7] Beura P C ,Wolters J ,Tenbohlen S .Application of Pathfinding Algorithms in Partial Discharge Localization in Power Transformers[J].Sensors,2024,24(2):
[8] JangjooA M ,AllahbakhshiM ,MirzaeiR H .Ultra‐high frequency sensors positioning on the power transformer to mitigate the negative effects on the partial discharge localization accuracy[J].IET Generation, Transmission & Distribution,2024,18(3):585-595.
[9] S. W S ,H. A G ,A. M A , et al.Design of a compact ultra-high frequency antenna for partial discharge detection in oil immersed power transformers[J].Ain Shams Engineering Journal,2022,13(2):
[10] Akbari M A ,Mohamadreza A ,Peter W , et al.Optimal frequency selection for detection of partial discharges in power transformers using the UHF measurement technique[J].Measurement,2021,172