Abstract
As the weak link of the cable assembly, the internal insulation structure of the cable terminal is complex, the installation requirements are high, and the operating environment is complex, which is prone to external interference and insulation failure. However, the existing detection means of the cable terminal of the rolling stock is complicated, expensive, vulnerable to field noise interference and inefficient detection. In this study, a new method for diagnosis of cable termination insulation status by measuring the field strength along the cable termination surface is proposed. The characteristics of axial electric field distribution of defective cable terminals are studied by using multi-physical field simulation method to realize the degree of axial development of faulty cable terminal. The electric field sensor was used to measure the surface field intensity distribution of cable terminals with different degrees of interface defects, and the electric field intensity distribution law of cable terminals with different degrees of defects is obtained. The distribution of the interquartile range and variance of the electric field intensity along the cable terminal is analyzed. The results show that the greater the interface defect, the greater the interquartile range and variance of the electric field intensity along the cable terminal. Therefore, the development degree of interface defects can be judged by testing the surface electric field intensity of cable terminal.
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References
Bai L, Zhou L, Li L, Chen Y, Guo L (2019) Partial discharge of cable termination on EMU of China high-speed railway below zero degrees centigrade. IET Sci Meas Technol 13(6):912–921
Zhou L, Zhu S, Bai L, Liu Y, Zhu L, Guo L (2019) Influence of stress tubes interface on partial discharge of vehicle cable terminal at low temperatures. High Voltage Eng 45(4):1266–1273
Mazzanti G, Marzinotto M (2017) Advanced electro-thermal life and reliability model for high voltage cable systems including accessories. IEEE Electr Insul Mag 3(33):17–25
Lai Q, Chen J, Hu L, Cao J, **e Y, Guo D, Liu G, Wang P, Zhu N (2020) Investigation of tail pipe breakdown incident for 110 kV cable termination and proposal of fault prevention. Eng Fail Anal 108:104353
Du B, Han T (2014) Tree characteristics in silicone rubber/SiO2 nanocomposites under low temperature. IEEE Trans Diel Electron Ind 21(2):503–510
Nie YJ, Zhao XP, Li ST (2020) Research progress in condition monitoring and insulation diagnosis of XLPE cable. High Voltage Eng 464:1361–1371
Chou CJ, Chen CH (2018) Measurement and analysis of partial discharge of high and medium voltage power equipment. In: 2018 7th International symposium on next generation electronics (ISNE), Taipei, Taiwan
Bai LL, Zhou LJ, Cao WD, Che XY, **ng LM, Li LN (2020) Characteristics of partial discharge in air gap defects in EPR cable termination under −40 °C condition. High Voltage Eng 4610:3605–3614
Álvarez F, Garnacho F, Ortego J, Sánchez-Urán M (2015) Application of HFCT and UHF sensors in on-line partial discharge measurements for insulation diagnosis of high voltage equipment. Sensors (Basel, Switzerland) 15:7360–7387
Yii CC, Rohani MNKH, Isa M, Hassan SIS (2017) Multi-end PD location algorithm using segmented correlation and trimmed mean data filtering techniques for mv underground cable. IEEE Trans Dielectr Electr Insul 24:92–98
Ma S, Chen M, Wu J, Wang Y, Jia B, Jiang Y (2019) High-voltage circuit breaker fault diagnosis using a hybrid feature transformation approach based on random forest and stacked autoencoder. IEEE Trans Ind Electron 66:9777–9788
Dey D, Chatterjee B, Dalai S (2018) A deep learning framework using convolution neural network for classification of impulse fault patterns in transformers with increased accuracy. IEEE Trans Dielectr Electr Insul 24(6):3894–3897
Hayt AJ Jr, William H, Buck JAS (2018) Buck engineering electromagnetics. **’an Jiaotong University Press, **’an
Zhao TH, Zhang Y, Wang JX (2021) Load outlier identification method based on spatial density clustering and abnormal data domain. Autom Electric Power Syst 45
Acknowledgments
This work is supported by National Natural Science Foundation of China (U1966602) and Excellent Young Scientists Fund of China (51922090).
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Tang, Y., Xu, Y., Gao, G., Liu, K., Chen, K., Wu, G. (2024). A Novel Detection Method for Interface Defect Development of High-Speed Train Cable Terminal. In: Dong, X., Cai, L. (eds) The Proceedings of 2023 4th International Symposium on Insulation and Discharge Computation for Power Equipment (IDCOMPU2023). IDCOMPU 2023. Lecture Notes in Electrical Engineering, vol 1102. Springer, Singapore. https://doi.org/10.1007/978-981-99-7405-4_5
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DOI: https://doi.org/10.1007/978-981-99-7405-4_5
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