Online Preventive Maintenance of HT Switchgear with Ultrasound Inspection
Keywords:
Partial discharge, preventive maintenance, ultrasound monitoring, switchgear, online electrical fault detection...Abstract
Partial discharge (PD) in insulation of equipment is prevalent cause of breakdown in switchgear. Even PD slowly deteriorate the insulation, and it take years before breakdown though it was difficult to detect PD in early stage. By combination of the basic characteristic of PD (radiate ultrasound waves) and advancement of technology to detect and quantify ultrasound noise, we have devised a preventive maintenance methodology to detect PD.
In BSP we have history of breakdowns due to Partial Discharge. Some breakdowns cause interruption in production from only one equipment where some breakdowns cause interruption in whole plant. One such breakdown is on 5th Aug 2012, where failure of end termination of 11KV feeder from MSDS-2 to SS-15 caused production loss of around 8 hours in whole 4 MT area of the plant. Financial loss of this breakdown will cross 8 digit figure.
We needed an online preventive maintenance policy to detect these faults in early stage to plan shutdown and rectify faults before any breakdown. Ultrasound inspection is the solution for our problem...
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References
IEC 60270: Partial Discharge Measurements - Advanced Test Equipment Rentals, accessed on July 14, 2025, https://www.atecorp.com/compliance-standards/iec/iec-60270
[2] Partial discharge - Wikipedia, accessed on July 14, 2025, https://en.wikipedia.org/wiki/Partial_discharge
[3] . H. Alshalawi and F. S. Al-Ismail, "Partial Discharge Detection Based on Ultrasound Using Optimized Deep Learning Approach," in IEEE Access, vol. 12, pp. 5151-5162, 2024, doi: 10.1109/ACCESS.2024.3350555
[4] Hong Liu, Zhixian Zhang, Zhiqing Shu, Jianxin Wang, Ruimin Song, Haoyuan Tian, Xuetao Duan, Wentao Zhang, Yuxuan Song, WeigenChen,Ultrasonic detection of partial discharge in oil-paper insulation based on fiber-optic dual-coupled F-P sensor,Measurement,Volume 263,2026,120172,ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2025.120172.
[5] T. Boczar, S. Borucki, A. Cichon, and D. Zmarzly, “Application possibilities of artificial neural networks for recognizing partial discharges measured by the acoustic emission method,” EEE Transactions on Dielectrics and Electrical Insulation, vol. 16, no. 1, pp. 214–223, 2009.
[6] L. Lundgaard, “Partial discharge. xiii. acoustic partial discharge detection fundamental considerations,” IEEE Electrical Insulation Magazine, vol. 8, no. 4, pp. 25–31, 1992.
[7] M. Frigo and S. G. Johnson, “The design and implementation of fftw3,” Proceedings of the IEEE, vol. 93, no. 2, pp. 216–231, 2005.
[8] J. B. Allen and L. R. Rabiner, “A unified approach to short-time fourier analysis and synthesis,” Proceedings of the IEEE, vol. 65, no. 11, pp. 1558–1564, 1977.
[9] “Short-timefft,” 2019. [Online]. Available: https://www.mathworks.com/ help/dsp/ref/dsp.stft.html
[10] J. Gu, Z. Wang, J. Kuen, L. Ma, A. Shahroudy, B. Shuai, T. Liu, X. Wang, G.Wang, J. Cai et al., “Recent advances in convolutional neural networks,” Pattern recognition, vol. 77, pp. 354–377, 2018.....
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