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Internal Discharge Patterns Identification of Void in High Voltage Solid Insulation Using Phase Resolved Method

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Proceedings of the 12th International Conference on Robotics, Vision, Signal Processing and Power Applications (RoViSP 2021)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1123))

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Abstract

The occurrence of partial discharge in solid insulation indicates the deteriorating performance level of the high-voltage insulation system. The improvement process becomes complicated because no visual evidence of its existence in the system. Thus, one way to discover these possible insulation defects is through PD data representation. The phase-resolved PD pattern (PRPD) has become the most widely used tool to diagnose and visually represent PD data as well as discover possible insulation defects. Certain types of defects show characteristic clusters of partial discharges, which help to differentiate them. The observable parameters of PDs are crucial to relate to the characteristics of the PD defect in order to identify the type of defect and eventually ensure the reliable operation of HV equipment. This work aims to investigate the characteristics of internal discharges in solid insulation converted from the raw data to the PD patterns using PRPD. Two primary distributions which are Hn(φ) and Hqn(φ) results are presented to show the different asymmetry distribution gives different characteristics of PD defects.

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Acknowledgements

This work was supported in part by Universiti Sains Malaysia (USM) under the Research Universiti Grant (RUI) 1001/PELECT/8014050 (UO1620/2018/0320), and in part by the Ministry of Higher Education, Malaysia, under the Fundamental Research Grant Scheme FRGS/1/2019/TK04/UNIMAP/03/8.

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Correspondence to M. Kamarol .

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Rosle, N., Rohani, M.N.K.H., Muhamad, N.A., Suandi, S.A., Kamarol, M. (2024). Internal Discharge Patterns Identification of Void in High Voltage Solid Insulation Using Phase Resolved Method. In: Ahmad, N.S., Mohamad-Saleh, J., Teh, J. (eds) Proceedings of the 12th International Conference on Robotics, Vision, Signal Processing and Power Applications. RoViSP 2021. Lecture Notes in Electrical Engineering, vol 1123. Springer, Singapore. https://doi.org/10.1007/978-981-99-9005-4_12

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