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Power Transmission Line Fault Detection and Diagnosis Based on Artificial Intelligence Approach and its Development in UAV: A Review

  • Review-Electrical Engineering
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Abstract

This paper provides a systematic, comprehensive, up-to-date study of the various artificial intelligence (AI) techniques on the detection and classification of faults on power transmission line. We review the latest start of the art of various intelligent approaches and even discuss the differences and outcomes of implementing intelligent methods in the protection scheme and the integrated protection scheme. Besides, there has been an increase in demand and interest for the application of AI approaches in drone to aid in detection and classification of faults. However, there are not many surveys pertaining to the development of the unmanned aerial vehicle (UAV) for the application of intelligent methods in this field. Thus, we also include in this paper the literature relevant to the implementation of various intelligent approaches in the unmanned aerial vehicle (UAV) for the fault detection and classification on power transmission line. Finally, we discuss the challenges and limitations faced in the implementation and propose ways to bridge the gap in the field for further research. This comprehensive study can act as a platform for new researchers to assess the possible different intelligent methods in detecting and classifying faults on power transmission line with a set of references that were dedicated to the attentive contributions.

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Acknowledgement

The authors would like to thank all the anonymous reviewers and editors handling the submission. This work was supported by Xiamen University Malaysia Research Fund under Grant XMUMRF/2018-C2/IECE/0001 and Guangxi University under Grant A3020051008.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Xiamen University Malaysia, Jalan Sunsuria, Bandar Sunsuria, 43900, Sepang, Selangor, Malaysia

    Shen Yuong Wong, Clifford Wei Chang Choe, Yik Wen Low, Dennis Yang Shen Cheah & Chiia Pang

  2. School of Electrical Engineering, Guangxi University, Nanning, Guangxi Province, 530004, China

    Hui Hwang Goh

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Correspondence to Shen Yuong Wong or Hui Hwang Goh.

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Wong, S.Y., Choe, C.W.C., Goh, H.H. et al. Power Transmission Line Fault Detection and Diagnosis Based on Artificial Intelligence Approach and its Development in UAV: A Review. Arab J Sci Eng 46, 9305–9331 (2021). https://doi.org/10.1007/s13369-021-05522-w

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