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The various types of high-voltage instrument transformers (HVITs) play a highly significant role in the power system. They are necessary for routine operations such as control and monitoring, protection, and metering. However, HVITs remain vulnerable to defects due to high voltage or current-based electric, magnetic, and thermal stresses. The defects in HVITs are degenerative and require detection at the incipient stages to avoid any catastrophic events. This article provides a comprehensive study of HVITs condition monitoring techniques. The research field of condition monitoring includes the theoretical analysis and investigations of the possible defects, the mathematical modeling techniques to simulate those defects, the signal processing, and artificial intelligence (AI)-based techniques to establish the defect detection algorithms and statistical segregation of the real-world data. All these domains for HVIT are systematically summarized in this article. Finally, this article concludes by presenting a general roadmap for the development of advanced intelligent and online diagnostic methods.
Asefi et al. (Wed,) studied this question.