Abstract
This paper describes the possibilities of machine learning application in the tasks of technical state assessment of high-voltage instrument transformers. An analytical review of modern systems for technical state assessment of high-voltage equipment is presented, their advantages and disadvantages are described. A mathematical model of an automated system for assessing the high-voltage instrument current and voltage transformers based on gradient boosting over decision trees has been developed. The efficiency of the developed solution is proved using the example of analysis of a real distribution zone, which allows identifying the state of instrument transformers with an accuracy of 84%.
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