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Electrical equipment and the stable operation of the power system have a close connection; qualified electrical equipment can ensure the normal operation of the power system. The electrical fault factors are numerous, and it is necessary to carry out early discovery and early resolution of electrical faults. Based on this, this paper analyzes an electrical equipment fault diagnosis system using machine learning algorithms, and at the same time conducts simulation experiments on the performance of the system, and its results show that the diagnosis system proposed in this paper can shorten the detection time and improve the detection accuracy. It is expected that the research in this paper can provide a corresponding basis for the efficient diagnosis of electrical equipment faults.

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Fault Diagnosis and Simulation Testing of Electrical Equipment Based on Machine Learning Algorithms

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Chenyu Li

摘要

Electrical equipment and the stable operation of the power system have a close connection; qualified electrical equipment can ensure the normal operation of the power system. The electrical fault factors are numerous, and it is necessary to carry out early discovery and early resolution of electrical faults. Based on this, this paper analyzes an electrical equipment fault diagnosis system using machine learning algorithms, and at the same time conducts simulation experiments on the performance of the system, and its results show that the diagnosis system proposed in this paper can shorten the detection time and improve the detection accuracy. It is expected that the research in this paper can provide a corresponding basis for the efficient diagnosis of electrical equipment faults.