Abstract

The power IoT (Internet of things) realizes the holographic perception of power grid state, and drives the data sharing and application through the Internet of things platform, data center and business center, providing a more comprehensive data base for the construction of equipment state maintenance. Edge computing provides a real-time processing method with low delay for equipment condition monitoring, it also provides a more comprehensive data basis for equipment condition maintenance. The paper proposed a framework design of equipment condition based maintenance knowledge base using machine learning. The combination of production rules and Petri net model are used to realize knowledge compilation and reasoning, and complete the intelligent decision of equipment fault repair.

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