Review of Knowledge and Data-driven Primary Equipment Health Management Methods
The scale of power system has been expanding year by year,and its reliability requirements for power supply are increasing.Implementing health management of power primary equipment based on the mechanism of power equip-ment and monitoring data,using knowledge,data-driven,and their integration-driven methods,is a feasible approach to improve power supply reliability and reduce operational costs.This paper provides an overview of knowledge-driven,da-ta-driven,and their integration-driven methods for health management of power primary equipment.First,we outline the key technologies of knowledge-driven,data-driven,and their integration-driven approaches.Then,we review the research status of these three driving methods in three application scenarios related to power primary equipment:image recogni-tion,state parameter sensing and fault diagnosis,state assessment,and operational maintenance.Finally,we summarize the challenges in the application of these three driving methods in power equipment health management,considering as-pects such as hardware conditions,data sources,and knowledge model construction,and provide suggestions for future development.
power primary equipmenthealth managementknowledge-drivendata-drivenknowledge-data fusion driven
万方数据
维普
