A Knowledge Graph and Rule Engine Based Operational Reasoning Framework for Electromechanical Equipments

To address the demand for autonomous operation of complex electromechanical equipment, this paper investigates knowledge organization and expression in electromechanical operations. An operational knowledge graph and a rule reasoning platform are constructed to enable intelligent decision support. First, a construction method for the equipment operation knowledge graph was proposed, where a node system was built through event argument extraction to manage operational rules efficiently. Secondly, with the support of electromechanical equipment knowledge graph and rule engine, a rule reasoning method based on knowledge graph is designed, combined with Rete algorithm to efficiently match the rule conditions, realizing real-time decision-making and dynamic management of electromechanical equipment operation. Experimentally verified, the system can significantly improve the efficiency of equipment fault detection. The research results can not only improve the intelligent level of reasoning and decision-making of electromechanical equipment operation, but also provide a common technical framework for knowledge management and decision support of other complex equipment systems.