Knowledge graph ontology model construction based on hierarchy structure and failure analysis for wind turbines

Wind turbines have been widely employed to convert wind kinetic energy into mechanical and end electrical energy as clean and pollution-free renewable energy for handling energy shortages and environmental pollution. In order to better manage and utilize fault knowledge and improve fault diagnosis efficacy of wind turbines, this study constructs a knowledge graph ontology model with system architecture and failure analysis. The model embraces equipment, fault and maintenance knowledge with attribute values in the system-function-motion-action-component (SFMAC) hierarchy structure that is a motion-oriented layered structure division method especially suitable for mechanical systems to obtain the most fundamental and smallest motion of power and motion transmission, namely translation and rotation meta-actions. Equipment knowledge is obtained by the SFMAC hierarchy structure, in which failure analysis integrating fault tree analysis (FTA) and failure mode and effects analysis (FMEA) is implemented to map failure behaviors and events and draw failure cause and effect fault trees from the action layer to the component and system layers respectively for garnering fault and maintenance knowledge. The constructed model is more hierarchical, complete and plain to present relationships of equipment, fault and maintenance knowledge in wind turbines.