Research on intelligent management of the full lifecycle of power communication equipment based on knowledge graphs

A new abstract has been updated.The specific content is as follows: As power communication networks grow more intelligent and complex, traditional management models struggle with information silos, weak knowledge links, and low decision efficiency when handling massive heterogeneous data across equipment lifecycles.To address this, this paper proposes a knowledge graph-based intelligent management method for power communication equipment's full lifecycle.It organises multi-source data from procurement, installation, operation, maintenance, and decommissioning stages, constructs a domain ontology, and uses NLP and entity-relationship extraction to fuse unstructured knowledge.A graph database-stored lifecycle knowledge graph supports state tracing, fault diagnosis, and maintenance recommendations.Experiments show the method integrates equipment chain information, boosts data efficiency, and enhances O&M decision intelligence, supporting reliable power communication system operations.