Diesel Engine Fault Diagnosis Research and System Design Based on Knowledge Graph
Due to the short construction period and high cost of highway construction projects,diesel engine on the highway construction site needs to receive timely fault diagnosis and troubleshooting when it malfunctions.It uses the BiLSTM-CRF model to extract fault entities and relationships,a structured semantic network is used to describe the knowledge of diesel engine faults,and a knowledge graph in the field of diesel engine faults is constructed.At the same time,Bayesian networks are combined to achieve fault cause inference and complete its knowledge graph.A diesel engine fault diagnosis system based on knowledge graph is also designed to comprehensively improve the maintenance efficiency of construction machinery on highway construction site.
国家科技期刊平台
NSTL
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