Research on the Construction and Expansion of Knowledge Graph for Fault Diagnosis of Submersible Electric Pumps
Marine oilfield submersible pump wells are numerous,productive,and costly to repair.Existing fault diagnosis methods for submersible pumps based on knowledge graphs have certain limitations in practical applications due to the scarcity of corpus data,resulting in a significant gap compared to internationally advanced pump inspection systems.This article focuses on enhancing and expanding the knowledge graph for fault diagnosis in submersible pumps by augmenting corpus data,reconstructing the ontology of the graph,and annotating small-sample corpora.Through the expansion of corpus data and the improvement of the graph structure,the coverage and accuracy of the knowledge graph are significantly improved.Additionally,this paper explores relation extraction,knowledge fusion,and knowledge completion.By utilizing techniques such as text similarity,Pearson correlation coefficient,manual screening,and threshold methods,entities and relationships within the graph are integrated,disambiguated,and completed.Expert knowledge is also employed to further review and correct the knowledge graph,enhancing its quality and enhancing its applicability in practical fault diagnosis for submersible pumps.
NETL
NSTL
万方数据
