Research on Knowledge Graph Construction of Nuclear Power Equipment Quality Control with Value Chain Collaboration

doi:10.3901/JME.2025.13.174

Abstract

Abstract: To address the issues of information isolation, lack of connectivity, and data loss and deficiency during the flow of information between organizations and platforms in the value chain of nuclear power equipment, the quality control requirements of the nuclear power equipment value chain are analyzed. The knowledge graph, whose construction and application are further explored, introduced to organize the knowledge embedded in quality texts, facilitating sharing and reusing, to support collaborative quality control. Firstly, a multi-stage hierarchical ontology model across time and space is designed based on an analysis of characteristics of quality texts in the nuclear power equipment value chain. Secondly, an improved few-shot-learning-based entity recognition model and a relative position-based entity relationship matching method are proposed, and then knowledge triples are extracted to construct the knowledge graph. Thirdly, through comprehensive scenario analysis and expert interviews, a set of question-and-answer templates for user interaction with the knowledge graph is designed, a frame based on Retrieval Augmented Generation is defined, and an application for questions and answers aiming at collaborative quality control in the nuclear power equipment value chain is developed. Finally, the effectiveness and superiority of the above methods are validated by comparing with the large language models ChatGPT and keyword matching model. The improved entity recognition model demonstrates better performance in handling smaller quality texts. And the nuclear power equipment quality control with value chain collaboration can be effectively supported through user interaction with the knowledge graph, which contributes positively to the improvement of management levels and efficiency.

Key words: value chain collaboration, quality control, knowledge graph, meta-learning

CLC Number:

TP391
TH166

YANG Jiaxing, WEN Peihan, HU Yaping. Research on Knowledge Graph Construction of Nuclear Power Equipment Quality Control with Value Chain Collaboration[J]. Journal of Mechanical Engineering, 2025, 61(13): 174-191.

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