金属加工（热加工）Issue(9)：70-79,10.
面向船用薄板焊接的缺陷根因分析框架
Root cause analysis framework for welding defects in marine thin plate applications
摘要
Abstract
Thin plate welding constitutes a core process in shipbuilding.During this process,thin plates are prone to various defects,posing potential safety hazards during vessel service.This paper proposes a data-driven full-chain diagnostic solution for defects in marine thin plate welding.First,the Mamba Residual Graph Convolutional Network for Spatio-Temporal Reconstruction(MRGSTR)is introduced,which facilitates real-time unsupervised anomaly detection on multivariate time-series(MTS)data from welding sensors based on a reconstruction approach.Subsequently,a CNN-BiGRU-based defect detection method is designed,and Bayesian networks are employed to fuse time-series data with a process knowledge graph for root cause analysis.Finally,a multi-agent Retrieval-Augmented Generation(RAG)system for operation and maintenance of thin plate welding defect detection is integrated,when a comprehensive defect detection chain is established:"Sensor data anomaly detection-Defect identification-Root cause analysis-Repair recommendations",aiming to provide an evolvable pathway for future engineering implementation.关键词
薄板焊接/缺陷检测/根因分析Key words
thin plate welding/defect detection/root cause analysis引用本文复制引用
王安民,吉永军,李程炜,夏阳,刘天元,鲍劲松..面向船用薄板焊接的缺陷根因分析框架[J].金属加工（热加工）,2026,(9):70-79,10.基金项目
国家自然科学基金面上项目(52475513) （52475513）
国家自然科学基金青年项目(52405536). （52405536）
