防务技术2026,Vol.59Issue(5):325-337,13.DOI:10.1016/j.dt.2025.11.015
Interactive effects of process parameters and porosity defect evaluation in thermoplastic composite resistance welding:A model-data-driven AOA-BP neural network framework
Interactive effects of process parameters and porosity defect evaluation in thermoplastic composite resistance welding:A model-data-driven AOA-BP neural network framework
摘要
关键词
Thermoplastic composite material/Resistance welding/Finite element model/Machine learning/Defect analysisKey words
Thermoplastic composite material/Resistance welding/Finite element model/Machine learning/Defect analysis引用本文复制引用
Yajie Feng,Juan Xiao,Hongjian Gu,Fang Qi,Zhiyuan Ning,Xigao Jian,Liangliang Shen,Jian Xu..Interactive effects of process parameters and porosity defect evaluation in thermoplastic composite resistance welding:A model-data-driven AOA-BP neural network framework[J].防务技术,2026,59(5):325-337,13.基金项目
This work was supported by the National Key Research and Development Program"Advanced Structures and Composite Ma-terials"Special Project(Grant No.2024YFB3712800) (Grant No.2024YFB3712800)
"Ningbo 3315 Plan Innovation Team"(Grant No.2017A-28-C) (Grant No.2017A-28-C)
the Funda-mental Research Funds for the Central Universities(Grant No.DUT22LAB605). (Grant No.DUT22LAB605)