Weld Geometry Monitoring for Metal Inert Gas Welding Process with Galvanized Steel Plates Using Bayesian Network

作     者：MA Guohong LI Jian HE Yinshui XIAO Wenbo 马国红;李健;何银水;肖文波

作者机构：Key Laboratory of Lightweight and High Strength Structural Materials of Jiangxi ProvinceSchool of Mechanical and Electrical EngineeringNanchang UniversityNanchang 330031China School of Environment and Chemical EngineeringNanchang UniversityNanchang 330031China Key Laboratory of Nondestructive Testing Ministry of EducationNanchang Hangkong UniversityNanchang 330063China 

出 版 物：《Journal of Shanghai Jiaotong university(Science)》 (上海交通大学学报（英文版）)

年 卷 期：2021年第26卷第2期

页      面：239-244页

核心收录：

学科分类：12[管理学] 080503[工学-材料加工工程] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 080201[工学-机械制造及其自动化] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：the National Natural Science Foundation of China(No.51665037) the Open Fund of the Key Laboratory of Lightweight and High Strength Structural Materials of Jiangxi Province(No.20171BCD40003) the Open Fund of the Key Tahoratory of Nondestructive Testing Ministry of Education,Nanchang Hangkong University of China.(No.EW201980090) 

主　　题：galvanized steel plate weld geometry laser vision sensor Bayesian network(BN) back propagation neural network(BPNN) 

摘      要：We present a novel method to monitor the weld geometry for metal inert gas(MIG)welding process with galvanized steel plates using Bayesian network(BN),and propose an effective method of extracting the weld reinforcement and width *** laser vision sensor is mounted after the welding torch and used to profile the *** the extracted weld geometry and the adopted process parameters,a back propagation neural network(BPNN)is constructed offline and used to predict the weld reinforcement and width corresponding to the current parameter settings.A BN from welding experience and tests is presented to implement the decision making of welding current/voltage when the error between the predictive geometry and the actual one *** study can deal with the negative welding tendency to adapt to welding randomness and indicates a valuable application prospect in the welding field.