Multi-objective optimization of process parameters for ultra-narrow gap welding based on Universal Kriging and NSGA Ⅱ  

作　　者：马生明 张爱华 顾建军 漆宇晟 马晶 王平 Ma Shengming;Zhang Aihua;Gu Jason;Qi Yusheng;Ma Jing;Wang Ping(College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China;Department of Electrical and Computer Engineering,Dalhousie University,Halifax,NS,B3J 2X4 Canada)

机构地区：[1]College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China [2]Department of Electrical and Computer Engineering,Dalhousie University,Halifax,NS,B3J 2X4 Canada

出　　处：《China Welding》2023年第3期28-35,共8页中国焊接（英文版）

基　　金：Project was supported by National Natural Science Foundation of China(Grant No.62173170).

摘　　要：The successful confinement of the arc by the flux band depends on the welding process parameters for achieving single-pass,multi-layer, and ultra-narrow gap welding. The sidewall fusion depth, the width of the heat-affected zone, and the line energy are utilized as comprehensive indications of the quality of the welded joint. In order to achieve well fusion and reduce the heat input to the base metal.Three welding process characteristics were chosen as the primary determinants, including welding voltage, welding speed, and wire feeding speed. The metamodel of the welding quality index was built by the orthogonal experiments. The metamodel and NSGA-Ⅱ(Non-dominated sorting genetic algorithm Ⅱ) were combined to develop a multi-objective optimization model of ultra-narrow gap welding process parameters. The results showed that the optimized welding process parameters can increase the sidewall fusion depth, reduce the width of the heataffected zone and the line energy, and to some extent improve the overall quality of the ultra-narrow gap welding process.

关 键 词：ultra-narrow gap optimization of process parameters non-dominated sorting genetic algorithm II the sidewall fusion depth 

分 类 号：TG44[金属学及工艺—焊接]