基于混合模型的TC4涂层激光熔覆工艺多目标优化  

Multi-Objective Optimization of Laser Cladding Process of TC4 Coating Based on Hybrid Model

作　　者：秦景鹏 舒林森[1,2] 巩江涛 Qin Jingpeng;Shu Linsen;Gong Jiangtao(School of Mechanical Engineering,Shaanci University of Technology,Hanzhong 72300l,Shaanzi,China;Shanzi Key Laboratory of Industrial Automation,Hanzhong 72300l,Shaanzi,China)

机构地区：[1]陕西理工大学机械工程学院,陕西汉中723001 [2]陕西省工业自动化重点实验室,陕西汉中723001

出　　处：《应用激光》2024年第12期38-45,共8页Applied Laser

基　　金：国家自然科学基金项目资助(52075544);陕西省秦创原“科学家+工程师”队伍建设项目(2023KXJ-123)。

摘　　要：为有效改善TC4钛合金熔覆涂层的质量缺陷,提出一种基于RSM-NSGA-Ⅱ的混合多目标优化模型。选用激光功率、送粉速度和扫描速度为因素,稀释率、宽高比和显微硬度为响应,构建基于RSM的输入与响应关系的回归模型,并采用方差分析模型的可靠性,然后再运用NSGA-Ⅱ算法实现工艺多目标优化,最后分析最优涂层的微观组织。结果表明,优化后最优工艺参数组合为:激光功率2250 W,扫描速度19 mm/s,送粉速率1.3 r/min。优化后的3个响应均有明显改善,稀释率降低了13.2%,宽高比增加了7.1%,显微硬度增大了6.4%。To enhance the quality of TC4 titanium alloy cladding coating,a hybrid multi-objective optimization model integrating response surface methodology(RSM)and the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)was developed.The model focused on optimizing the laser power,feeding speed,and scanning speed as factor,with the objectives of minimizing the dilution rate,maximizing the aspect ratio,and enhancing microhardness.The regression model of the relationship between input and response based on RSM was constructed,and the reliability of the variance analysis model was used.Then NSGA-Ⅱ algorithm was used to realize the multi-objective optimization of the process.The results show that the optimal combination of process parameters is as follows:laser power 2250 W,scanning speed 19 mm/s,powder feeding rate 1.3 r/min.The optimization resulted in substantial improvements,with a 13.2% reduction in the dilution rate,a 7.1% increase in the aspect ratio,and a 6.4% enhancement inmicrohardness.

关 键 词：TC4钛合金 激光熔覆 响应曲面法 NSGA-Ⅱ算法 多目标优化 

分 类 号：TG174.44[金属学及工艺—金属表面处理]