首页|基于综合满意度函数的D2钢激光抛光工艺参数优化方法

基于综合满意度函数的D2钢激光抛光工艺参数优化方法

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目的 同步提升D2模具钢激光抛光效果及抛光质量的稳定性.方法 提出了一种基于综合满意度函数的D2钢激光抛光工艺参数优化方法.首先,以表面粗糙度、显微硬度和抛光深度为优化目标,基于Box-Behnken方法,以激光功率、扫描速度和搭接率为试验因素进行3因素3水平试验.其次,基于试验数据构建各优化目标均值与标准差的双响应面模型,采用熵权理论获得了各优化目标均值与标准差的客观熵权,并与主观熵权结合构建综合熵权.最后,将双响应面模型与综合熵权引入满意度函数构建了改进综合满意度模型,通过随机梯度下降法获得最佳工艺参数组合.结果 在激光功率为551 W、扫描速度为9 mm/s、搭接率为0.55的条件下,表面粗糙度均值由Ra=5.188μm下降至Ra=1.056μm,降幅为79.65%,粗糙度标准差为0.0128μm;显微硬度由541.3HV0.5下降至509.3HV0.5,降幅为5.91%,显微硬度标准差为12.9811HV0.5;抛光深度为0.331 mm,抛光深度标准差为0.0024 mm.结论 该方法可以有效提升D2模具钢激光抛光效果,同时避免抛光后表面质量波动,可为其他模具钢激光抛光工艺参数寻优提供方法借鉴.
Optimization Method of Laser Polishing Process Parameters for D2 Steel Based on Comprehensive Satisfaction Function
Due to its excellent wear resistance and good workability,D2 steel is widely used in various cold work moulds.However,after long time working,the roughness of D2 die steel on the surface of the die will be greatly increased,which will seriously affect the precision of the products.Laser polishing technology,as a non-contact,stable and easily automated surface treatment technology,can effectively reduce the roughness of the material surface.However,in the laser polishing process,due to the laser beam working back and forth,the roughness or hardness of the polished overlap or corners,etc.will be unstable compared with the unpolished part.How to control this instability,so that the whole laser polished part of the various values tend to stabilize,there are still few research reports.Therefore,in order to simultaneously improve the laser polishing effect and the stability of the polishing quality of D2 die steel,a method for optimizing the laser polishing process parameters of D2 steel based on the comprehensive satisfaction function was proposed.Firstly,a continuous laser was used for laser polishing based on the Box-Behnken method for a 3-factor,3-level experimental design with surface roughness,microhardness and polishing depth as the optimization objectives,and laser power,scanning speed and overlap rate as the experimental factors.Secondly,the dual-response surface model of the mean value and standard deviation of each objective was constructed according to the experimental data,and the objective entropy weight of the mean value and standard deviation of each objective was obtained according to the entropy weight theory,and the comprehensive entropy weight was constructed in combination with the subjective entropy weight.Finally,the dual-response surface model and comprehensive entropy right were introduced into the satisfaction function to construct an improved comprehensive satisfaction model,and the optimal combination of process parameters was obtained according to the stochastic gradient descent method,which was compared with the optimized dual-response surface method to prove the superiority of the method.The experimental results showed that with the laser power of 551 W,the scanning speed of 9 mm/s,and the overlap rate of 0.55,the roughness decreased from Ra=5.188 μm to Ra=1.056 μm with a reduction of 79.65% and the standard deviation of the roughness was 0.0128 μm.The microhardness decreased from 541.3HV0.5 to 509.3HV0.5 with a reduction of 5.91% and the standard deviation of microhardness was 12.9811HV0.5.At the same time,the depth of polishing was 0.331 mm and the standard deviation of the depth of polishing was 0.0024 mm.Comparison of the comprehensive results of the improved comprehensive satisfaction model method with the dual-response surface method,combining with the results of the friction wear experiments after the optimal combination of process parameters and traditional mechanical polishing,shows that the method proposed in this paper can maximize the microhardness while effectively reducing the surface roughness,keeping the polishing depth as small as possible.This method can provide a reference for the optimization of laser polishing process parameters for D2 die steel.

D2 steellaser polishingprocess parameter optimizationcomprehensive satisfaction functiondual-response surface modelcomprehensive entropy weight

梁强、徐永航、杜彦斌、王敬、徐彬源

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重庆工商大学 机械工程学院,重庆 400067

重庆工商大学 智能装备绿色设计与制造重庆市重点实验室,重庆 400067

D2钢 激光抛光 工艺参数优化 综合满意度函数 双响应面模型 综合熵权

重庆市教育科学规划课题重点项目重庆市自然科学基金面上项目重点实验室平台开放基金重庆工商大学研究生创新型科研项目

2019-GX-015CSTB2022NSCQ-MSX0473KFJJ2019078yjscxx2023-211-54

2024

表面技术
中国兵器工业第五九研究所,中国兵工学会防腐包装分会,中国兵器工业防腐包装情报网

表面技术

CSTPCD北大核心
影响因子:1.39
ISSN:1001-3660
年,卷(期):2024.53(16)
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