| 引用本文: | 向亮,谢晖,付山.基于响应面遗传算法的低碳钢激光切割工艺分析及参数优化[J].材料科学与工艺,2022,30(1):14-20.DOI:10.11951/j.issn.1005-0299.20210198. |
| XIANG Liang,XIE Hui,FU Shan.Analysis and optimization of laser cutting process of low carbon steel based on response surface method and genetic algorithm[J].Materials Science and Technology,2022,30(1):14-20.DOI:10.11951/j.issn.1005-0299.20210198. |
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| 摘要: |
| 为了研究光纤激光加工工艺对Q235低碳钢板切割质量的影响,采用1 000 W光纤激光切割机对3 mm厚低碳钢板切割质量影响规律进行了研究。设计了Box-Behnken实验,使用粗糙度仪和高精度电子秤完成了切面粗糙度和试样挂渣量的测量,研究了在氧气熔化切割方式下激光功率、切割速度、激光频率、激光占空比和辅助气体压力等工艺参数对粗糙度和挂渣量的影响规律。实验结果表明:挂渣量的大小主要决定于激光功率、切割速度、激光频率和辅助气体压力；粗糙度的大小主要决定于激光功率、激光频率、激光占空比和辅助气体压力。根据试验测量结果结合响应面法得到了粗糙度和挂渣量的响应面模型,然后采用遗传算法对响应面模型进行多目标优化,得到最优工艺参数为:激光功率1 000 W,切割速度40 mm/s,激光频率200 Hz,激光占空比91.5%,辅助气体压力0.59 MPa。 |
| 关键词: 光纤激光切割 低碳钢 工艺参数 粗糙度 挂渣量 响应面法 遗传算法 |
| DOI：10.11951/j.issn.1005-0299.20210198 |
| 分类号:TG485 |
| 文献标识码:A |
| 基金项目:湖南省创新型省份建设专项(2019GK5018);佛山市科技创新项目(1920001000041);佛山广工大研究院创新创业人才团队计划项目(2019年). |
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| Analysis and optimization of laser cutting process of low carbon steel based on response surface method and genetic algorithm |
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XIANG Liang, XIE Hui, FU Shan
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(College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410000, China)
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| Abstract: |
| To investigate the influence of fiber laser cutting process on the cutting quality for Q235 low carbon steel plates, low carbon steel plate samples with thickness of 3 mm were studied by 1 000 W fiber laser cutting machine. The Box-Behnken experiment was designed. The roughness tester and high-precision electronic scale were adopted to measure the cutting surface roughness and dross amount of the samples. The influences of the process parameters of laser power, cutting speed, laser frequency, laser duty ratio, and auxiliary gas pressure on the surface roughness and dross amount were studied under the oxygen melting cutting method. Experimental results show that the amount of dross was mainly determined by the laser power, cutting speed, laser frequency, and auxiliary gas pressure; the roughness was mainly determined by the laser power, laser frequency, laser duty ratio, and auxiliary gas pressure. Based on the test results, the response surface method was applied to obtain the response surface model of surface roughness and dross amount. Then genetic algorithm was used for the multi-objective optimization of the response surface model, and the optimal process parameters were obtained: laser power 1 000 W, cutting speed 40 mm/s, laser frequency 200 Hz, laser duty ratio 91.5%, and auxiliary gas pressure 0.59 MPa. |
| Key words: fiber laser cutting low carbon steel process parameters surface roughness dross amount response surface method genetic algorithm |
