表面技术2024，Vol.53Issue(9)：167-179,13.DOI:10.16490/j.cnki.issn.1001-3660.2024.09.016
基于响应面法的Ni60/WC涂层表面织构皮秒分束工艺参数预测研究
Prediction of Textured Picosecond Beam Splitting Process Parameters of Ni60/WC Coating Based on Response Surface Method
摘要
Abstract
The research shows that the bionic texture on the surface of the moving pair has a significant improvement on the surface interface wear resistance and lubrication properties,reasonable micro-pit texture design and laser beam splitting technology applied on the Ni60/WC coating can significantly improve the wear resistance of the fracturing pump plunger dynamic seal system.However,the efficiency of selecting texture laser processing parameters by experimental method is very low,which is not conducive to the fast and accurate selection of processing parameters of target texture.In order to directly obtain the functional relationship between process parameters and machining targets under beam splitting laser,the prediction model of processing target parameters and six-beam laser processing process parameters was established,and the interaction between laser frequency,scanning speed and scanning times and the influence of response target on the optimization of surface texture ablation parameters of the Ni60/WC coating were discussed.A six-beam picosecond laser micro-machining platform was established.A circular pit texture with a diameter of 200 μm was arranged on the surface of the Ni60/WC coating using the processing parameters designed by the CCD response surface method.The three-dimensional morphology of the circular pit morphology was tested with a white light interferometer.The laser processing parameters were optimized by the prediction models with different target suggestions,and the effects of laser frequency,scanning speed and scanning times on the pits were analyzed by the perturbation diagram generated by Design-Expert software and the 3D relationship diagram of different influencing factors.The results showed that:as the index of machining optimization,the scanning times had the most significant influence on the texture diameter;but as the preset value,the energy gathered on a single pulse spot was the key factor affecting the texture diameter error.The most significant influence on texture depth was the scanning frequency and the scanning frequency,and the texture depth was positively correlated with the scanning frequency and the laser frequency.The interaction between different influencing factors was a key point affecting the texture processing results.Through the experimental verification of the optimized parameters of the prediction model,it was found that the error rates of the quality evaluation index of the circular pit texture and its prediction index were 19.37%and 3.57%,respectively,in the optimization process parameters of the prediction model established with the texture diameter,depth and comprehensive target.When the laser power was 6 W,the optimal process parameter combination of six-beam laser processing was as follows:speed at 5 500 mm/s,frequency at 400 kHz and scanning times of 2.Taking the comprehensive objective obtained by the comprehensive weighting method as the response objective,the optimization prediction model of rounded pit texture six-beam laser processing parameters of the Ni60/WC coating surface established by the response surface method has a high accuracy,which can realize the accurate prediction of texture laser parameters required by Ni60/WC coating surface processing,and avoid the repetitive and tedious process in the selection of processing parameters by the experimental method.It lays an experimental foundation for the further research and application of bionic texture in the field of fracturing pump plunger processing.关键词
皮秒激光/分束激光加工/Ni60/WC/圆凹坑织构/CCD响应面法/参数预测Key words
picosecond laser/split-beam laser processing/Ni60/WC/circular pit texture/CCD response surface method/parameter forecast分类
信息技术与安全科学引用本文复制引用
钟林,张文超,敬佳佳,伍小龙,王国荣,罗敏敏,王紫萱,魏刚,王杰,冷晓栋,曾秦涛..基于响应面法的Ni60/WC涂层表面织构皮秒分束工艺参数预测研究[J].表面技术,2024,53(9):167-179,13.基金项目
成都市国际合作项目(2019-GH02-00055-HZ) （2019-GH02-00055-HZ）
四川省科技厅自然科学基金创新研究群体项目(2023NSFSC1980) （2023NSFSC1980）
国家自然科学基金面上项目(51775463) （51775463）
四川省科技计划项目(2021YJ0347) Chengdu International Cooperation Project(2019-GH02-00055-HZ) （2021YJ0347）
Natural Science Foundation of Sichuan Provincial Science and Technology Department(2023NSFSC1980) （2023NSFSC1980）
National Natural Science Foundation Project(51775463) （51775463）
Science and Technology Project of Sichuan Province(2021YJ0347) （2021YJ0347）
