飞秒激光环切加工不锈钢微孔工艺及其质量控制神经网络模型  

Annular drilling process and quality control neural network model of stainless steel micro-hole with femtosecond laser

作　　者：岳端木 孙会来[1] 杨雪 孙建林 Yue Duanmu;Sun Huilai;Yang Xue;Sun Jianlin(School of Mechanical Engineering,Tianjin Polytechnic University,Tianjin 300387,China)

机构地区：[1]天津工业大学机械工程学院,天津300387

出　　处：《红外与激光工程》2021年第10期136-145,共10页Infrared and Laser Engineering

摘　　要：利用飞秒激光微纳加工系统开展环切加工喷油器微孔的理论和实验研究。以06Cr19Ni10不锈钢为靶材,选取影响飞秒激光环切制孔过程的主要参数,基于L25(55)的正交表设计了5因素5水平的正交实验,分析激光功率、重复频率、离焦量、扫描速度和扫描次数对微孔加工影响的显著性水平,探究微孔的成形演化规律以及各参数对微孔几何精度和形貌的影响,最终得到相对最优的参数水平组合为:激光功率1.0 W,重复频率9.0 kHz,离焦量200μm,扫描速度1.0 mm/s,扫描次数40次;基于BP神经网络建立关于上述5个参数为输入,微孔出入口孔径为输出的映射模型,通过对正交实验数据的迭代训练以及验证,最终建立出相对误差保持在7.6%以内的神经网络预测模型。Theoretical and experimental research on annular drilling of injector micro-hole by using the femtosecond laser micromachining system.The 06Cr19Ni10 stainless steel was used as the target material,and the orthogonal experiments with 5 factor and 5 level were designed based on L_(25)(5^(5))orthogonal table.The significance level of the influence of laser power,repetition frequency,defocus,scanning speed and scanning times on micro-hole processing was analyzed and the formation and evolution rule of micro-hole were explored.Then,the influence of various parameters on the micro-hole accuracy and topography was explored.Finally,the relatively optimal laser processing parameters were as follows:laser power was 1.0 W,repetition frequency was9.0 kHz,defocus distance was 200μm,scanning speed was 1.0 mm/s,scanning times was 40 times.In addition,based on BP neural network,a mapping model with the above five parameters as input and micro-hole entrance and exit aperture as output was set up.The results show that the prediction error of the relationship model is less than 7.6%by iterative training and verification of orthogonal experimental data.

关 键 词：飞秒激光 环切制孔 正交实验 BP神经网络 

分 类 号：TN249[电子电信—物理电子学]