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

被引：0
|
作者：
Yue D. [1 ]
Sun H. [1 ]
Yang X. [1 ]
Sun J. [1 ]
机构：
[1] School of Mechanical Engineering, Tianjin Polytechnic University, Tianjin
来源：
Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering | 2021年 / 50卷 / 10期
关键词：
Annular drilling hole; BP neural network; Femtosecond laser; Orthogonal experiment;
D O I：
10.3788/IRLA20200446
中图分类号：
学科分类号：
摘要：
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 L25(55) 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 was 9.0 kHz, defocus distance was 200 μm, 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. © 2021, Editorial Board of Journal of Infrared and Laser Engineering. All right reserved.
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