激光清洗7075铝合金清洗质量建模及多目标优化研究

doi:10.3901/JME.2025.03.422

摘要/Abstract

摘要： 在激光清洗过程中，由于激光加工的能量参数和运动参数众多，如何保证高效高精度清洗质量的情况下协调控制参数成为了一个难题。为了解决这些问题，设计以工艺参数(激光功率、扫描速度、脉冲频率)为优化变量，清洗后表面粗糙度、氧元素去除率、静态接触角为多目标优化指标的BOX-Behnke design(BBD)响应面试验，建立响应面模型与GA-BP神经网络模型，提出一种基于佳点集与自适应正态分布权重改进的多目标麻雀算法，解决其自身初始种群质量差、易于陷入局部最优解、迭代后期种群多样性较小，局部开发能力不高的问题。进一步对模型进行优化，通过TOPSIS获取的最优工艺参数组合为：脉冲频率2.6 kHz、激光功率 245 W、扫描速度 2 900 mm/s。进行多种算法求解的对比分析及工艺试验，验证算法有效性。结果表明：应用所提出模型与算法进行优化，对比原始样件，其表面粗糙度降低了40.26%，氧元素含量下降了96.97%，静态接触角提高了58.32%，清洗质量显著提升。

关键词: 激光清洗, 铝合金, 清洗质量, 工艺参数, 多目标优化

Abstract: In the process of laser cleaning, it has become a challenge to coordinate and control parameters to ensure efficient and high-precision cleaning quality due to the numerous energy and motion parameters involved in laser processing. To address these issues, a BOX Behnke design (BBD) response surface experiment is designed with process parameters (laser power, scanning speed, pulse frequency) as optimization variables, and surface roughness, oxygen removal rate, and static contact angle as multi-objective optimization indicators after cleaning. A response surface model and GA-BP neural network model are established. Particularly, a multi-objective sparrow algorithm based on the improvement of the good point set and adaptive normal distribution weights is proposed. Therefore, the problems of poor initial population quality, easy to fall into local optima, low population diversity in the later stages of iteration, and low local development ability have been solved. Furthermore, the model is optimized and the optimal process parameter combination obtained through TOPSIS is as follows: pulse frequency 2.6 kHz, laser power 245 W, and scanning speed 2 900 mm/s. In addition, comparative analysis and process experiments of multiple algorithms are conducted to verify the effectiveness of the algorithms. The results showed that the proposed model and algorithm are applied for optimization. As a result, compared with the original sample, the surface roughness is reduced by 40.26%, the oxygen content is reduced by 96.97%, the static contact angle is increased by 58.32%, and the cleaning quality was significantly improved.

Key words: laser cleaning, aluminium alloy, cleaning quality, process parameters, multi objective optimization

中图分类号:

TG156

王蔚, 李晓旭, 刘伟军, 卞宏友, 邢飞, 王静. 激光清洗7075铝合金清洗质量建模及多目标优化研究[J]. 机械工程学报, 2025, 61(3): 422-439.

WANG Wei, LI Xiaoxu, LIU Weijun, BIAN Hongyou, XING Fei, WANG Jing. Modeling and Multi-objective Optimization of Laser Cleaning Quality of 7075 Aluminum Alloy[J]. Journal of Mechanical Engineering, 2025, 61(3): 422-439.

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