首页|液压支柱钢表面激光再制造工艺参数的多目标优化

液压支柱钢表面激光再制造工艺参数的多目标优化

Multi-Objective Optimization of Laser Remanufacturing Process Parameters for Steel Surface of Hydraulic Prop

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为了获得奥氏体不锈钢在液压支柱钢表面激光熔覆的最佳工艺参数,选取工艺参数激光功率、扫描速度、送粉速度为输入变量,将熔覆层质量作为评价指标建立数学模型,设计了 16组正交实验.利用自适应混沌粒子群算法进行寻优,对熔覆层宏观形貌和显微组织进行实验分析,验证优化后的工艺参数的合理性与准确性,并将综合评价值相近的两组试件进行对比.结果表明:激光功率为1200 W、扫描速度为13 mm/s、送粉速度为1.72 g/min是最佳的工艺参数组合;采用自适应混沌粒子群算法对工艺参数进行优化,能够有效地改善熔覆层的宏观缺陷和表面性能,证明了该优化算法在激光熔覆领域应用的可行性.
In order to obtain the optimal parameters of laser cladding process parameters of austenitic stainless steel alloy on hydraulic prop steel surface,the process parameters laser power,scanning speed,powder feeding speed are selected as input variables,and the quality of cladding layer is used as evaluation index to establish a mathematical model.16 groups of orthogonal experiments are designed.Using adaptive chaotic particle swarm optimization algorithm to perform optimization,and the macro-morphology and microstructure of the cladding layer are analysed by experiments to verify the rationality and accuracy of the optimized process parameters.Two groups of specimens with similar comprehensive evaluation values are compared.The results show that the best combination of process parameters are laser power of 1200 W,scanning speed of 13 mm/s,and the powder feeding speed of 1.72 g/min.Using adaptive chaotic particle swarm optimization algorithm to optimize the process parameters can effectively improve the macroscopic defects and surface properties of the cladding layer,which proves the feasibility of the optimization algorithm in the field of laser cladding.

laser claddingmulti-objective optimizationprincipal component analysisadaptive chaotic particle swarm algorithm

王燕燕、何炜、舒林森

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陕西理工大学机械工程学院,陕西汉中723000

陕西省工业自动化重点实验室,陕西汉中723000

激光熔覆 多目标优化 主成分分析法 自适应混沌粒子群算法

国家自然基金青年基金陕西省教育厅专项科研计划项目

5150526818JK0150

2024

激光与光电子学进展
中国科学院上海光学精密机械研究所

激光与光电子学进展

CSTPCD北大核心
影响因子:1.153
ISSN:1006-4125
年,卷(期):2024.61(5)
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