基于混合遗传蚁群优化随机森林算法的激光熔覆Ni60裂纹预测与工艺参数优化

doi:10.3969/j.issn.1004-132X.2025.06.019

摘要/Abstract

摘要： 为了探究激光熔覆Ni60过程中熔覆层裂纹与加工工艺参数之间的复杂非线性映射关系，采用熵值法结合TOPSIS综合评价法对熔覆层裂纹进行综合表征评价，并使用混合遗传蚁群算法（HGA-ACO）优化随机森林算法（RFA）超参数，搭建工艺参数与裂纹评价指标间预测模型，最后使用遗传算法进行工艺参数反向寻优。研究结果表明：与ACO-RFA模型相比，HGA-ACO-RFA在预测精度与评价指标方面有显著改善，反向寻优获得的最优工艺参数可制备出几乎无裂纹的熔覆层。

关键词: 激光熔覆, 裂纹, 评价方法, 混合遗传蚁群算法, 随机森林算法

Abstract: To explore the complex nonlinear mapping relationship between the cracks in the cladding layer and the processing parameters during laser cladding of Ni60, the entropy method combined with TOPSIS comprehensive evaluation method was used to comprehensively characterize and evaluate the cracks in the cladding layers. The HGA-ACO was used to optimize the hyperparameters of the RFA, and a prediction model between processing parameters and crack evaluation indicators was constructed. Finally, the genetic algorithm was used for reverse optimization of processing parameters. Results show that compared with the ACO-RFA model, HGA-ACO-RFA significantly improves prediction accuracy and evaluation indicators, and the optimal processing parameters obtained through reverse optimization may prepare almost crack free cladding layers.

Key words: laser cladding, crack, evaluation method, hybrid genetic ant colony algorithm(HGA-ACO), random forest algorithm(RFA)

中图分类号:

李涛, 邓林辉, 莫彬, 石非凡, 刘伟嵬. 基于混合遗传蚁群优化随机森林算法的激光熔覆Ni60裂纹预测与工艺参数优化[J]. 中国机械工程, 2025, 36(06): 1322-1328,1337.

LI Tao, DENG Linhui, MO Bin, SHI Feifan, LIU Weiwei. Prediction of Cracks and Optimization of Processing Parameters in Laser Cladding of Ni60 Based on HGA-ACO-RFA[J]. China Mechanical Engineering, 2025, 36(06): 1322-1328,1337.

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链接本文: https://www.cmemo.org.cn/CN/10.3969/j.issn.1004-132X.2025.06.019

https://www.cmemo.org.cn/CN/Y2025/V36/I06/1322

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