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用CFOA对H13压钢进行激光覆盖的高级多目标优化
Tianlu Liu1, Ruichen Wang1, Bin Han1
1School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China.
Materials (Basel, Switzerland)
|April 24, 2025
概括
本研究介绍了一种新的参数建模和优化方法,使用捕捞鱼优化算法 (CFOA) 来激光覆盖H13型钢. 该方法显著改善了覆盖质量指标,如稀释率和微硬度.
科学领域:
- 材料科学与工程 材料科学与工程
- 制造过程 制造过程 制造过程
- 计算智能是一种计算智能.
背景情况:
- 激光覆盖质量受到复杂,非线性过程参数相互作用的严重影响.
- 现有的研究往往忽视了与表面特性一起优化过程参数.
- 在理解参数,表面特征和优化策略之间的综合关系方面存在差距.
研究的目的:
- 开发一种新的参数建模和优化方法,用于使用捕捞鱼优化算法 (CFOA) 进行激光覆盖.
- 系统地分析激光功率,扫描速度和粉末料率对H13压钢外质量的影响.
- 为了弥合有关激光覆盖过程参数和表面特性优化的研究差距.
主要方法:
- 采用直角实验设计建立一个回归模型来预测外质量指标 (稀释率,微硬度,面积比).
- 利用分析层次过程 (AHP) 将多目标优化问题转换为单个目标框架.
- 应用了捕捞鱼优化算法 (CFOA) 进行参数建模和优化.
主要成果:
- 确定了一个最佳的参数组合:1628.19W的激光功率,9.9mm/s的扫描速度和14.73g/min的粉末料速度.
- 取得了显著的实验改进:稀释率提高了19.71%,微硬度提高了3.37%,面积比提高了28.66%.
- 与传统的优化方法相比,证明了CFOA优越的全球搜索能力和精度.
结论:
- 拟议的基于CFOA的方法提供了一种创新和有效的方法来优化激光覆盖工艺.
- 本研究提供了H13型钢修复和表面性能增强的实际解决方案.
- 突出了元启发算法在推进复杂制造过程优化方面的多功能性和稳定性.
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