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用自适应的古怪搜索算法预测蒸汽光滑的FDM零件的表面和尺寸特征的建模
Jasgurpreet Singh Chohan1, Nitin Mittal2, Rupinder Singh3
1Department of Mechanical Engineering, Chandigarh University, Mohali, 140413 India.
概括
沉积建模 (FDM) 部件可以使用蒸汽光滑来改进. 这项研究优化了FDM和蒸汽光滑参数,以在3D打印原型中获得更好的表面表面,硬度和精度.
科学领域:
- 添加剂制造 添加剂制造 添加剂制造
- 材料科学 材料科学 材料科学
- 计算智能是一种计算智能.
背景情况:
- 沉积建模 (FDM) 提供了优势,但受到表面粗性和尺寸变化的影响.
- 这些局限性限制了FDM部件在关键应用中的使用.
- 蒸汽光滑 (化学加工) 是一种后加工技术,用于提高FDM零件的质量.
研究的目的:
- 为了确定最佳的FDM和蒸汽光滑参数.
- 为了最大限度地提高FDM零件的表面表面,硬度和尺寸精度.
- 开发一个预测模型,用于后处理的FDM原型,使用自适应的子搜索算法.
主要方法:
- 使用乙蒸气对FDM打印的关节假肢进行蒸汽光滑.
- 实验设计 (DOE) 使用六个不同的参数和三次重复.
- 实现一个自适应的古怪搜索算法与5个目标函数,从回归分析.
主要成果:
- 开发一个预测模型,对蒸汽光滑FDM零件的输入和输出参数进行关联.
- 成功优化参数以解决表面表面,硬度和尺寸精度.
- 验证实验显示,预测和实际测量之间存在很强的一致性.
结论:
- 自适应的子搜索算法有效地优化了FDM和蒸汽光滑参数.
- 在FDM零件的表面表面,硬度和尺寸精度方面取得了显著的改进.
- 开发的方法提高了FDM适用于功能原型和关键应用的适用性.
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