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碳玻璃增强混合复合材料激光加工参数的多目标优化:集成灰色关系分析,回归和ANN
Ashish A Desai1,2, S N Khan1, Pooja Bagane3
1Mechanical Engineering Department, Rajarshi Shahu College of Engineering, Tathawade, Pune, Maharashtra, India.
MethodsX
|December 17, 2024
概括
使用回归,MOGRA和ANN优化碳玻璃纤维增强混合复合材料 (CGFRP) 的CO2激光切割,提高了精度和效率6.125%. 这提高了用于航空航天和汽车应用的制造业.
科学领域:
- 材料科学与工程 材料科学与工程
- 制造业 制造技术 制造技术
- 复合材料 复合材料 复合材料
背景情况:
- 纤维增强聚合物 (FRP) 在高性能应用中至关重要.
- 精确高效的复合材料加工,如碳玻璃纤维增强混合复合材料 (CGFRP) 提出了重大挑战.
- 二氧化碳激光加工为先进的复合材料制造提供了潜力.
研究的目的:
- 为了提高CGFRPs的CO2激光切割的精度和效率.
- 优化激光加工参数,以提高表面质量和成本效益.
- 为优化混合复合材料的激光切割建立一个强大的框架.
主要方法:
- 使用Taguchi L27直角阵列进行参数分析.
- 多目标灰色关系分析 (MOGRA) 用于优化.
- 人工神经网络 (ANN) 用于预测建模和相关性分析.
- 回归模型用于理解参数关系.
主要成果:
- 确定了最佳的激光加工参数 (LPW3CSD1FOL1GPR1 和 LPW3CSD2FOL1GPR2).
- 通过优化参数,实现了6.125%的切割等级改进.
- ANN模型显示,机械加工结果的预测准确性得到了提高.
- 开发了一个CGFRP激光切割的多目标优化框架.
结论:
- 回归,MOGRA和ANN的综合方法有效地优化了CGFRP的CO2激光切割.
- 优化参数可以显著提高准确性和效率.
- 开发的框架为高性能复合材料组件的成本效益制造提供了一条途径.
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