用RFSSW技术创建的EN AW-7075-T6合金接头的负载能力预测的分析方法
Rafał Kluz1, Magdalena Bucior1, Andrzej Kubit1
1Department of Manufacturing and Production Engineering, Rzeszow University of Technology, Al. Powst. Warszawy 8, 35-959 Rzeszow, Poland.
Materials (Basel, Switzerland)
|April 13, 2024
概括
补充摩擦动点接 (RFSSW) 通过优化接参数来提高飞机结构可靠性. 与经典模型相比,神经网络显著提高了负载能力预测的准确性,确保了更高质量的连接.
科学领域:
- 材料科学 材料科学 材料科学
- 机械工程 机械工程
- 制造过程 制造过程 制造过程
背景情况:
- 飞机结构的高可靠性需要具有可预测性能的强大的接工艺.
- 补充摩擦动点接 (RFSSW) 对于在航空航天应用中加入合金至关重要.
- 优化RFSSW参数对于实现高负载能力和强度最小变化至关重要.
研究的目的:
- 为了确定EN AW-7075-T6 Alclad合金板的RFSSW的最佳技术参数.
- 为了提高预测接负载能力和工艺变化的准确性.
- 确保飞机结构连接具有统一的功能特性和高质量.
主要方法:
- 使用Statistica 13.3软件进行神经网络计算,以建模RFSSW参数.
- 将神经网络模型的预测与经典模型和以前的实验数据进行了比较.
- 使用负载能力的最大误差和标准偏差指标评估预测准确性.
主要成果:
- 与经典模型相比,神经网络在预测负载能力方面取得了显著更高的准确性 (最大误差1.55%,std dev 3.74%) (最大误差6.13%,std dev 14.51%).
- 神经模型允许确定可确保实现所需负载能力的高概率 (P = 0.999935) 的参数.
- 由于高误差和对输入参数变化的敏感性,经典模型是不够的.
结论:
- 神经网络建模为航空航天应用中优化RFSSW参数提供了卓越的方法.
- 这种方法确保了使用EN AW-7075-T6.6制造的飞机结构的可靠性和质量控制.
- 这项研究表明神经模型能够实现关键接属性的近乎完美的预测准确性.
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