根据多层感知器集成的贝叶斯式感知器优化电性能的刚度优化
Xiaowei Dong1, Feng Sun1, Ye Li1
1School of Mechanical Engineering, Shenyang University of Technology, Shenyang, 110870, China.
Scientific reports
|October 30, 2025
概括
本研究介绍了一种混合多层感知器 (MLP) 和贝叶斯优化 (BO) 方法,用于电性能优化. 这种新方法显著提高了静态刚性,减少了变形,优于传统技术.
科学领域:
- 机械工程 机械工程
- 制造业 制造技术 制造技术
- 计算工程 计算工程 计算工程
背景情况:
- 电性能优化对于精密加工至关重要.
- 传统方法面临着高维参数空间和非线性动态的挑战.
- 现有的方法在复杂的优化任务中可能缺乏效率和准确性.
研究的目的:
- 为优化电性能提出一种新的混合方法.
- 模拟设计参数和性能指标之间的复杂关系.
- 为了有效地确定最佳的电配置,以提高准确性和效率.
主要方法:
- 多层感知器 (MLP) 的集成用于模拟非线性关系.
- 贝叶斯优化 (BO) 的应用,用于高效的空间导航设计.
- 使用ANSYS进行有限元模拟电应力和变形.
主要成果:
- 确定了影响轴承应力变形的关键设计参数:悬架长度,支跨度和轴承刚度.
- 与多目标遗传算法 (MOGA) 相比,静态刚度增加了25.7N/μm.
- 减少了0.2微米的螺旋变形,证明了卓越的性能.
结论:
- 拟议的MLP-BO框架提供了卓越的优化效率,准确性和全球搜索能力.
- 这种混合方法为设计高性能电提供了宝贵的见解.
- 该方法适用于其他需要复杂优化的精密制造系统.
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