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使用辐射基函数神经网络的木塑复合材料表面削中切削力和温度的研究
Feng Ji1,2, Zhaolong Zhu1,3
1Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing Forestry University, Nanjing 210037, China.
Materials (Basel, Switzerland)
|October 29, 2025
概括
这项研究探讨了木塑复合材料 (WPC) 加工,发现料速度和切割深度会影响切割力. 一个使用辐射基函数神经网络的预测模型准确估计了力量和温度.
科学领域:
- 材料科学 材料科学 材料科学
- 制造业 工程 制造工程
- 计算科学 计算科学
背景情况:
- 木塑复合材料 (WPC) 在建筑和家具中提供了可持续和耐用的替代品.
- 优化WPC的加工流程对于高效的生产和材料利用至关重要.
研究的目的:
- 研究切割参数对WPC面磨力和温度的影响.
- 开发和验证WPC加工反应的预测模型,使用辐射基函数神经网络.
主要方法:
- 在CNC加工中心使用多晶钻石切割机进行了面试验.
- 切割参数 (料速度,切割的辐射深度,线速度) 系统地变化.
- 开发了一个辐射基函数神经网络来预测切割力和温度.
主要成果:
- 增加的料速度和辐射切割深度通常会增加切割力.
- 较高的线速度减少了切削力,但增加了切削温度.
- 该RBF神经网络在预测切割力 (R2 ≈ 0.91) 和切割温度 (R2 ≈ 0.81) 方面取得了很高的准确性.
结论:
- 辐射基函数神经网络建模是预测WPC面部削反应的可行方法.
- 结果为优化WPC加工中的切割参数提供了宝贵的见解.
- 这项研究支持木塑复合材料组件的高效精确制造.
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