首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part C. Journal of mechanical engineering science >Establishment of micropit diameter prediction models based on the support vector machine optimization
【24h】

Establishment of micropit diameter prediction models based on the support vector machine optimization

机译:基于支持向量机优化的微型直径预测模型的建立

获取原文
获取原文并翻译 | 示例
           

摘要

Many studies on microtextures have focused on the effect of laser processing parameters on microtextured morphology from the experimental point of view, and not on its influence on the physical field and stress field around the microtextures. This has resulted in the lack of accurate predictions on micropit diameters, thus reducing the processing efficiency. In order to address these problems, the effects of laser processing parameters on the precision machining, physical field, and stress field of micropit textures for a ball-end milling cutter were studied by experiments and simulation. The optimum laser processing parameters include laser power of 70%, scanning speed of 1700 mm/s, and scanning of seven times. Based on the optimized data of a support vector machine, the prediction models of micropit diameters for laser machining were established. The errors of the models are less than 10%, thus verifying their accuracy. This study can serve as a theoretical reference for the efficient processing of titanium alloys.
机译:许多关于微横纹理的研究专注于激光加工参数对来自实验性观点的激光加工参数对微织物形态的影响,而不是对微纹理周围物理场和应力场的影响。这导致缺乏对MicroPit直径的准确预测,从而降低了加工效率。为了解决这些问题,通过实验和仿真研究了激光加工参数对球端铣刀的微量纹理的精密加工,物理场和应力场的影响。最佳激光加工参数包括70%,扫描速度为1700 mm / s的激光功率,扫描七次。基于支持向量机的优化数据,建立了用于激光加工的微量型直径的预测模型。模型的误差小于10%,从而验证了它们的准确性。该研究可以作为钛合金有效加工的理论参考。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号