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Machine learning approach for fatigue life prediction of additive manufactured components accounting for localized material properties

机译:用于预测增材制造部件疲劳寿命的机器学习方法,考虑了局部材料特性

摘要

A method and a system for fatigue life prediction of additive manufactured components accounting for localized material properties. The method and the system is employed for prediction of fatigue life properties of an additive manufactured element, with a data collection step in which several data points for maximum stress vs. cycles to failure for different given processing steps of the element are collected, with a training step in which a Machine Learning system is trained with the collected data, and with an evaluation step in which the trained Machine Learning system is confronted with actual processing steps and used to predict the fatigue life properties of the element.
机译:一种考虑局部材料特性的增材制造部件疲劳寿命预测方法和系统。该方法和系统用于预测增材制造元件的疲劳寿命特性,其数据收集步骤中收集了元件不同给定加工步骤的最大应力与失效周期的多个数据点,并具有训练步骤,其中机器学习系统使用收集的数据进行训练, 以及评估步骤,其中经过训练的机器学习系统面对实际处理步骤,并用于预测元件的疲劳寿命特性。

著录项

  • 公开/公告号US11586161B2;US2023011586161B2;US11586161B2;US11586161

    专利类型

  • 公开/公告日2023-02-21

    原文格式PDF

  • 申请/专利权人 SIEMENS INDUSTRY SOFTWARE NV;

    申请/专利号US17606285;US201900017606285;US201917606285A;US201917606285

  • 发明设计人

    申请日2019-07-10

  • 分类号G05B13/02;B33Y50;G06N20;G05B19/4099;G05B23/02;

  • 国家

  • 入库时间 2024-06-14 23:50:59

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