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System and Method for Providing Real-Time Prediction of Time to Fatigue Failure Under Stochastic Loading

机译:用于在随机负载下提供疲劳失效时间的实时预测的系统和方法

摘要

A prediction system predicts a failure time of a mechanical system of interest in real-time. A sensor/sensors array senses a characteristic of the mechanical system of interest. An artificial neural network system includes an artificial neural network (ANN), a training module (140) configured to train the ANN, and a real-time prediction module. Real-time data is recorded by the sensor/s and converted in real-time into an estimated failure time of the mechanical system of interest and a corresponding uncertainty quantification. A reporting module receives and displays the estimated failure time and the uncertainty quantification.
机译:预测系统在实时预测机械兴趣系统的失效时间。 传感器/传感器阵列感测到感兴趣的机械系统的特征。 人工神经网络系统包括人工神经网络(ANN),训练模块(140),被配置为训练ANN,以及实时预测模块。 实时数据由传感器/ s记录并实时转换成有趣的机械系统的估计失效时间和相应的不确定量化。 报告模块接收并显示估计的故障时间和不确定性量化。

著录项

  • 公开/公告号US2022036161A1

    专利类型

  • 公开/公告日2022-02-03

    原文格式PDF

  • 申请/专利权人 MASSACHUSETTS INSTITUTE OF TECHNOLOGY;

    申请/专利号US202016941841

  • 发明设计人 MAOR FARID;

    申请日2020-07-29

  • 分类号G06N3/04;G06N3/08;G06K9/62;

  • 国家 US

  • 入库时间 2022-08-24 23:36:24

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