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DEVICES, SYSTEMS, AND METHODS FOR FORECASTING DEVICE FAILURES

机译:用于设备故障的设备,系统和方法

摘要

Devices, systems, and methods obtain sensor data that were generated by a plurality of sensors; obtain event data that include occurrences of an event; calculate first characteristics of the sensor data that were generated by the plurality of sensors within a temporal range of an occurrence of the event; identify, in the sensor data, sensor data that were generated by the plurality of sensors within the temporal range of at least one other occurrence of the event based on the first characteristics; calculate second characteristics of the sensor data that were generated by the plurality of sensors within the temporal range of the at least one other occurrence of the event, normalize at least some of the sensor data based on the first characteristics and on the second characteristics, thereby generating normalized sensor data, and train a machine-learning model based on the normalized sensor data.
机译:设备,系统和方法获得由多个传感器产生的传感器数据; 获取包含事件发生的事件数据; 计算在事件发生的时间范围内由多个传感器产生的传感器数据的第一特征; 在传感器数据中,在传感器数据中,在基于第一特征的至少一个其他发生事件的时间范围内由多个传感器产生的传感器数据; 计算由事件的至少一个其他发生的时间范围内由多个传感器产生的传感器数据的第二特征,基于第一特征和第二特征来归一化至少一些传感器数据。 产生标准化的传感器数据,并基于归一化传感器数据训练机器学习模型。

著录项

  • 公开/公告号US2022014635A1

    专利类型

  • 公开/公告日2022-01-13

    原文格式PDF

  • 申请/专利权人 CANON SOLUTIONS AMERICA INC.;

    申请/专利号US202016924791

  • 发明设计人 JEFFREY DAVID KANE;

    申请日2020-07-09

  • 分类号H04N1;G06N20;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-24 23:20:09

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