公开(公告)号：US20190146436A1

公开(公告)日：2019-05-16

申请号：US15809804

申请日：2017-11-10

Applicant: General Electric Company

Inventor： Victor Manuel Perez Zarate ,  Luis Gabriel De Alba Rivera ,  Brock Estel Osborn ,  Katherine Tharp Nowicki ,  Michael William Bailey ,  Michael Evans Graham

IPC: G05B19/042

CPC classification number: G05B19/042 ,  G05B2219/2639 ,  G06Q10/20

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to generate a workscope. An example apparatus includes a workscope mapper, workscope strategy analyzer, and workscope selector. The workscope strategy analyzer is to evaluate each of the plurality of workscopes using dynamic optimization to determine a maintenance value and benefit to an asset associated with each workscope based on a stage in a remaining life of a constraint at which the evaluation is executed and a state of the asset. The dynamic optimization is to determine a prediction of the maintenance value based on a probability of a future change in state and associated workscope value until the end of life of the constraint. The maintenance value, used to select a workscope from the plurality of workscopes, is to be determined by the dynamic optimization as a sum of the associated workscope values until the end of life of the constraint.

公开(公告)号：US10796018B2

公开(公告)日：2020-10-06

申请号：US15809804

申请日：2017-11-10

Applicant: General Electric Company

Inventor： Victor Manuel Perez Zarate ,  Luis Gabriel De Alba Rivera ,  Brock Estel Osborn ,  Katherine Tharp Nowicki ,  Michael William Bailey ,  Michael Evans Graham

IPC: G05B19/042 ,  G06Q10/00 ,  G06F21/62 ,  G06F19/00 ,  G06Q50/24 ,  H04N1/00 ,  G06F21/53 ,  G06F21/60 ,  G06T11/00 ,  G16H40/67 ,  G16H10/60 ,  G16H30/20

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to generate a workscope. An example apparatus includes a workscope mapper, workscope strategy analyzer, and workscope selector. The workscope strategy analyzer is to evaluate each of the plurality of workscopes using dynamic optimization to determine a maintenance value and benefit to an asset associated with each workscope based on a stage in a remaining life of a constraint at which the evaluation is executed and a state of the asset. The dynamic optimization is to determine a prediction of the maintenance value based on a probability of a future change in state and associated workscope value until the end of life of the constraint. The maintenance value, used to select a workscope from the plurality of workscopes, is to be determined by the dynamic optimization as a sum of the associated workscope values until the end of life of the constraint.

公开(公告)号：US20140298097A1

公开(公告)日：2014-10-02

申请号：US13852632

申请日：2013-03-28

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Kati Illouz ,  Brock Estel Osborn

IPC: G06F11/34

CPC classification number: G06F11/0739 ,  G06F11/076 ,  G06F11/0793

Abstract: A method implemented using a processor based device for generating a corrected data for deriving a decision related to a data source includes receiving measurement data representative of an operational parameter from the data source. The operational parameter includes a monotonous time series data. The method also includes identifying an event based on the measurement data and determining an event category based on the identified event. The method further includes processing the measurement data using a statistical data correction technique, based on the determined event category, to generate the corrected data for deriving the decision related to the data source.

Abstract translation: 使用基于处理器的设备实现的用于生成用于导出与数据源相关的决定的校正数据的方法包括从数据源接收表示操作参数的测量数据。 操作参数包括单调的时间序列数据。 该方法还包括基于测量数据识别事件并且基于所识别的事件来确定事件类别。 该方法还包括基于所确定的事件类别使用统计数据校正技术来处理测量数据，以产生用于导出与数据源有关的决定的校正数据。

公开(公告)号：US20140188777A1

公开(公告)日：2014-07-03

申请号：US13728572

申请日：2012-12-27

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Weizhong Yan ,  Anil Varma ,  Brock Estel Osborn ,  James Kenneth Aragones ,  Piero Patrone Bonissone ,  Naresh Sundaram Iyer ,  Hai Qiu

IPC: G06N5/02

CPC classification number: G06N5/04 ,  G06F11/008

Abstract: A computer-implemented system for identifying a precursor to a failure of a particular type of component in a physical system is provided. The physical system includes sensors coupled to the physical system. The computer-implemented system includes a computing device, a database, a processor, and a memory device. The memory device includes historical data including sensor measurements. When instructions are executed by the processor, the processor receives the historical data from the memory device. The processor generates a predictive model. The predictive model uses, as inputs, sensor measurements in the historical data. The predictive model is able to differentiate between sensor measurements taken before the repair event and those taken after the repair event without a time of the repair event being an input to the predictive model. The processor designates at least one sensor measurements used as inputs to the predictive model as precursors to the failure of the component.

Abstract translation: 提供了一种用于识别物理系统中特定类型的组件的故障的前兆的计算机实现的系统。 物理系统包括耦合到物理系统的传感器。 计算机实现的系统包括计算设备，数据库，处理器和存储设备。 存储器件包括包括传感器测量的历史数据。 当处理器执行指令时，处理器从存储器件接收历史数据。 处理器生成预测模型。 预测模型使用历史数据中的传感器测量作为输入。 该预测模型能够区分在修复事件之前进行的传感器测量与在修复事件之后进行的传感器测量之间，而没有修复事件的时间是预测模型的输入。 处理器指定用作预测模型的输入的至少一个传感器测量值作为组件故障的前兆。