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    System and Method for Inferring Vehicle Health
    2.
    发明申请
    System and Method for Inferring Vehicle Health 审中-公开
    车辆健康的系统和方法

    公开(公告)号：US20160063418A1

    公开(公告)日：2016-03-03

    申请号：US14476030

    申请日：2014-09-03

    Applicant: General Electric Company

    Inventor： Nicholas Edward Roddy ,  Dustin Ross Garvey ,  Rui Xu

    IPC: G06Q10/06

    CPC classification number: G06Q10/06315

    Abstract: A system and method for inferring vehicle health are disclosed. The computer-implemented method comprises identifying a plurality of candidate vehicles for consideration for use for a task, and receiving corresponding event data for at least one of the plurality of candidate vehicles. The event data may correspond to at least one occurrence of at least one suspected problem for the corresponding candidate vehicle. A corresponding health score can be generated for each one of the plurality of candidate vehicles. The corresponding health score for the at least one of the plurality of candidate vehicles can be generated based on the corresponding event data for the at least one of the plurality of candidate vehicles. The generated health scores can indicate a likelihood of failure for their corresponding candidate vehicles.

    Abstract translation: 公开了一种用于推断车辆健康的系统和方法。 计算机实现的方法包括识别多个候选车辆以供考虑用于任务，以及接收多个候选车辆中的至少一个的对应的事件数据。 事件数据可以对应于对应的候选车辆的至少一个可疑问题的至少一次出现。 可以为多个候选车辆中的每一个产生相应的健康评分。 可以基于多个候选车辆中的至少一个候选车辆的相应事件数据来生成多个候选车辆中的至少一个候选车辆的对应健康得分。 所产生的健康状况分数可能表明其相应的候选车辆失败的可能性。

    SYSTEMS AND METHODS FOR CONCEPT DRIFT LEARNING WITH ALTERNATING LEARNERS
    3.
    发明申请
    SYSTEMS AND METHODS FOR CONCEPT DRIFT LEARNING WITH ALTERNATING LEARNERS 审中-公开

    公开(公告)号：US20180150036A1

    公开(公告)日：2018-05-31

    申请号：US15820963

    申请日：2017-11-22

    Applicant: General Electric Company

    Inventor： Yunwen Xu ,  Paul Ardis ,  Rui Xu ,  Weizhong Yan

    IPC: G05B13/04

    CPC classification number: G05B13/041 ,  G05B13/0265 ,  G06Q10/20

    Abstract: According to some embodiments, a system and method are provided to model a sparse data asset. The system comprises a processor and a non-transitory computer-readable medium comprising instructions that when executed by the processor perform a method to model a sparse data asset. Relevant data and operational data associated with the newly operational are received. A transfer model based on the relevant data and the received operational data. An input into the transfer model is received and a predication based on data associated with the received operational data and the relevant data is output.

    Systems and methods for global cyber-attack or fault detection model
    6.
    发明授权
    Systems and methods for global cyber-attack or fault detection model 有权

    公开(公告)号：US11740618B2

    公开(公告)日：2023-08-29

    申请号：US17239054

    申请日：2021-04-23

    Applicant: GENERAL ELECTRIC COMPANY

    Inventor： Rui Xu ,  Weizhong Yan ,  Masoud Abbaszadeh ,  Matthew Christian Nielsen

    IPC: G05B23/02 ,  G06N3/08 ,  G06N3/045

    CPC classification number: G05B23/024 ,  G05B23/027 ,  G05B23/0221 ,  G06N3/045 ,  G06N3/08

    Abstract: An industrial asset may have monitoring nodes that generate current monitoring node values representing a current operation of the industrial asset. An abnormality detection computer may detect when a monitoring node is currently being attacked or experiencing a fault based on a current feature vector, calculated in accordance with current monitoring node values, and a detection model that includes a decision boundary. A model updater (e.g., a continuous learning model updater) may determine an update time-frame (e.g., short-term, mid-term, long-term, etc.) associated with the system based on trigger occurrence detection (e.g., associated with a time-based trigger, a performance-based trigger, an event-based trigger, etc.). The model updater may then update the detection model in accordance with the determined update time-frame (and, in some embodiments, continuous learning).

    SYSTEM AND METHOD FOR DIAGNOSING MACHINE FAULTS
    7.
    发明申请
    SYSTEM AND METHOD FOR DIAGNOSING MACHINE FAULTS 审中-公开
    用于诊断机器故障的系统和方法

    公开(公告)号：US20150120248A1

    公开(公告)日：2015-04-30

    申请号：US14067179

    申请日：2013-10-30

    Applicant: General Electric Company

    Inventor： Dustin Ross Garvey ,  Rui Xu ,  Feng Xue ,  Bouchra Bouqata ,  Nicholas Edward Roddy

    IPC: G01M99/00

    CPC classification number: G01M5/0033 ,  G05B23/0227 ,  G07C5/0808

    Abstract: A method for diagnosing machine faults, includes obtaining sensory data from a machine and obtaining a plurality of measured structural features based on the sensory data. The method also includes obtaining a plurality of reference cases corresponding to the sensory data, from a database. The plurality of reference cases include a plurality of reference structural features and a plurality of fault identifiers. The method further includes computing a statistical parameter based on the plurality of reference cases and obtaining a first subset of reference structural features from the plurality of reference structural features based on the computed statistical parameter. The method also includes computing a plurality of similarity values based on the obtained first subset of reference structural features and the plurality of measured structural features. The method further includes identifying at least one fault identifier among the plurality of fault identifiers, based on the computed plurality of similarity values.

    Abstract translation: 一种用于诊断机器故障的方法，包括从机器获取感觉数据，并且基于感觉数据获得多个测量的结构特征。 该方法还包括从数据库获得与感觉数据相对应的多个参考情况。 多个参考案例包括多个参考结构特征和多个故障标识符。 该方法还包括基于多个参考情况计算统计参数，并且基于所计算的统计参数从多个参考结构特征获得参考结构特征的第一子集。 该方法还包括基于获得的参考结构特征和多个测量结构特征的第一子集来计算多个相似度值。 该方法还包括基于所计算的多个相似度值来识别多个故障识别器中的至少一个故障标识符。

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