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    Computer-implemented methods and systems for determining fleet conditions and operational management thereof
    4.
    发明授权
    Computer-implemented methods and systems for determining fleet conditions and operational management thereof 有权
    用于确定船队状况和运行管理的计算机实现的方法和系统

    公开(公告)号：US09552567B2

    公开(公告)日：2017-01-24

    申请号：US13728378

    申请日：2012-12-27

    Applicant: General Electric Company

    Inventor： Naresh Sundaram Iyer ,  Anil Varma ,  James Kenneth Aragones ,  Weizhong Yan ,  Piero Patrone Bonissone ,  Feng Xue

    IPC: G06N99/00 ,  G06Q10/08 ,  G06Q10/06

    CPC classification number: G06N5/04 ,  G06N99/005 ,  G06Q10/0631 ,  G06Q10/087 ,  G07C5/008

    Abstract: A method for determining fleet conditions and operational management thereof, performed by a central system includes receiving fleet data from at least one distributed data repository. The fleet data is substantially representative of information associated with a fleet of physical assets. The method also includes processing the received fleet data for the fleet using at least one process of a plurality of processes. The plurality of processes assess the received fleet data into processed fleet data. The method additionally includes determining a fleet condition status using the processed fleet data and the at least one process of the plurality of processes. The method further includes generating a fleet response. The fleet response is substantially representative of a next operational step for the fleet of physical assets. The method also includes transmitting the fleet response to at least one of a plurality of fleet response recipients.

    Abstract translation: 由中央系统执行的用于确定车队状况和其操作管理的方法包括从至少一个分布式数据存储库接收车队数据。 船队数据实质上代表与实体资产船队相关联的信息。 该方法还包括使用多个过程的至少一个过程处理车队接收的车队数据。 多个过程将接收到的车队数据评估为处理后的车队数据。 该方法另外包括使用处理的车队数据和多个过程中的至少一个过程来确定车队状况状态。 该方法还包括产生车队响应。 舰队反应实质上代表了有形资产队伍的下一个操作步骤。 该方法还包括将车队响应发送到多个车队响应接收者中的至少一个。

    SYSTEMS FOR VEHICLE CONTROL
    5.
    发明申请
    SYSTEMS FOR VEHICLE CONTROL 审中-公开
    车辆控制系统

    公开(公告)号：US20160062356A1

    公开(公告)日：2016-03-03

    申请号：US14936670

    申请日：2015-11-09

    Applicant: General Electric Company

    Inventor： Bret Dwayne Worden ,  Nicholas Edward Roddy ,  Feng Xue ,  Dustin Garvey

    IPC: G05D1/00 ,  G07C5/00

    CPC classification number: G05D1/0027 ,  G05D1/0022 ,  G05D1/0055 ,  G06Q10/06 ,  G07C5/008

    Abstract: A vehicle control system includes a transceiver and a control unit. The transceiver is configured to communicate with plural vehicles, to receive operational parameter values from the plural vehicles. The operational parameter values are generated by sensors on board the vehicles and relate to operation of the vehicles during movement of the vehicles along one or more routes. The control unit is configured to generate respective vehicle operational assessments of the vehicles based on the received operational parameter values. The vehicle operational assessments are representative of respective states of operational readiness of the vehicles. The control unit is further configured to generate control signals, relating to control of the vehicles for operation along the one or more designated routes, based on the operational assessments. The control signals are configured to control at least one device, either on board or off board the vehicles.

    Abstract translation: 车辆控制系统包括收发器和控制单元。 收发器被配置为与多个车辆进行通信，以接收来自多个车辆的操作参数值。 操作参数值由车辆上的传感器产生，并且涉及在沿着一个或多个路线的车辆移动期间车辆的操作。 控制单元被配置为基于接收到的操作参数值来生成车辆的各个车辆操作评估。 车辆操作评估代表各车辆的运行准备状态。 控制单元还被配置为基于操作评估产生与用于沿着一个或多个指定路线的操作的车辆的控制有关的控制信号。 控制信号被配置为控制至少一个设备，无论是在车上还是车辆上。

    SYSTEM AND METHOD FOR DIAGNOSING MACHINE FAULTS
    6.
    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。

    Deep causality learning for event diagnosis on industrial time-series data
    7.
    发明授权
    Deep causality learning for event diagnosis on industrial time-series data 有权

    公开(公告)号：US11415975B2

    公开(公告)日：2022-08-16

    申请号：US16564283

    申请日：2019-09-09

    Applicant: GENERAL ELECTRIC COMPANY

    Inventor： Hao Huang ,  Feng Xue ,  Weizhong Yan

    IPC: G05B23/00 ,  G05B23/02 ,  G06F17/16 ,  G06N3/08 ,  G06N3/04 ,  G05B19/406

    Abstract: According to embodiments, a system, method and non-transitory computer-readable medium are provided to receive time series data associated with one or more sensors values of a piece of machinery at a first time period, perform a non-linear transformation on the time-series data to produce one or more nonlinear temporal embedding outputs, and projecting each of the nonlinear temporal embedding outputs to a different dimension space to identify at least one causal relationship in the nonlinear temporal embedding outputs. The nonlinear embeddings are further projected to the original dimension space to produce one or more causality learning outputs. Nonlinear dimensional reduction is performed on the one or more causality learning outputs to produce reduced dimension causality learning outputs. The learning outputs are mapped to one or more predicted outputs which include a prediction of one or more of the sensor values at a second time period.

    INSPECTION SYSTEMS AND METHODS INCLUDING IMAGE RETRIEVAL MODULE
    8.
    发明申请
    INSPECTION SYSTEMS AND METHODS INCLUDING IMAGE RETRIEVAL MODULE 有权

    公开(公告)号：US20220067082A1

    公开(公告)日：2022-03-03

    申请号：US17011909

    申请日：2020-09-03

    Applicant: General Electric Company

    Inventor： Xiao Bian ,  Bernard Patrick Bewlay ,  Colin James Parris ,  Feng Xue ,  Shaopeng Liu ,  Arpit Jain ,  Shourya Sarcar

    IPC: G06F16/583 ,  G06F16/901 ,  G06F16/51 ,  G06N3/04

    Abstract: A method of inspecting a component using an image retrieval module includes storing an inspection image file in a memory and identifying a region of interest in the inspection image file. The method further includes accessing a database storing image files and determining feature vectors associated with the image files. The method also includes determining a hash code for each image file based on the feature vectors and classifying a subset of image files as relevant based on the hash codes. The method further includes sorting the subset of image files based on the feature vectors and generating search results based on the sorted subset of image files. The image retrieval module includes a convolutional neural network configured to learn from the determination of the feature vectors and increase the accuracy of the image retrieval module in classifying the image files.

    COMPUTER-IMPLEMENTED METHODS AND SYSTEMS FOR DETECTING A CHANGE IN STATE OF A PHYSICAL ASSET
    9.
    发明申请
    COMPUTER-IMPLEMENTED METHODS AND SYSTEMS FOR DETECTING A CHANGE IN STATE OF A PHYSICAL ASSET 审中-公开
    用于检测物理资料状态变化的计算机实现方法和系统

    公开(公告)号：US20140188772A1

    公开(公告)日：2014-07-03

    申请号：US13728755

    申请日：2012-12-27

    Applicant: GENERAL ELECTRIC COMPANY

    Inventor： Dustin Ross Garvey ,  Neil Holger White Eklund ,  Feng Xue

    IPC: G06N5/02

    CPC classification number: G06F11/008 ,  G05B23/024 ,  G06F11/3055

    Abstract: A computer-implemented method for detecting a change in state of a physical asset is performed by a computer device. The computer device includes a processor and a memory device. The method includes receiving at least one input signal associated with the physical asset in a time period. The time period includes a first period and a second period. The method further includes receiving at least one output signal associated with the physical asset in the time period. The method also includes generating a predicted estimate and estimate residuals based upon the at least one input signal. The method additionally includes determining estimation errors. The method also includes detecting a probability of change in state of the physical asset. The method further includes transmitting the probability of change in state of the physical asset to a servicer of the physical asset.

    Abstract translation: 用于检测物理资产的状态变化的计算机实现的方法由计算机设备执行。 计算机设备包括处理器和存储设备。 该方法包括在一段时间内接收与物理资产相关联的至少一个输入信号。 时间段包括第一周期和第二周期。 该方法还包括在该时间段内接收与物理资产相关联的至少一个输出信号。 该方法还包括基于至少一个输入信号生成预测估计和估计残差。 该方法还包括确定估计误差。 该方法还包括检测物理资产状态变化的概率。 该方法还包括将物理资产状态的变化概率发送给实体资产的服务者。

    System and method for receiving analysis requests and configuring analytics systems
    10.
    发明授权
    System and method for receiving analysis requests and configuring analytics systems 有权
    用于接收分析请求和配置分析系统的系统和方法

    公开(公告)号：US09552270B2

    公开(公告)日：2017-01-24

    申请号：US14482279

    申请日：2014-09-10

    Applicant: GENERAL ELECTRIC COMPANY

    Inventor： Anil Varma ,  Nicholas Roddy ,  Feng Xue

    IPC: G06F9/50 ,  G06F11/30

    CPC classification number: G06F11/301 ,  G06F9/50 ,  G06F9/5011 ,  G06F11/3051 ,  G06F2201/875 ,  G06F2209/501

    Abstract: A method for analyzing data is disclosed that includes receiving an analysis request to analyze selected data corresponding to one or more monitored assets, wherein the analysis request includes one or more parameters corresponding to performance categories of computing resources for processing the analysis request, the performance categories include at least one of a time for processing the analysis request or a cost for processing the analysis request; determining a computing resource allocation plan for processing the analysis request based on the one or more parameters; and processing the analysis request using the determined computing resource allocation plan to provide analysis results. Also disclosed is an analytic router that includes a mapper, an estimator, an optimizer, and a resource provisioner.

    Abstract translation: 公开了一种用于分析数据的方法，包括接收分析请求以分析对应于一个或多个受监视资产的所选数据，其中分析请求包括与用于处理分析请求的计算资源的性能类别对应的一个或多个参数， 包括用于处理分析请求的时间中的至少一个或用于处理分析请求的成本; 确定用于基于所述一个或多个参数来处理所述分析请求的计算资源分配计划; 以及使用所确定的计算资源分配计划处理分析请求以提供分析结果。 还公开了一种分析路由器，其包括映射器，估计器，优化器和资源提供器。

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