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    Computer-implemented methods and systems for determining fleet conditions and operational management thereof
    2.
    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。

    METHOD, SYSTEM, AND PROGRAM STORAGE DEVICE FOR AUTOMATING PROGNOSTICS FOR PHYSICAL ASSETS
    3.
    发明申请
    METHOD, SYSTEM, AND PROGRAM STORAGE DEVICE FOR AUTOMATING PROGNOSTICS FOR PHYSICAL ASSETS 有权
    用于物理资产自动化的方法，系统和程序存储设备

    公开(公告)号：US20160253440A1

    公开(公告)日：2016-09-01

    申请号：US14632780

    申请日：2015-02-26

    Applicant: General Electric Company

    Inventor： Satish Giridhar Iyengar ,  John Anderson Fergus Ross ,  Frederick Wilson Wheeler ,  Naresh Sundaram Iyer ,  Paulo Ricardo dos Santos Mendonca ,  Ashok Sundaresan ,  Yujiao Zheng

    IPC: G06F17/50

    CPC classification number: G06F17/5009 ,  G01R31/3651 ,  G06F2217/76

    Abstract: In an example embodiment, a method of calculating end-of-life (EOL) predictions for a physical asset is provided. A state-space model for the physical asset is obtained, the state-space model being a physics-based model describing a state of the physical asset at a particular time given measurements or observations for the physical asset. Then a current state of the physical asset is inferred. Then a long-term prediction is derived for the physical asset based on the inferred current state of the physical asset and the state-space model for the physical asset. Then an EOL probability distribution function is generated for the physical asset based on the long-term prediction, the EOL probability distribution function describing a range of estimates of EOL for the physical asset and their corresponding confidence intervals.

    Abstract translation: 在一个示例性实施例中，提供了一种计算终身寿命（EOL）预测物理资产的方法。 获得物理资产的状态空间模型，状态空间模型是基于物理的模型，描述在特定时间对物理资产进行测量或观测的物理资产的状态。 然后推断出物理资产的当前状态。 然后根据物理资产的推定当前状态和实物资产的状态空间模型，为物理资产导出长期预测。 然后根据长期预测为物理资产生成一个EOL概率分布函数，该EOL概率分布函数描述物理资产的EOL估计范围及其对应的置信区间。

    Autonomous reasoning and experimentation agent for molecular discovery
    4.
    发明授权
    Autonomous reasoning and experimentation agent for molecular discovery 有权

    公开(公告)号：US11158400B2

    公开(公告)日：2021-10-26

    申请号：US16739239

    申请日：2020-01-10

    Applicant: General Electric Company

    Inventor： Jason Nichols ,  Johan Michael Reimann ,  Nurali Virani ,  Naresh Sundaram Iyer

    IPC: G16C20/20 ,  G16C20/70 ,  G06N7/00 ,  G06N20/00

    Abstract: According to some embodiments, a system, method and non-transitory computer-readable medium are provided comprising a Hypothesis Generation Engine (HGE) to receive one or more property target values for a material; a memory for storing program instructions; an HGE processor, coupled to the memory, and in communication with the HGE, and operative to execute program instructions to: receive the one or more property target values for the material; analyze the one or more property target values as compared to one or more known values in a knowledge base; generate, based on the analysis, an initial set of hypothetical structures, wherein each hypothetical structure includes at least one property target value; execute a likelihood model for each candidate material to generate a likelihood probability for each hypothetical structure, wherein the likelihood probability is a measure of the likelihood that the hypothetical structure will have the target property value; convert each hypothetical structure into a natural language representation; execute an abduction kernel on the natural language representation with the at least one likelihood probability, to output at least one proposed structure that satisfies a likelihood threshold for having the property target value; and receive the output of the executed abduction kernel at a testing module to determine whether the output satisfies the property target values. Numerous other aspects are provided.

    System and method for generating a schedule to extract a resource from a reservoir
    5.
    发明授权
    System and method for generating a schedule to extract a resource from a reservoir 有权

    公开(公告)号：US10605054B2

    公开(公告)日：2020-03-31

    申请号：US15433086

    申请日：2017-02-15

    Applicant: General Electric Company

    Inventor： Robert Carl Lloyd Klenner ,  Eric Robertson ,  Guoxiang Liu ,  Naresh Sundaram Iyer ,  Steven Hector Azzaro

    IPC: E21B41/00 ,  G05B19/418 ,  E21B43/26 ,  E21B43/12 ,  E21B47/06 ,  E21B47/04

    Abstract: A system includes a schedule generator having one or more processors configured to obtain resource extraction parameters for extracting a resource from a reservoir. The resource extraction parameters include well creation parameters associated with drilling wellbores, well stimulation parameters associated with introducing fracturing fluid into the wellbores, and production parameters associated with extracting the resource through the wellbores. The schedule generator selects initial trial schedules having different values of the resource extraction parameters and receives initial resource output data generated by execution of the initial trial schedules with a designated reservoir model. The schedule generator generates a surrogate model based on the initial resource output data and the initial trial schedules and uses the surrogate model to perform iterations of selecting modified trial schedules until a predetermined condition is satisfied.

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