公开(公告)号：US20230385186A1

公开(公告)日：2023-11-30

申请号：US18321545

申请日：2023-05-22

Applicant: General Electric Company

Inventor： Hema K Achanta ,  Masoud Abbaszadeh ,  Weizhong Yan ,  Mustafa Tekin Dokucu

IPC: G06F11/36 ,  H04L9/40 ,  H04L41/16 ,  G06N3/08 ,  G06F18/24 ,  G06F18/214 ,  H04L43/12 ,  G06V10/82 ,  G06F11/263 ,  H04W12/128

CPC classification number: G06F11/3684 ,  H04L63/1441 ,  H04L41/16 ,  G06N3/08 ,  G06F18/24 ,  G06F18/214 ,  H04L43/12 ,  G06V10/82 ,  G06F11/263 ,  H04W12/128 ,  G06N3/0418

Abstract: According to some embodiments, a system, method and non-transitory computer-readable medium are provided to protect a cyber-physical system having a plurality of monitoring nodes comprising: a normal space data source storing, for each of the plurality of monitoring nodes, a series of normal monitoring node values over time that represent normal operation of the cyber-physical system; a situational awareness module including an abnormal data generation platform, wherein the abnormal data generation platform is operative to generate abnormal data to represent abnormal operation of the cyber-physical system using values in the normal space data source and a generative model; a memory for storing program instructions; and a situational awareness processor, coupled to the memory, and in communication with the situational awareness module and operative to execute the program instructions to: receive a data signal, wherein the received data signal is an aggregation of data signals received from one or more of the plurality of monitoring nodes, wherein the data signal includes at least one real-time stream of data source signal values that represent a current operation of the cyber-physical system; determine, via a trained classifier, whether the received data signal is a normal signal or an abnormal signal, wherein the trained classifier is trained with the generated abnormal data and normal data; localize an origin of an anomaly when it is determined the received data signal is the abnormal signal; receive the determination and localization at a resilient estimator module; execute the resilient estimator module to generate a state estimation for the cyber-physical system. Numerous other aspects are provided.

公开(公告)号：US20210088563A1

公开(公告)日：2021-03-25

申请号：US16580525

申请日：2019-09-24

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Weizhong Yan ,  Honggang Wang

IPC: G01R19/25 ,  G01R31/08 ,  G06N3/08

Abstract: Briefly, embodiments are directed to a system, method, and article for identifying power system event signatures. Input measurement data may be received from one or more data sources relating to a power grid system. The input measurement data may comprise normal system operation measurement data and power system event measurement data. A processor may perform operations during an online application phase. During the online application phase, a feature matrix may be generated for the power system event measurement data and the at least one trained auto-associative model. The feature matrix for the power system event measurement data may be processed to determine power system event residuals. Also during the online application phase, the power system event signatures may be identified based on residual statistics for normal system operation measurement data residuals and on the power system event residuals.

公开(公告)号：US10956578B2

公开(公告)日：2021-03-23

申请号：US16152546

申请日：2018-10-05

Applicant: General Electric Company

Inventor： Hema Achanta ,  Lalit Keshav Mestha ,  Weizhong Yan

IPC: G06F21/57 ,  G05B19/048

Abstract: According to some embodiments, a system, method and non-transitory computer-readable medium are provided to protect a decision manifold of a control system for an industrial asset, comprising: a detection and neutralization module including: a decision manifold having a receiver configured to receive a training dataset comprising data, wherein the decision manifold is operative to generate a first decision manifold with the received training dataset; and a detection model; a memory for storing program instructions; and a detection and neutralization processor, coupled to the memory, and in communication with the detection and neutralization module and operative to execute program instructions to: receive the first decision manifold, wherein the first decision manifold separates a normal operating space from an abnormal operating space; determine whether there are one or more inadequacies with the detection model; generate a corrected decision manifold based on the determined one or more inadequacies with the detection model; receive a projected adversary strategy; generate a resilient decision manifold based on the corrected decision manifold and received projected adversary strategy; and an output configured to output a neutralized signal to operate the industrial asset via the control system. Numerous other aspects are provided.

公开(公告)号：US10686806B2

公开(公告)日：2020-06-16

申请号：US15681827

申请日：2017-08-21

Applicant: General Electric Company

Inventor： Masoud Abbaszadeh ,  Lalit Keshav Mestha ,  Weizhong Yan

IPC: H04L29/06

Abstract: According to some embodiments, a plurality of monitoring nodes may each generate a series of current monitoring node values over time that represent a current operation of the industrial asset. A node classifier computer, coupled to the plurality of monitoring nodes, may receive the series of current monitoring node values and generate a set of current feature vectors. The node classifier computer may also access at least one multi-class classifier model having at least one decision boundary. The at least one multi-class classifier model may be executed and the system may transmit a classification result based on the set of current feature vectors and the at least one decision boundary. The classification result may indicate, for example, whether a monitoring node status is normal, attacked, or faulty.

公开(公告)号：US20170024649A1

公开(公告)日：2017-01-26

申请号：US14808402

申请日：2015-07-24

Applicant: General Electric Company

Inventor： Weizhong Yan ,  Lijie YU

IPC: G06N5/04 ,  G06N99/00

CPC classification number: G06N3/0454 ,  G05B23/0283 ,  G06N3/0445

Abstract: Some embodiments are associated with a receipt, at a feature learning platform, of sensor data associated with normal operation of an industrial asset, the sensor data including values for a plurality of sensors over a period of time. The feature learning platform may extract a plurality of features via hierarchically deep learning, which may capture characteristics of normal operation of the industrial asset and provide the learned features to a classification modeling platform. The classification modeling platform may then create classification models utilizing the learned features, and the classification models may be executed to automatically identify a potential anomaly for an operating industrial asset.

Abstract translation: 一些实施例与在特征学习平台处的与工业资产的正常操作相关联的传感器数据的收据相关联，所述传感器数据包括一段时间内的多个传感器的值。 特征学习平台可以通过分级深度学习提取多个特征，其可以捕获工业资产的正常操作的特征并将学习的特征提供给分类建模平台。 然后，分类建模平台可以使用学习的特征来创建分类模型，并且可以执行分类模型以自动识别经营的工业资产的潜在异常。

公开(公告)号：US20150356455A1

公开(公告)日：2015-12-10

申请号：US14298282

申请日：2014-06-06

Applicant: General Electric Company

Inventor： Lei Wu ,  Weizhong Yan ,  Jianhui Chen ,  Dong Ryeol Lee

IPC: G06N7/02 ,  G06F17/16 ,  G06N99/00

CPC classification number: G06K9/00979 ,  G06K9/6256 ,  G06K9/6269

Abstract: Some embodiments are associated with a support vector machine having model parameters. According to some embodiments, a set of evaluation data may be received and a computer processor may automatically tune the model parameters during a training process using the set of evaluation data. The automatically tuned model parameters for the support vector machine may then be output directly from the training process.

Abstract translation: 一些实施例与具有模型参数的支持向量机相关联。 根据一些实施例，可以接收一组评估数据，并且计算机处理器可以在使用该组评估数据的训练过程期间自动调整模型参数。 然后可以直接从训练过程输出用于支持向量机的自动调谐的模型参数。

公开(公告)号：US20140188768A1

公开(公告)日：2014-07-03

申请号：US13729720

申请日：2012-12-28

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Piero Patrone Bonissone ,  Neil Holger White Eklund ,  Feng Xue ,  Naresh Sundaram Iyer ,  Weizhong Yan

IPC: G06N99/00

CPC classification number: G06N20/00

Abstract: A computer-implemented system for creating customized model ensembles on demand is provided. An input module is configured to receive a query. A selection module is configured to create a model ensemble by selecting a subset of models from a plurality of models, wherein selecting includes evaluating an aspect of applicability of the models with respect to answering the query. An application module is configured to apply the model ensemble to the query, thereby generating a set of individual results. A combination module is configured to combine the set of individual results into a combined result and output the combined result, wherein combining the set of individual results includes evaluating performance characteristics of the model ensemble relative to the query.

Abstract translation: 提供了一种用于根据需要创建定制模型组合的计算机实现的系统。 输入模块被配置为接收查询。 选择模块被配置为通过从多个模型中选择模型的子集来创建模型集合，其中选择包括评估模型在回答查询时的适用性的一个方面。 应用模块被配置为将模型集合应用于查询，从而生成一组单独的结果。 组合模块被配置为将该组个体结果组合成一个组合结果并输出组合结果，其中组合该单独结果包括评估模型集合相对于该查询的性能特征。

公开(公告)号：US20140188767A1

公开(公告)日：2014-07-03

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

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。

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).

公开(公告)号：US11544426B2

公开(公告)日：2023-01-03

申请号：US16601732

申请日：2019-10-15

Applicant: General Electric Company

Inventor： Honggang Wang ,  Weizhong Yan ,  Kaveri Mahapatra

IPC: G06F30/20 ,  G06F30/18 ,  G06F7/58 ,  H02J3/00 ,  G06N7/00 ,  G06F119/06 ,  G06F113/04 ,  G06F111/10 ,  G06F111/02 ,  G06Q50/06 ,  G06F17/14

Abstract: A system for enhanced sequential power system model calibration is provided. The system is programmed to store a model of a device. The model includes a plurality of parameters. The system is also programmed to receive a plurality of events associated with the device, receive a first set of calibration values for the plurality of parameters, generate a plurality of sets of calibration values for the plurality of parameters, for each of the plurality of sets of calibration values, analyze a first event of the plurality of events using a corresponding set of calibration values to generate a plurality of updated sets of calibration values, analyze the plurality of updated sets of calibration values to determine a current updated set of calibration values, and update the model to include the current updated set of calibration values.