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Patent Agency Ranking
公开(公告)号：US20210084056A1
公开(公告)日：2021-03-18
申请号：US16574558
申请日：2019-09-18
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Masoud ABBASZADEH , Mustafa Tekin DOKUCU , Justin Varkey JOHN
Abstract: An industrial asset may have a plurality of monitoring nodes, each monitoring node generating a series of monitoring node values over time representing current operation of the industrial asset. An abnormality detection computer may determine that an abnormal monitoring node is currently being attacked or experiencing a fault. Responsive to an indication that a monitoring node is currently being attacked or experiencing a fault, the system may automatically replace monitoring node values from the at least one abnormal monitoring node currently being attacked or experiencing a fault with virtual node values. The system may also determine when the abnormal monitoring node or nodes will switch from the virtual node values back to monitoring node values.
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公开(公告)号：US20210399546A1
公开(公告)日：2021-12-23
申请号：US17288617
申请日：2018-11-05
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Anup MENON , Chaitanya Ashok BAONE , Honggang WANG , Mustafa Tekin DOKUCU
IPC: H02J3/00
Abstract: A dynamic simulation engine, having system parameters, may be provided for a component of an electrical power system (e.g., a generator, wind turbine, etc.). A model parameter tuning engine may receive, from a measurement data store, measurement data measured by an electrical power system measurement unit (e.g., a phasor measurement unit or digital fault recorder measuring a disturbance event). The model parameter tuning engine may then pre-condition the measurement data and set-up an optimization problem based on a result of the pre-conditioning. The system parameters of the dynamic simulation engine may be determined by solving the optimization problem with an iterative method until at least one convergence criteria is met. According to some embodiments, solving the optimization problem includes a Jacobian approximation that does not call the dynamic simulation engine if an improvement of residual meets a pre-defined criteria.
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公开(公告)号：US20210037044A1
公开(公告)日：2021-02-04
申请号：US16525807
申请日：2019-07-30
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Hema K, Achanta , Masoud ABBASZADEH , Weizhong YAN , Mustafa Tekin DOKUCU
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.
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公开(公告)号：US20210081270A1
公开(公告)日：2021-03-18
申请号：US16574493
申请日：2019-09-18
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Masoud ABBASZADEH , Mustafa Tekin DOKUCU , Justin Varkey JOHN
Abstract: An industrial asset may have a plurality of monitoring nodes, each monitoring node generating a series of monitoring node values over time representing current operation of the industrial asset. An abnormality detection computer may determine that an abnormal monitoring node is currently being attacked or experiencing a fault. An autonomous, resilient estimator may continuously execute an adaptive learning process to create or update virtual sensor models for that monitoring node. Responsive to an indication that a monitoring node is currently being attacked or experiencing a fault, a level of neutralization may be automatically determined. The autonomous, resilient estimator may then be dynamically reconfigured to estimate a series of virtual node values based on information from normal monitoring nodes, appropriate virtual sensor models, and the determined level of neutralization. The series of monitoring node values from the abnormal monitoring node or nodes may then be replaced with the virtual node values.
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公开(公告)号：US20190129367A1
公开(公告)日：2019-05-02
申请号：US15794769
申请日：2017-10-26
Applicant: General Electric Company
Inventor： Chaitanya Ashok BAONE , Nan DUAN , Anup MENON , Mustafa Tekin DOKUCU
Abstract: A power system model parameter conditioning tool including a server control processor in communication with phasor measurement unit monitored data records of multiple disturbance events, a model calibration unit providing event screening, power system model simulation, and simultaneous tuning of model parameters. The model calibration performing a simulation using default model parameters, the processor comparing the simulation results to the monitored data. If the prediction is within threshold, then terminating conditioning; else performing parameter identifiability analysis to determine differing effects of various model parameters on power system model accuracy, selecting a parameter set causing a degradation in power system model prediction, and updating the default model parameters corresponding to members of the parameter set with values selected to reduce the degradation. A method and a non-transitory computer readable medium are also disclosed.
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