General Electric Company

Lockheed Martin Corporation

Transportation IP Holdings, LLC

Westinghouse Air Brake Technologies Corporation

Ge Infrastructure Technology, LLC

Matthew Christian Nielsen

Samhita Dasgupta

Robert John Filkins

Masoud Abbaszadeh

Weizhong Yan

Min-Yi Shih

Todd Ryan Tolliver

Robert Dean King

Christopher James Kapusta

William P Kornrumpf

Richard J Saia

Christopher Donald Johnson

Lembit Salasoo

Joseph Alfred Iannotti

Glen Peter Koste

Glenn Scott Claydon

Renato Guida

Zhi Zhou

Glenn A Forman

Santosh Sambamoorthy Veda

John Erik Hershey

Kevin Matthew Durocher

Bruno Hans Haider

Todd Garrett Wetzel

Michael Joseph Dell'Anno

Justin Varkey John

Mauricio Castillo-Effen

Jeffrey Bernard Fortin

Aditya Kumar

Irene Michelle Berry

Laura Jean Meyer

Hongwei Liao

Joji Joykutty

Kenneth Brakeley Welles

Harry Kirk Mathews, Jr

Stanton Earl Weaver, Jr

James Wilson Rose

Charles Erklin Seeley

Vitali Victor Lissianski

Brian Lee Lawrence

John Scott Price

Ronald Dean Watkins

Richard Louis Frey

Joseph Manak

Bruce Matthew Dunham

Vladimir Zamansky

Jason Wayne Black

Mustafa Tekin Dokucu

Allen Lawrence Garner

Brent Allen Clothier

Kelvin Ma

Surinder Prabhjot Singh

David Toledano

Conner Brooks Shane

Hema Kumari Achanta

Rajesh Tyagi

Ruijie Shi

Eric Michael Breitung

James Gerard Lopez

James Patrick Francis Lyons

Richard Anthony Depuy

Jayanth Kalle Marasanapalle

Ilkin Onur Dulgeroglu

Victor Manuel Perez Zarate

Rui Xu

Stanton E Weaver

Jigar Jayesh Shah

James Howard Schermerhorn

Chien-Hung Chen

Glenn Alan Forman

Harry Kirk Mathews Jr

A system is provided having one or more charging stations that are electrically coupled with a power distribution grid and that may selectively couple with one or more energy storage devices; and a controller that may control transfer of electric power between the one or more charging stations, the one or more energy storage devices, and the power distribution grid. The controller may determine the amount of electric power transferred based at least in part on one or more assessment values.

System and method for a charging station

According to some embodiments, a system, method, and non-transitory computer readable medium are provided comprising a plurality of real-time monitoring nodes to receive streams of monitoring node signal values over time that represent a current operation of the cyber physical system; and a threat detection computer platform, coupled to the plurality of real-time monitoring nodes, to: receive the monitoring node signal values; compute an anomaly score; compare the anomaly score with an adaptive threshold; and detect that one of a particular monitoring node and a system is outside a decision boundary based on the comparison, and classify that particular monitoring node or system as anomalous. Numerous other aspects are provided.

Attack detection and localization with adaptive thresholding

According to some embodiments, a system, method and non-transitory computer readable medium are provided comprising a memory storing processor-executable steps; and a processor to execute the processor-executable steps to cause the system to: receive a first data value of a plurality of data values from a data store, wherein the first data value is from a digital twin model of an industrial asset; determine, via a vulnerability module, whether the received at least one data value is a near boundary case or not a near boundary case; in a case it is determined the first data value is a near boundary case, generate one or more adversarial samples for the first data value; input each of the one or more adversarial samples to the digital twin model; execute the digital twin model to output a system response for each input adversarial sample; determine whether the system response to each input adversarial sample has a negative impact; in a case it is determined the system response has a negative impact for a given input adversarial sample, update a trained attack detection model with the given input adversarial sample; and generate a second decision boundary based on the updated trained attack detection model. Numerous other aspects are provided.

Vulnerability-driven cyberattack protection system and method for industrial assets

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).

Systems and methods for global cyber-attack or fault detection model

Methods and systems for using manifolds learning of airline network traffic to detect airline network traffic disruptions. In an embodiment, a computer processor transmits a request for abnormal airline network traffic simulation data to a simulation device, receives the abnormal airline network traffic simulation data, and generates, utilizing a manifolds learning process, simulated abnormal airline network traffic manifolds representation data. In some embodiments, the process may next include transmitting a request for current airline network traffic data to a current network traffic computer, receiving the current airline network traffic data, and generating a current airline network traffic dataset. In some implementations, the current airline network traffic dataset is then mapped to the abnormal airline network traffic manifolds representation, a determination made that a threshold number of data points of the current airline network traffic dataset maps to the abnormal airline traffic manifolds representation, and then an alarm is transmitted to an operator device indicating that a disruption of airline network traffic is imminent.

Systems and methods for manifolds learning of airline network data

Methods and systems for self-certifying secure operation of a cyber-physical system having a plurality of monitoring nodes. In an embodiment, an artificial intelligence (AI) watchdog computer platform obtains, using the output of a local features extraction process of time series data of a plurality of monitoring nodes of a cyber-physical system and a global features extraction process, global features extraction data. The AI watchdog computer platform then obtains reduced dimensional data, generates an updated decision boundary, compares the updated decision boundary to a certification manifold, determines based on the comparison that the updated decision boundary is certified, and determines, based on an anomaly detection process, whether the cyber-physical system is behaving normally or abnormally.

Self-certified security for assured cyber-physical systems

A system includes a control unit having one or more processors and a communication interface. The communication interface is configured to communicate with one or more charging stations that are electrically coupled to receive electrical power from a power distribution grid and that are configured to selectively charge one or more energy storage devices connected to the charging stations. The one or more processors are configured to generate first control signals for communication by the communication interface to the one or more charging stations to control transfer of reactive and/or active power from the charging stations to the power distribution grid. The control signals are generated based at least in part on a load cycle profile of one or more electric machines electrically coupled to the power distribution grid.

System and method of power control for an energy storage charging station

Systems and methods may be associated with a cyber-physical system, and a blueprint repository data store may contain electronic files that represent behavior-based asset monitoring parameters for different cyber-physical system asset types. A behavior-based asset monitoring creation computer platform may receive an indication of an asset type of the cyber-physical system. The behavior-based asset monitoring creation computer platform may then search the blueprint repository data store and retrieve an electronic file representing behavior-based asset monitoring parameters for the asset type of the cyber-physical system to be monitored. The behavior-based asset monitoring creation computer platform may also receive, from the remote operator device, adjustments to the retrieved behavior-based asset monitoring parameters and automatically configure, based on the adjusted behavior-based asset monitoring parameters, at least a portion of settings for an abnormal detection model. The abnormal detection model may then be created about output to be executed by an abnormal detection platform.

Framework to develop cyber-physical system behavior-based monitoring

A system includes a control unit having a processor and a communication interface. The communication interface is configured to communicate with one or more charging stations that are electrically coupled to receive electrical power from a power distribution grid and that are configured to selectively charge one or more energy storage devices connected to the charging stations. The processor is configured to generate first control signals for communication by the communication interface to the one or more charging stations to control transfer of reactive and/or active power from the charging stations to the power distribution grid. The control signals are generated based at least in part on a load cycle profile of one or more electric machines electrically coupled to the power distribution grid.

A method of providing a recommendation for optimizing operations of a set of industrial assets is disclosed. Digital twins of the set of industrial assets are generated. The digital twins include data structures representing states of each of a plurality of subsystems of the set of industrial assets over a time period. The states are estimated based on an application of simulations using cumulative damage models. The cumulative damage models model the effects of exogenous factors on the operation of the set of industrial assets over the time period. The digital twins are analyzed with respect to simulated operating performances to determine an optimized control of operations of the industrial assets. The optimized control of operations is calculated to jointly and severally to increase the specified operating performance criteria in time present and future of the industrial assets or decrease an economic risk associated with the operation of the industrial assets, within a specified probability. The recommendation is presented in a user interface for use in optimizing the operation of the industrial assets or automatically changing operating setpoints pertaining to the industrial assets.

Controlling aircraft operations and aircraft engine components assignment

Some embodiments are directed to an Internet of Things ('IoT') associate to facilitate implementation of a digital twin of a twinned physical system. The IoT associate may include a communication port to communicate with at least one component, the at least one component comprising a sensor or an actuator associated with the twinned physical system, and a gateway to exchange information via the IoT. A computer processor and local data storage, coupled to the communication port and gateway, may receive a digital twin model from a data warehouse via the IoT. The computer processor may be programmed to, for at least a selected portion of the twinned physical system, execute the digital twin model in connection with the at least one component and operation of the twinned physical system.

Internet of things associate

A system for determining identity information corresponding to an electrically operable machine is disclosed, where the electrically operable machine receives electricity from a power supply port. The system includes at least one sensor to generate a signal indicative of the electricity being drawn by the electrically operable machine from the power supply port. The system further includes a controller communicatively coupled to the at least one sensor and configured to determine the identity information corresponding to the electrically operable machine based on one or more electrical characteristics of the signal sensed by the at least one sensor. Method and non-transitory computer readable media for determining the identity of the electrically operable vehicle are also disclosed. Moreover, a system for controlling charging of a vehicle that is operated at least partially by the electricity is also disclosed.

System and method for determining identity information of an electrically operable machine

A fastening device may include a hollow void. The hollow void may contain an inner coil proximate to a first end of the device, a sensing portion to sense a characteristic associated with the fastening device during a sensing time window, and a controller. The controller may rectify an alternating current from the inner coil during a charging time window, store energy associated with the rectified alternating current, and use the stored energy to charge the sensing portion during the sensing time window. An outer coil outside the fastening device may be located proximate to a second end of the device as compared to the inner coil. An interface portion outside the fastening device may provide an alternating current to the outer coil during the charging time window, detect the sensed characteristic via the outer coil during the sensing time window, and transmit an indication of the detected characteristic value.

Fastening device with integrated sensor

A system and method for guiding and coordinating vehicular traffic determine tasks to be completed by vehicles in a transportation network in order to complete an objective, allocate the tasks among the vehicles, and determine sets of allowable actions for the vehicles based on the allocation of the tasks. The sets of allowable actions dictate plural different allowable actions that the vehicles are allowed to perform in order to complete the tasks allocated to the vehicles. The allowable actions are determined such that the vehicles are scheduled to complete the tasks and complete the objective without the vehicles colliding or blocking movement of each other. The allowable actions are communicated to the vehicles such that the vehicles are permitted to select one or more of the allowable actions and prohibited from performing one or more other actions during performance of the tasks allocated to the vehicles.

Vehicular traffic guidance and coordination system and method

Growing community of inventors

Scotia, NY, United States of America

Matthew Christian Nielsen