General Electric Company

Lockheed Martin Corporation

Dresser, Inc.

Utc Fire & Security Americas Corporation, Inc.

Transportation IP Holdings, LLC

Nbcuniversal Media, LLC

General Electric Renovables Espana, S.l.

Ge Medical Systems Information Technologies Gmbh

Ge Global Sourcing LLC

Utc Fire and Security Corporation

Baker Hughes Holdings LLC

Frederick Wilson Wheeler

Peter Henry Tu

Xiaoming Liu

Brett Alexander Matthews

Jilin Tu

Justin Scott Shriver

Bernhard Erich Hermann Claus

Jeffrey Michael Fries

Yuri Alexeyevich Plotnikov

Robert Claude Prescott

Ajith Kuttannair Kumar

Kevin George Harding

Joseph Forrest Noffsinger

Edward James Nieters

Brian Lee Staton

Gil Abramovich

Charles Burton Theurer

Huan Tan

Weizhong Yan

Douglas Roy Forman

Mark Lewis Grabb

John Michael Lizzi

Yi Xu

Arpit Jain

George Theodore Dalakos

Balajee Kannan

Romano Patrick

Omar Al Assad

Larry Gene Schoonover

Shiraj Sen

Ghulam Ali Baloch

Shubao Liu

John Erik Hershey

Saad Ahmed Sirohey

John Anderson Fergus Ross

Jeffrey Wayne Eberhard

Jeffrey Michael Ashe

Ralph Thomas Hoctor

Glen Peter Koste

Naresh Sundaram Iyer

Ali Can

Danian Zheng

Kai Erik Thomenius

Siavash Yazdanfar

Seth D Silverstein

Anthony Wykeham Jacomb-Hood

Jeffrey Jacob Bizub

Leonardo Cesar Kammer

Gregory Boverman

Majid Nayeri

Harold Randall Smart

Samhitha Palanganda Poonacha

Yan Tong

Dayu Huang

Timothy Robert Brown

Tannous Frangieh

John Joseph Mihok

Ameet Shridhar Deshpande

Viktor Holovashchenko

Tai-Peng Tian

Joseph Czechowski, Iii

Yonatan Gefen

Cynthia Elizabeth Landberg

Pramod Sharma

Shuai Li

Su Liu

John Patrick Kaufhold

Paulo Ricardo Dos Santos Mendonca

Sachin Narahari Dekate

Robert D Barnes

Daniel Curtis Gray

Manthram Sivasubramaniam

Brian Allen Rittenhouse

David Charles Korim

Anthony James Hoogs

Dhiraj Arora

Gregory Michael Kautz

Michael James Rizzo

Iyad Batal

Satish Giridhar Iyengar

Ashok Sundaresan

Pranav Agarwal

Marco Guerriero

Jan De Vaan

Yujiao Zheng

Sudipta Mukhopadhyay

Somasekhar Dhavala

Inderdeep Kaur

Siyun Wang

Justin Edwin Barton

Misha Gupta

Vidya Sagar Meesala

James Huu Phan

Justin Shriver

Larry Schoonover

A robotic system includes a controller configured to obtain image data from one or more optical sensors and to determine one or more of a location and/or pose of a vehicle component based on the image data. The controller also is configured to determine a model of an external environment of the robotic system based on the image data and to determine tasks to be performed by components of the robotic system to perform maintenance on the vehicle component. The controller also is configured to assign the tasks to the components of the robotic system and to communicate control signals to the components of the robotic system to autonomously control the robotic system to perform the maintenance on the vehicle component.

Integrated robotic system and method for autonomous vehicle maintenance

The present disclosure is directed to a method for responding to a friction coefficient signal of a pitch bearing of a pitch drive mechanism of a wind turbine and/or for controlling the pitch drive mechanism(s) and/or a bank of ultracapacitors. The method and system include: accessing high-frequency measurement data of the at least one pitch bearing; estimating, via a torque balance model implemented by a controller, a frictional torque of the at least one pitch bearing based, at least in part, on the high-frequency measurement data; estimating, via the controller, a friction coefficient signal of the at least one pitch bearing based, at least in part, on the frictional torque; comparing the friction coefficient signal with a friction threshold; determining whether the friction coefficient signal deviates from the friction threshold based, at least in part, on the comparison; and, if so, acting.

System and method for responding to a friction coefficient signal of a wind turbine

A method for detecting anomalies during operation of an asset to improve performance of the asset includes collecting, via a server, data relating to operation of the asset or a group of assets containing the asset. The data includes normal and abnormal asset behavior of the asset or the group of assets containing the asset. Further, the method includes automatically removing, via an iterative algorithm programmed in the server that utilizes one or more inputs or outputs of an anomaly detection analytic, portions of the data containing the abnormal asset behavior to form a dataset containing only the normal asset behavior. The method also includes training, via a computer-based model programmed in the server, the anomaly detection analytic using, at least, the dataset containing only the normal asset behavior. Moreover, the method includes applying, via the server, the anomaly detection analytic to the asset so as to monitor for anomalies during operation thereof.

System and method for training anomaly detection analytics to automatically remove outlier data

A method for controlling a wind turbine connected to an electrical grid includes receiving, via a controller, a state estimate of the wind turbine. The method also includes determining, via the controller, a current condition of the wind turbine using, at least, the state estimate, the current condition defining a set of condition parameters of the wind turbine. Further, the method includes receiving, via the controller, a control function from a supervisory controller, the control function defining a relationship of the set of condition parameters with at least one operational parameter of the wind turbine. Moreover, the method includes dynamically controlling, via the controller, the wind turbine based on the current condition and the control function for multiple dynamic control intervals.

Odometer-based control of a wind turbine power system

A method for operating a wind turbine includes determining one or more loading and travel metrics or functions thereof for one or more components of the wind turbine during operation of the wind turbine. The method also includes generating, at least in part, at least one distribution of cumulative loading data for the one or more components using the one or more loading and travel metrics during operation of the wind turbine. Further, the method includes applying a life model of the one or more components to the at least one distribution of cumulative loading data to determine an actual damage accumulation for the one or more components of the wind turbine to date. Moreover, the method includes implementing a corrective action for the wind turbine based on the damage accumulation.

System for operating a wind turbine using cumulative load histograms based on actual operation thereof

A method for detecting damage in a bearing coupled to a rotating shaft of a rotary machine includes receiving one or more measurement signals from one or more first sensors for monitoring movement of the rotating shaft in one or more directions over a time period. The method also includes removing an effect of one or more environmental and/or operating conditions of the rotary machine from the one or more measurement signals over the time period. After removing, the method includes analyzing changes in the one or more measurement signals from the one or more first sensors, wherein changes in the one or more measurement signals above a predetermined threshold or of a certain magnitude are indicative of a damaged bearing. Moreover, the method includes implementing a corrective action when the changes in the one or more measurement signals are above the predetermined threshold.

Systems and methods for detecting damage in rotary machines

Systems for examining a route inject one or more electrical examination signals into a conductive route from onboard a vehicle system traveling along the route, detect one or more electrical characteristics of the route based on the one or more electrical examination signals, and detect a break in conductivity of the route responsive to the one or more electrical characteristics decreasing by more than a designated drop threshold for a time period within a designated drop time period. Feature vectors may be determined for the electrical characteristics and compared to one or more patterns in order to distinguish between breaks in the conductivity of the route and other causes for changes in the electrical characteristics.

Route examining system

A method for evaluating performance of a wind turbine includes operating the wind turbine in a first operational mode. The method also includes generating a first set of operational data relating to the first operational mode. More specifically, the first set of operational data includes, at least, a first parameter and a second parameter. Further, the first and second parameters of the first set are measured during different time periods during the first operational mode. The method further includes changing the first operational mode to a second operational mode. Moreover, the method includes generating a second set of operational data relating to the second operational mode. The second set of operational data also includes, at least, a first parameter and a second parameter. Thus, the method includes determining a performance characteristic of the first and second operational modes based on the first and second sets of operational data.

Offset toggle method for wind turbine operation

A system that provides localized monitoring of characteristics of instrument gas that a valve assembly uses to modulate the flow of a working fluid. The system includes components that generate an output in response to, for example, particulates, humidity, temperature, and other characteristics of the instrument gas. Processing of data and information in the output can help to diagnose changes in the characteristics of the instrument gas. This diagnosis is useful to predict a time frame during which the valve assembly and components associated therewith might fail and/or require maintenance before the valve assembly manifests significant problem that are detrimental to a process line.

System and method to monitor characteristics of an operating fluid in a process line

A system receives a plurality of data samples associated with a control valve with each of the plurality of data samples associated with a setpoint and a position. A first subset of the data samples that are in a control zone associated with normal operation of the control valve is determined. In a case that a second subset of the data samples are determined to be (i) not in the first subset and (ii) close to a minimum position of the plurality of data samples and (iii) have setpoints less than their associated positions, an alert associated with a low obstruction is indicated. In a case that a second subset of the data samples are determined to be (i) not in the first subset and (ii) close to the maximum position of the plurality of data samples and (iii) have setpoint greater than their associated position, an alert is indicated.

Obstruction detection for a control valve

According to some embodiments, a signal processing unit may receive distributed acoustic sensing data associated with a first set of a plurality of pipeline locations. The signal processing unit may also receive collected physical data representing a physical characteristic of a second set of a plurality of pipeline locations. The signal processing unit may then utilize a pipeline model having the distributed acoustic sensing data and collected physical data as inputs to automatically generate at least one alert indicating an increased probability of damage to the pipeline.

Systems and methods to provide pipeline damage alerts

A method to detect cycling of components that result from use of a tight shut-off mode on a valve assembly. Embodiments of the method use operating data from the valve assembly. This operating data includes data that reflects a position for the closure member relative to the seat. This position often corresponds with a measured position of one or more components (e.g., the valve stem) on the valve assembly. In one embodiment, the method includes steps for comparing the measured position to a boundary criteria that defines one or more boundary values proximate, and often equal to, the threshold levels of the tight shut-off mode. The method can also includes steps for identifying patterns in the data that indicate that the closure member is cycling from its closed position to a second position due to tight shut-off mode.

Method for detecting an operating condition on a valve assembly and implementation thereof

A system to monitor a composite system component may include a plurality of sensors mounted proximate to the composite system component. A signal processing unit may receive, from each of the plurality of sensors, a series of sensed values associated with the composite system component and determine a kurtosis value for each series of sensed values. A threshold exceedance detector may detect if at least one of the kurtosis values exceeds a pre-determined threshold value. A delamination location estimation unit may calculate an estimated location of a composite system component delamination alert signal based on calculated time difference delay values of detected signal impulses in the series of sensed values using at least four of the plurality of sensors. A delamination alert output may then transmit a composite system component delamination alert signal, along with the estimated location, when at least one of the kurtosis values exceeds the pre-determined threshold.

System for sensing and locating delamination

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Niskayuna, NY, United States of America

Frederick Wilson Wheeler