Caterpillar Inc.

Solar Turbines Inc.

Michael Seskin

Anthony James Grichnik

Amit Jayachandran

Mary Lou Kesse

James Mason

Wade S Willden

Evan Earl Jacobson

Stephan Donald Roozenboom

Timothy Joe Felty

David M Milam

Burton Roland Clarke

Roy Thomas Collins

Kevin C Brady

Andrea Brazzale-Anderson

Amar Patel

Marco Perez

Kermit H Dove, Jr

Brian Lee Boggs

Danny L Weis

A method is provided for a virtual sensor system. The method may include obtaining data records associated with a plurality of input parameters and at least one output parameter and adjusting values of the input parameters based on autocorrelation of respective input parameters. The method may also include reconfiguring the input parameters based on cross-correlation of respective input parameters relative to the output parameter and establishing a first virtual sensor process model indicative of interrelationships between the adjusted and reconfigured input parameters and the output parameter.

Virtual sensor based engine control system and method

A method is provided for model optimization. The method may include obtaining respective distribution descriptions of a plurality of input parameters to a model indicative of interrelationships between the input parameters and one or more output parameters. The method may also include specifying respective search ranges for the plurality of input parameters and simulating the model to determine a desired set of input parameters based on a zeta statistic of the model. Further, the method may include determining respective desired distributions of the input parameters based on the desired set of input parameters; determining significance levels of the input parameters in interacting with the output parameter based on the simulation and the desired distributions of the input parameters; and presenting the significance levels.

Process modeling and optimization method and system

A method is provided for designing a product. The method may include obtaining data records relating to one or more input variables and one or more output parameters associated with the product and selecting one or more input parameters from the one or more input variables. The method may also include generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records and providing a set of constraints to the computational model representative of a compliance state for the product. Further the method may include using the computational model and the provided set of constraints to generate statistical distributions for the one or more output parameters. The one or more input parameters and the one or more output parameters represent a design for the product.

Asymmetric random scatter process for probabilistic modeling system for product design

A method for modifying data coverage in a modeling system is disclosed. The method may include obtaining data records relating to a plurality of input variables and one or more output parameters and selecting a plurality of input parameters from the plurality of input variables. The method may further include evaluating a coverage of the data records in a modeling space and modifying the coverage of the data records, if a data coverage condition is detected. The method may also include generating a computational model indicative of interrelationships between the plurality of input parameters and the one or more output parameters based on the data records.

System and method for improving data coverage in modeling systems

A computer-implemented method is provided for determining a corrective action. The method may include obtaining diagnostic data and calculating, using the diagnostic data, a prognostic. The method may also include retrieving, when the prognostic is above an alarm level, historical records and calculating a Bayesian posterior probability using the diagnostic data and the historical records. Further, the method may include calculating a prognostic prescience metric using the diagnostic data and the historical records and determining, based on the Bayesian posterior probability, the prognostic prescience metric, and an economic calculation, the corrective action.

Determining a corrective action based on economic calculation

A method of correlating thermal sensors data with temperature sensor data is disclosed. The method may include generating one or more temperature sensor data points and receiving the one or more temperature sensor data points at a remote location. The method may also include generating one or more thermal sensor data points or images and receiving the one or more thermal sensor data points or images at the remote location. Additionally, the method may include correlating the one or more thermal sensor data points or images based on the one or more temperature sensor data points and generating a notification when a temperature of one or more correlated thermal sensor data points or images fails to maintain a determined relationship with a preset limit in one or more locations other than the location of one or more temperature sensor data point.

Health monitoring through a correlation of thermal images and temperature data

A method is provided for designing a product. The method may include obtaining data records relating to one or more input variables and one or more output parameters associated with the product and selecting one or more input parameters from the one or more input variables. The method may also include generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records and providing a set of constraints to the computational model representative of a compliance state for the product. Further the method may include using the computational model and the provided set of constraints to generate statistical distributions for the one or more input parameters based on a symmetric random scatter process and the one or more output parameters. The one or more input parameters and the one or more output parameters represent a design for the product.

Symmetric random scatter process for probabilistic modeling system for product design

A method is provided for designing a product. The method may include obtaining data records relating to one or more input variables and one or more output parameters associated with the product; and pre-processing the data records based on characteristics of the input variables. The method may also include selecting one or more input parameters from the one or more input variables; and generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records. Further, the method may include providing a set of constraints to the computational model representative of a compliance state for the product; and using the computational model and the provided set of constraints to generate statistical distributions for the one or more input parameters and the one or more output parameters, wherein the one or more input parameters and the one or more output parameters represent a design for the product.

Probabilistic modeling system for product design

A prediction based engine control system is disclosed. The engine control system may have sensor configured to sense a current engine operation and generate a corresponding signal and a controller in communication with the sensor. The controller may be configured to receive the signal, compare the current engine operation to an allowable range of engine operation, predict a future engine operation based on the signal, and limit current engine operation based on the prediction, even when the current engine operation is within the allowable range of operation.

Prediction based engine control system and method

A method is provided for developing a product. The method includes obtaining data records from a plurality of stages of development of the product; identifying respective objectives of the plurality of stages and corresponding objective factors of the objectives; and determining common variables associated with the objectives based on the objective factors. The method includes selecting one or more input parameters based on the common variables and one or more output parameters based on the objectives; and updating the data records to generate desired data records indicative characteristics of the one or more input parameters and the one or more output parameters. The method includes generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records; and providing a set of constraints to the computational model representative of a design of the product.

Product design optimization method and system

A method is provide for providing sensors for a machine. The method may include obtaining data records including data from a plurality of sensors for the machine and determining a virtual sensor corresponding to one of the plurality of sensors. The method may also include establishing a virtual sensor process model of the virtual sensor indicative of interrelationships between at least one sensing parameters and a plurality of measured parameters based on the data records and obtaining a set of values corresponding to the plurality of measured parameters. Further, the method may include calculating the values of the at least one sensing parameters substantially simultaneously based upon the set of values corresponding to the plurality of measured parameters and the virtual sensor process model and providing the values of the at least one sensing parameters to a control system.

Virtual sensor system and method

A method is provided for a control system. The method may include obtaining data records associated one or more input variables and one or more output parameters, and selecting one or more input parameters from the one or more input variables. The method may also include generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records, and determining desired respective statistical distributions of the one or more input parameters of the computational model.

Control system and method

A method for a virtual sensor system corresponding to a target physical sensor is provided. The method may include selecting a plurality of measured parameters provided by a set of physical sensors based on operational characteristics of the virtual sensor system. The method may also include establishing a virtual sensor process model indicative of interrelationships between one or more sensing parameter and the plurality of measured parameters. Further the method may include obtaining a set of values corresponding to the plurality of measured parameters; calculating a value of the sensing parameter based upon the set of values corresponding to the plurality of measured parameters and the virtual sensor process model; and providing the value of the sensing parameter to a control system.

Virtual sensor based control system and method

A method for diagnosing a system is provided. The method may include obtaining a plurality of input parameters from the system. The system may generate actual values of one or more output parameters based on the plurality of input parameters. The method may also include independently deriving values of the one or more output parameters, based on the plurality of input parameters, using a computational model, and detecting a divergence between the derived values and the actual values. Further, the method may include identifying respective desired statistic distributions of the plurality of input parameters, based on the actual values of the one or more output parameters, using the computational model.

Diagnostic and prognostic method and system

A method is provided for a virtual sensor system. The method may include establishing a virtual sensor process model indicative of interrelationships between a plurality of sensing parameters and a plurality of measured parameters, and obtaining a set of values corresponding to the plurality of measured parameters. The method may also include calculating the values of the plurality of sensing parameters simultaneously based upon the set of values corresponding to the plurality of measured parameters and the virtual sensor process model, and providing the values of the plurality of sensing parameters to a control system.

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Cardiff, CA, United States of America

Michael Seskin