General Electric Company

Katherine Tharp Nowicki

Michael William Bailey

Michael Evans Graham

Mustafa Tekin Dokucu

Brock Estel Osborn

Aditya Kumar

Gregory Jon Chiaramonte

Victor Manuel Perez Zarate

Steven Richard Levin

Donald Horn

Mei Gao

Vivek Gandhi

Ronald Plybon

Luis Gabriel De Alba Rivera

William Edwin Hurst

Ronald Cileman Plybon

Donald J Horn

Methods, apparatus, systems, and articles of manufacture are disclosed to perform prognostic health monitoring of a turbine engine. An example apparatus includes a health quantifier calculator to execute a computer-generated model to generate first sensor data of a turbine engine, the first sensor data based on simulating a sensor monitoring the turbine engine using asset monitoring information, a parameter tracker to execute a tracking filter using the first sensor data and second sensor data to generate third sensor data corresponding to the turbine engine, the second sensor data based on obtaining sensor data from a sensor monitoring the turbine engine, the third sensor data based on comparing the first sensor data to the second sensor data, the health quantifier calculator to execute the computer-generated model using the third sensor data to generate an asset health quantifier of the turbine engine; and a report generator to generate a report including the asset health quantifier and a workscope recommendation based on the asset health quantifier when the asset health quantifier satisfies a threshold.

Methods and apparatus for prognostic health monitoring of a turbine engine

Methods, apparatus, systems and articles of manufacture are disclosed to generate a workscope. An example apparatus includes a workscope mapper, workscope strategy analyzer, and workscope selector. The workscope strategy analyzer is to evaluate each of the plurality of workscopes using dynamic optimization to determine a maintenance value and benefit to an asset associated with each workscope based on a stage in a remaining life of a constraint at which the evaluation is executed and a state of the asset. The dynamic optimization is to determine a prediction of the maintenance value based on a probability of a future change in state and associated workscope value until the end of life of the constraint. The maintenance value, used to select a workscope from the plurality of workscopes, is to be determined by the dynamic optimization as a sum of the associated workscope values until the end of life of the constraint.

Methods and apparatus to generate an optimized workscope

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Cincinnati, OH, United States of America

Katherine Tharp Nowicki