Patents by Inventor Joshua Luke Wiedemann

Joshua Luke Wiedemann has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • System and method of forecasting aircraft engine operational data for predictive analytics
    Patent number: 11952149
    Abstract: Systems and methods for forecasting aircraft engine operational data are provided. The forecasted data can be used for use with predictive analytics, for example. In one aspect, a method is provided. The method includes receiving engine data associated with an engine. The engine data includes data points for various operational parameters. The method further includes determining forecasted data points for the operational parameters. The forecasted data points for a given one of the operational parameters are determined by applying one or more regression techniques to the data points associated with the given one of the operational parameters. The forecasted data points can be input into various types of models, such as a cumulative damage model. For instance, using the forecasted data points, a cumulative damage model can generate a plurality of forecasts and can output a cumulative probability distribution.
    Type: Grant
    Filed: September 17, 2020
    Date of Patent: April 9, 2024
    Assignee: General Electric Company
    Inventors: Joshua Luke Wiedemann, Craig Miller Kuhne
  • SYSTEM AND METHOD OF FORECASTING AIRCRAFT ENGINE OPERATIONAL DATA FOR PREDICTIVE ANALYTICS
    Publication number: 20220081129
    Abstract: Systems and methods for forecasting aircraft engine operational data are provided. The forecasted data can be used for use with predictive analytics, for example. In one aspect, a method is provided. The method includes receiving engine data associated with an engine. The engine data includes data points for various operational parameters. The method further includes determining forecasted data points for the operational parameters. The forecasted data points for a given one of the operational parameters are determined by applying one or more regression techniques to the data points associated with the given one of the operational parameters. The forecasted data points can be input into various types of models, such as a cumulative damage model. For instance, using the forecasted data points, a cumulative damage model can generate a plurality of forecasts and can output a cumulative probability distribution.
    Type: Application
    Filed: September 17, 2020
    Publication date: March 17, 2022
    Inventors: Joshua Luke Wiedemann, Craig Miller Kuhne