US Patent Application 18366294. METHODS AND SYSTEMS FOR INFERRED INFORMATION PROPAGATION FOR AIRCRAFT PROGNOSTICS simplified abstract
METHODS AND SYSTEMS FOR INFERRED INFORMATION PROPAGATION FOR AIRCRAFT PROGNOSTICS
Organization Name
Inventor(s)
Charles Eugene Martin of Westlake Village CA (US)
Tsai-Ching Lu of Thousand Oaks CA (US)
Steve Slaughter of Scottsdale AZ (US)
Alice A. Murphy of Mesa AZ (US)
METHODS AND SYSTEMS FOR INFERRED INFORMATION PROPAGATION FOR AIRCRAFT PROGNOSTICS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18366294 titled 'METHODS AND SYSTEMS FOR INFERRED INFORMATION PROPAGATION FOR AIRCRAFT PROGNOSTICS
Simplified Explanation
The patent application describes a method and system for analyzing data from aircraft components to identify potential issues before they occur.
- The method involves dividing the data into subsets using a time-window and calculating Mutual Information (MI) values for each pair of variables within each subset.
- Relationship graphs are then constructed using the MI values, and these graphs are clustered to group similar relationships together.
- The time-ordered sequence of clustered relationship graphs is analyzed to identify features or patterns in the component that may indicate potential problems.
Original Abstract Submitted
Methods and systems are provided for inferred information propagation for aircraft prognostics. The method includes receiving, by a processor, an original time-series of data points for a component as an input; preprocessing the input to divide the original time-series of data into subsets of data by applying a time-window over the original time-series of data points; and computing, by the processor, a Mutual Information (MI) value for each pair of variables within each subset of data. The method also includes constructing, by the processor, a sequence of relationship graphs using the computed MI values; clustering, by the processor, each relationship graph; and analyzing, by the processor, the time-ordered sequence of clustered relationship graphs to identify features in the component.
