United States of America As Represented by the Administrator of Nasa

Battelle Memorial Institute

Thomas A Ferryman

Paul D Whitney

Brett Amidan

Robert E Lynch

Thomas R Chidester

Robert E Lawrence

Gary L Prothero

Timothy P Romanowski

Alan R Willse

Amanda M White

Daniel Edgar Robin

Scott K Cooley

Joseph Griffith Jay

Chris J Mosbrucker

Loren J Rosenthal

Adi Andrei

Jason W Prothero

Irving C Statler

James R Skorpik

Bary Wallace Wilson

Frank L Greitzer

Lars J Kangas

Don Simone Daly

Laurent Bloch

Kristine M Terrones

Melody A Maynard

Ronald A Pawlowski

Douglas A Drew

Robert J Ainsworth

William L Craine

Vincent J Zaccardi

A method and computer-based apparatus for monitoring the degradation of, predicting the remaining service life of, and/or planning maintenance for, an operating system are disclosed. Diagnostic information on degradation of the operating system is obtained through measurement of one or more performance characteristics by one or more sensors onboard and/or proximate the operating system. Though not required, it is preferred that the sensor data are validated to improve the accuracy and reliability of the service life predictions. The condition or degree of degradation of the operating system is presented to a user by way of one or more calculated, numeric degradation figures of merit that are trended against one or more independent variables using one or more mathematical techniques. Furthermore, more than one trendline and uncertainty interval may be generated for a given degradation figure of merit/independent variable data set. The trendline(s) and uncertainty interval(s) are subsequently compared to one or more degradation figure of merit thresholds to predict the remaining service life of the operating system. The present invention enables multiple mathematical approaches in determining which trendline(s) to use to provide the best estimate of the remaining service life.

Method and apparatus to predict the remaining service life of an operating system

Method and system for displaying information on one or more aircraft flights, where at least one flight is determined to have at least one atypical flight phase according to specified criteria. A flight parameter trace for an atypical phase is displayed and compared graphically with a group of traces, for the corresponding flight phase and corresponding flight parameter, for flights that do not manifest atypicality in that phase.

Information display system for atypical flight phase

Method and system for analyzing, separately or in combination, kinetic energy and potential energy and/or their time derivatives, measured or estimated or computed, for an aircraft in approach phase or in takeoff phase, to determine if the aircraft is or will be put in an anomalous configuration in order to join a stable approach path or takeoff path. A reference value of kinetic energy and/or potential energy (or time derivatives thereof) is provided, and a comparison index for the estimated energy and reference energy is computed and compared with a normal range of index values for a corresponding aircraft maneuver. If the computed energy index lies outside the normal index range, this phase of the aircraft is identified as anomalous, non-normal or potentially unstable.

Energy index for aircraft maneuvers

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis.

Identification of atypical flight patterns

According to the present invention, a conversion or representation of categorical data was created that allows a significant number of exploratory multivariate analysis methods to be brought to bear on categorical data. Whereas previously, each response to a question might have been modeled as an outcome from a multinomial probability distribution; according to the present invention each response is represented as an actual discrete probability distribution with all its mass in one cell. With this interpretation or conversion, the vector of measurements for each individual can be viewed as a member of the linear space that includes vectors of probability distributions.

Method for generating analyses of categorical data

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Richland, WA, United States of America

Thomas A Ferryman