The Boeing Company

Nile Hanov

James M Ethington

Liessman E Sturlaugson

Jason M Keller

In an example, a method for determining whether to perform aircraft maintenance is described. The method comprises selecting groupings of sensors and/or parameters associated with an aircraft type. The method comprises receiving feature data that corresponds to each grouping of sensors and/or parameters. The method comprises determining, from the feature data, values for predetermined operational metrics. The method comprises comparing the values to values for predetermined operational metrics that correspond to at least one other flight of the aircraft. The method comprises determining, based on comparing the values for the predetermined operational metrics, values of additional operational metrics. The method comprises training a machine learning model using at least the values for the additional operational metrics. The method comprises providing, based on an output of the machine learning model, an instruction to perform maintenance on one or more of the plurality of portions of the aircraft or another aircraft.

Methods and systems for performing aircraft maintenance

A vehicle maintenance scheduling and fault monitoring apparatus includes a vehicle system maintenance rules generation module and a vehicle system fault detection module. The rules generation module determines a correlation between pairs of precedent historical vehicle fault data, of historical time-stamped vehicle fault data, and a subsequent different historical vehicle fault data, and generates vehicle system maintenance rules based on the correlation determined for the pairs of the precedent historical vehicle fault data and the subsequent different historical vehicle fault data. The fault detection module monitors faults of the vehicle system, determines an imminent occurrence of a subsequent vehicle fault, based on application of the vehicle system maintenance rules to the plurality of time-stamped precedent vehicle fault data, and generates a maintenance report corresponding to the imminent occurrence of the subsequent vehicle fault so that proactive maintenance is performed on the vehicle system.

Apparatus and method for vehicle maintenance scheduling and fault monitoring

A vehicle health monitoring system including a rules generation module that receives historical time-stamped vehicle fault data for a vehicle system, determines a correlation between pairs of a precedent historical vehicle fault data, of the historical time-stamped vehicle fault data, and a subsequent different historical vehicle fault data, of the historical time-stamped vehicle fault data, and generates maintenance rules based on the correlation determined for the pairs. A fault detection module of the system monitors faults of the vehicle system, where the vehicle faults include a plurality of time-stamped precedent vehicle fault data, applies the rules to the plurality of time-stamped precedent vehicle fault data, determines an imminent occurrence of a subsequent vehicle fault, and generates a maintenance report corresponding to the imminent occurrence of the subsequent vehicle fault so that proactive maintenance is performed on the vehicle system.

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Huntington Beach, CA, United States of America

Nile Hanov