Maintenance computing system and method for aircraft with predictive classifier

A maintenance computing method, comprising:

• executing an inspection classifier using a processor and associated memory, the inspection classifier including at least a first artificial intelligence model, executing the inspection classifier including:
• receiving run-time event input data from a plurality of data sources associated with a vehicle, the data sources including structural health monitoring sensors instrumented on the vehicle;
• extracting features of the run-time event input data;
• determining a predicted inspection classification based upon the extracted features, the predicted inspection classification being one of a plurality of candidate inspection classifications;
• outputting the predicted inspection classification;
• receiving user input of an adopted inspection classification for the run-time event input data;
• and
• performing feedback training of the first artificial intelligence model using the run-time event input data and the adopted inspection classification as a feedback training data pair.

A maintenance computing system, comprising:

• a processor and a non-volatile memory storing executable instructions that, in response to execution by the processor, cause the processor to:
• execute an inspection classifier configured to determine a predicted inspection classification based on run-time event input data from structural health monitoring sensors instrumented on a vehicle;
• output the predicted inspection classification;
• receiving user input of an adopted inspection classification for the run-time event input data;
• performing feedback training of the inspection classifier using the run-time event input data and the adopted inspection classification as a feedback training data pair;
• execute a repair classifier to determine a predicted repair classification based upon run-time inspection input data including inspection-associated input data and the adopted inspection classification;
• output the predicted repair classification;
• receive user input of an adopted repair classification for the run-time inspection input data;
• and
• perform feedback training of the repair classifier using the run-time inspection input data and the adopted repair classification as a feedback training data pair.