Failure Root Cause Determination Through the Aircraft Fault Messages Using Tree Augmented Naive Bayes and k-Nearest Neighbors

Paper #:
  • 2015-01-2592

Published:
  • 2015-09-15
DOI:
  • 10.4271/2015-01-2592
Citation:
Malere, J. and Olivares Loesch Vianna, W., "Failure Root Cause Determination Through the Aircraft Fault Messages Using Tree Augmented Naive Bayes and k-Nearest Neighbors," SAE Technical Paper 2015-01-2592, 2015, doi:10.4271/2015-01-2592.
Abstract:
This paper presents a method to determine the root cause of an aircraft component failure by means of the aircraft fault messages history. The k-Nearest Neighbors (k-NN) and the Tree-Augmented naive Bayes (TAN) methods were used in order to classify the failure causes as a function of the fault messages (predictors). The contribution of this work is to show how well the fault messages of aircraft systems can classify specific components failure modes. The training set contained the messages history from a fleet and the root causes of a butterfly valve reported by the maintenance stations. A cross-validation was performed in order to check the loss function value and to compare both methods performance. It is possible to see that the use of just fault messages for the valve failure classification provides results that close to 2/3 and could be used for faster troubleshooting procedures.
Access
Now
SAE MOBILUS Subscriber? You may already have access.
Buy
Select
Price
List
Download
$27.00
Mail
$27.00
Members save up to 40% off list price.
Share
HTML for Linking to Page
Page URL

Related Items

Technical Paper / Journal Article
2004-09-21
Book
2003-12-17
Article
2016-12-08