March 5, 1999

Sylvain Létourneau
School of Information Technology and Engineering
University of Ottawa, Ottawa

Machine Learning For Prediction of Aircraft Component Failure

The operation and maintenance of modern sensor-equipped systems such as aircraft generate vast amounts of numerical and symbolic data. Learning models from this data to predict component failures may lead to saving of several thousands of dollars, reducing the number of delays, and increasing the overall level of safety. Several data mining techniques exist to learn models from vast amounts of data. However, the use of these techniques to infer the desired models from the data obtained during the operation and maintenance of aircraft is extremely challenging. Difficulties that need to be addressed include: data selection, data labeling, data and models integration, and evaluation. In this talk, I'll present solutions we have developed for these problems and discuss results obtained for different aircraft components.

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