Abstract

A new algorithm for assessment of Engine Health Monitoring (EHM) data in aircraft is proposed. The diagnostic tool quantifies step changes, shifts and trends in EHM data by means of a transformation that aggregates concurrent readings of EHM data into a single fuzzy state. A Genetic Fuzzy System is used to detect the occurance of a specific trend of interest in the sequence of states. The activation of the rules is represented in a 2D map by means of an extension of the Radviz visualization algorithm to fuzzy data.

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