Engine Health Monitoring for engine fleets using fuzzy radviz

Author
A. Martínez
L. Sánchez
I. Couso
Palabras clave
2D map
aerospace engineering
aerospace engines
aircraft
Bandwidth
condition monitoring
data visualisation
diagnostic tool
EHM data
engine fleets
engine health monitoring
Engines
fault diagnosis
fuzzy data
fuzzy Radviz
fuzzy set theory
genetic algorithms
genetic fuzzy system
Genetic Fuzzy Systems
Low Quality Data
Maintenance engineering
Market research
mechanical engineering computing
Monitoring
Radviz visualization algorithm
rule activation
single fuzzy state
states sequence
Temperature measurement
Turbines
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.
Year of Publication
2013
Date Published
July
DOI
10.1109/FUZZ-IEEE.2013.6622420
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Number of Pages
1-8