Abstract
Advanced Feature Selection for Simplified Pattern Recognition within the Damage Identification Framework
Highlights
There has been considerable success in recent years in considering the problem of damage identification as one of pattern recognition
The first author was involved in a body of research, funded by DERA/QinetiQ [1,2,3,4], on Structural Health Monitoring (SHM) which proposed a health monitoring system based upon novelty detection techniques
The first two parts [1,2] of the earlier work were concerned with experimental validation of novelty detection techniques to carry out the first level of health monitoring on a simulated stiffened skin panel and on the wing of a Gnat aircraft
Summary
There has been considerable success in recent years in considering the problem of damage identification as one of pattern recognition. The first two parts [1,2] of the earlier work were concerned with experimental validation of novelty detection techniques to carry out the first level of health monitoring on a simulated stiffened skin panel and on the wing of a Gnat aircraft. Both these investigations met with a large degree of success. The two parts [3,4] extended these techniques to levels 2 and 3 in the damage hierarchy, respectively These were conducted on the wing of the Gnat aircraft. Reference [4] extended this work to damage assessment by using a neural network classifier, in conjunction with
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