This paper is concerned with the experimental validation of a structural health monitoring methodology, previously only investigated using synthetic data. The structure considered here is a simplified model of a metallic aircraft wingbox i.e., a plate incorporating stiffening elements. Damage is simulated by a saw-cut to one of the panel stringers (stiffeners). The analysis approach uses novelty detection based on measured transmissibilities from the structure. Three different novelty detection algorithms are considered here: outlier analysis, density estimation and an auto-associative neural network technique. All three methods ire shown to be successful to an extent, although a critical comparison indicates reservations about the density estimation approach when used on sparse data sets. (to be continued)
Experimental validation of a structural health monitoring methodology: Part 1. Novelty detection on a laboratory structure
Experimentelle Überprüfung einer Methode zur Strukturstabilitäts-Überwachung: Teil 1. Neuartige Detektionsmethode, angewandt auf eine Laborstruktur
Journal of Sound and Vibration ; 259 , 2 ; 323-343
2003
21 Seiten, 19 Bilder, 1 Tabelle, 19 Quellen
Article (Journal)
English
A Validation Methodology for Structural Health Monitoring
SAE Technical Papers | 2011
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