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EXPERIMENTAL VALIDATION OF A STRUCTURAL HEALTH MONITORING METHODOLOGY: PART I. NOVELTY DETECTION ON A LABORATORY STRUCTURE

โœ Scribed by K. WORDEN; G. MANSON; D. ALLMAN

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
420 KB
Volume
259
Category
Article
ISSN
0022-460X

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โœฆ Synopsis

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 are shown to be successful to an extent, although a critical comparison indicates reservations about the density estimation approach when used on sparse data sets.

๐Ÿ“œ SIMILAR VOLUMES

EXPERIMENTAL VALIDATION OF A STRUCTURAL
EXPERIMENTAL VALIDATION OF A STRUCTURAL HEALTH MONITORING METHODOLOGY: PART II. NOVELTY DETECTION ON A GNAT AIRCRAFT
โœ G. MANSON; K. WORDEN; D. ALLMAN ๐Ÿ“‚ Article ๐Ÿ“… 2003 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 509 KB

This paper concerns the second phase of an experimental validation programme for a structural health monitoring methodology based on novelty detection. This phase seeks to apply one of the methods considered in the first stage of the work on a more realistic structure, namely the wing of a Gnat airc