22 June 2000 Long-term stability of normal condition data for novelty detection
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Abstract
As a technique of diagnosing failure in structures and systems, the method of novelty detection shows considerable merit. The basis of the approach is simple: given measured data from normal condition of the structure, the diagnostic system builds an internal representation of the system normal condition in such a way that subsequent departures from this condition can be identified with confidence in a robust manner. The success or failure of the method is contingent on the accuracy of the description of normal condition. In many cases, the normal condition data may have quite a complex structure: for example, an aircraft may experience a wide range of ambient temperatures in the course of a single flight. Also, the operational loads experienced by the craft as a result of flight manoeuvres may have wide-ranging effects on the measured states. The object of the current paper is to explore the normal condition space for a simple benchmark monitoring system. The said system uses Lamb-wave inspection to diagnose damage in a composite plate. Both short-term and long-term experiments are carried out in order to examine the variations in normal condition as a result of run-in of the instrumentation and variations in ambient temperature. The exercise is not purely academic as the fiber-optic monitoring system is a serious candidate for a practical diagnostic system.
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Graeme Manson, S. Gareth Pierce, Keith Worden, Thomas Monnier, Philippe Guy, Kathryn Atherton, "Long-term stability of normal condition data for novelty detection", Proc. SPIE 3985, Smart Structures and Materials 2000: Smart Structures and Integrated Systems, (22 June 2000); doi: 10.1117/12.388835; https://doi.org/10.1117/12.388835
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