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Spatial scanning for anomaly detection in acoustic emission testing of an aerospace structure

Hensman, J., Worden, K., Eaton, Mark Jonathan, Pullin, Rhys, Holford, Karen Margaret and Evans, Samuel Lewin 2011. Spatial scanning for anomaly detection in acoustic emission testing of an aerospace structure. Mechanical Systems and Signal Processing 25 (7) , pp. 2462-2474. 10.1016/j.ymssp.2011.02.016

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Abstract

Acoustic emission (AE) monitoring of engineering structures potentially provides a convenient, cost-effective means of performing structural health monitoring. Networks of AE sensors can be easily and unobtrusively installed upon structures, giving the ability to detect and locate damage-related strain releases (‘events’) in the structure. Use of the technique is not widespread due to the lack of a simple and effective method for detecting abnormal activity levels: the sensitivity of AE sensor networks is such that events unrelated to damage are prevalent in most applications. In this publication, we propose to monitor AE activity in a structure using a spatial scanning statistic, developed and used effectively in the field of epidemiology. The technique is demonstrated on an aerospace structure – an Airbus A320 main landing gear fitting – undergoing fatigue loading, and the method is compared to existing techniques. Despite its simplicity, the scanning statistic proves to be an extremely effective tool in detecting the onset of damage in the structure: it requires little to no user intervention or expertise, is inexpensive to compute and has an easily interpretable output. Furthermore, the generic nature of the method allows the technique to be used in a variety of monitoring scenarios, to detect damage in a wide range of structures.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics
Uncontrolled Keywords: Spatial scanning statistics; Acoustic emission; Fracture detection; Damage identification; Damage localisation
Publisher: Elsevier
ISSN: 0888-3270
Last Modified: 03 Oct 2019 00:39
URI: http://orca.cf.ac.uk/id/eprint/8250

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