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An evidence-based approach to damage location on an aircraft structure

By K. Worden, G. Manson and Thierry Denoeux

Abstract

International audienceThis paper discusses the use of evidence-based classifiers for the identification of damage. In particular, a neural network approach to Dempster-Shafer theory is demonstrated on the damage location problem for an aircraft wing. The results are compared with a probabilistic classifier based on a multi-layer perceptron neural network and shown to give similar results. The question of fusing classifiers is considered and it is shown that a combination of the Dempster-Shafer and MLP classifiers gives a significant improvement over the use of individual classifiers for the aircraft wing data

Topics: Dempster–Schafer theory, Structural health monitoring, Damage location, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Publisher: Elsevier
Year: 2009
DOI identifier: 10.1016/j.ymssp.2008.11.003
OAI identifier: oai:HAL:hal-00450962v1
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