Optimizing the number of acoustic emission sensors using the bees algorithm for detecting surface fractures

Packianather, Michael S. ORCID: https://orcid.org/0000-0002-9436-8206, Eaton, Mark ORCID: https://orcid.org/0000-0002-7388-6522, Papadopoulos, Ioannis and Alexopoulos, Theocharis 2018. Optimizing the number of acoustic emission sensors using the bees algorithm for detecting surface fractures. Procedia CIRP 67 , pp. 362-367. 10.1016/j.procir.2017.12.227

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Abstract

Non-destructive testing methods have gained popularity as they become more widely available. Although there are several techniques that could be used for this purpose, this paper focuses on acoustic emission sensors for detecting surface fractures and the use of the Bees Algorithm, a swarm-based technique, for optimizing the number of sensors required to reliably detect surface fractures. The paper describes the approach that has been used in this study where the dimension of the surface is specified by the user. The results show that, in theory and through simulation, that the Bees Algorithm is capable of determining the minimum number of sensors needed to locate the surface fracture with an acceptable level of accuracy. The method described could be used for the purpose of optimization in other engineering as well as non-engineering applications.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Elsevier
ISSN:	2212-8271
Date of First Compliant Deposit:	19 March 2019
Last Modified:	05 May 2023 07:05
URI:	https://orca.cardiff.ac.uk/id/eprint/120401

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