Rule extraction for classification of acoustic emission signals using Ant Colony Optimisation

Omkar, SN and Raghavendra, Karanth U (2008) Rule extraction for classification of acoustic emission signals using Ant Colony Optimisation. In: Engineering Applications of Artificial Intelligence, 21 (8). pp. 1381-1388.

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Abstract

Ant Colony Optimization (ACO) is used to obtain rules that can classify the data into pre-defined classes. It can be used to classify acoustic emission (AE) signals to their respective sources. ACO based technique has an advantage over conventional statistical techniques like maximum likelihood estimate, nearest neighbor classifier, etc., because they are distribution free, i.e., no knowledge is required about the distribution of data. AE test is carried Out using pulse, pencil and spark signal source on the surface of solid steel block. The signal parameters are measured using AET 5000 system. Classification of AE signal is done using Ant Colony Optimization, and the simplicity of the rules generated is emphasized.

Item Type:	Journal Article
Publication:	Engineering Applications of Artificial Intelligence
Publisher:	Elsevier Science
Additional Information:	Copyright of this article belongs to Elsevier Science.
Keywords:	Acoustic emission;Swarm Intelligence;ACO; Rule extraction;Classification matrix.
Department/Centre:	Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited:	04 Nov 2009 08:28
Last Modified:	19 Sep 2010 04:58
URI:	http://eprints.iisc.ac.in/id/eprint/17843

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