ANT-BASED SEARCH STRATEGY FOR INDUSTRIAL MULTIPLE-FAULT DIAGNOSTICS

Pasquale Arpaia, Carlo Manna, Giuseppe Montenero

Abstract

A swarm-intelligence solution to industrial problems of automatic multiple-faults diagnostics is proposed. In particular, drawbacks of swarm-based algorithms in heuristic search strategy related to the mutual dependence of solutions are overcome by a likelihood-based trail intensity modification of ant-colony optimization. Experimental results of comparison tests with an evolutionary state-of-the-art solution of a case study on an advanced industrial system for remote monitoring, diagnostics, and maintenance are reported.

Keywords

artificial intelligence, industrial diagnostics, multiple faults diagnosis

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IMEKO-WC-2009-TC4-558.pdf

DOI

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IMEKO TC

TC4 - Measurement of Electrical Quantities

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