Application of Some Artificial Intelligence Techniques in Induction Motor Fault Diagnosis

Autor:	Edison R. C. da Silva, Hubert Razik, Lane M. R. Baccarini, Maurício B. de R. Corrêa, Cursino B. Jacobina
Jazyk:	English<br />Portuguese
Rok vydání:	2011
Předmět:	Artificial Intelligence Methods Diagnosis Technique Induction Motor Fault Diagnosis Electrical engineering. Electronics. Nuclear engineering TK1-9971
Zdroj:	Eletrônica de Potência, Vol 16, Iss 3 (2011)
Druh dokumentu:	article
ISSN:	1414-8862 1984-557X
DOI:	10.18618/REP.20113.241248
Popis:	In spite of the advantages of the use of the induction motor in a large number industrial applications, various stresses natures like thermal, electrical, mechanical or environmental could affect the life span of this induction motor drive. In recent years, monitoring and fault detection of electrical machines have moved from traditional techniques to artificial intelligence techniques. This paper gives examples of application of nine AI techniques already applied to induction motor fault diagnosis: neural networks, fuzzy logic, neural-fuzzy, genetic algorithms, vector support machine, particle swarm optimization, artificial immune system and gaussian bootstrap process. Functions that can be accomplished by them are highlighted.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/f90b6afa76c6452084358bc56a8cc400 Zobrazit plný text záznamu View record in DOAJ