Misalignment identification in induction motors using orbital pattern analysis

José Juan Carbajal-Hernández, Luis Pastor Sańchez-Fernández, Victor Manuel Landassuri-Moreno, José Jesús De Medel-Juárez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Induction motors are the most common engine used worldwide. When they are summited to extensive working journals, e.g. in industry, faults may appear, generating a performance reduction on them. Several works have been focused on detecting early mechanical and electrical faults before damage appears in the motor. However, the main drawback of them is the complexity on the motor's signal mathematical processing. In this paper, a new methodology is proposed for detecting misalignment faults in induction motors. Through signal vibration and orbital analysis, misalignment faults are studied, generating characteristically patterns that are used for fault identification. Artificial Neural Networks are evolved with an evolutionary algorithm for misalignment pattern recognition, using two databases (training and recovering respectively). The results obtained, indicate a good performance of Artificial Neural Networks with low confusion rates, using experimental patterns obtained from real situations where motors present a certain level of misalignment. © Springer-Verlag 2013.
Original languageAmerican English
Title of host publicationMisalignment identification in induction motors using orbital pattern analysis
Pages50-58
Number of pages44
ISBN (Electronic)9783642418266
DOIs
StatePublished - 1 Dec 2013
EventLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duration: 1 Jan 2014 → …

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8259 LNCS
ISSN (Print)0302-9743

Conference

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Period1/01/14 → …

Fingerprint

Pattern Analysis
Induction Motor
Misalignment
Induction motors
Fault
Neural networks
Artificial Neural Network
Fault Identification
Evolutionary algorithms
Pattern recognition
Vibration Signal
Pattern Recognition
Engines
Evolutionary Algorithms
Engine
Damage
Industry
Processing
Methodology

Cite this

Carbajal-Hernández, J. J., Sańchez-Fernández, L. P., Landassuri-Moreno, V. M., & De Medel-Juárez, J. J. (2013). Misalignment identification in induction motors using orbital pattern analysis. In Misalignment identification in induction motors using orbital pattern analysis (pp. 50-58). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8259 LNCS). https://doi.org/10.1007/978-3-642-41827-3_7
Carbajal-Hernández, José Juan ; Sańchez-Fernández, Luis Pastor ; Landassuri-Moreno, Victor Manuel ; De Medel-Juárez, José Jesús. / Misalignment identification in induction motors using orbital pattern analysis. Misalignment identification in induction motors using orbital pattern analysis. 2013. pp. 50-58 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Carbajal-Hernández, JJ, Sańchez-Fernández, LP, Landassuri-Moreno, VM & De Medel-Juárez, JJ 2013, Misalignment identification in induction motors using orbital pattern analysis. in Misalignment identification in induction motors using orbital pattern analysis. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8259 LNCS, pp. 50-58, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1/01/14. https://doi.org/10.1007/978-3-642-41827-3_7

Misalignment identification in induction motors using orbital pattern analysis. / Carbajal-Hernández, José Juan; Sańchez-Fernández, Luis Pastor; Landassuri-Moreno, Victor Manuel; De Medel-Juárez, José Jesús.

Misalignment identification in induction motors using orbital pattern analysis. 2013. p. 50-58 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8259 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Carbajal-Hernández JJ, Sańchez-Fernández LP, Landassuri-Moreno VM, De Medel-Juárez JJ. Misalignment identification in induction motors using orbital pattern analysis. In Misalignment identification in induction motors using orbital pattern analysis. 2013. p. 50-58. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-41827-3_7