Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/31478
Title: Poincaré plot features from vibration signal for gearbox fault diagnosis
Authors: Alvarez Palomeque, Lourdes Ximena
Jadan Aviles, Diana Carolina
Cerrada Lozada, Mariela
Sánchez, René Vinicio
Macancela Poveda, Jean Carlo
Keywords: Gearbox faults classification
Multi-class Support Vector Machines
Poincare plots
Rotatory machines
Issue Date: 2018
metadata.dc.ucuenca.embargoend: 28-Dec-2050
Publisher: Institute of Electrical and Electronics Engineers Inc.
metadata.dc.description.city: 
Salinas
metadata.dc.type: ARTÍCULO DE CONFERENCIA
Abstract: 
This paper describes a method for fault diagnosis in gearboxes using features extracted from the Poincare plot of the vibration signal. Several features describing the geometrical shape of the Poincare plot are calculated and three of these features are selected for performing the classification of 10 types of faults recorded in the gearbox vibration signal dataset. A multi-class Error-Correcting Output Code Support Vector Machine is trained for performing the classification of faults. The cross-validation performed show that the highest accuracy attained is 95.3% when signals recorded using the load L1 are considered.
Description: 
This paper describes a method for fault diagnosis in gearboxes using features extracted from the Poincare plot of the vibration signal. Several features describing the geometrical shape of the Poincare plot are calculated and three of these features are selected for performing the classification of 10 types of faults recorded in the gearbox vibration signal dataset. A multi-class Error-Correcting Output Code Support Vector Machine is trained for performing the classification of faults. The cross-validation performed show that the highest accuracy attained is 95.3% when signals recorded using the load L1 are considered.
URI: http://dspace.ucuenca.edu.ec/handle/123456789/31478
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85045739957&origin=inward
ISBN: 978-153863894-1
ISSN: 0000-0000
Appears in Collections:Artículos

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