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Memorias de investigación
Artículos en revistas:
GEAR DYNAMICS MONITORING USING DISCRETE WAVELET TRANSFORMATION AND MULTI-LAYER PERCEPTRON NEURAL NETWORKS
Año:2012
Áreas de investigación
  • Ingenierías
Datos
Descripción
This paper presents a multi-stage algorithm for the dynamic condition monitoring of a gear. The algorithm provides information referred to the gear status (fault or normal condition) and estimates the mesh stiffness per shaft revolution in case that any abnormality is detected. In the first stage, the analysis of coefficients generated through discrete wavelet transformation (DWT) is proposed as a fault detection and localization tool. The second stage consists in establishing the mesh stiffness reduction associated with local failures by applying a supervised learning mode and coupled with analytical models. To do this, a multi-layer perceptron neural network has been configured using as input features statistical parameters sensitive to torsional stiffness decrease and derived from wavelet transforms of the response signal. The proposed method is applied to the gear condition monitoring and results show that it can update the mesh dynamic properties of the gear on line.
Internacional
Si
JCR del ISI
Si
Título de la revista
Applied Soft Computing
ISSN
1568-4946
Factor de impacto JCR
2,14
Información de impacto
Volumen
12
DOI
http://dx.doi.org/10.1016/j.asoc.2012.04.003
Número de revista
Desde la página
2867
Hasta la página
2878
Mes
SIN MES
Ranking
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 115 / 23 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 100 / 18 Q1
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: JAVIER SANZ CORRETGE (ACCIONA WINDPOWER)
  • Autor: Ricardo Perera Velamazan (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Mecánica Estructural y Construcciones Industriales
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