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A neural network approach for remaining useful life prediction utilizing both failure and suspension histories

Author
ZHIGANG TIAN1 ; WONG, Lorna2 ; SAFAEI, Nima2
[1] Concordia Institute for Information Systems Engineering, Concordia University, 1515 Ste-Catherine Street, West EV-7.637, Montreal, Quebec,H3 G 2W1, Canada
[2] Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto,M5S 3G8, Canada
Source

Mechanical systems and signal processing. 2010, Vol 24, Num 5, pp 1542-1555, 14 p ; ref : 26 ref

ISSN
0888-3270
Scientific domain
Control theory, operational research; Mechanics acoustics
Publisher
Elsevier, Kidlington
Publication country
United Kingdom
Document type
Article
Language
English
Author keyword
Artificial neural networks Bearing Prediction Remaining useful life Suspension history
Keyword (fr)
Durabilité Modélisation Monitorage Palier Pompe Rupture Réseau neuronal Traitement signal
Keyword (en)
Durability Modeling Monitoring Bearing(mechanics) Pump Rupture Neural network Signal processing
Keyword (es)
Durabilidad Modelización Monitoreo Descansillo Bomba Ruptura Red neuronal Procesamiento señal
Classification
Pascal
001 Exact sciences and technology / 001B Physics / 001B40 Fundamental areas of phenomenology (including applications) / 001B40F Solid mechanics / 001B40F30 Structural and continuum mechanics / 001B40F30N Fracture mechanics (crack, fatigue, damage...)

Pascal
001 Exact sciences and technology / 001B Physics / 001B40 Fundamental areas of phenomenology (including applications) / 001B40F Solid mechanics / 001B40F30 Structural and continuum mechanics / 001B40F30R Measurement and testing methods

Discipline
Physics : solid mechanics
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
22879387

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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