Vestas V90-3MW Wind Turbine Gearbox Health Assessment Using a Vibration-Based Condition Monitoring System
Joint Authors
Wang, Bin
Romero, A.
Lage, Y.
Soua, S.
Gan, T.-H.
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-20
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
Reliable monitoring for the early fault diagnosis of gearbox faults is of great concern for the wind industry.
This paper presents a novel approach for health condition monitoring (CM) and fault diagnosis in wind turbine gearboxes using vibration analysis.
This methodology is based on a machine learning algorithm that generates a baseline for the identification of deviations from the normal operation conditions of the turbine and the intrinsic characteristic-scale decomposition (ICD) method for fault type recognition.
Outliers picked up during the baseline stage are decomposed by the ICD method to obtain the product components which reveal the fault information.
The new methodology proposed for gear and bearing defect identification was validated by laboratory and field trials, comparing well with the methods reviewed in the literature.
American Psychological Association (APA)
Romero, A.& Lage, Y.& Soua, S.& Wang, Bin& Gan, T.-H.. 2016. Vestas V90-3MW Wind Turbine Gearbox Health Assessment Using a Vibration-Based Condition Monitoring System. Shock and Vibration،Vol. 2016, no. 2016, pp.1-18.
https://search.emarefa.net/detail/BIM-1119520
Modern Language Association (MLA)
Romero, A.…[et al.]. Vestas V90-3MW Wind Turbine Gearbox Health Assessment Using a Vibration-Based Condition Monitoring System. Shock and Vibration No. 2016 (2016), pp.1-18.
https://search.emarefa.net/detail/BIM-1119520
American Medical Association (AMA)
Romero, A.& Lage, Y.& Soua, S.& Wang, Bin& Gan, T.-H.. Vestas V90-3MW Wind Turbine Gearbox Health Assessment Using a Vibration-Based Condition Monitoring System. Shock and Vibration. 2016. Vol. 2016, no. 2016, pp.1-18.
https://search.emarefa.net/detail/BIM-1119520
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1119520