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Bearing temperature monitoring of a Wind Turbine using physics-based model

Philippe Cambron (Ecole de technologie superieure, Montreal, Canada)
Antoine Tahan (Ecole de technologie superieure, Montreal, Canada)
Christian Masson (Ecole de technologie superieure, Montreal, Canada)
Francis Pelletier (Arista Renewables Energies, Montreal, Canada)

Journal of Quality in Maintenance Engineering

ISSN: 1355-2511

Article publication date: 9 October 2017

550

Abstract

Purpose

The purpose of this paper is to propose a method to monitor a Wind Turbine’s (WT) main bearing, based on the difference between the temperature as measured by the Supervisory Control and Data Acquisition system (SCADA).

Design/methodology/approach

The monitoring of the main bearing is based on the difference between the measured temperature and the estimated temperature obtained from a dynamic model. The model used is based on the law of energy conservation. Several validation metrics have suggested that this model is accurate.

Findings

The Exponentially Weighted Moving Average control chart for two cases studies is used for the monitoring for the main bearing; this method has shown great potential for industrial applications. A failure was detected three weeks before the current actual alarm settings used by SCADA were able to identify the issue.

Originality/value

The proposed method is a monitoring method that can be used on most industrial wind farms and provide important information on the condition of the WTs’ main bearing.

Keywords

Acknowledgements

This research was made possible with the help of the National Science and Engineering Research Council of Canada (NSERC) and Quebec’s Nature and Technology Research Fund (FRQNT) joint Industrial Innovation Scholarships Program. Special thanks go to the participating industrial partner.

Citation

Cambron, P., Tahan, A., Masson, C. and Pelletier, F. (2017), "Bearing temperature monitoring of a Wind Turbine using physics-based model", Journal of Quality in Maintenance Engineering, Vol. 23 No. 4, pp. 479-488. https://doi.org/10.1108/JQME-06-2016-0028

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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