Next Article in Journal
The Impact of Carsharing on Public Transit and Non-Motorized Travel: An Exploration of North American Carsharing Survey Data
Previous Article in Journal
Energy-Saving Potential of Building Envelope Designs in Residential Houses in Taiwan
Article Menu

Export Article

Open AccessArticle
Energies 2011, 4(11), 2077-2093; doi:10.3390/en4112077

Wind Turbine Gearbox Condition Monitoring with AAKR and Moving Window Statistic Methods

School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
*
Author to whom correspondence should be addressed.
Received: 30 August 2011 / Revised: 24 October 2011 / Accepted: 21 November 2011 / Published: 23 November 2011
View Full-Text   |   Download PDF [396 KB, uploaded 17 March 2015]   |  

Abstract

Condition Monitoring (CM) of wind turbines can greatly reduce the maintenance costs for wind farms, especially for offshore wind farms. A new condition monitoring method for a wind turbine gearbox using temperature trend analysis is proposed. Autoassociative Kernel Regression (AAKR) is used to construct the normal behavior model of the gearbox temperature. With a proper construction of the memory matrix, the AAKR model can cover the normal working space for the gearbox. When the gearbox has an incipient failure, the residuals between AAKR model estimates and the measurement temperature will become significant. A moving window statistical method is used to detect the changes of the residual mean value and standard deviation in a timely manner. When one of these parameters exceeds predefined thresholds, an incipient failure is flagged. In order to simulate the gearbox fault, manual temperature drift is added to the initial Supervisory Control and Data Acquisitions (SCADA) data. Analysis of simulated gearbox failures shows that the new condition monitoring method is effective. View Full-Text
Keywords: wind turbine condition monitoring; gearbox; Autoassociative Kernel Regression; residual analysis; moving window statistics wind turbine condition monitoring; gearbox; Autoassociative Kernel Regression; residual analysis; moving window statistics
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Guo, P.; Bai, N. Wind Turbine Gearbox Condition Monitoring with AAKR and Moving Window Statistic Methods. Energies 2011, 4, 2077-2093.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top