Paper Title:
Wind Turbine Gearbox Failure Prediction Based on Time Series Analysis and Statistical Process Control
  Abstract

The Time Series method and Statistical Process Control strategy is applied to predict failures of wind turbine gearboxes. First, based on the real-time temperature data of gearboxes measured by temperature sensors, the temperature prediction model under normal operating conditions is established by ARIMA model. The analysis of the predicted values and the actual values of gearbox temperature is done, and proves that its residuals are normally distributed; then combined with statistical process control (SPC) methods, the big number of temperature data is used to calculate the standard deviation(σ) of residuals, and the gearbox failure threshold will be identified; Finally, the temperature data are analyzed both in normal operating condition and the failure condition to determine the operation status of the gearbox, statistical analysis and residual charts are carried out for gearbox failure prediction, verifying the feasibility and effectiveness of the proposed method.

  Info
Periodical
Advanced Materials Research (Volumes 347-353)
Chapter
Chapter 3: Development and Utilization of Wind Energy
Edited by
Weiguo Pan, Jianxing Ren and Yongguang Li
Pages
2236-2240
DOI
10.4028/www.scientific.net/AMR.347-353.2236
Citation
F. F. Wang, X. Q. Xiao, H. S. Zhao, "Wind Turbine Gearbox Failure Prediction Based on Time Series Analysis and Statistical Process Control", Advanced Materials Research, Vols. 347-353, pp. 2236-2240, 2012
Online since
October 2011
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Price
$32.00
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