Wind Turbine Gearbox Failure Prediction Based on Time Series Analysis and Statistical Process Control

Abstract:

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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)

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 et al., "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:

$35.00

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