Wind Turbine Fault Feature Extraction under Varying Wind Speed condition

9th Symposium on Fluid-Structure Interactions, Flow-Sound Interactions, Flow-Induced Vibration & Noise

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Field Value
 
Title Wind Turbine Fault Feature Extraction under Varying Wind Speed condition
 
Creator Xiaojiao Gu
Changzheng Chen
He Lu
 
Subject
 
Description In actual wind turbine fault feature extraction, wind speed condition is often varying, so the fault feature information is often difficult to extract. A novel fault feature extraction method aimed at the problem of detecting wind turbine fault feature in the condition of varying wind speed is proposed based on the Grey Wolf Optimizer (GWO) and the stochastic resonance (SR) of bistable Duffing oscillator. First, estimate the detecting frequency domain of the fault feature signal according to the wind speed and collect the vibration signal of the wind turbine with appropriate sampling frequency. The collected signals are normalized so that the signal strength is in the proper range of processing. Following this, according to the wind speed scale transform coefficient is introduced to transform frequency-time scale. Furthermore, the damping ratio of Duffing oscillator is adjusted to the optimal value by GWO method. Finally, the recognizable signal is obtained by the Duffing system and scale recovery is done for the recognizable signal. The fault feature signal in the original signal is extracted. The test result of the wind turbine main bearing shows that the proposed method can extract wind turbine fault feature information in the condition of varying wind speed.
 
Publisher Paper Management System for FIV2018
 
Contributor
 
Date 2018-05-13 16:12:35
 
Type Peer-reviewed Paper

 
Format application/pdf
 
Identifier http://www.fiv2018.com/ocs/index.php/fiv2018/fivcan/paper/view/213
 
Source Paper Management System for FIV2018; FIV2018 Conference
 
Language en
 
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