Research on fault diagnosis method of wind turbine based on partial least square method

In view of the complex structure of large wind turbine system and the characteristics of the operation process variable, this paper puts forward a fault diagnosis method based on multivariate statistics. The mathematical model based on partial least squares (PLS) without the need of complex model. T...

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Bibliographic Details
Published in2016 2nd IEEE International Conference on Computer and Communications (ICCC) pp. 925 - 928
Main Authors Lv, Feng, Zhang, Zeyu, Zhai, Kun, Ju, Xiyuan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2016
Subjects
Artificial neural networks
Fault diagnosis
Monitoring
multivariate statistics
PLS
Principal component analysis
Propulsion
Turbines
wind turbine
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DOI10.1109/CompComm.2016.7924839

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Summary:In view of the complex structure of large wind turbine system and the characteristics of the operation process variable, this paper puts forward a fault diagnosis method based on multivariate statistics. The mathematical model based on partial least squares (PLS) without the need of complex model. Through the original data PLS algorithm built the relationship between input and output variables and get the monitoring model. Computer simulation results show this method can effectively reduce the dimension of data and realize the fault diagnosis. Compared with PCA, PLS are more fully use the sample space information, improve the accuracy of fault diagnosis effectively.
DOI:10.1109/CompComm.2016.7924839