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Fault diagnosis of wind turbine based on H-SKDB model

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DOI: 10.23977/acss.2020.040101 | Downloads: 13 | Views: 439

Author(s)

Baoyi Wang 1, Dongbing Yuan 1, Shaomin Zhang 1

Affiliation(s)

1 School of Control and Computer Engineering,North China Electric Power University,Baoding 071003,China

Corresponding Author

Baoyi Wang

ABSTRACT

The wind farm is in a bad wind area, which causes wind turbine faults to occur. Fault diagnosis of wind turbines is helpful for the maintenance and operation of wind turbines. The SKDB (Extensible Bayesian Network) model has the characteristics of high fault diagnosis accuracy and short training time. Based on the SKDB model, the Bayesian network structure is constructed by the method of mutual information addition calculation, then a fault diagnosis model of wind turbine based on H-SKDB is proposed, which realizes the fault diagnosis of wind turbine equipment information status. The experimental results show that the fault diagnosis method has higher calculation accuracy and shorter calculation time.

KEYWORDS

Bayesian Network, Fault Diagnosis, Wind Turbine, H-SKDB

CITE THIS PAPER

Baoyi Wang, Dongbing Yuan and Shaomin Zhang. Fault diagnosis of wind turbine based on H-SKDB model. Advances in Computer, Signals and Systems (2020) 4: 1-6. DOI: http://dx.doi.org/10.23977/acss.2020.040101.

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