An intelligent approach to the condition monitoring of large scale wind Turbines

Wenxian Yang; Peter J. Tavner; Christopher J. Crabtree

An intelligent approach to the condition monitoring of large scale wind Turbines

Wenxian Yang, Peter J. Tavner, Christopher J. Crabtree

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In view of the limitations of the condition monitoring (CM) techniques nowadays available for wind turbines (WTs), a fully intelligent condition monitoring technique has been developed in this paper using Empirical Mode Decomposition (EMD). The EMD method is characterized by its powerful capability in processing non-stationary and nonlinear signals and by being an efficient sifting algorithm. The effectiveness and the merits of the proposed technique in wind turbine condition monitoring have been experimentally validated on a Wind Turbine Condition Monitoring Test Rig.

Original language	English
Title of host publication	European Wind Energy Conference and Exhibition 2009, EWEC 2009
Publisher	European Wind Energy Association
Pages	4503-4508
Number of pages	6
Volume	7
ISBN (Print)	9781615677467
Publication status	Published - 16 Mar 2009
Externally published	Yes
Event	European Wind Energy Conference and Exhibition 2009 - Marseille, France Duration: 16 Mar 2009 → 19 Mar 2009

Conference

Conference	European Wind Energy Conference and Exhibition 2009
Abbreviated title	EWEC 2009
Country/Territory	France
City	Marseille
Period	16/03/09 → 19/03/09

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "An intelligent approach to the condition monitoring of large scale wind Turbines",

abstract = "In view of the limitations of the condition monitoring (CM) techniques nowadays available for wind turbines (WTs), a fully intelligent condition monitoring technique has been developed in this paper using Empirical Mode Decomposition (EMD). The EMD method is characterized by its powerful capability in processing non-stationary and nonlinear signals and by being an efficient sifting algorithm. The effectiveness and the merits of the proposed technique in wind turbine condition monitoring have been experimentally validated on a Wind Turbine Condition Monitoring Test Rig.",

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booktitle = "European Wind Energy Conference and Exhibition 2009, EWEC 2009",

publisher = "European Wind Energy Association",

note = "European Wind Energy Conference and Exhibition 2009, EWEC 2009 ; Conference date: 16-03-2009 Through 19-03-2009",

}

An intelligent approach to the condition monitoring of large scale wind Turbines. / Yang, Wenxian; Tavner, Peter J.; Crabtree, Christopher J.

European Wind Energy Conference and Exhibition 2009, EWEC 2009. Vol. 7 European Wind Energy Association, 2009. p. 4503-4508.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An intelligent approach to the condition monitoring of large scale wind Turbines

AU - Yang, Wenxian

AU - Tavner, Peter J.

AU - Crabtree, Christopher J.

PY - 2009/3/16

Y1 - 2009/3/16

N2 - In view of the limitations of the condition monitoring (CM) techniques nowadays available for wind turbines (WTs), a fully intelligent condition monitoring technique has been developed in this paper using Empirical Mode Decomposition (EMD). The EMD method is characterized by its powerful capability in processing non-stationary and nonlinear signals and by being an efficient sifting algorithm. The effectiveness and the merits of the proposed technique in wind turbine condition monitoring have been experimentally validated on a Wind Turbine Condition Monitoring Test Rig.

AB - In view of the limitations of the condition monitoring (CM) techniques nowadays available for wind turbines (WTs), a fully intelligent condition monitoring technique has been developed in this paper using Empirical Mode Decomposition (EMD). The EMD method is characterized by its powerful capability in processing non-stationary and nonlinear signals and by being an efficient sifting algorithm. The effectiveness and the merits of the proposed technique in wind turbine condition monitoring have been experimentally validated on a Wind Turbine Condition Monitoring Test Rig.

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KW - Empirical mode decomposition

KW - Wind turbine

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M3 - Conference contribution

AN - SCOPUS:84870017047

SN - 9781615677467

VL - 7

SP - 4503

EP - 4508

BT - European Wind Energy Conference and Exhibition 2009, EWEC 2009

PB - European Wind Energy Association

T2 - European Wind Energy Conference and Exhibition 2009

Y2 - 16 March 2009 through 19 March 2009

ER -

An intelligent approach to the condition monitoring of large scale wind Turbines

Abstract

Conference

UN SDGs

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