A Novel Method and its Field Tests for Monitoring and Diagnosing Blade Health for Wind Turbines

Author

Ki-Yong Oh ; Joon-Young Park ; Jun-Shin Lee ; Epureanu, Bogdan I. ; Jae-Kyung Lee

Author_Institution

Dept. of Mech. Eng., Univ. of Michigan, Ann Arbor, MI, USA

Volume

64

Issue

6

fYear

2015

fDate

Jun-15

Firstpage

1726

Lastpage

1733

Abstract

A new diagnostic method is proposed to efficiently monitor the structural health and detect damages in wind turbine blades. A high-resolution real-time blade condition monitoring system that considers the harsh turbine operating environment and uses optical sensors and a wireless network is presented. A hybrid algorithm, which merges probabilistic analysis, design loads, and real-time load estimates, is introduced to enhance operational safety and reliability. Moreover, the alarm limits are updated every 10 min through a learning algorithm to further improve reliability. The proposed algorithm was implemented in a blade monitoring system. The effectiveness of the proposed algorithm was demonstrated for a 3-MW wind turbine in the Yeongheung wind farm.

Keywords

blades; condition monitoring; reliability; structural engineering; wind turbines; Yeongheung wind farm; alarm limits; blade health diagnosis; diagnostic method; harsh turbine operating environment; hybrid algorithm; operational safety; optical sensors; real-time load estimates; reliability; structural health; wind turbine blade condition monitoring system; wireless network; Blades; Monitoring; Strain; Temperature measurement; Temperature sensors; Wind turbines; Blade monitoring; condition monitoring system; failure diagnosis; structural health monitoring; wind turbines; wind turbines.;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/TIM.2014.2381791

Filename

7010028