Active vibration-based structural health monitoring system for wind turbine blade: Demonstration on an operating Vestas V27 wind turbine

被引:77
作者
Tcherniak, Dmitri [1 ]
Molgaard, Lasse L. [2 ]
机构
[1] Bruel & Kjaer Sound & Vibrat Measurement AS, Skodsborgvej 307, DK-2850 Naerum, Denmark
[2] Tech Univ Denmark, Dept Appl Math & Comp Sci, Lyngby, Denmark
来源
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL | 2017年 / 16卷 / 05期
关键词
Wind turbines; blade damage; actuator; accelerometers; semi-supervised learning; IDENTIFICATION; BRIDGE;
D O I
10.1177/1475921717722725
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study presents a structural health monitoring system that is able to detect structural defects of wind turbine blade such as cracks, leading/trailing-edge opening, or delamination. It is shown that even small defects of at least 15cm size can be detected remotely without stopping the wind turbine. The structural health monitoring system presented is vibration-based: mechanical energy is artificially introduced by means of an electromechanical actuator, whose plunger periodically hits the blade. The induced vibrations propagate along the blade and are picked up by accelerometers mounted along the blade. The vibrations in mid-range frequencies are utilized: this range is above the frequencies excited by blade-wind interaction, ensuring a good signal-to-noise ratio. At the same time, the corresponding wavelength is short enough to deliver required damage detection resolution and long enough to be able to propagate the entire blade length. This article demonstrates the system on a Vestas V27 wind turbine. One blade of the wind turbine was equipped with the system, and a 3.5-month monitoring campaign was conducted while the turbine was operating normally. During the campaign, a defecta trailing-edge openingwas artificially introduced into the blade and its size was gradually increased from the original 15 to 45cm. Using a semi-supervised learning algorithm, the system was able to detect even the smallest amount of damage while the wind turbine was operating under different weather conditions. This article provides detailed information about the instrumentation and the measurement campaign and explains the damage detection algorithm.
引用
收藏
页码:536 / 550
页数:15
相关论文
共 23 条
[1]   Damages of wind turbine blade trailing edge: Forms, location, and root causes [J].
Ataya, Sabbah ;
Ahmed, Mohamed M. Z. .
ENGINEERING FAILURE ANALYSIS, 2013, 35 :480-488
[2]   Structural health monitoring for a wind turbine system: a review of damage detection methods [J].
Ciang, Chia Chen ;
Lee, Jung-Ryul ;
Bang, Hyung-Joon .
MEASUREMENT SCIENCE AND TECHNOLOGY, 2008, 19 (12)
[3]   Time-series methods for fault detection and identification in vibrating structures [J].
Fassois, Spilios D. ;
Sakellariou, John S. .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2007, 365 (1851) :411-448
[4]  
Garcia D, 2015, P INT C DAM ASS STRU
[5]   Structural health and prognostics management for the enhancement of offshore wind turbine operations and maintenance strategies [J].
Griffith, D. Todd ;
Yoder, Nathanael C. ;
Resor, Brian ;
White, Jonathan ;
Paquette, Joshua .
WIND ENERGY, 2014, 17 (11) :1737-1751
[6]   Initiation of trailing edge failure in full-scale wind turbine blade test [J].
Haselbach, Philipp Ulrich ;
Branner, Kim .
ENGINEERING FRACTURE MECHANICS, 2016, 162 :136-154
[7]   Adaptive regularization parameter optimization in output-error-based finite element model updating [J].
Hua, X. G. ;
Ni, Y. Q. ;
Ko, J. M. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (03) :563-579
[8]   Bayesian model updating of a coupled-slab system using field test data utilizing an enhanced Markov chain Monte Carlo simulation algorithm [J].
Lam, Heung-Fai ;
Yang, Jiahua ;
Au, Siu-Kui .
ENGINEERING STRUCTURES, 2015, 102 :144-155
[9]   Bayesian structural damage detection of steel towers using measured modal parameters [J].
Lam, Heung-Fai ;
Yang, Jiahua .
EARTHQUAKES AND STRUCTURES, 2015, 8 (04) :935-956
[10]  
Larsen GC, 2014, P EUR WORKSH STRUCT