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Structural Health Monitoring of Wind Turbine Blades

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Wind Turbine Control and Monitoring

Part of the book series: Advances in Industrial Control ((AIC))

Abstract

Wind turbine blades usually achieve a very long operating life of 20–30 years. During their operation, the blades encounter complex loading with a high number of cycles as well as severe weather. All of these factors result in accumulated damage, acceleration of fatigue damage, and even sudden blade failure, which can cause catastrophic damage to the wind turbine. In recent years, many structural health monitoring (SHM) techniques, including global and local methods, have been developed and applied as important and valid tools to detect the damage of wind turbine blades. This chapter provides a comprehensive review and analysis on the state of the art of SHM for blades. Then, the SHM techniques are described in detail. For the global method, this chapter discusses mainly the vibration-based damage detection problem for wind turbine blades given the rotation effects. For the local methods, a fatigue damage detection system used for wind turbine blade is developed using high spatial resolution differential pulse-width pair Brillouin optical time-domain analysis (DPP-BOTDA) sensing system and PZT sensors is introduced to detect the tiny damage under static loading.

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Abbreviations

A :

Section area of elements

b max,k :

The largest length of the signal curve of every time series as the interval time is k

b min,k :

The length of the signal curve which pass through no damaged region as the interval time is k

C :

System damping matrix

E :

Elastic modulus, the residual error

FD max :

The largest value of estimated FD of the curve of each time series

J :

FD-based damage acuteness index

K :

System stiffness matrix

K s :

The structural stiffness

K d :

The additional stiffness

K 0 :

Is the normal modal stiffness matrix

K 1(α):

The stiffness matrix of the geometric nonlinearities

L :

The length of time series of PZT signal

M :

System mass matrix

n :

The degrees of freedom of the structure, the refractive index of the fiber core

NI :

The damage index based on PCA method

\(\bar{NI}\) :

The mean value of NI

t :

Time

T :

The loading matrix

u 0 :

The displacement in x direction

v :

The external force

V a :

The velocity of the acoustic wave

\(\nu_{\text{B}}\) :

The Brillouin frequency shift

v 0 :

The displacement in y direction

X :

The scores matrix

\(\hat{X}\) :

The reconstructed data

Y :

The compressed data

Z :

The displacements of the degrees of freedom of the structure

\(\dot{Z}\) :

The velocities of the degrees of freedom of the structure

\(\mathop Z\limits^{..}\) :

The accelerations of the degrees of freedom of the structure

U :

The potential energy of strain

α:

The modal coordinate, the first Rayleigh damping coefficients

β:

The second Rayleigh damping coefficients

\(\varepsilon\) :

The normal strain

\(\lambda\) :

The eigenvalues, the vacuum wavelength of the pump light

σ:

Standard deviation

ω:

The angular frequency

[]:

The Gauss’ notation

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Authors and Affiliations

  1. School of Civil Engineering, Harbin Institute of Technology, 150090, Harbin, China

    Hui Li, Wensong Zhou & Jinlong Xu

Authors
  1. Hui Li
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  2. Wensong Zhou
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  3. Jinlong Xu
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Corresponding author

Correspondence to Hui Li .

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Editors and Affiliations

  1. University of Girona, Girona, Spain

    Ningsu Luo

  2. Polytechnic University of Catalonia, Barcelona, Spain

    Yolanda Vidal

  3. Polytechnic University of Catalonia, Barcelona, Spain

    Leonardo Acho

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Li, H., Zhou, W., Xu, J. (2014). Structural Health Monitoring of Wind Turbine Blades. In: Luo, N., Vidal, Y., Acho, L. (eds) Wind Turbine Control and Monitoring. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-319-08413-8_9

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  • DOI: https://doi.org/10.1007/978-3-319-08413-8_9

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