TY - JOUR
T1 - Wideband Vibro-Acoustic Modulation for Crack Detection in Wind Turbine Blades
AU - Alnutayfat, Abdullah
AU - Sutin, Alexander
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/9
Y1 - 2023/9
N2 - Featured Application: The vibro-acoustic modulation (VAM) method used to detect the defect in wind turbine (WT) blades can be integrated into the currently used structural health monitoring (SHM) system. This integration does not necessitate additional hardware, and it can utilize signal-processing algorithms to extract the non-linear effects described in this paper. Wind turbines (WT) are a popular method used in energy production, but blade failure and maintenance costs pose significant challenges for the industry. Early detection of blade defects is vital to prevent collapse. This paper examines the modulation of blade vibrations via low-frequency blade rotation, mirroring the vibro-acoustic modulation (VAM) method. Specifically, we study the modulation of blade vibrations, which are generated via blade interactions with air turbulence and have a wide frequency range. These vibrations are modulated by the alternating bending stress experienced during blade rotation. For the simulation of VAM, we employ a simple breathing crack model, which considers a mechanical oscillator with parameters that are periodically changed in response to low-frequency blade rotation. The modulation of the wideband signal by blade rotation can be extracted using the detection of envelope modulation on noise (DEMON) algorithm. This model was applied for the estimation of the modulation of a large (52-m-long) WT blade. Steel specimens have been used in laboratory experiments to demonstrate the feasibility of VAM using a probe broadband noise signal. This paper presents the first work to experimentally and theoretically apply wideband signals in VAM. It further explores the analysis of the use of natural vibrations within VAM for the SHM of WT blades.
AB - Featured Application: The vibro-acoustic modulation (VAM) method used to detect the defect in wind turbine (WT) blades can be integrated into the currently used structural health monitoring (SHM) system. This integration does not necessitate additional hardware, and it can utilize signal-processing algorithms to extract the non-linear effects described in this paper. Wind turbines (WT) are a popular method used in energy production, but blade failure and maintenance costs pose significant challenges for the industry. Early detection of blade defects is vital to prevent collapse. This paper examines the modulation of blade vibrations via low-frequency blade rotation, mirroring the vibro-acoustic modulation (VAM) method. Specifically, we study the modulation of blade vibrations, which are generated via blade interactions with air turbulence and have a wide frequency range. These vibrations are modulated by the alternating bending stress experienced during blade rotation. For the simulation of VAM, we employ a simple breathing crack model, which considers a mechanical oscillator with parameters that are periodically changed in response to low-frequency blade rotation. The modulation of the wideband signal by blade rotation can be extracted using the detection of envelope modulation on noise (DEMON) algorithm. This model was applied for the estimation of the modulation of a large (52-m-long) WT blade. Steel specimens have been used in laboratory experiments to demonstrate the feasibility of VAM using a probe broadband noise signal. This paper presents the first work to experimentally and theoretically apply wideband signals in VAM. It further explores the analysis of the use of natural vibrations within VAM for the SHM of WT blades.
KW - crack detection
KW - vibro-acoustic modulation (VAM)
KW - wideband vibration
KW - wind turbine blade
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U2 - 10.3390/app13179570
DO - 10.3390/app13179570
M3 - Article
AN - SCOPUS:85170398682
VL - 13
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 17
M1 - 9570
ER -