Ultrasound-based identification of damage in wind turbine blades using novelty detection

•Novelty detection is proposed as a novel paradigm for US NDT of wind turbines blades.•ND considers one class classification and does not require signatures from defects.•The proposed signal processing chain comprises both FFT and PCA.•A performance comparison among different novelty detection metho...

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Bibliographic Details
Published in:Ultrasonics 2020-12, Vol.108, p.106166-106166, Article 106166
Main Authors: Oliveira, Moisés A., Simas Filho, Eduardo F., Albuquerque, Maria C.S., Santos, Ygor T.B., da Silva, Ivan C., Farias, Cláudia T.T.
Format: Article
Language:English
Subjects:
Machine learning
Novelty detection
Ultrasonic nondestructive testing
Wind energy
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Summary:•Novelty detection is proposed as a novel paradigm for US NDT of wind turbines blades.•ND considers one class classification and does not require signatures from defects.•The proposed signal processing chain comprises both FFT and PCA.•A performance comparison among different novelty detection methods is presented.•The results are evaluated considering a practical ultrasonic NDT scenario. Among the renewable energy sources, wind power generation presents competitive costs and high installation potential in many countries. Ensuring the integrity of the generation equipment plays an important role for reliable energy production. Therefore, nondestructive test procedures are required, especially for turbine blades, which are subject to severe operational conditions due to phenomena such as lightning strikes, mechanical stress, humidity and corrosion. Nondestructive ultrasonic test techniques are commonly applied in their predictive maintenance. This work proposes the use of novelty detection methods combined with nondestructive ultrasound testing to identify structural problems in wind turbine blades. Ultrasound signals are preprocessed using both, wavelet denoising and principal component analysis. Novelty detection deals with the one-class classification problem, when only the normal condition signatures are required for the classification system design. For the nondestructive test of turbine blades, this is an interesting paradigm because it is not always possible to obtain test samples from all of the existing flaw conditions. Our experimental results indicate the efficiency of the proposed method.
ISSN:0041-624X
1874-9968
DOI:10.1016/j.ultras.2020.106166