Vibration-Response-Only Structural Health Monitoring for Offshore Wind Turbine Jacket Foundations via Convolutional Neural Networks
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Control, Modeling, Identification and Applications (CoDAlab), Department of Mathematics, Escola d’Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya (UPC), Campus Diagonal-Besós (CDB), Eduard Maristany, 16, 08019 Barcelona, Spain
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Mechatronics Engineering, Faculty of Mechanical Engineering and Production Science (FIMCP), Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil 09-01-5863, Ecuador
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(12), 3429; https://doi.org/10.3390/s20123429
Received: 25 May 2020
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Revised: 15 June 2020
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Accepted: 16 June 2020
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Published: 17 June 2020
(This article belongs to the Special Issue Toward Data-Driven Structural Health Monitoring: New Approaches and Sensor-Based Methods)
This work deals with structural health monitoring for jacket-type foundations of offshore wind turbines. In particular, a vibration-response-only methodology is proposed based on accelerometer data and deep convolutional neural networks. The main contribution of this article is twofold: (i) a signal-to-image conversion of the accelerometer data into gray scale multichannel images with as many channels as the number of sensors in the condition monitoring system, and (ii) a data augmentation strategy to diminish the test set error of the deep convolutional neural network used to classify the images. The performance of the proposed method is analyzed using real measurements from a steel jacket-type offshore wind turbine laboratory experiment undergoing different damage scenarios. The results, with a classification accuracy over 99%, demonstrate that the stated methodology is promising to be utilized for damage detection and identification in jacket-type support structures.
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Keywords:
structural health monitoring; damage detection; damage identification; offshore wind turbine foundation; jacket; signal-to-image conversion; convolutional neural network
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MDPI and ACS Style
Puruncajas, B.; Vidal, Y.; Tutivén, C. Vibration-Response-Only Structural Health Monitoring for Offshore Wind Turbine Jacket Foundations via Convolutional Neural Networks. Sensors 2020, 20, 3429. https://doi.org/10.3390/s20123429
AMA Style
Puruncajas B, Vidal Y, Tutivén C. Vibration-Response-Only Structural Health Monitoring for Offshore Wind Turbine Jacket Foundations via Convolutional Neural Networks. Sensors. 2020; 20(12):3429. https://doi.org/10.3390/s20123429
Chicago/Turabian StylePuruncajas, Bryan, Yolanda Vidal, and Christian Tutivén. 2020. "Vibration-Response-Only Structural Health Monitoring for Offshore Wind Turbine Jacket Foundations via Convolutional Neural Networks" Sensors 20, no. 12: 3429. https://doi.org/10.3390/s20123429
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