Damage detection for tethers of submerged floating tunnels based on convolutional neural networks

Min, Seongi; Jeong, Kiwon; Noh, Yunhak; Won, Deokhee; Kim, Seungjun

doi:10.1016/j.oceaneng.2022.111048

Cited by 14 publications

(5 citation statements)

References 33 publications

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“…These methods play a promising role in the process of structural damage localization. 58 Once the damage location is determined, it is able to evaluate the damage degree to support the structural RUL estimation and maintenance decision-making.…”

Section: Structure Health Monitoring Of Offshore Jacket Structuresmentioning

confidence: 99%

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Leng

Gardoni

Wang

et al. 2023

Structural Health Monitoring

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Structural health monitoring (SHM) has been recognized as a useful tool for safety management and risk reduction of offshore wind farms. In complex offshore environment, jacket structures of offshore wind turbines are prone to damages due to corrosion and fatigue. Effective SHM on jacket structures can substantially reduce their operation risk and costs. This work reviews the latest progress on the SHM of offshore wind jacket structures. The achievements in the structural damage identification, location, quantification, and remaining useful life (RUL) estimation are respectively introduced in detail, and existing challenges are discussed. Possible solutions to the challenges using the Digital Twin (DT) technology are put forward. The DT is able to mirror a real jacket structure into a virtual model, and Bayesian updating can refresh the virtual model parameters in real-time to keep consistency between virtual model and physical structure; then, just-in-time SHM can be carried out for jacket structures by performing damage detection, location, quantification, and RUL estimation using the virtual model. As a result, the DT may provide engineers and researchers a practicable tool for safety monitoring and risk reduction of fixed foundation offshore wind structures.

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Section: Structure Health Monitoring Of Offshore Jacket Structuresmentioning

confidence: 99%

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Leng

Gardoni

Wang

et al. 2023

Structural Health Monitoring

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“…It demonstrates superior performance in solving complex problems and can be applied to classification and regression. Owing to these characteristics, the algorithm has been applied in various fields, e.g., structural health monitoring [8][9][10]17] and behavior estimation [7,[18][19][20].…”

Section: Dnn Frameworkmentioning

confidence: 99%

“…They compared the estimation performance of several AI algorithms and confirmed that the neural network model had the highest performance. Min et al [8] conducted a study to detect tendon damage in a submerged floating tunnel based on the dynamic response of a structure by applying a deep learning algorithm. Deep learning algorithms that predict or classify based on generated data exhibit high efficiency.…”

Section: Introductionmentioning

confidence: 99%

DNN-Based Estimation of the Maximum Lateral Flange Moments of Horizontally Curved I-Girder Bridges

2023

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Horizontally curved I-girder bridges are known to be complex. Bending and torsion forces are imposed on the bridges owing to their shapes with initial curvatures. This torsion is a combination of pure and warping forces. The horizontally curved I-girder is significantly affected by warping behavior, which decreases the bending rigidity of its member. To investigate the warping behavior of the horizontally curved I-girder bridges a finite element analysis (FEA) must be performed. In this study, an FEA was performed to investigate the warping torsional behavior of a horizontally curved I-girder bridge, and a structural response database was obtained. Based on the database, the least absolute shrinkage and selection operator was employed to select features affecting the warping behavior. Subsequently, deep neural network models were trained with selected features for an input layer and maximum lateral flange moment data for an output layer. Several models were constructed and compared according to the number of hidden layers and neurons, and the model with the highest performance was proposed. Finally, it was confirmed that the estimated lateral flange moments computed by the proposed model showed a good correlation with the FEA results.

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“…Kwon et al [11] investigated a digital-twin-assisted artificial neural network (ANN) model that can predict the dynamic and structural behaviors of an SFT using numerical accelerometers and angle sensors sparsely distributed along its length. For possible damage to the cable, Min et al [12] proposed an advanced damage detection method for the tethers of SFT based on the convolutional neural network, and the proposed model could be effectively used for a submerged structure based on the feasibility study. Shao et al [13] presented a novel sensitive damage detection approach for the main tube and the tether system of the SFT in the context of statistical pattern recognition to analyze the vibrating behaviors induced by currents acting upon both the tube and the tethers by making use of the time-domain force and displacement series.…”

Section: Introductionmentioning

confidence: 99%

Numerical Analysis of Hydrodynamic Characteristics of Two-Dimensional Submerged Structure in Irregular Waves

Jin,

Zhang,

Zhou

et al. 2024

Water

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A comprehensive two-dimensional (2D) time-domain numerical model is established to investigate the interaction of irregular waves and submerged structures with different sections. The model specifically focuses on the dual-lane submerged floating tunnel (SFT) designs, encompassing elliptical, twin-circular, and round rectangular sections. For the hydrodynamic analysis, we adopt the second-order potential flow theory, while for the mooring line simulations, we employ the slender rod theory, taking into account the entire hydrodynamic load acting on it. In the coupled dynamic analysis, the fourth-order Adams–Bashforth–Moulton method, Newmark-β method, and Newton–Raphson iteration scheme are utilized for the coupled motion equation of the floating body and the dynamic equation of the mooring riser system. Experimental free decay tests are conducted to determine the damping coefficients of various section shapes in different directions. Our analysis delves into the detailed motion responses and mooring tensions of the SFTs with different section forms under irregular waves. We compare and contrast these responses in both time and frequency domains, particularly focusing on movement trends. The elliptical section structure emerges as the most stable design based on our comparisons. These findings provide valuable insights for the selection of optimal section shapes for dual-lane SFTs.

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Damage detection for tethers of submerged floating tunnels based on convolutional neural networks

Cited by 14 publications

References 33 publications

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

DNN-Based Estimation of the Maximum Lateral Flange Moments of Horizontally Curved I-Girder Bridges

Numerical Analysis of Hydrodynamic Characteristics of Two-Dimensional Submerged Structure in Irregular Waves

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