Quantitative Detection of Multiple Damages in Wind Turbine Blade Based on the Operating Deflection Shape and Natural Frequencies

[1]  M. Abdel Wahab,et al.  A robust technique for damage identification of marine fiberglass rectangular composite plates using 2-D discrete wavelet transform and radial basis function networks , 2022, Ocean Engineering.

[2]  J. Leng,et al.  Finite element analysis of damage mechanisms of composite wind turbine blade by considering fluid/solid interaction. Part I: full-scale structure , 2022, Composite Structures.

[3]  A. Tatar,et al.  Artificial neural network, support vector machine, decision tree, random forest, and committee machine intelligent system help to improve performance prediction of low salinity water injection in carbonate oil reservoirs , 2022, Journal of Petroleum Science and Engineering.

[4]  B. Wilkinson,et al.  Satellite-derived bathymetry using machine learning and optimal Sentinel-2 imagery in South-West Florida coastal waters , 2022, GIScience & Remote Sensing.

[5]  Shuqing Wang,et al.  Damage detection of wind turbine blades by Bayesian multivariate cointegration , 2022, Ocean Engineering.

[6]  K. Yuan,et al.  A Novel General-purpose Three-dimensional Continuously Scanning Laser Doppler Vibrometer System for Full-field Vibration Measurement of a Structure with a Curved Surface , 2022, Journal of Sound and Vibration.

[7]  D. Coker,et al.  Crack propagation in the Double Cantilever Beam using Peridynamic theory , 2022, Composite Structures.

[8]  Jiabin Zhang,et al.  A detection method integrating modal deflection curvature difference and natural frequency for structural stiffness degradation , 2022, Engineering Failure Analysis.

[9]  Jin-hai Zheng,et al.  A method for quantitative damage identification in a high-piled wharf based on modal strain energy residual variability , 2022, Ocean Engineering.

[10]  Xudong Chen,et al.  Parametric analyses on the impact fracture of laminated glass using the combined finite-discrete element method , 2022, Composite Structures.

[11]  E. Chatzi,et al.  A framework for quantifying the value of vibration-based structural health monitoring , 2022, Mechanical Systems and Signal Processing.

[12]  A. Mahmoodzadeh,et al.  Prediction of Mode-I Rock Fracture Toughness using Support Vector Regression with Metaheuristic Optimization Algorithms , 2022, Engineering Fracture Mechanics.

[13]  Xiang Zhang,et al.  Machine learning approaches to rock fracture mechanics problems: Mode-I fracture toughness determination , 2021, Engineering Fracture Mechanics.

[14]  Q. Meng,et al.  Data-driven fatigue life prediction in additive manufactured titanium alloy: A damage mechanics based machine learning framework , 2021, Engineering Fracture Mechanics.

[15]  E. O'brien,et al.  Wavelet-based operating deflection shapes for locating scour-related stiffness losses in multi-span bridges , 2021, Structure and Infrastructure Engineering.

[16]  Do Hyoung Shin,et al.  Damage detection of catenary mooring line based on recurrent neural networks , 2021 .

[17]  Alireza Mojtahedi,et al.  Damage detection in an offshore platform using incomplete noisy FRF data by a novel Bayesian model updating method , 2020 .

[18]  Ning Hao,et al.  Damage detection on hull girder of ship subjected to explosion loading , 2020 .

[19]  Moo-Hyun Kim,et al.  Structural health monitoring of towers and blades for floating offshore wind turbines using operational modal analysis and modal properties with numerical-sensor signals , 2019, Ocean Engineering.

[20]  Weidong Zhu,et al.  A Comprehensive Study on Detection of Hidden Delamination Damage in a Composite Plate Using Curvatures of Operating Deflection Shapes , 2019, Journal of Nondestructive Evaluation.

[21]  C. Casavola,et al.  Acoustic emission waveform analysis in CFRP under Mode I test , 2019, Engineering Fracture Mechanics.

[22]  Jiangqi Long,et al.  Identification of damage locations based on operating deflection shape , 2013 .

[23]  Chunlin Zhang,et al.  Crack location identification of rotating rotor systems using operating deflection shape data , 2013 .

[24]  Bing Li,et al.  Identification of a crack in a beam based on the finite element method of a B-spline wavelet on the interval , 2006 .

[25]  Lu Huang,et al.  Dynamics- and Laser-Based Boundary Effect Evaluation Method for Damage Inspection of One- and Two-Dimensional Structures , 2006 .

[26]  Bing Li,et al.  Detection of crack location and size in structures using wavelet finite element methods , 2005 .

[27]  Xingju Wang,et al.  A Multi-step Interpolated-FFT procedure for full-field nonlinear modal testing of turbomachinery components , 2022, Mechanical Systems and Signal Processing.

[28]  Nicholas A. Valente,et al.  Streamlined particle filtering of phase-based magnified videos for quantified operational deflection shapes , 2022, Mechanical Systems and Signal Processing.

[29]  R. Nigam,et al.  Selection of suitable mother wavelet along with vanishing moment for the effective detection of crack in a beam , 2022 .

[30]  Xuhui He,et al.  A response reconstruction method based on empirical mode decomposition and modal synthesis method , 2022, Mechanical Systems and Signal Processing.