Time-Frequency-Based Data-Driven Structural Diagnosis and Damage Detection for Cable-Stayed Bridges

[1]  Fei Yan,et al.  Numerical simulation of fatigue behavior for cable-stayed orthotropic steel deck bridges using mixed-dimensional coupling method , 2017 .

[2]  Hong Hao,et al.  Damage detection in bridge structures under moving loads with phase trajectory change of multi-type vibration measurements , 2017 .

[3]  Zhibin Lin,et al.  Data-driven support vector machine with optimization techniques for structural health monitoring and damage detection , 2017, KSCE Journal of Civil Engineering.

[4]  Mahmoud R. Maheri,et al.  Multi-stage approach for structural damage detection problem using basis pursuit and particle swarm optimization , 2016 .

[5]  Weizhen Chen,et al.  Prediction of fatigue life of welded details in cable-stayed orthotropic steel deck bridges , 2016 .

[6]  Inaki Val,et al.  Wireless sensor nodes for generic signal conditioning: Application to Structural Health Monitoring of wind turbines , 2016 .

[7]  Gabriele Comanducci,et al.  On vibration-based damage detection by multivariate statistical techniques: Application to a long-span arch bridge , 2016 .

[8]  Claudomiro Sales,et al.  A novel unsupervised approach based on a genetic algorithm for structural damage detection in bridges , 2016, Eng. Appl. Artif. Intell..

[9]  Jinping Ou,et al.  The state of the art in structural health monitoring of cable-stayed bridges , 2016 .

[10]  Siu-Seong Law,et al.  Structural Health Monitoring Based on Vehicle-Bridge Interaction: Accomplishments and Challenges , 2015 .

[11]  Lei Deng,et al.  Development of high synchronous acquisition accuracy wireless sensor network for machine vibration monitoring , 2015 .

[12]  Roozbeh Rashedi,et al.  Capital renewal optimisation for large-scale infrastructure networks: genetic algorithms versus advanced mathematical tools , 2015 .

[13]  T. Guo,et al.  FATIGUE RELIABILITY ASSESSMENT OF ORTHOTROPIC STEEL BRIDGE DECKS BASED ON PROBABILISTIC MULTI-SCALE FINITE ELEMENT ANALYSIS , 2015 .

[14]  Şevket Ateş,et al.  Nonlinear dynamic analysis of base isolated cable-stayed bridge under earthquake excitations , 2014 .

[15]  Robert X. Gao,et al.  Wavelets for fault diagnosis of rotary machines: A review with applications , 2014, Signal Process..

[16]  Paulo B. Lourenço,et al.  Damage Detection on the Z24 Bridge by a Spectral-Based Dynamic Identification Technique , 2014 .

[17]  Spilios D. Fassois,et al.  A functional model based statistical time series method for vibration based damage detection, localization, and magnitude estimation , 2013 .

[18]  Fulei Chu,et al.  Recent advances in time–frequency analysis methods for machinery fault diagnosis: A review with application examples , 2013 .

[19]  Cheng-Wu Chen,et al.  RETRACTED: Sensitivity of initial damage detection for steel structures using the Hilbert-Huang transform method , 2013 .

[20]  Genda Chen,et al.  A moving‐window least squares fitting method for crack detection and rigidity identification of multispan bridges , 2013 .

[21]  Rafael Gallego,et al.  Model-based damage reconstruction in composites from ultrasound transmission , 2013 .

[22]  Daniel G. Linzell,et al.  Optimization of Design Details in Orthotropic Steel Decks Subjected to Static and Fatigue Loads , 2013 .

[23]  J Johan Maljaars,et al.  Fatigue assessment for deck plates in orthotropic bridge decks , 2012 .

[24]  Filipe Magalhães,et al.  Vibration based structural health monitoring of an arch bridge: From automated OMA to damage detection , 2012 .

[25]  Balbir S. Dhillon,et al.  Early fault diagnosis of rotating machinery based on wavelet packets—Empirical mode decomposition feature extraction and neural network , 2012 .

[26]  Z. Xiang,et al.  Damage detection by mode shape squares extracted from a passing vehicle , 2012 .

[27]  Haifan Xiang,et al.  Concept and requirements of sustainable development in bridge engineering , 2011 .

[28]  Charles R. Farrar,et al.  Machine learning algorithms for damage detection under operational and environmental variability , 2011 .

[29]  L. Bornn,et al.  Damage detection in initially nonlinear systems , 2010 .

[30]  L. Tang,et al.  Gear Fault Detection Based on Teager-Huang Transform , 2010 .

[31]  Hui Li,et al.  Bearing fault detection and diagnosis based on order tracking and Teager-Huang transform , 2010 .

[32]  Hoon Sohn,et al.  Damage diagnosis under environmental and operational variations using unsupervised support vector machine , 2009 .

[33]  Jinhee Lee.  IDENTIFICATION OF MULTIPLE CRACKS IN A BEAM USING NATURAL FREQUENCIES , 2009 .

[34]  Ronaldo C. Battista,et al.  Fatigue life estimates for a slender orthotropic steel deck , 2008 .

[35]  Vikram Pakrashi,et al.  Structural damage detection and calibration using a wavelet-kurtosis technique , 2007 .

[36]  Charles R. Farrar,et al.  The fundamental axioms of structural health monitoring , 2007, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[37]  Yang Yu,et al.  The application of energy operator demodulation approach based on EMD in machinery fault diagnosis , 2007 .

[38]  Yi-Qing Ni,et al.  Technology developments in structural health monitoring of large-scale bridges , 2005 .

[39]  Hani G. Melhem,et al.  Damage detection of structures by wavelet analysis , 2004 .

[40]  A. J. Bahr,et al.  Design and performance of wireless sensors for structural health monitoring , 2002 .

[41]  S. Chinchalkar.  DETERMINATION OF CRACK LOCATION IN BEAMS USING NATURAL FREQUENCIES , 2001 .

[42]  Mehmet Imregun,et al.  STRUCTURAL DAMAGE DETECTION USING ARTIFICIAL NEURAL NETWORKS AND MEASURED FRF DATA REDUCED VIA PRINCIPAL COMPONENT PROJECTION , 2001 .

[43]  Jing Lin,et al.  Feature Extraction Based on Morlet Wavelet and its Application for Mechanical Fault Diagnosis , 2000 .

[44]  Grant P. Steven,et al.  VIBRATION-BASED MODEL-DEPENDENT DAMAGE (DELAMINATION) IDENTIFICATION AND HEALTH MONITORING FOR COMPOSITE STRUCTURES — A REVIEW , 2000 .

[45]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[46]  Charles R. Farrar,et al.  A summary review of vibration-based damage identification methods , 1998 .

[47]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.