Temperature Effect on Vibration Properties and Vibration-Based Damage Identification of Bridge Structures: A Literature Review

A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications

Avcı, O., Abdeljaber, O., Serkan Kiranyaz, B., Hussein, M. F. M., Gabbouj, M., & Inman, D. J. (2020) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2020.107077 · Cited by 1,463 · see citing works

Emerging Artificial Intelligence Methods in Structural Engineering

Salehi, H., & Burgueño, R. (2018) · Engineering Structures · doi:10.1016/j.engstruct.2018.05.084 · Cited by 1,068 · see citing works

Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review

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Machine Learning Algorithms in Civil Structural Health Monitoring: A Systematic Review

Flah, M., Nunez, I., Chaabene, W. B., & Nehdi, M. L. (2020) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-020-09471-9 · Cited by 540 · see citing works

A sunflower optimization (SFO) algorithm applied to damage identification on laminated composite plates

Gomes, G. F., da Cunha, S. S., & Ancelotti, A. C. (2018) · Engineering With Computers · doi:10.1007/s00366-018-0620-8 · Cited by 365 · see citing works

Unsupervised deep learning approach using a deep auto-encoder with a one-class support vector machine to detect damage

Wang, Z., & Cha, Y. (2020) · Structural Health Monitoring · doi:10.1177/1475921720934051 · Cited by 343 · see citing works

Temperature effect on vibration properties of civil structures: a literature review and case studies

Xia, Y., Chen, B., Weng, S., Ni, Y., & Xu, Y. L. (2012) · Journal of Civil Structural Health Monitoring · doi:10.1007/s13349-011-0015-7 · Cited by 316 · see citing works

Surface fatigue crack identification in steel box girder of bridges by a deep fusion convolutional neural network based on consumer-grade camera images

Xu, Y., Bao, Y., Chen, J., Zuo, W., & Li, H. (2018) · Structural Health Monitoring · doi:10.1177/1475921718764873 · Cited by 292 · see citing works

Hierarchical Bayesian model updating for structural identification

Behmanesh, I., Moaveni, B., Lombaert, G., & Papadimitriou, C. (2015) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2015.03.026 · Cited by 287 · see citing works

Field monitoring and numerical analysis of Tsing Ma Suspension Bridge temperature behavior

Xia, Y., Chen, B., Zhou, X., & Xu, Y. L. (2012) · Structural Control and Health Monitoring · doi:10.1002/stc.515 · Cited by 242 · see citing works

An efficient artificial neural network for damage detection in bridges and beam-like structures by improving training parameters using cuckoo search algorithm

Tran-Ngoc, H., Khatir, S., Roeck, G. D., Bui-Tien, T., & Wahab, M. M. A. (2019) · Engineering Structures · doi:10.1016/j.engstruct.2019.109637 · Cited by 209 · see citing works

A wavelet-based damage detection algorithm based on bridge acceleration response to a vehicle

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Lost data recovery for structural health monitoring based on convolutional neural networks

Fan, G., Li, J., & Hao, H. (2019) · Structural Control and Health Monitoring · doi:10.1002/stc.2433 · Cited by 188 · see citing works

A machine-learning approach for structural damage detection using least square support vector machine based on a new combinational kernel function

Ghiasi, R., Torkzadeh, P., & Noori, M. (2016) · Structural Health Monitoring · doi:10.1177/1475921716639587 · Cited by 170 · see citing works

Investigation of dynamic properties of long-span cable-stayed bridges based on one-year monitoring data under normal operating condition

Mao, J., Wang, H., Feng, D., Tao, T., & Zheng, W. (2018) · Structural Control and Health Monitoring · doi:10.1002/stc.2146 · Cited by 163 · see citing works

Structural Damage Localization and Quantification Based on a CEEMDAN Hilbert Transform Neural Network Approach: A Model Steel Truss Bridge Case Study

Mousavi, A. A., Zhang, C., Masri, S. F., & Gholipour, G. (2020) · Sensors · doi:10.3390/s20051271 · Cited by 143 · see citing works

Nonlinear finite element model updating for damage identification of civil structures using batch Bayesian estimation

Ebrahimian, H., Astroza, R., Conte, J. P., & CALLAFON, R. A. D. (2016) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2016.02.002 · Cited by 139 · see citing works

On-line Bayesian model updating for structural health monitoring

Rocchetta, R., Broggi, M., Huchet, Q., & Patelli, E. (2017) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2017.10.015 · Cited by 136 · see citing works

Temperature-based structural health monitoring baseline for long-span bridges

Yarnold, M. T., & Moon, F. (2015) · Engineering Structures · doi:10.1016/j.engstruct.2014.12.042 · Cited by 132 · see citing works

A robust Bayesian methodology for damage localization in plate-like structures using ultrasonic guided-waves

Cantero‐Chinchilla, S., Chiachío, J., Chiachío, M., Chronopoulos, D., & Jones, I. A. (2018) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2018.12.021 · Cited by 131 · see citing works

Predicting thermal response of bridges using regression models derived from measurement histories

Kromanis, R., & Kripakaran, P. (2014) · Computers & Structures · doi:10.1016/j.compstruc.2014.01.026 · Cited by 128 · see citing works

Effects of changing ambient temperature on finite element model updating of the Dowling Hall Footbridge

Moaveni, B., & Behmanesh, I. (2012) · Engineering Structures · doi:10.1016/j.engstruct.2012.05.009 · Cited by 122 · see citing works

Efficiency of Jaya algorithm for solving the optimization-based structural damage identification problem based on a hybrid objective function

Dinh-Cong, D., Ho-Huu, V., Vo-Duy, T., Quyen, N.-T. H., & Nguyen-Thoi, T. (2017) · Engineering Optimization · doi:10.1080/0305215x.2017.1367392 · Cited by 121 · see citing works

Vibration-Based Structural Damage Identification under Varying Temperature Effects

Huang, M., Gül, M., & Zhu, H. (2018) · Journal of Aerospace Engineering · doi:10.1061/(asce)as.1943-5525.0000829 · Cited by 118 · see citing works

Variation of structural vibration characteristics versus non-uniform temperature distribution

Xia, Y., Xu, Y. L., Wei, Z.-L., Zhu, H.-P., & Zhou, X. (2010) · Engineering Structures · doi:10.1016/j.engstruct.2010.09.027 · Cited by 115 · see citing works

Structural damage identification using improved Jaya algorithm based on sparse regularization and Bayesian inference

Ding, Z., Li, J., & Hao, H. (2019) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2019.06.029 · Cited by 114 · see citing works

Damage detection under varying temperature using artificial neural networks

Gu, J., Gül, M., & Wu, X. (2017) · Structural Control and Health Monitoring · doi:10.1002/stc.1998 · Cited by 111 · see citing works

An indirect method for bridge mode shapes identification based on wavelet analysis

Jian, X., Xia, Y., & Sun, L. (2020) · Structural Control and Health Monitoring · doi:10.1002/stc.2630 · Cited by 111 · see citing works

A Bayesian approach based on a Markov-chain Monte Carlo method for damage detection under unknown sources of variability

Figueiredo, E., Radu, L., Keith Worden, B., & Farrar, C. R. (2014) · Engineering Structures · doi:10.1016/j.engstruct.2014.08.042 · Cited by 110 · see citing works

In-Service Condition Assessment of a Long-Span Suspension Bridge Using Temperature-Induced Strain Data

Xia, Q., Cheng, Y., Zhang, J., & Zhu, F. (2016) · Journal of Bridge Engineering · doi:10.1061/(asce)be.1943-5592.0001003 · Cited by 103 · see citing works

Deep learning-based detection of structural damage using time-series data

Dang, V.-H., Raza, M., Nguyen, T., Bui-Tien, T., & Nguyen, H. X. (2020) · Structure and Infrastructure Engineering · doi:10.1080/15732479.2020.1815225 · Cited by 103 · see citing works

Constructing input to neural networks for modeling temperature-caused modal variability: mean temperatures, effective temperatures, and principal components of temperatures

Zhou, H. F., Ni, Y. Q., & Ko, J. M. (2010) · Engineering Structures · doi:10.1016/j.engstruct.2010.02.026 · Cited by 102 · see citing works

The use of a non-probabilistic artificial neural network to consider uncertainties in vibration-based-damage detection

Padil, K. H., Bakhary, N., & Hao, H. S. (2016) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2016.06.007 · Cited by 100 · see citing works

A robust damage detection method based on multi-modal analysis in variable temperature conditions

Gillich, G.-R., Furdui, H., Wahab, M. M. A., & Korka, Z.-I. (2018) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2018.05.037 · Cited by 99 · see citing works

Vision-based defects detection for bridges using transfer learning and convolutional neural networks

Zhu, J., Zhang, C., Qi, H., & Lu, Z. (2019) · Structure and Infrastructure Engineering · doi:10.1080/15732479.2019.1680709 · Cited by 99 · see citing works

The application of a damage detection method using Artificial Neural Network and train-induced vibrations on a simplified railway bridge model

Shu, J., Zhang, Z., González, I., & Karoumi, R. (2013) · Engineering Structures · doi:10.1016/j.engstruct.2013.02.031 · Cited by 97 · see citing works

Eliminating Temperature Effect in Vibration-Based Structural Damage Detection

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Damage identification in steel girder bridges using modal strain energy-based damage index method and artificial neural network

Nick, H., Aziminejad, A., Hosseini, M. H., & Laknejadi, K. (2020) · Engineering Failure Analysis · doi:10.1016/j.engfailanal.2020.105010 · Cited by 88 · see citing works

Supervised Deep Learning with Finite Element simulations for damage identification in bridges

Fernández-Navamuel, A., Zamora-Sánchez, D., Omella, Á. J., Pardo, D., García-Sánchez, D., & Magalhães, F. (2022) · Engineering Structures · doi:10.1016/j.engstruct.2022.114016 · Cited by 88 · see citing works

Damage detection accommodating nonlinear environmental effects by nonlinear principal component analysis

Hsu, T., & Loh, C. (2009) · Structural Control and Health Monitoring · doi:10.1002/stc.320 · Cited by 87 · see citing works

Structural health monitoring of Canton Tower using Bayesian framework

Kuok, S., & Yuen, K. (2012) · Smart Structures and Systems · doi:10.12989/sss.2012.10.4_5.375 · Cited by 87 · see citing works

Improved damage identification in bridge structures subject to moving loads: Numerical and experimental studies

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Experimental Study of Thermal Effects on a Long-Span Suspension Bridge

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Experimental and finite element investigation of temperature distributions in concrete-encased steel girders

Abid, S. R., Mussa, F. I., Tayşi, N., & Özakça, M. (2017) · Structural Control and Health Monitoring · doi:10.1002/stc.2042 · Cited by 85 · see citing works

Temperature-induced variations of measured modal frequencies of steel box girder for a long-span suspension bridge

Ding, Y., & Li, A. (2011) · International Journal of Steel Structures · doi:10.1007/s13296-011-2004-4 · Cited by 84 · see citing works

Application of Internet of Things Technology and Convolutional Neural Network Model in Bridge Crack Detection

Zhang, L., Zhou, G., Han, Y., Lin, H., & Wu, Y. (2018) · IEEE Access · doi:10.1109/access.2018.2855144 · Cited by 84 · see citing works

Sensor data-driven structural damage detection based on deep convolutional neural networks and continuous wavelet transform

Chen, Z., Wang, Y., Wu, J., Deng, C., & Hu, K. (2021) · Applied Intelligence · doi:10.1007/s10489-020-02092-6 · Cited by 84 · see citing works

Structural damage identification based on modal frequency strain energy assurance criterion and flexibility using enhanced Moth-Flame optimization

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Damage detection on a three-storey steel frame using artificial neural networks and genetic algorithms

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Structural damage assessment under varying temperature conditions

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A hybrid ANN-based imperial competitive algorithm methodology for structural damage identification of slab-on-girder bridge using data mining

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Vibration based damage detection in composite beams under temperature variations using Poincaré maps

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Long-term monitoring of a PSC box girder bridge: Operational modal analysis, data normalization and structural modification assessment

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Damage detection and localization of a steel truss bridge model subjected to impact and white noise excitations using empirical wavelet transform neural network approach

Mousavi, A. A., Zhang, C., Masri, S. F., & Gholipour, G. (2021) · Measurement · doi:10.1016/j.measurement.2021.110060 · Cited by 67 · see citing works

A synthesis of peak picking method and wavelet packet transform for structural modal identification

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Damage detection in girder bridges using modal curvatures gapped smoothing method and Convolutional Neural Network: Application to Bo Nghi bridge

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Structural damage identification based on substructure method and improved whale optimization algorithm

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Data Anomaly Detection of Bridge Structures Using Convolutional Neural Network Based on Structural Vibration Signals

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Operational modal identification of structures based on improved empirical wavelet transform

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Structural damage detection based on posteriori probability support vector machine and Dempster–Shafer evidence theory

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Damage assessment in plate-like structures using a two-stage method based on modal strain energy change and Jaya algorithm

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Investigation of Temperature Effects on Steel-Truss Bridge Based on Long-Term Monitoring Data: Case Study

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Modal identification based on continuous wavelet transform and ambient excitation tests

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Damage identification based on convolutional neural network and recurrence graph for beam bridge

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Damage detection using wavelet entropy of acoustic emission waveforms in concrete under flexure

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Damage Identification of Bridge Structures Considering Temperature Variations-Based SVM and MFO

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Measuring and modelling the thermal performance of the Tamar Suspension Bridge using a wireless sensor network

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SHM under varying environmental conditions: an approach based on model order reduction and deep learning

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A Hybrid Particle Swarm Optimization (PSO)‐Simplex Algorithm for Damage Identification of Delaminated Beams

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Multiple damage detection in laminated composite beams by data fusion of Teager energy operator-wavelet transform mode shapes

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Computer Vision-Based Bridge Damage Detection Using Deep Convolutional Networks with Expectation Maximum Attention Module

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Structural damage detection of steel bridge girder using artificial neural networks and finite element models

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Wavelet packet energy–based damage identification of wood utility poles using support vector machine multi-classifier and evidence theory

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CNN-based damage identification method of tied-arch bridge using spatial-spectral information

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Bayesian seismic strong-motion response and damage estimation with application to a full-scale seven story shear wall structure

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Structural effects of temperature gradient on a continuous prestressed concrete girder bridge: analysis and field measurements

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Bayesian structural identification of a hysteretic negative stiffness earthquake protection system using unscented Kalman filtering

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Thermal strain extraction methodologies for bridge structural condition assessment

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Structural Health Monitoring of a Prestressed Concrete Bridge Based on Statistical Pattern Recognition of Continuous Dynamic Measurements over 14 years

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Effect of Temperature on Daily Modal Variability of a Steel-Concrete Composite Bridge

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Structural damage identification based on cuckoo search algorithm

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Two-step approach for fatigue crack detection in steel bridges using convolutional neural networks

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Bayesian structural identification of a long suspension bridge considering temperature and traffic load effects

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Bridge Temperature Profiles Revisited: Thermal Analyses Based on Recent Meteorological Data from Nevada

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Parameter identification for damaged condition investigation on masonry arch bridges using a Bayesian approach

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Damage identification of bridge structure considering temperature variations based on particle swarm optimization - cuckoo search algorithm

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Non-probabilistic method to consider uncertainties in structural damage identification based on Hybrid Jaya and Tree Seeds Algorithm

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Bayesian probabilistic approach for model updating and damage detection for a large truss bridge

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An efficient adaptive sequential Monte Carlo method for Bayesian model updating and damage detection

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Mechanism of the effect of temperature on frequency based on long-term monitoring of an arch bridge

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Damage detection in Ca-Non Bridge using transmissibility and artificial neural networks

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Structural Damage Identification Based on l1Regularization and Bare Bones Particle Swarm Optimization with Double Jump Strategy

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Structural damage identification using modified Hilbert–Huang transform and support vector machine

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Convolutional neural network based structural health monitoring for rocking bridge system by encoding time‐series into images

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Bridge Damage Identification from Moving Load Induced Deflection Based on Wavelet Transform and Lipschitz Exponent

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Application of a mode shape derivative-based damage index in artificial neural network for structural damage identification in shear frame building

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Guided Modal Strain Energy-Based Approach for Structural Damage Identification Using Tug-of-War Optimization Algorithm

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Structural Damage Identification Under Temperature Variations Based on PSO–CS Hybrid Algorithm

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Damage identification method of prestressed concrete beam bridge based on convolutional neural network

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Bayesian damage identification based on autoregressive model and MH-PSO hybrid MCMC sampling method

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Structural damage detection based on MAC flexibility and frequency using moth-flame algorithm

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Uncertainty Handling in Structural Damage Detection via Non-Probabilistic Meta-Models and Interval Mathematics, a Data-Analytics Approach

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Modeling of Temperature Time-Lag Effect for Concrete Box-Girder Bridges

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A novel PSO-based algorithm for structural damage detectionusing Bayesian multi-sample objective function

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