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

Azimi, Mohsen, Eslamlou, Armin, Pekcan, Gokhan·2020·Sensors
DOI 10.3390/s20102778

Cites (232)

Items 201–233 of 233

  1. Structural damage detection using hybrid deep learning algorithm
    Đặng Việt Hưng, Ha Manh Hung, Pham Hoang Anh, Nguyen Truong Thang · 2020 · Journal of Science and Technology in Civil Engineering (JSTCE) - HUCE
  2. Vibration-Based Support Vector Machine for Structural Health Monitoring
    Hong Xia Pan, Mohsen Azimi, Guoqing Gui, Fei Yan, Zhibin Lin · 2017 · Lecture notes in civil engineering
  3. Automated damage-sensitive feature extraction using unsupervised convolutional neural networks
    Young‐Jin Cha, Zilong Wang · 2018 · Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
  4. Three-dimensional multiscale finite element models for in-service performance assessment of bridges
    Maryam Mashayekhi, Erin Santini‐Bell · 2018 · Computer-Aided Civil and Infrastructure Engineering
  5. Online Sequential Extreme Learning Machine for Vibration-Based Damage Assessment Using Transmissibility Data
    Viviana Meruane · 2015 · Journal of Computing in Civil Engineering
  6. Deep learning-based concrete crack detection using hybrid images
    Keunyoung Jang, Byunghyun Kim, Soojin Cho, Yun‐Kyu An · 2018 · Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
  7. Potential and Limitations of a Deconvolution Approach for Guided Wave Structural Health Monitoring
    T Cicero, P. Cawley, F. Simonetti, Stan I. Rokhlin · 2009 · Structural Health Monitoring
  8. Frequency domain CNN and dissipated energy approach for damage detection in building structures
    Mario López-Pacheco, Jesús Morales‐Valdez, Wen Yu · 2020 · Soft Computing
  9. Vision-based concrete crack detection technique using cascade features
    Young‐Jin Cha, Dharshan Lokekere Gopal, Rahmat Ali · 2018 · Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
  10. Image-Based Comprehensive Maintenance and Inspection Method for Bridges Using Deep Learning
    Xuefeng Zhao, Shengyuan Li, Hongguo Su, Lei Zhou, Kenneth J. Loh · 2018 · ASME Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS)
  11. Eigen-Level Data Fusion Model by Integrating Rough Set and Probabilistic Neural Network for Structural Damage Detection
    Shao-Fei Jiang, Chunming Zhang, Juan Yao · 2011 · Advances in Structural Engineering
  12. Automated Vision-Based Loosened Bolt Detection Using the Cascade Detector
    Lovedeep Ramana, Wooram Choi, Young‐Jin Cha · 2017 · Conference proceedings of the Society for Experimental Mechanics
  13. Performance comparison of deep learning frameworks in image classification problems using convolutional and recurrent networks
    Rubén D. Fonnegra, Bryan Blair, Gloria M. Díaz · 2017 · IEEE Colombian Conference on Communications and Computing (COLCOM)
  14. Vision-based Automated Bridge Component Recognition Integrated With High-level Scene Understanding
    Yasutaka Narazaki, Vedhus Hoskere, Tu A. Hoang, Billie F. Spencer · 2018 · arXiv (Cornell University)
  15. A Two-Stage Crack Detection Method for Concrete Bridges Using Convolutional Neural Networks
    Yundong Li, Weigang Zhao, Xueyan Zhang, Qichen ZHOU · 2018 · IEICE Transactions on Information and Systems
  16. Prediction of Unmeasured Mode Shape Using Artificial Neural Network for Damage Detection
    Lyn Dee Goh, Norhisham Bakhary, Alias Abdul Rahman, B. H. Ahmad · 2013 · Jurnal Teknologi
  17. An Experimental Technique for Structural Diagnostic Based on Laser Vibrometry and Neural Networks
    Paolo Castellini, Gian Marco Revel · 2000 · Shock and Vibration
  18. Automated Bridge Component Recognition using Video Data
    Yasutaka Narazaki, Vedhus Hoskere, Tu A. Hoang, Billie F. Spencer · 2018 · arXiv (Cornell University)
  19. Swarm-based Parallel Control of Adjacent Irregular Buildings Considering Soil–structure Interaction
    Mohsen Azimi, Asghar Molaei-Yeznabad · 2020 · Journal of Sensor and Actuator Networks
  20. Fatigue Crack Detection Using Unmanned Aerial Systems in Under-Bridge Inspection
    Sattar Dorafshan, Marc Maguire, Nathan V. Hoffer, Calvin Coopmans · 2017 · Digital Commons - USU (Utah State University)
  21. Damage detection with an autonomous UAV using deep learning
    Young‐Jin Cha, Dongho Kang · 2018 · Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
  22. Automated Vision-based Bridge Component Extraction Using Multiscale Convolutional Neural Networks
    Yasutaka Narazaki, Vedhus Hoskere, Tu A. Hoang, Billie F. Spencer · 2018 · arXiv (Cornell University)
  23. Detection of Cracks in Concrete Structures from Digital Camera Images
    Suguru Kaneko, Soichi Oka, Naoki Matsumiya · 2012 · NTT technical review
  24. NEW DIRECTIONS IN STRUCTURAL HEALTH MONITORING
    Khalid M. Mosalam, Sifat Muin, Yuqing Gao · 2019 · NED University Journal of Research
  25. Identification of Defects in Pavement Images Using Deep Convolutional Neural Networks
    А. N. Soloviev, Boris Vladimirovich Sobol, Pavel Vladimirovich Vasiliev · 2019 · Springer proceedings in physics
  26. FATIGUE ASSESSMENT OF COMPLEX STRUCTURAL COMPONENTS OF STEEL BRIDGES INTEGRATING FINITE ELEMENT MODELS AND FIELD-COLLECTED DATA
    Maryam Mashayekhizadeh · 2019 · University of New Hampshire Scholars Repository (University of New Hampshire at Manchester)
  27. Rebar Detection and Localization for Non-destructive Infrastructure Evaluation of Bridges Using Deep Residual Networks
    Habib Ahmed, Hung Manh La, Gökhan Pekcan · 2019 · Lecture notes in computer science
  28. Small Unmanned Aerial Vehicle (sUAV) Inspections in GPS Denied Area beneath Bridges
    Andrew P. Tomiczek, Jennifer A. Bridge, PETER G. IFJU, Travis J. Whitley, Chad Tripp, Andrew E. Ortega, Jeroen J. Poelstra, Stephen A. Gonzalez · 2018 · ASCE Structures Congress
  29. Nonlinear Seismic Response Reconstruction in Minimally Instrumented Buildings—Validation Using NEESWood Capstone Full-Scale Tests
    Milad Roohi, Eric M. Hernandez, David V. Rosowsky · 2019 · International Workshop on Structural Health Monitoring (IWSHM)
  30. Design of Structural Vibration Control Using Smart Materials and Devices for Earthquake-Resistant and Resilient Buildings
    Mohsen Azimi · 2017 · NDSU Repository (North Dakota State University)
  31. Deep learning-based rapid inspection of concrete structures
    Soojin Cho, Byunghyun Kim, Yein Lee · 2018 · Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
  32. Automated volumetric damage detection and quantification using region-based convolution neural networks and an inexpensive depth camera
    Young‐Jin Cha, Gustavo H. Beckman, Dimos J. Polyzois · 2018 · Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
  33. Deep Learning in Pavement Image Analysis and Automated Distress Detection: A Review
    Kasthurirangan Gopalakrishnan · 2018