相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Autonomous bolt loosening detection using deep learning
Yang Zhang et al.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2020)
Dirt and mud detection and diagnosis on a wind turbine blade employing guided waves and supervised learning classifiers
Alfredo Arcos Jimenez et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)
Crack and Noncrack Classification from Concrete Surface Images Using Machine Learning
Hyunjun Kim et al.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2019)
AE monitoring of a concrete arch road tunnel: Damage evolution and localization
Amedeo Manuello et al.
ENGINEERING FRACTURE MECHANICS (2019)
Automatic crack detection for tunnel inspection using deep learning and heuristic image post-processing
Eftychios Protopapadakis et al.
APPLIED INTELLIGENCE (2019)
Deep learning-based automatic volumetric damage quantification using depth camera
Gustavo H. Beckman et al.
AUTOMATION IN CONSTRUCTION (2019)
Remote proximity proximity monitoring between mobile construction resources using camera-mounted UAVs
Daeho Kim et al.
AUTOMATION IN CONSTRUCTION (2019)
Linear and nonlinear features and machine learning for wind turbine blade ice detection and diagnosis
Alfredo Arcos Jimenez et al.
RENEWABLE ENERGY (2019)
Prediction of long-term temperature effect in structural health monitoring of concrete dams using support vector machines with Jaya optimizer and salp swarm algorithms
Fei Kang et al.
ADVANCES IN ENGINEERING SOFTWARE (2019)
DeepCrack: A deep hierarchical feature learning architecture for crack segmentation
Yahui Liu et al.
NEUROCOMPUTING (2019)
Automatic damage detection of historic masonry buildings based on mobile deep learning
Niannian Wang et al.
AUTOMATION IN CONSTRUCTION (2019)
A vision-based method for crack detection in gusset plate welded joints of steel bridges using deep convolutional neural networks
Cao Vu Dung et al.
AUTOMATION IN CONSTRUCTION (2019)
Multi-classifier for reinforced concrete bridge defects
Philipp Huethwohl et al.
AUTOMATION IN CONSTRUCTION (2019)
Automated real-time damage detection strategy using raw dynamic measurements
Rhara de Almeida Cardoso et al.
ENGINEERING STRUCTURES (2019)
Automatic pixel-level multiple damage detection of concrete structure using fully convolutional network
Shengyuan Li et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2019)
Image-based post-disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization
Xiao Liang
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2019)
Zernike-moment measurement of thin-crack width in images enabled by dual-scale deep learning
FuTao Ni et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2019)
Wider or Deeper: Revisiting the ResNet Model for Visual Recognition
Zifeng Wu et al.
PATTERN RECOGNITION (2019)
Exploring and cleaning big data with random sample data blocks
Salman Salloum et al.
JOURNAL OF BIG DATA (2019)
Robust Concrete Crack Detection Using Deep Learning-Based Semantic Segmentation
Donghan Lee et al.
INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES (2019)
Comprehensive damage assessment in concrete affected by different internal swelling reaction (ISR) mechanisms
L. F. M. Sanchez et al.
CEMENT AND CONCRETE RESEARCH (2018)
Deep Transfer Learning for Image-Based Structural Damage Recognition
Yuqing Gao et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2018)
Infrared thermography model for automated detection of delamination in RC bridge decks
Tarek Omar et al.
CONSTRUCTION AND BUILDING MATERIALS (2018)
A novel unsupervised deep learning model for global and local health condition assessment of structures
Mohammad Hossein Rafiei et al.
ENGINEERING STRUCTURES (2018)
NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naive Bayes Data Fusion
Fu-Chen Chen et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2018)
Applications of neural network models for structural health monitoring based on derived modal properties
Chia-Ming Chang et al.
MEASUREMENT (2018)
On switching response surface models, with applications to the structural health monitoring of bridges
K. Worden et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
Damage Detection of a Concrete Column Subject to Blast Loads Using Embedded Piezoceramic Transducers
Kai Xu et al.
SENSORS (2018)
Application of Crack Identification Techniques for an Aging Concrete Bridge Inspection Using an Unmanned Aerial Vehicle
In-Ho Kim et al.
SENSORS (2018)
Automatic Pixel-Level Crack Detection and Measurement Using Fully Convolutional Network
Xincong Yang et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2018)
Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete
Sattar Dorafshan et al.
CONSTRUCTION AND BUILDING MATERIALS (2018)
Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique
Byunghyun Kim et al.
SENSORS (2018)
An Integrated Machine Learning Algorithm for Separating the Long-Term Deflection Data of Prestressed Concrete Bridges
Xijun Ye et al.
SENSORS (2018)
Damage degree identification of crane girder based on the support vector machine
Xiangdong Li et al.
2018 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-CHONGQING 2018) (2018)
Statistical pattern recognition approach for long-time monitoring of the G.Meazza stadium by means of AR models and PCA
Alessio Datteo et al.
ENGINEERING STRUCTURES (2017)
Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing
Hyunjun Kim et al.
SENSORS (2017)
Early detection of anomalies in dam performance: A methodology based on boosted regression trees
Fernando Salazar et al.
STRUCTURAL CONTROL & HEALTH MONITORING (2017)
Concrete dam deformation prediction model for health monitoring based on extreme learning machine
Fei Kang et al.
STRUCTURAL CONTROL & HEALTH MONITORING (2017)
A novel machine learning-based algorithm to detect damage in high-rise building structures
Mohammad Hossein Rafiei et al.
STRUCTURAL DESIGN OF TALL AND SPECIAL BUILDINGS (2017)
Anomaly detection in earth dam and levee passive seismic data using support vector machines and automatic feature selection
Wendy D. Fisher et al.
JOURNAL OF COMPUTATIONAL SCIENCE (2017)
Wall-climbing robot for non-destructive evaluation using impact-echo and metric learning SVM
Bing Li et al.
INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS (2017)
Detection of fatigue cracking in steel bridge girders: A support vector machine approach
Hassene Hasni et al.
ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING (2017)
Overall assessment of Alkali-Aggregate Reaction (AAR) in concretes presenting different strengths and incorporating a wide range of reactive aggregate types and natures
L. F. M. Sanchez et al.
CEMENT AND CONCRETE RESEARCH (2017)
A Stereovision-based Crack Width Detection Approach for Concrete Surface Assessment
Baohua Shan et al.
KSCE JOURNAL OF CIVIL ENGINEERING (2016)
Life-cycle of structural systems: recent achievements and future directions
Dan M. Frangopol et al.
STRUCTURE AND INFRASTRUCTURE ENGINEERING (2016)
Use of Damage Rating Index to Quantify Alkali-Silica Reaction Damage in Concrete: Fine versus Coarse Aggregate
L. F. M. Sanchez et al.
ACI MATERIALS JOURNAL (2016)
A machine learning-based algorithm for processing massive data collected from the mechanical components of movable bridges
F. Necati Catbas et al.
AUTOMATION IN CONSTRUCTION (2016)
Comparison of Visual Inspection and Structural-Health Monitoring As Bridge Condition Assessment Methods
Duzgun Agdas et al.
JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES (2016)
Signal Processing Techniques for Vibration-Based Health Monitoring of Smart Structures
Juan Pablo Amezquita-Sanchez et al.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING (2016)
A clustering approach for structural health monitoring on bridges
Alberto Diez et al.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING (2016)
Machine learning: Trends, perspectives, and prospects
M. I. Jordan et al.
SCIENCE (2015)
An empirical comparison of machine learning techniques for dam behaviour modelling
F. Salazar et al.
STRUCTURAL SAFETY (2015)
Time-varying identification model for dam behavior considering structural reinforcement
Huaizhi Su et al.
STRUCTURAL SAFETY (2015)
Application of support vector machine for pattern classification of active thermometry-based pipeline scour monitoring
Xuefeng Zhao et al.
STRUCTURAL CONTROL & HEALTH MONITORING (2015)
Quantitative structure-activity relationship model for amino acids as corrosion inhibitors based on the support vector machine and molecular design
Hongxia Zhao et al.
CORROSION SCIENCE (2014)
Predicting piezometric water level in dams via artificial neural networks
Vesna Rankovic et al.
NEURAL COMPUTING & APPLICATIONS (2014)
Development of support vector regression identification model for prediction of dam structural behaviour
Vesna Rankovic et al.
STRUCTURAL SAFETY (2014)
Two online dam safety monitoring models based on the process of extracting environmental effect
Lin Cheng et al.
ADVANCES IN ENGINEERING SOFTWARE (2013)
Integration of Artificial Neural Networks with Radial Basis Function Interpolation in Earthfill Dam Seepage Modeling
Vahid Nourani et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2013)
Monitoring of long-term static deformation data of Fei-Tsui arch dam using artificial neural network-based approaches
Ching-Yun Kao et al.
STRUCTURAL CONTROL & HEALTH MONITORING (2013)
A Fully Non-Contact Ultrasonic Propagation Imaging System for Closed Surface Crack Evaluation
D. Dhital et al.
EXPERIMENTAL MECHANICS (2012)
Extreme Learning Machine for Regression and Multiclass Classification
Guang-Bin Huang et al.
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS (2012)
Tall Buildings and Urban Habitat of the 21st Century: A Global Perspective
Mir M. Ali et al.
BUILDINGS (2012)
Interpretation of concrete dam behaviour with artificial neural network and multiple linear regression models
J. Mata
ENGINEERING STRUCTURES (2011)
A robust automatic crack detection method from noisy concrete surfaces
Yusuke Fujita et al.
MACHINE VISION AND APPLICATIONS (2011)
Long-Term Monitoring and Identification of Bridge Structural Parameters
Serdar Soyoz et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2009)
Overview of current and future energy storage technologies for electric power applications
Ioannis Hadjipaschalis et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2009)
Seismic damage identification in buildings using neural networks and modal data
Maria P. Gonzalez et al.
COMPUTERS & STRUCTURES (2008)
Damage detection of truss bridge joints using Artificial Neural Networks
M. Mehrjoo et al.
EXPERT SYSTEMS WITH APPLICATIONS (2008)
Structural health monitoring for a wind turbine system: a review of damage detection methods
Chia Chen Ciang et al.
MEASUREMENT SCIENCE AND TECHNOLOGY (2008)
Convex incremental extreme learning machine
Guang-Bin Huang et al.
NEUROCOMPUTING (2007)
Structural health monitoring of civil infrastructure
J. M. W. Brownjohn
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2007)
Extreme learning machine: Theory and applications
Guang-Bin Huang et al.
NEUROCOMPUTING (2006)
Experimental study of laser Doppler vibrometer and ambient vibration for vibration-based damage detection
Dionysius M. Siringoringo et al.
ENGINEERING STRUCTURES (2006)
Wireless detection of internal delamination cracks in CFRP laminates using oscillating frequency changes
R Matsuzaki et al.
COMPOSITES SCIENCE AND TECHNOLOGY (2006)
A new structural health monitoring system for composite laminates
B Verijenko et al.
COMPOSITE STRUCTURES (2005)
Neural network estimation of ground peak acceleration at stations along Taiwan high-speed rail system
T Kerh et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2005)
Evaluation of the expansion attained to date by concrete affected by alkali-silica reaction.: Part III:: Application to existing structures
MA Bérubé et al.
CANADIAN JOURNAL OF CIVIL ENGINEERING (2005)
Characterization of microscopic damage in composite laminates and real-time monitoring by embedded optical fiber sensors
N Takeda
INTERNATIONAL JOURNAL OF FATIGUE (2002)
Automated modal analysis by scanning laser vibrometry: Problems and uncertainties associated with the scanning system calibration
M Martarelli et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2001)