Unsupervised deep learning method for bridge condition assessment based on intra-and inter-class probabilistic correlations of quasi-static responses

Identification of time-varying nonlinear structural physical parameters by integrated WMA and UKF/UKF-UI

(2021) Ning Yang et al.   NONLINEAR DYNAMICS

Review of Bridge Structural Health Monitoring Aided by Big Data and Artificial Intelligence: From Condition Assessment to Damage Detection

(2020) Limin Sun et al.   JOURNAL OF STRUCTURAL ENGINEERING

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

(2020) Mohsen Azimi et al.   SENSORS

Detecting structural damage under unknown seismic excitation by deep convolutional neural network with wavelet-based transmissibility data

(2020) Ying Lei et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Structural damage identification based on unsupervised feature-extraction via Variational Auto-encoder

(2020) Xirui Ma et al.   MEASUREMENT

Machine learning paradigm for structural health monitoring

(2020) Yuequan Bao et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

(2019) Billie F. Spencer et al.   Engineering

The State of the Art of Data Science and Engineering in Structural Health Monitoring

(2019) Yuequan Bao et al.   Engineering

A novel unscented Kalman filter for recursive state-input-system identification of nonlinear systems

(2019) Ying Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Clarifying and quantifying the geometric correlation for probability distributions of inter-sensor monitoring data: A functional data analytic methodology

(2019) Zhicheng Chen et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A novel unsupervised deep learning model for global and local health condition assessment of structures

(2018) Mohammad Hossein Rafiei et al.   ENGINEERING STRUCTURES

Condition assessment of cables by pattern recognition of vehicle-induced cable tension ratio

(2018) Shunlong Li et al.   ENGINEERING STRUCTURES

Structural damage identification based on autoencoder neural networks and deep learning

(2018) Chathurdara Sri Nadith Pathirage et al.   ENGINEERING STRUCTURES

1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data

(2018) Osama Abdeljaber et al.   NEUROCOMPUTING

Computer vision and deep learning–based data anomaly detection method for structural health monitoring

(2018) Yuequan Bao et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Development and application of a deep learning–based sparse autoencoder framework for structural damage identification

(2018) Chathurdara Sri Nadith Pathirage et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Convolutional neural network-based data anomaly detection method using multiple information for structural health monitoring

(2018) Zhiyi Tang et al.   Structural Control & Health Monitoring

Malfunction diagnosis of sensors based on correlation of measurements

(2017) Wei Lu et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Strain features and condition assessment of orthotropic steel deck cable-supported bridges subjected to vehicle loads by using dense FBG strain sensors

(2017) Shiyin Wei et al.   Smart Materials and Structures

Robust dimensionality reduction and damage detection approaches in structural health monitoring

(2014) Nguyen LD Khoa et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

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

(2013) Jiangpeng Shu et al.   ENGINEERING STRUCTURES

Multivariate statistical analysis for early damage detection

(2013) João Pedro Santos et al.   ENGINEERING STRUCTURES

Real-time identification of time-varying tension in stay cables by monitoring cable transversal acceleration

(2013) Hui Li et al.   Structural Control & Health Monitoring

In-Service Condition Assessment of Bridge Deck Using Long-Term Monitoring Data of Strain Response

(2011) Y. Q. Ni et al.   Journal of Bridge Engineering