A combined finite element and hierarchical Deep learning approach for structural health monitoring: Test on a pin-joint composite truss structure

A FE model updating technique based on SAP2000-OAPI and enhanced SOS algorithm for damage assessment of full-scale structures

(2020) D. Dinh-Cong et al.   APPLIED SOFT COMPUTING

Vibration signal denoising for structural health monitoring by residual convolutional neural networks

(2020) Gao Fan et al.   MEASUREMENT

Towards semi-supervised and probabilistic classification in structural health monitoring

(2020) L.A. Bull et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

An effective deep feedforward neural networks (DFNN) method for damage identification of truss structures using noisy incomplete modal data

(2020) Tam T. Truong et al.   Journal of Building Engineering

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

(2020) Onur Avci et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Vibration-response-only statistical time series structural health monitoring methods: A comprehensive assessment via a scale jacket structure

(2019) Nikos A Spanos et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Non-probabilistic method to consider uncertainties in frequency response function for vibration-based damage detection using Artificial Neural Network

(2019) Khairul H. Padil et al.   JOURNAL OF SOUND AND VIBRATION

Hierarchical fault classification for resource constrained systems

(2019) Stephen Adams et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Monitoring of multi-bolt connection looseness using entropy-based active sensing and genetic algorithm-based least square support vector machine

(2019) Furui Wang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Structural damage identification based on autoencoder neural networks and deep learning

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

Prediction of contact stiffness in bolted interface with natural frequency experiment and FE analysis

(2018) Guang Zhao et al.   TRIBOLOGY INTERNATIONAL

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Probability distribution of decay rate: a statistical time-domain damping parameter for structural damage identification

(2018) Ali M Ay et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Hierarchical convolutional neural networks for fashion image classification

(2018) Yian Seo et al.   EXPERT SYSTEMS WITH APPLICATIONS

Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

(2017) Osama Abdeljaber et al.   JOURNAL OF SOUND AND VIBRATION

Automated structural health monitoring based on adaptive kernel spectral clustering

(2017) Rocco Langone et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Active vibration-based structural health monitoring system for wind turbine blade: Demonstration on an operating Vestas V27 wind turbine

(2017) Dmitri Tcherniak et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Machine learning algorithms for damage detection: Kernel-based approaches

(2016) Adam Santos et al.   JOURNAL OF SOUND AND VIBRATION

Vibration characteristics and damage detection in a suspension bridge

(2016) Wasanthi R. Wickramasinghe et al.   JOURNAL OF SOUND AND VIBRATION

A probabilistic multi-class classifier for structural health monitoring

(2015) Nazih Mechbal et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Structural health monitoring with statistical methods during progressive damage test of S101 Bridge

(2014) Michael Döhler et al.   ENGINEERING STRUCTURES

Bolt loosening analysis and diagnosis by non-contact laser excitation vibration tests

(2013) Feblil Huda et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Vibration based health monitoring for a lightweight truss structure: Experimental assessment of several statistical time series methods

(2010) F.P. Kopsaftopoulos et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Statistical pattern recognition for Structural Health Monitoring using time series modeling: Theory and experimental verifications

(2009) Mustafa Gul et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING