Damage detection in a novel deep-learning framework: a robust method for feature extraction

Damage detection of building structures under ambient excitation through the analysis of the relationship between the modal participation ratio and story stiffness

(2018) Hyo Seon Park et al.   JOURNAL OF SOUND AND VIBRATION

Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization

(2018) Feng Jia et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Optimal filter design with progressive genetic algorithm for local damage detection in rolling bearings

(2018) Jacek Wodecki et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Data fusion of multi-scale representations for structural damage detection

(2018) Tian Guo et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A new surface fractal dimension for displacement mode shape-based damage identification of plate-type structures

(2018) Binkai Shi et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing

(2018) Haidong Shao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

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

A novel deep learning-based method for damage identification of smart building structures

(2018) Yang Yu et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Vibration-based structural health monitoring under changing environmental conditions using Kalman filtering

(2018) Kalil Erazo et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Wavelet-based analysis of mode shapes for statistical detection and localization of damage in beams using likelihood ratio test

(2017) Vahid Shahsavari et al.   ENGINEERING STRUCTURES

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

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

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

(2017) Khairul H. Padil et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A multi-stage approach for damage detection in structural systems based on flexibility

(2016) E. Grande et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A concept of complex-wavelet modal curvature for detecting multiple cracks in beams under noisy conditions

(2016) Mao-Sen Cao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Output-only damage detection using vehicle-induced displacement response and mode shape curvature index

(2016) Dongming Feng et al.   Structural Control & Health Monitoring

Two-dimensional curvature mode shape method based on wavelets and Teager energy for damage detection in plates

(2015) Wei Xu et al.   JOURNAL OF SOUND AND VIBRATION

Deep learning

(2015) Yann LeCun et al.   NATURE

Numerical and experimental analysis of uncertainty on modal parameters estimated with the stochastic subspace method

(2014) Gilles Tondreau et al.   JOURNAL OF SOUND AND VIBRATION

Damage identification for beams in noisy conditions based on Teager energy operator-wavelet transform modal curvature

(2013) Maosen Cao et al.   JOURNAL OF SOUND AND VIBRATION

Output-only structural health monitoring in changing environmental conditions by means of nonlinear system identification

(2013) Edwin Reynders et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Structural damage detection with limited input and output measurement signals

(2011) Ying Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Ultrahigh yield stress in a general electrorheological fluid under compression

(2010) Yu Tian et al.   Smart Materials and Structures