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

2016/11/10 by Osama Abdeljaber, Onur Avcı, Onur Avci +4 · 11 citations
Engineering · #Structural Health Monitoring Techniques #Infrastructure Maintenance and Monitoring #Ultrasonics and Acoustic Wave Propagation

paper · doi:10.1016/j.jsv.2016.10.043

Cited by

• Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019
• Structural identification with physics-informed neural ordinary differential equations
• Domain Adaptation in Structural Health Monitoring of Civil Infrastructure: A Systematic Review
• A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects
• Deep recurrent-convolutional neural network learning and physics Kalman filtering comparison in dynamic load identification
• A convolutional neural network deep learning method for model class selection
• A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
• Transformer-Based Approach to Optimal Sensor Placement for Structural Health Monitoring of Probe Cards
• 1D convolutional neural networks and applications: A survey
• Experimental validation of universal filtering and smoothing for linear system identification using adaptive tuning
• Quantifying the Value of Seismic Structural Health Monitoring for post-earthquake recovery of electric power system in terms of resilience enhancement