structural-health-monitoring

Collection of works in my PhD at Virginia Tech, mostly focused on computer vision and machine learning applications in structural inspection and structural health monitoring.

Incorporating Inductive Bias into Deep Learning: A Perspective from Automated Visual Inspection in Aircraft Maintenance

Application of LSTM network for Structural Health Monitoring & Non-Destructive Testing

A Scalable Deep Learning Framework for Wave-Based Inverse Problems

A specialized instance segmentation dataset for concrete crack detection using Keras Mask R-CNN with pixel-wise annotations for structural health monitoring.

CONCEPT is a dataset of lamb-wave measured in composite structures in healthy and damaged states. This experiment was conducted at the SHM Lab from UNESP Ilha Solteira.

Repository to tutorials on the implementation of the Transitional Ensemble Markov Chain Monte Carlo (TEMCMC) sampler for Bayesian Model Updating.

ViMag: A Visual Vibration Toolbox

Project for dynamic identification and structural health monitoring of real structures using data-based statistical time series analysis

BERT is a dataset that presents vibration tests performed on an aluminum beam with a bolted joint with various tightening torques and hysteresis effects. This experiment was conducted at the SHM Lab from UNESP Ilha Solteira.

This repository contains a novel time-series dataset for impact detection and localization on a plastic thin-plate, towards Structural Health Monitoring applications, using ceramic piezoelectric transducers (PZTs) connected to an Internet of Things (IoT) device.

Domain Knowledge based data augementation for Structural Health Monitoring

Frequency Domain Decomposition

Perception Modelling by Invariant Representation of Deep Learning for Automated Structural Diagnostic in Aircraft Maintenance: A Study Case using DeepSHM

Structural Health Monitoring of Wind Turbines

Interactive Defect Quantification through Extended Reality

This project presents the possibility of utilizing Convolutional Neural Networks in image processing to analyze structures and the possible damages that have occured to them

Learning based Image Scale Estimation (LISE) for Quantitative Visual Inspection

Toolbox for analyzing bridges using ANN and other methods