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

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.

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

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.

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.

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

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.

ViMag: A Visual Vibration Toolbox

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

Frequency Domain Decomposition

Interactive Defect Quantification through Extended Reality

Domain Knowledge based data augementation for Structural Health Monitoring

Structural Health Monitoring of Wind Turbines

Toolbox for analyzing bridges using ANN and other methods

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

Structural Health Monitoring is one of the recent area which has not seen significant application of deep-neural network. The major limitation is due to unavailability of huge number of labeled data set.

Structural Health Monitoring System data analysis