Structural Health Monitoring System data analysis
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Updated
Jan 12, 2023 - MATLAB
Structural Health Monitoring System data analysis
Peak picking technique for basic frequency domain
A method for distributed modal parameters identifiction: distributed single-channel based parameters estimation at edge; multi-channel modal parameters integration at remote.
Open-source framework for infrastructure defect detection with transfer learning. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001503
This suite is an ensemble of codes developed to conduct a vibration analysis of a assembled structure.
Repository containing multiple EOV Mitigation Procedures for Structural Health Monitoring.
This repository is about reading and examining the shaker test data
Structural Health Monitoring of Wind Turbines
This repository contains Python scripts used to obtain results from the paper "A Latent Variable Approach for Mitigation of Environmental and Operational Variability in Vibration-Based SHM – A Linear Approach," presented at the EWSHM2024.
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.
Master's Thesis project on using machine learning as a part of a SHM assesment on a damaged, post-tensioned bridge.
Este benchmark ontains a set of data and information relating to researches involving Structural Integrity Monitoring (SHM) via Electromechanical Impedance (EMI) and Guided Waves (GW)
Results for Synthetic Data Augmentation: Deep Leaf-Bootstrapping GAN for Image-based Structural Scene and Damage Identification
Homeworks done for SHM Course on PPGEM (FEIS/UNESP).
Defect Detection and Quantification Toolbox
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.
Physical Knowledge assisted Machine Learning for Structural Health Monitoring
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
Frequency Domain Decomposition, including Peak Picking technique
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