An investigation into the advantages/disadvantages of some image noise removal techniques
-
Updated
Mar 11, 2018 - MATLAB
An investigation into the advantages/disadvantages of some image noise removal techniques
This repository is mainly to show the source code of neural component analysis.
CVA-PLSR for detecing faults in wind turbines
An automated production line visual inspection project for the identification of faults in Coca-Cola bottles leaving a production facility
This project is used to estimate, isolate and diagnose faults for a quadcopter and a PVTOL and also use a methods to control the system by tolerating the fault. Both quadcopter and PVTOL systems have nonlinear dynamics. The ways for fault estimation in this project consist of nonlinear AO and linear PIO for the PVTOL and qLPV PIO for the quadcop…
ahuDoctor detects hard and soft faults in multiple zone VAV AHU systems
MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).
MATLAB Code for abnormal detection using Support Vector Data Description (SVDD).
Este es el repositorio del artículo: "Detection of High-Resistance Connections in Industrial Power Systems During Induction Motor Start-up".
This project focuses on detecting and analyzing wear in drill bits during the drilling process. It involves studying three types of drill wear (flank, chisel, and outer corner wear) along with a healthy drill condition, using four corresponding datasets. The goal is to determine the most effective strategy for identifying drill bit wear.
Repository associated with the paper "Failure Detection and Fault Tolerant Control of a Jet-Powered Flying Humanoid Robot", published in IEEE ICRA 2023.
Chemical Engineering final-year project simulating a copper solvent extraction process with control valve faults using PCA and statistical classification to identify when the process enters a fault state
Add a description, image, and links to the fault-detection topic page so that developers can more easily learn about it.
To associate your repository with the fault-detection topic, visit your repo's landing page and select "manage topics."