Essays about: "Model based diagnostics"

Showing result 1 - 5 of 56 essays containing the words Model based diagnostics.

  1. 1. Battery Degradation and Health Monitoring in Lithium-Ion Batteries: An Evaluation of Parameterization and Sensor Fusion Strategies

    University essay from Linköpings universitet/Institutionen för systemteknik

    Author : Simon Saber; [2024]
    Keywords : model-based diagnostics; modellbaserad diagnostik;

    Abstract : The purpose of this project was to perform model-based diagnosis on Li-ion batteries using real-world data and sensor fusion algorithms. The data used in this project was collected and distributed by NASA and mainly consists of voltage and current measurements collected on numerous batteries that were repeatedly charged and discharged from their beginning of life, and until surpassing their end of life. READ MORE

  3. 2. Detection and Analysis of Anomalies in Tactical Sensor Systems through Structured Hypothesis Testing

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Fredrik Ohlson; [2023]
    Keywords : Tactical sensor systems; Sensor fusion; Model based diagnostics; Hypothesis testing; Taktiska sensor system; Sensor fusion; Modellbaserad diagnostisering; Hypotesprövning;

    Abstract : The project explores the domain of tactical sensor systems, focusing on SAAB Gripen’s sensor technologies such as radar, RWR (Radar Warning Receiver), and IRST (InfraRed Search and Track). The study employs structured hypothesis testing and model based diagnostics to examine the effectiveness of identifying and isolating deviations within these systems. READ MORE

  4. 3. A Machine Learning Approach on Analysis of Emission Spectra for Application in XFEL Experiments

    University essay from Uppsala universitet/Institutionen för fysik och astronomi

    Author : Harald Agelii; [2023]
    Keywords : Structural biology; Machine learning; Neural networks; emission spectrum; XFEL; X-ray free electron laser; SFX; Serial femtosecond X-ray crystallography; Proteins; Diagnostics;

    Abstract : In this thesis we investigate two potential applications of machine learning in the context of X-ray imaging and spectroscopy of biological samples, particularly such using X-ray free electron lasers (XFEL). We first investigate the possibility of using an emission spectrum, recorded from a sample after being probed by an incident X-ray, as a diagnostic tool. READ MORE

  5. 4. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods

    University essay from KTH/Fysik

    Author : Jeanette Marie Victoria Skeppland Hole; [2023]
    Keywords : ECG; ECG-analysis; QRS detector; Artificial Intelligence; Machine Learning; Deep neural networks; Long short-term memory; Convolutional neural network; Multilayer perceptron; EKG; EKG-analys; QRS detektor; Artificiell intelligens; Maskininlärning; Djupa neurala nätverk; Long short-term memory; Convolutional neural network; Multilayer perceptron;

    Abstract : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). READ MORE

  6. 5. Exploring Feature Selection Techniques for Machine Learning-based Melanoma Skin Cancer Classification

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Thomas Eriksson Mueller; Viktor Fornstad; [2023]
    Keywords : Machine Learning; Feature Selection; Melanoma; Computer Aided Diagnosis; Bachelor Thesis; Maskininlärning; Attributurval; Melanom; Datorstödd Diagnostik; Kandidatarbete;

    Abstract : One of the most globally common types of cancer is skin cancer, where melanoma is the most deadly form. An important and promising tool for diagnosing diseases such as skin cancer is computer aided diagnostics, a tool which utilizes machine learning to predict and classify cancer. READ MORE