Sökning: "fault scenario"

Visar resultat 1 - 5 av 23 uppsatser innehållade orden fault scenario.

  1. 1. Adaptive Model-Based Temperature Monitoring for Electric Powertrains : Investigation and Comparative Analysis of Transfer Learning Approaches

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Chenzhou Huang; [2023]
    Nyckelord :Transfer Learning; Condition Monitoring; Domain Adaptation; Neural Network; Powerstrain.; Siirto-oppiminen; kunnonvalvonta; verkkotunnuksen mukauttaminen; neuroverkko; voimansiirto.; Överföring lärande; tillståndsövervakning; domänanpassning; neuralt nätverk; Powerstrain;

    Sammanfattning : In recent years, deep learning has been widely used in industry to solve many complex problems such as condition monitoring and fault diagnosis. Powertrain condition monitoring is one of the most vital and complicated problems in the automation industry since the condition of the drive affects its health, performance, and reliability. LÄS MER

  3. 2. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Ziyou Li; [2023]
    Nyckelord :Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

    Sammanfattning : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. LÄS MER

  4. 3. System impact of micro-production

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Industriell elektroteknik och automation

    Författare :Annie Haraldsson; [2023]
    Nyckelord :Fault ride through; LVRT; micro-production; solar production; photovoltaics; fault simulation; network modeling; power system disturbances; PMU-registrations; fault analysis; Technology and Engineering;

    Sammanfattning : The focus in this thesis has been active power from small scale solar production and what possible impacts an increased proportion of small scale production can have, in a larger context, during short circuit (SC) faults in the grid. The main research question prompting this work was whether active power from small scale solar pro- duction can help support voltages during SC faults, and meet LVRT-requirements in the RfG. LÄS MER

  5. 4. Uncertainty Analysis : Severe Accident Scenario at a Nordic Nuclear Power Plant

    Master-uppsats, Högskolan Dalarna/Institutionen för information och teknik

    Författare :Josefin Hedly; Mikaela De Young; [2023]
    Nyckelord :Nuclear power plant; microdata analysis; Random Forest; k-Nearest Neighbor; SVM;

    Sammanfattning : Nuclear Power Plants (NPP) undergo fault and sensitivity analysis with scenario modelling to predict catastrophic events, specifically releases of Cesium 137 (Cs-137). The purpose of this thesis is to find which of 108 input-features from Modular Accident Analysis Program (MAAP)simulation code are important, when there is large release of Cs-137 emissions. LÄS MER

  7. 5. Software Fault Detection in Telecom Networks using Bi-level Federated Graph Neural Networks

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Rémi Bourgerie; [2023]
    Nyckelord :5G 4G; Federated Learning; Graoh Learning; Graph-based Federated Learning; Temporal Graph Neural Networks; Time Series; Anomaly Detection; Fault Detection; 5G 4G; Federerat lärande; Graf lärande; Grafbaserat federerat lärande; Temporal Graph Neural Networks; Tidsserier; Upptäckt av anomalier; Upptäckt av fel;

    Sammanfattning : The increasing complexity of telecom networks, induced by the recent development of 5G, is a challenge for detecting faults in the telecom network. In addition to the structural complexity of telecommunication systems, data accessibility has become an issue both in terms of privacy and access cost. LÄS MER