Sökning: "vehicle fault detection"
Visar resultat 1 - 5 av 20 uppsatser innehållade orden vehicle fault detection.
1. Audio Anomaly Detection in Cars
Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaperSammanfattning : Audio anomaly detection in the context of car driving is a crucial task for ensuring vehicle safety and identifying potential faults. This paper aims to investigate and compare different methods for unsupervised audio anomaly detection using a data set consisting of recorded audio data from fault injections and normal "no fault" driving. LÄS MER
2. A Deep Learning Approach To Vehicle Fault Detection Based On Vehicle Behavior
Master-uppsats, Malmö universitet/Institutionen för datavetenskap och medieteknik (DVMT)Sammanfattning : Vehicles and machinery play a crucial role in our daily lives, contributing to our transportationneeds and supporting various industries. As society strives for sustainability, the advancementof technology and efficient resource allocation become paramount. LÄS MER
3. Exogenous Fault Detection in Aerial Swarms of UAVs
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : In this thesis, the main focus is to formulate and test a suitable model forexogenous fault detection in swarms containing unmanned aerial vehicles(UAVs), which are aerial autonomous systems. FOI Swedish DefenseResearch Agency provided the thesis project and research question. LÄS MER
4. Effektivisering av felsökningssystem för stridsfordon
Uppsats för yrkesexamina på grundnivå, Umeå universitet/Institutionen för tillämpad fysik och elektronikSammanfattning : This study was conducted in collaboration with BAE Systems Hägglunds in Örnsköldsvik. They wanted help with their objective of researching the necessary components of a testability analysis. The primary goal was to enhance the efficiency of troubleshooting and diagnostics for their combat vehicle, Cv90. LÄS MER
5. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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