Sökning: "railway sleepers"

Visar resultat 1 - 5 av 20 uppsatser innehållade orden railway sleepers.

1. 1. Data Augmentations for Improving Vision-Based Damage Detection : in Land Transport Infrastructure

   Master-uppsats, KTH/Lantmäteri – fastighetsvetenskap och geodesi

   Författare :Punnawat Siripatthiti; [2023]
   Nyckelord :Computer Vision; Data Augmentation; Object Detection; Crack Detection; Road Damage Detection; Sleeper Defect Detection; datorseende; dataökning; objektdetektering; sprickdetektering; vägbeläggning; järnvägsslipers;

   Sammanfattning : Crack, a typical term most people know, is a common form of distress or damage in road pavements and railway sleepers. It poses significant challenges to their structural integrity, safety, and longevity. Over the years, researchers have developed various data-driven technologies for image-based crack detection in road and sleeper applications. LÄS MER

3. 2. Railway Fastener Fault Detection using YOLOv5

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för visuell information och interaktion

   Författare :Alva Efraimsson; Elin Lemón; [2022]
   Nyckelord :Fastener Fault Detection; Object Detection; YOLOv5; Machine Learning; Railway Maintenance; Proactive Maintenance;

   Sammanfattning : The railway system is an important part of the sociotechnical society, as it enables efficient, reliable, and sustainable transportation of both people and goods. Despite increasing investments, the Swedish railway has encountered structural and technical problems due to worn-out infrastructure as a result of insufficient maintenance. LÄS MER

4. 3. Detecting Defective Rail Joints on the Swiss Railways with Inception ResNet V2 : Simplifying Predictive Maintenance of Railway Infrastructure

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

   Författare :Anton Lu; [2022]
   Nyckelord :Rail Defect Detection; Rail Image Classification; Rail Joints; Object Detection; Image Classification; Deep Learning; Järnvägsfeldetektering; Järnvägsbildigenkänning; Järnvägsskarvar; Objectigenkänning; Bildklassificering; Djupinlärning;

   Sammanfattning : Manual investigation of railway infrastructure is a labor-intensive and time-consuming task, and automating it has become a high priority for railway operators to reduce unexpected infrastructure expenditure. In this thesis, we propose a new image classification approach for classifying defect and non-defective rail joints in image data, based on previous fault detection algorithms using object detection. LÄS MER

5. 4. Influence of load distribution on trough bridges

   Master-uppsats, Luleå tekniska universitet/Institutionen för samhällsbyggnad och naturresurser

   Författare :Jacob Gustafsson; [2021]
   Nyckelord :Bridge; Trough bridge; Concrete; Load distribution; Ballast;

   Sammanfattning : There are approximately 4000 railway bridges in Sweden and a common construction type is the short span concrete trough bridge. With the current standards the load distribution through ballast is assumed to be uniformly distributed with a distribution slope of 2:1 according to the Swedish Administration of Transport or 4:1 according to Eurocode 1. LÄS MER

7. 5. A Machine Learning-Based Approach for Fault Detection of Railway Track and its Components

   Master-uppsats, Luleå tekniska universitet/Drift, underhåll och akustik

   Författare :Johnny Asber; [2020]
   Nyckelord :Condition Based Maintenance in Railway; Machine Learning; Deep Learning; ResNet-50;

   Sammanfattning : The hard equation of railway safety versus the high commercial profits can only be achieved through the use of new inspection methods supported by modern technologies. The track and its components can have different types of troubles, such as rail surface defects, broken sleepers, missing fasteners, and irregular ballast levels. LÄS MER