Learning Based Experimental Approach For Condition Monitoring Using Laser Cameras In Railway Tracks

Santur, Yunus; Karaköse, Mehmet; Akın, Erhan

doi:10.18100/ijamec.270656

Cited by 19 publications

(15 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Cao et al [ 29 ] proposed a defect inspection method of rail surface based on the line-structured light. Santur et al [ 30 ] described a computer-vision based approach allowing for a fast-contactless detection of the rail surface and lateral defects such as fracture, scouring and wear with high accuracy. However, so far very few studies have reported methods for establishing a complete closed mesh model of scratch data which is the precondition of online rail-repair as mentioned above.…”

Section: Introductionmentioning

confidence: 99%

Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair

Guo

Huang

Liu

et al. 2020

Sensors

View full text Add to dashboard Cite

Rail surface scratching occurs with increasing frequency, seriously threatening the safety of vehicles and humans. Online repair of rail-surface scratches on damaged rails with scratch depths >1 mm is of increased importance, because direct rail-replacement has the disadvantages of long operation time, high manpower and high material costs. Advanced online repair of rail-surface scratch using three-dimensional (3D) metal printing technology such as laser cladding has become an increasing trend, desperately demanding a solution for the fast and precise establishment of a complete closed mesh model of rail-surface scratch data. However, there have only been limited studies on the topic so far. In this paper, the complete closed mesh model is well established based on a novel triangulation algorithm relying on the topological features of the point-cloud model (PCM) of scratch-data, which is obtained by implementing a scratch-data-computation process following a rail-geometric-feature-fused algorithm of random sample consensus (RANSAC) performed on the full rail-surface PCM constructed by 3D laser vision. The proposed method is universal for all types of normal-speed rails in China. Experimental results show that the proposed method can accurately acquire the complete closed mesh models of scratch data of one meter of 50 Kg/m-rails within 1 min.

show abstract

Section: Introductionmentioning

confidence: 99%

Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair

Guo

Huang

Liu

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Görüntü iĢleme teknikleri; bilgisayar türevi makineler tarafından, görüntüden anlam çıkarmak için kullanıldıkları gibi görüntüdeki gürültüleri eleme, görüntünün renk dengesini düzenleme ve daha yüksek çözünürlüklü görüntüler elde etme gibi görüntü iyileĢtirme iĢlemleri için de yaygın olarak kullanılırlar. GeliĢen teknoloji ile birlikte günümüzde görüntü iĢleme yöntemlerinin birçok alanda kullanımları mevcuttur [1,2].…”

Section: Gi̇ri̇ş (Introduction)unclassified

Optimizasyon Tabanlı Adaptif Görüntü Mozaikleme Algoritması

Karaköse

Yetiş

Müezzinoğlu

2017

Bilişim Teknolojileri Dergisi

Self Cite

View full text Add to dashboard Cite

Özet-Görüntü iĢleme, dijital ortamdaki görüntüler üzerinde bir amaç doğrultusunda gerekli analizler veya değiĢikliklerin yapılmasına yönelik çalıĢmaları kapsamaktadır. Son zamanlarda görüntü iĢleme tekniklerinden en çok kullanılanlardan biri de ortak sahneleri içeren resimler üzerinde iĢlem yapan ve bunları çakıĢtırarak birleĢtiren görüntü mozaikleme iĢlemidir. Bu çalıĢmada kendi kameramızdan elde ettiğimiz görüntüler üzerinde MATLAB ortamında görüntü mozaikleme iĢlemi gerçekleĢtirilmiĢtir. Görüntü mozaikleme için, özellik tabanlı görüntü mozaiklemenin temel adımları olan anahtar noktaların tespiti, bu noktaların eĢleĢtirilmesi, hatalı eĢleĢmelerin elenmesi ve homografi tahmini uygulanmıĢtır. Uygulamada özellik çıkarımı için SIFT algoritması seçilmiĢ, elde edilen homografi matrisi yardımı ile gerekli dönüĢüm iĢlemleri uygulanarak görüntü mozaikleme iĢlemi gerçekleĢtirilmiĢtir. Mozaikleme iĢleminin kalitesini artırmak adına optimizasyon yöntemi olan genetik algoritmadan yararlanılmıĢtır. Uygulamada giriĢ görüntü sayıları ve mozaikleme parametreleri farklı seçilerek çeĢitli karĢılaĢtırma iĢlemleri yapılmıĢtır.Anahtar Kelimeler-Genetik algoritma, Görüntü iĢleme, Görüntü mozaikleme, Optimizasyon. Optimization Based Adaptive Image Mosaicing AlgorithmAbstract-Image processing involves studies to make necessary analyzes or changes in an image aimed at digital images. One of the most recent use of image processing techniques is image mosaicking, which processes and combines images containing common scenes. In this study, we performed image mosaicing in the MATLAB environment on the images we acquired from our own camera. The key steps for feature-based image mosaicking which are detection of key points, matching of these points, elimination of mismatches and homography estimation are applied for image mosaicing. In the application, the SIFT algorithm was selected for feature extraction and image transformation was performed with the help of the obtained homography matrix. In order to increase the quality of the mosaic process, genetic algorithm, which is an optimization method, has been used. Various comparisons were performed by taking different input counts and by choosing different image mosaicing parameters.

show abstract

“…There are many faults on the rail line. As a result of these failures, the train and rail track components may be damaged [1][2][3]. Generally, the areas where failures occur are the rail mantle and the rail surface.…”

Section: Introductionmentioning

confidence: 99%

“…In the non-contact methods, the railway line is monitored using laser or normal cameras [8][9][10]. In recent years, image processing based methods _______________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________, 1,2,3 have been developed and contactless status monitoring has been performed. Non-contact condition monitoring methods are quite fast compared to contact condition monitoring methods.…”

Section: Introductionmentioning

confidence: 99%

A Fault Diagnosis Approach for Rail Surface Anomalies Using FPGA in Railways

Yaman

Karaköse

Akın

2017

ijamec

Self Cite

View full text Add to dashboard Cite

Railway transport is a widely used means of transportation for passenger and cargo transportation. In recent years, more emphasis has been placed on railway transport. With the development of high-speed trains, it has become important for passenger transport. Due to the heavy construction of the train, continuous failures occur in the railway line. Various methods of inspection are available to detect these failures. In case of early fault detection and repair of major accidents can be prevented. In this study, an FPGA based method is proposed for rail surface inspection and fault diagnosis. The proposed method is realized by image processing with FPGA. The image is taken on the railway line with the camera attached to the FPGA development board. Pre-processing is performed on the obtained image. Edge extraction is applied to the image after pre-processing. The rail surface is detected using the image obtained as a result of edge extraction. The proposed method works in real time to monitor and diagnose faults. It detects many defects on the track surface. In addition, the proposed method measures the size of the fault on the rail surface. In this study, FPGA based condition monitoring device was developed. An architecture has been developed for implementing the proposed method with FPGA. This work using FPGA technology is low cost and fast compared to other methods. The proposed method is quite advantageous because of its realtime operation.

show abstract

Learning Based Experimental Approach For Condition Monitoring Using Laser Cameras In Railway Tracks

Cited by 19 publications

References 14 publications

Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair

Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair

Optimizasyon Tabanlı Adaptif Görüntü Mozaikleme Algoritması

A Fault Diagnosis Approach for Rail Surface Anomalies Using FPGA in Railways

Contact Info

Product

Resources

About