TY  - JOUR
TT  - Learning Based Experimental Approach For Condition Monitoring Using Laser Cameras In Railway Tracks
AU  - Santur, Yunus
AU  - Karaköse, Mehmet
AU  - Akın, Erhan
PY  - 2016
DA  - December
DO  - 10.18100/ijamec.270656
JF  - International Journal of Applied Mathematics Electronics and Computers
PB  - PLUSBASE AKADEMİ ORGANİZASYON VE DANIŞMANLIK
WT  - DergiPark
SN  - 2147-8228
SP  - 1
EP  - 5
IS  - Special Issue-1
KW  - Railway Inspection
KW  - Anomaly Detect
KW  - Computer Vision
KW  - Laser Camera
N2  - Detecting the rail surface faults is one ofthe most important components of railway inspection process which should beperformed periodically. Today, the railway inspection process is commonlyperformed using computer vision. Performing railway inspection based on imageprocessing can lead to false-positive results. The fact that the oil and dustresidues occurring on railway surfaces can be detected as an error by the imageprocessing software can lead to loss of time and additional costs in therailway maintenance process. In this study, a hardware and softwarearchitecture are presented to perform railway surface inspection using 3D lasercameras. The use of 3D laser cameras in railway inspection process provideshigh accuracy rates in real time. The reading rate of laser cameras to read upto 25.000 profiles per second is another important advantage provided in realtime railway inspection. Consequently, a computer vision-basedapproach in which 3D laser cameras that could allow for contactless and fastdetection of the railway surface and lateral defects such as fracture, scouringand wear with high accuracy are used in the railway inspection process wasproposed in the study.
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UR  - https://doi.org/10.18100/ijamec.270656
L1  - https://dergipark.org.tr/en/download/article-file/252042
ER  -