چكيده به لاتين
Today, rail transportation is known as one of the safest moods of transportation in cuurent society and development of high-speed railways has increased tendency to use it for passenger transport rapidly. On the other hand, from the beginning of the railway to the present day
It has also been used to transport cargo, so railway and its components due to the speed of rolling stocks, high traffic volume, high axial load, variety of loads(Static, dynamic, semi-dynamic, vertical, longitudinal, lateral) are always exposed to breakdown and damage which can lead to an accident and irreversible financial and human losses, Therefore, in the first place, the identification of defects in the next stage, the elimination of identified defects is of great importance. Sleepers is one of the components of the railway pavement, whose main task is to maintain the stability of the line and transfer and distribute load from the rail to the ballast, so in case failure, other components of the line will be damaged too. Nowadays, identifying sleepers defects is performed in the form of field detection and eye examinations which suffers from Problems such as human error, low speed of inspection, reporting deficiencies, high costs, etc. One of the new methods is the applications of image processing science and machine learning which is used to identify the defects of concrete and wooden sleepers in this research, so that the sleepers are imaged using a camera and then are processed and cracks within are detected, then captured images will be categorized by categorization Machine learning methods like support vector to eventually create a system that uses the sleepers image to report their status.
