An investigation of rail failure due to wear using statistical pattern recognition techniques. (April 2022)

• Record Type: Journal Article
• Authors: Masoudi, Aghdas; Davarpanah Jazi, Mohammad; Mohrekesh, Majid; Masoudi Nejad, Reza
• Is Part Of: Engineering failure analysis. Volume 134(2022)
• Publication Date: 2022-04
• Subjects: Wear -- Rail -- Pattern recognition -- Rail/wheel contact -- Worn profile; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2022.106084
• Languages: English
• ISSNs: 1350-6307

Abstract

Highlights: The purpose of this paper is to identify the timely failure due to wear in rails. The image processing techniques is used for wear detection in rails. This provides a methodological basis for quantitative indicators of wear. Comparing the results from image processing method is in accordance with field observations. The accuracy of the proposed method indicates the validity of the proposed model. Abstract: The purpose of controlling and detecting errors in transportation systems is to ensure the correct operation of the system. The purpose of this paper is to identify wear in rails by using statistical pattern recognition methods. Due to the low accuracy of some of the current methods designing and introducing an easy way to be used in this area is required. The data of this paper were obtained by the field observation and using image captions of without worn profile and worn profile of railway rails, then the wear phenomenon was identified using the image processing method. Comparing the results of wear identification using pattern recognition techniques is in accordance with field observations. The true positive rate (sensitivity) is calculated and the accuracy of the proposed method indicates the validity of the proposed model.