Nondestructive Testing Technologies for Rail Inspection: A Review

Abstract

Alongside the development of high-speed rail, rail flaw detection is of great importance to ensure railway safety, especially for improving the speed and load of the train. Several conventional inspection methods such as visual, acoustic, and electromagnetic inspection have been introduced in the past. However, these methods have several challenges in terms of detection speed and accuracy. Combined inspection methods have emerged as a promising approach to overcome these limitations. Nondestructive testing (NDT) techniques in conjunction with artificial intelligence approaches have tremendous potential and viability because it is highly possible to improve the detection accuracy which has been proven in various conventional nondestructive testing techniques. With the development of information technology, communication technology, and sensor technology, rail health monitoring systems have been evolving, and have become equally significant and challenging because they can achieve real-time detection and give a risk warning forecast. This paper provides an in-depth review of traditional nondestructive techniques for rail inspection as well as the development of using machine learning approaches, combined nondestructive techniques, and rail health monitoring systems.

Corrugation and Squat Classification and Detection with VGG16 and YOLOv5 Neural Network Models

“…(a) (b) Fig. 2 The present technology utilized for the detection of rail surface defects are: (a) ultrasonic inspection [3]; and (b) machine visual inspection [19] These technologies, which often incorporate machine visual inspection techniques, have become significant and challenging because they offer real-time detection capabilities and can provide risk warning forecasts. Railway inspections have been enhanced with the ability to visually identify rail defects effortlessly.…”

“…While the most common track defects in Malaysia were not explicitly mentioned in [1], it is essential to note that rail surface defects such as corrugation and squats are examples of railway defects that can compromise the safety or reliability of the system if not detected and repaired in time. Various non-destructive testing (NDT) techniques and technologies, including ultrasonic testing, electromagnetic testing, eddy current testing, and visual inspection, have been explored for rail defect detection [3], [6]. These methods enable the detection of different defects on the surface and within the rail structure [7].…”

Dynamic calibration method for track geometry measurement system-a case study in China

“…The chord measurement method is often used in countries such as Switzerland and Austria, which measures the deviation from the ideal chord [7]. Another common method is the laser detection system, which uses high-precision lasers and optical instruments to detect track defects and misalignments [8]. Track detection technology in Germany relies mainly on the inertial reference method, which has used track detection vehicles such as the Gleismesstriebzug, Oberbau-Meßwagen-Einheit, RaiLab, ICE-S and VT612.9 [9].…”

RSDNet: A New Multiscale Rail Surface Defect Detection Model

“…During the train operation, frequent collisions between wheels and rails and the factor of outdoor environmental erosion can easily lead to defects on the rail surface, which may cause serious accidents if not handled in time [ 1 ]. The initial stage of track defect detection mainly adopts the inspection method; however, this method is inefficient and easily affected by subjective factors [ 2 ].…”