An ultrasonic sonar-based ranging technique is introduced for measuring full-field railroad crosstie (sleeper) deflections. Tie deflection measurements have numerous applications, such as detecting degrading ballast support conditions and evaluating sleeper or track stiffness. The proposed technique utilizes an array of air-coupled ultrasonic transducers oriented parallel to the tie, capable of “in-motion” contactless inspections. The transducers are used in pulse-echo mode, and the distance between the transducer and the tie surface is computed by tracking the time-of-flight of the reflected waveforms from the tie surface. An adaptive, reference-based cross-correlation operation is used to compute the relative tie deflections. Multiple measurements along the width of the tie allow the measurement of twisting deformations and longitudinal deflections (3D deflections). Computer vision-based image classification techniques are also utilized for demarcating tie boundaries and tracking the spatial location of measurements along the direction of train movement. Results from field tests, conducted at walking speed at a BNSF train yard in San Diego, CA, with a loaded train car are presented. The tie deflection accuracy and repeatability analyses indicate the potential of the technique to extract full-field tie deflections in a non-contact manner. Further developments are needed to enable measurements at higher speeds.

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This paper presents a high-speed non-contact rail inspection technique that has the potential of detecting internal rail defects at regular (revenue) train speeds. The technique utilizes an array of capacitive air-coupled ultrasonic transducers in continuous recording mode to extract a reconstructed transfer function for a rail segment in a passive manner. The passive approach utilizes the ambient excitation of the rail induced by the wheels of the test car and eliminates the need of a controlled source. A normalized cross correlation operator with modified Welch's periodogram technique is used to extract the transfer function in a manner that is independent of the uncontrolled excitation source (rolling wheels). Discontinuities in the rail (e.g., joints, welds and defects) alter the reconstructed transfer function which is statistically tracked using an outlier analysis for detection robustness and sensitivity. Field tests were carried out with a prototype at the Transportation Technology Center Inc (TTCI) in Pueblo, Colorado at testing speeds of up to 80 mph. The performance of the system in detecting rail discontinuities was assessed via Receiver Operating Characteristic curves for a range of varying operational parameters such as excitation strength, baseline distribution length, testing speed, and multiple runs.

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Background Continuous monitoring is essential for detecting internal defects in rails and prevent derailment related accidents. Existing techniques do not facilitate continuous monitoring because they require specialized test cars and can only operate at speeds of up to 30 mph. Objective The objective of this study is to evaluate the performance of a high-speed rail inspection system using a non-contact ultrasonic technique with the potential of operating at train revenue speeds. Methods The technique utilizes air-coupled transducers that record the ultrasonic guided waves generated by the rail-wheel contact and does not require a controlled acoustic source of excitation. A modified version of the traditional Welch’s periodogram technique is utilized to extract the Green’s function between two points on the rail. The passively extracted Green’s function is then analysed statistically to detect structural discontinuities (e.g., defects) in the rail. Results Results from fields tests performed at the Transportation Technology Centre (TTC) in Pueblo, CO, USA, demonstrate possible test speeds as high as 80 mph. From these field tests, the performance of the system is evaluated using Receiver Operating Characteristic (ROC) curves for a range of different operational parameters including test speed, location of the sensors relative to the locomotive (source), signal-to-noise ratio (SNR) of the raw signals, SNR of the reconstructed transfer function, baseline distribution length in the statistical analysis, wheel-rail interactions, and redundancies introduced from multiple runs over the same track. Conclusions This study presents the current stage of development and performance of the passive rail inspection system with full-scale experiments under field conditions. The results indicate the potential of the system to operate at high speeds as well as possible avenues of future improvement to the system.

A smart tie-tracking technology is proposed to measure the deflections of railroad crossties by means of non-contact ultrasonic testing in sonar mode and computer vision techniques. The sensing layout consists of an array of air-coupled capacitive transducers (in pulse-echo mode) and a high frame-rate camera, rigidly connected to the main frame of train car. The acquisition system is programmed such that the synchronized waveforms and images are collected and saved as train car moves. In the processing stage, a machine learning-based image classification approach is developed to discriminate tie/ballast images and demarcate the crossties’ boundaries. The relative deflections of the identified crossties are eventually computed by tracking the arrival time of the reflected waves from the surfaces flagged as tie. Further inspection of the deflection profiles can reveal crossties with potential poor ballast support condition. The proposed ‘tie sonar’ system was prototyped and used to reconstruct the deflection profile of the crossties scanned during a series of test runs at the Rail Defect Testing Facility of UC San Diego as well as the BNSF yard in San Diego, CA.