Rail Sample Laboratory Evaluation of Eddy Current Rail Inspection Sustainable System

Increasing the efficiency, frequency, and speed of rail defect detection can reduce maintenance costs and improve the sustainability of railways. The non-contact eddy current (EC) system can be operated along with a railcar for detecting rail flaws. Even if the EC can be utilized for rail defect identification and characterization, current commercial devices are not sufficient for defect classification on rails by providing highly sensitive signals for post-processing. In this study, we established an efficient and expandable eddy current rail inspection system and verified its capability for classification of different defect signals. The integrated hardware and software EC measurement system was firstly applied to detect notched cracks in steel samples with different crack depths and angles. The measured voltage and current analog inputs from the eddy current sensor were acquired and processed with a fast Fourier transformation (FFT) algorithm in the LabVIEW platform. The real-time impedance was then obtained by transferring signals to a normalized impedance plane plot. The processed EC signals showed adequate sensitivity and efficiency with changes of notched crack depths and angles during the sensor movement. A comparative case study on field rail samples was then conducted to examine the feasibility and capability of the established system on different types of actual rail defects. The experimental analysis and case study results demonstrate that the integrated eddy current system could possibly be used for non-destructive rail crack inspection and classification. The enhanced detection capability (especially on subsurface cracks) and real-time post-processing technique could further contribute to improving rail-life sustainability.

Automated summary

In this study, an efficient and expandable eddy current rail inspection system was established to classify different defect signals in order to improve rail-life sustainability. The system showed adequate sensitivity and efficiency in detecting notched cracks in steel samples and field rail samples. The enhanced detection capability and real-time post-processing technique contribute to the non-destructive inspection and classification of rail cracks.