TITLE:
Evaluation of On-Vehicle Bone-Conduct Acoustic Emission Detection for Rail Defects
AUTHORS:
Lei Jia, Jee Woong Park, Ming Zhu, Yingtao Jiang, Hualiang Teng
KEYWORDS:
Railroad Infrastructure, Rail Defect Detection, Rail Health Monitoring, Wavelet Analysis, Acoustic Emission Detection
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.15 No.1,
January
16,
2025
ABSTRACT: Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects, and this study evaluates an advanced on-vehicle AE detection approach using bone-conduct sensors—a solution to improve upon previous AE methods of using on-rail sensor installations, which required extensive, costly on-rail sensor networks with limited effectiveness. In response to these challenges, the study specifically explored bone-conduct sensors mounted directly on the vehicle rather than rails by evaluating AE signals generated by the interaction between rails and the train’s wheels while in motion. In this research, a prototype detection system was developed and tested through initial trials at the Nevada Railroad Museum using a track with pre-damaged welding defects. Further testing was conducted at the Transportation Technology Center Inc. (rebranded as MxV Rail) in Colorado, where the system’s performance was evaluated across various defect types and train speeds. The results indicated that bone-conduct sensors were insufficient for detecting AE signals when mounted on moving vehicles. These findings highlight the limitations of contact-based methods in real-world applications and indicate the need for exploring improved, non-contact approaches.