TITLE:
Evaluation of Air-Coupled Acoustic Emission Detection for Internal Rail Defects
AUTHORS:
Lei Jia, Jee Wong Park, Ming Zhu, Yingtao Jiang, Lihao Qiu, Hualiang Teng
KEYWORDS:
Railroad Infrastructure, Rail Defect Detection, Rail Health Monitoring, Wavelet Analysis, Acoustic Emission Detection
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.16 No.1,
December
22,
2025
ABSTRACT: Internal rail defects present significant safety risks. Acoustic Emission (AE) technology has emerged as a promising technique for detecting these defects. The goal of this research is to investigate the characteristics of AE signals from internal rail defects by employing air-coupled optical microphones. This first phase of the research was to evaluate the propagation characteristics of AE signals in lab-controlled pencil lead break (PLB) tests with two scenarios: signal attenuation in the air and within the rail. These tests were particularly designed to assess the prototype’s performance under varying conditions. The second phase involved real-world field tests at two test sites: the Nevada State Railroad Museum and the MxV Rail in Colorado. Data collected from both sites were analyzed to assess the effectiveness of detecting defects in rail. The test results revealed two key findings. First, the AE detection rate varied significantly between tests: 8.3% in the Nevada field test and 13.3% in the MxV Rail test. This difference suggests that AE detection rates may be influenced by defect size and conditions in the field environment. Second, wavelet packet power (WPP) analysis highlighted clear differences between PLB-induced AE signals and those from actual rail defects. While PLB signals displayed broader energy distribution across the frequency range, the AE signals from rail defects exhibited concentrated and intense peaks within the 100 - 160 kHz range. Overall, the non-contact sensor system demonstrated promise for detecting internal rail defects, effectively capturing AE signals.