Principal Investigator/Researcher

Ryan Sherman, Yingtao Jiang, and Ying Tian, University of Nevada, Las Vegas

Project Description

Inspection of rail for defects has historically been performed using ultrasonic technology. While the ultrasonic method has proven to be reliable, limitations exist in regard to the speed of the inspection. The proposed study aims to increase the speed of rail inspection while maintaining a high level of reliability through the use of acoustic emission.

An acoustic emission sensor will be developed capable of detecting rail defects at high speeds. Acoustic detection has been widely applied to detect changes in medium generating distinct sounds. For example, the technology has been successfully utilized to detect automobile crashes at intersections, cable wire breaks in bridges, and defects in wheel-set bearings. The acoustic flaw detection system will also be paired with an on-board GPS to provide defect location information.

To evaluate the sensor performance field testing will be conducted in three phases. Initial testing will be performed at low speeds with limited defect types to demonstrate the feasibility of the system. The second phase of testing will be completed at medium speeds with a wider range of defect types. Finally, the third phase of field testing will be conducted in China at speeds up to 180 mph. Throughout the field testing program the flaw detection system will be continually improved based on the research findings.

The expected outcome of the research will be a high speed flaw detection system using acoustic technology. Ultimately, the goal of the research is improving rail inspection speed and reliability thereby enhancing rail safety.

Final Report

Outputs

1 dissertation, 1 conference paper

  • Lei Jia, Non-Contact Acoustic Emission Detection of Rail Defects Using Air-Coupled Optical Microphones, Dissertation of Civil Engineering at the University of Nevada Las Vegas, 2024
  • Lei Jia, Ming Zhu, Ryan J. Sherman, Jee Woong Park, Yingtao Jiang, Hualiang Teng, Rail Defect Detection Technology: A Review of the Current Methods and an Acoustic Based Method Proposed for High-Speed-Rail, IRF GLOBAL R2T Conference, November 19-22, 2019 – Las Vegas, NV USA