An analysis of the simulated acoustic emission sources with different propagation distances,types and depths for rail defect detection |
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| Institution: | 1. Department of Civil Engineering, Changsha University, Changsha 410022, PR China;2. College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, PR China;3. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 610054, PR China;4. School of Physical Science and Technology, Southwest Jiaotong University, Chengdu 610031, PR China;1. Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150001, PR China;2. Department of Astronautics and Mechanics, Harbin Institute of Technology, Harbin, 150001, PR China;1. AC2T research GmbH, Viktor-Kaplan-Straße 2, A-2700 Wiener Neustadt, Austria;2. Institute of Applied Physics, Vienna University of Technology, Wiedner Hauptstraße 8 - 10/134, A-1040 Vienna, Austria;1. Birmingham Centre for Railway Research and Education, University of Birmingham, Birmingham, B15 2TT, UK;2. Advanced Steel Research Centre, WMG, University of Warwick, Coventry, CV4 7AL, UK;1. P6600, 6/F, Yeung Kin Man Academic Building, Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong;2. School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing 100083, China;3. Beijing Key Laboratory of Knowledge Engineering for Materials Science, Beijing 100083, China |
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| Abstract: | Acoustic Emission (AE) technique is an effective nondestructive detecting method, and has a promising application for rail defect detection. So far, little attention has been paid to propagation distances, types, and depths of AE sources, which are important for rail defect detection accurately. This paper presents an experimental study on the simulated AE sources with different propagation distances, types and depths for rail defect detection. Three simulated AE sources with different frequencies are seeded on the cross section of rail, and the depths of AE sources are changed in the vertical direction. After receiving AE signals, wavelet transform and Rayleigh–Lamb equations are utilized to extract time–frequency features and modes. Based on the wavelet transform with corresponding group-velocity curves, the influences of different propagation distances, the features of different source types and the rules of different source depths are examined. It is concluded that the features of AE sources with different propagation distances, types and depths can be obtained by AE technique for rail defect detection. It is very useful to analyze and detect defects in rail defect detection. |
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| Keywords: | Acoustic emission Wavelet transform Rayleigh–Lamb equations Rail defect detection |
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