In order to detect cracks in railroad tracks, various experiments have been examined by Acoustic Emission (AE) method. However, little work has been done on studying rail defect detection at high speed. This paper presents a study on AE detection of rail defect at high speed based on rail-wheel test rig. Meanwhile, Wavelet Transform and Shannon entropy are employed to detect defects. Signals with and without defects are acquired, and characteristic frequencies from them at different speeds are analyzed. Based on appropriate decomposition level and Energy-to-Shannon entropy ratio, the optimal wavelet is selected. In order to suppress noise effects and ensure appropriate time resolution, the length of time window is investigated. Further, the characteristic frequency of time window is employed to detect defect. The results clearly illustrate that the proposed method can detect rail defect at high speed effectively. (C) 2014 Elsevier Ltd. All rights reserved.
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