Multicomponent decomposition of a time-varying acoustic Doppler signal generated by a passing railway vehicle using Complex Shifted Morlet Wavelets |
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| Institution: | 1. Dynamics and Structures Laboratory, and Vehicle Systems Laboratory, Machine Design and Control Systems Section, School of Mechanical Engineering, National Technical University of Athens, Greece;2. Institute of Vehicles, Faculty of Automobiles and Heavy Machinery Engineering, Warsaw University of Technology, Poland;1. College of Mechanical and Transportation Engineering, China University of Petroleum -Beijing, Beijing, 102249, China;2. Department of Mechanical Engineering, George R. Brown School of Engineering, Rice University, Houston, TX, 77251, USA;1. Department of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361024, China;2. Department of Mechanical Engineering, University of Ottawa, Ottawa K1N6N5, Canada;3. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China;1. College of Traffic Engineering, Hunan University of Technology, Zhuzhou 412007, PR China;2. Laboratory of Science and Technology on Integrated Logistics Support, College of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, PR China;3. School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3HD, United Kingdom;1. School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology (QUT), Brisbane, Australia;2. School of Mechanical and Manufacturing Engineering, University of New South Wales (UNSW), Sydney, Australia;3. LKC Faculty of Engineering and Science, Universiti Tunku Abdul Rahman (UTAR), Selangor, Malaysia |
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| Abstract: | Complex Shifted Morlet Wavelets (CSMW) present a number of advantages, since the concept of shifting the Morlet wavelet in the frequency domain allow the simultaneous optimal selection of both the wavelet center frequency and the wavelet bandwidth. According to the proposed method, a cluster of CSMW wavelets is used, covering appropriate ranges in the frequency domain. Then, instead of directly processing the instantaneous frequency of each CSMW, an invariance approach is used to indirectly recover the individual harmonic components of the signal. This invariance approach is based actually on the same rotational approach, using the same matrix properties, which consists the core of the well known ESPRIT algorithm. Moreover, the DESFRI (DEtection of Source Frequencies via Rotational Invariance) approach is introduced to support the proposed CSMW method to semi-automated selection of the center frequency of the applied Morlet window. This approach is based on the singular values that are extracted as an intermediate product of the proposed decomposition process. By the application of the method in a multi-component synthetic signal a way to select the critical parameters of the Morlet wavelet, is investigated. The method is further tested on a time-varying acoustic Doppler signal generated by a passing railway vehicle, indicating promising results for the estimation of the variable instantaneous frequency and the multi-component decomposition of it. |
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| Keywords: | Complex Shifted Morlet Wavelets Instantaneous frequency Multicomponent decomposition Doppler Effect Wayside condition monitoring |
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