Experimental Study of Self-powered and Self-sensing System for the Rail Corrugation In-situ Inspection

doi:10.3901/JME.2021.18.107

Abstract

Abstract: Rail corrugation, as a widely periodic wear pattern of the railway track in urban rail transit, has already affected the safe operation of the railcar. Meanwhile, the rail corrugation also could cause high-pitched noise and vibration of the ground and nearby buildings. The current rail corrugation inspection trolley can only be employed offline, whereas offline monitoring devices require an external power supply. An approach of the rail corrugation in-situ inspection based on the rail vibration energy is proposed. The mechanics of the magnetic-floating energy harvester employs a triple-magnet repellent configuration to enhance broad-band energy harvesting of the rail vibration, and the best start position of the energy harvester is experimentally validated combing with the simulation analysis. The performance of self-powered and self-sensing harvester is verified by the experimental study which includes a comprehensive broad-band sinusoidal sweeping vibration test and a stochastic vibration test based on the measured railway track spectra, and the wavelet theory is implemented together to analyse the time-frequency distribution characteristics of the rail corrugation. Results indicate that the proposed rail corrugation in-situ inspection system could collect the rail vibration energy under the rail corrugation excitation across a wider frequency range and then determine the rail corrugation status by time-frequency characteristics of the induced voltage signal. The new approach of the rail corrugation in-situ inspection proposed by this study could realize the rail corrugation online in-situ inspection without external batteries and reduce manual involvement and workload for railway track inspection. It is very hopeful of accelerating the intelligent process of rail inspection technology.

Key words: rail corrugation, self-sensing, in-situ inspection, stochastic vibration, power spectrum density, wavelet

CLC Number:

U216

SUN Yuhua, WANG Ping, XU Jingmang, WANG Yuan, WANG Peigen, GAO Mingyuan. Experimental Study of Self-powered and Self-sensing System for the Rail Corrugation In-situ Inspection[J]. Journal of Mechanical Engineering, 2021, 57(18): 107-117.

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