Abstract
Bogie is one of the most critical parts of high-speed train and is directly related to the operation quality and safety of the train. However, currently no dynamic non-destructive testing method exists for real-time monitoring. Therefore, this paper proposes a new damage localization method for high-speed train bogie dynamic testing. The acoustic emission testing technology is applied to test the vulnerable welding parts of the bogie with time reversal localization method. Firstly, the bogie welding parts structure model based on finite element software is established. Then an acoustic emission damage signal is sent from the model and the acoustic emission source signal is received by the preset acoustic emission sensor. And the accurate localization of damage is achieved by dealing with the received signal according to the time reversal focusing principle and imaging the acoustic emission source. The simulation experiments show that the proposed method can accurately find the damaged localization. And finally, the method has been verified through experiment, and the results show it can effectively improve signal energy of the damage source, and the position of the damage source can be shown accurately through signal reconstruction and localization in the detection area.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant Nos. 11764030 and 51865033), Special Plan for the Construction of Superiority Scientific and Technological Innovation Teams in Jiangxi Province (Grant No. 20171BCB24008), Natural Science Foundation of Jiangxi Province (Grant No. 20171BAB206039), Science and Technology Planning Project of Jiangxi Quality Supervision Bureau (GZJKE201810), Science and Technology Project of Jiangxi Education Department (Grant No. GJJ170577 and GJJ180525), and Nanchang Hangkong University Graduate Innovation Special Fund (Grant No. YC2019044).
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Wei, X., Chen, Y., Lu, C. et al. Acoustic emission source localization method for high-speed train bogie. Multimed Tools Appl 79, 14933–14949 (2020). https://doi.org/10.1007/s11042-019-08580-3
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DOI: https://doi.org/10.1007/s11042-019-08580-3