Abstract
In this chapter, three experimental platforms for traction systems, including one dSPACE-based traction system of high-speed trains and two actual traction systems, will be introduced in details. First, we will briefly describe the traction system in terms of its system structure and operating mechanism. Then, experimental platforms together with their parameters will be introduced to present readers with useful background. Based on these platforms which will be used in the forthcoming Chaps. 4–8, a variety of experiments will be carried out to demonstrate the effectiveness of the designed methods in this book.
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References
Zhang S (2007) Fundamental application theory and engineering technology for railway high-speed trains. Science Press, Beijing, China
Chen H, Jiang B (2019) A review of fault detection and diagnosis for the traction system in high-speed trains. IEEE Trans Intell Transp Syst. https://doi.org/10.1109/TITS.2019.2897583
Feng J, Xu J, Liao W, Liu Y (2017) Review on the traction system sensor technology of a rail transit train. Sensors 17(6):1–16
Dong H, Ning B, Cai B, Hou Z (2010) Automatic train control system development and simulation for high-speed railways. IEEE Circuits Syst Mag 10(2):6–18
Chen H, Jiang B, Lu N, Mao Z (2018) Deep PCA based real-time incipient fault detection and diagnosis methodology for electrical drive in high-speed trains. IEEE Trans Veh Technol 67(6):4819–4830
Chen H, Jiang B, Chen W, Yi H (2018) Data-driven detection and diagnosis of incipient faults in electrical drives of high-speed trains. IEEE Trans Ind Electron 66(6):4716–4725
Chen Z, Ding SX, Peng T, Yang C, Gui W (2018) Fault detection for non-gaussian processes using generalized canonical correlation analysis and randomized algorithms. IEEE Trans Ind Electron 65(2):1559–1567
Chen H, Jiang B, Lu N, Mao Z (2017) Multi-mode kernel principal component analysis-based incipient fault detection for pulse width modulated inverter of China railway high-speed 5. Adv Mech Eng 9(10):1–12
Qin SJ (2003) Statistical process monitoring: basics and beyond. J Chemometrics 17:480–502
Chen H, Jiang B, Lu N (2018) A multi-mode incipient sensor fault detection and diagnosis method for electrical traction systems. Int J Control Autom Syst 16(4):1783–1793
Yang C, Yang C, Peng T, Yang X, Gui W (2017) A Fault-injection strategy for traction drive control systems. IEEE Trans Ind Electron 64(7):5719–5727
Chen H, Jiang B, Lu N (2018) A newly robust fault detection and diagnosis method for high-speed trains. IEEE Trans Intell Transp Syst 20(6):2198–2208
Yang X, Yang C, Peng T, Chen Z, Liu B, Gui W (2018) Hardware-in-the-loop fault injection for traction control system. IEEE J Emerg Sel Top Power Electron 6(2):696–706
Chen H, Jiang B, Lu N (2018) An improved incipient fault detection method based on Kullback-Leibler Divergence. ISA Trans 79:127–136
Finch JM, Giaouris D (2018) Controlled AC electrical drives. IEEE Trans Ind Electron 55(2):481–491
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Chen, H., Jiang, B., Lu, N., Chen, W. (2020). Traction Systems and Experimental Platforms. In: Data-driven Detection and Diagnosis of Faults in Traction Systems of High-speed Trains. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-030-46263-5_2
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DOI: https://doi.org/10.1007/978-3-030-46263-5_2
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