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Intelligent Sensing and Identification of Train Power System

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Principles of Intelligent Rail Transit

Part of the book series: Advances in High-speed Rail Technology ((ADVHIGHSPEED))

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Abstract

Each component of the train power system and its operation status cannot be set with traditional contact sensors (devices) to achieve information collection and transmission. In particular, the moving parts cannot use the contact sensing technology at all. Even if the micro-sensor can be “placed” on the moving parts, the wireless transmission method must be used to transmit the sensing signal.

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References

  1. Li X, Zhang X, Wu H et al (2010) Intelligent identification device and method for abnormal state of locomotive engine and transmission mechanism. Chinese Invention Patent CN201010522633.0

    Google Scholar 

  2. Zhang X, Guan H, Ying J et al (2010) Micro ultrasonic sensor. Chinese Invention Patent CN201010109779.2

    Google Scholar 

  3. Chen A, Wu H, Du X et al (2006) Electric soft braking method for Metro locomotive. Chinese Invention Patent CN200610030330.0

    Google Scholar 

  4. Wang B, Qu D, Peng X (2005) Try out the basics of speech recognition. National Defense Industry Press, Beijing

    Google Scholar 

  5. Zhu M, Xion W (2002) Computer voice technology. Beihang University Press, Beijing

    Google Scholar 

  6. Mao H, Fan C, Song G (2000) Study on algorithms of low bit rate Hi-Fi audio coding based on wavelet transform and psychoacoustic model. Acta Electron Sin 28(1):26–29 (in Chinese)

    Google Scholar 

  7. Cristani M, Bicego M, Murino V (2004) On-line adaptive background modelling for audio surveillance. In: International conference on pattern recognition. IEEE, 399–402

    Google Scholar 

  8. Shen JL, Hung JW, Lee LS (1998) Robust entropy-based endpoint detection for speech recognition in noisy environments. In: The 5th international conference on spoken language processing, incorporating the 7th Australian International Speech Science and Technology Conference, Sydney, pp 232–235

    Google Scholar 

  9. Wang L, Li C (2010) An improved speech endpoint detection method based on adaptive band-partition spectral entropy. Comput Simul 27(12): 373.375+395 (in Chinese)

    Google Scholar 

  10. Zhang H (2019) Research on abnormal acoustic detection algorithm for train operation safety monitoring system in station. Dissertation, Tianjin University of Technology

    Google Scholar 

  11. Zhang X, Ying J (2011) Principles of automobiles intelligent technology. Shanghai Jiao Tong University Press, Shanghai

    Google Scholar 

  12. Chen A, Zhang X, Du X et al (2006) Fault diagnosis system for traction circuit of metro locomotive based on waveform recognition. Chinese Invention Patent CN200610030327.9

    Google Scholar 

  13. Chen A, Wu H, Du X et al (2006) Fault diagnosis method for traction circuit of metro locomotive based on waveform recognition. Chinese Invention Patent CN200610030328.3

    Google Scholar 

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Correspondence to Xiubin Zhang .

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Zhang, X., Khan, M.M., Halimu, Y. (2023). Intelligent Sensing and Identification of Train Power System. In: Principles of Intelligent Rail Transit. Advances in High-speed Rail Technology. Springer, Singapore. https://doi.org/10.1007/978-981-19-6072-7_3

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  • DOI: https://doi.org/10.1007/978-981-19-6072-7_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-6071-0

  • Online ISBN: 978-981-19-6072-7

  • eBook Packages: EngineeringEngineering (R0)

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