Analysis of Vibration and Acoustic Signals for Noncontact Measurement of Engine Rotation Speed - Publication - MOST Wiedzy

Search

Analysis of Vibration and Acoustic Signals for Noncontact Measurement of Engine Rotation Speed

Abstract

The non-contact measurement of engine speed can be realized by analyzing engine vibration frequency. However, the vibration signal is distorted by harmonics and noise in the measurement. This paper presents a novel method for the measurement of engine rotation speed by using the cross-correlation of vibration and acoustic signals. This method can enhance the same frequency components in engine vibration and acoustic signal. After cross-correlation processing, the energy centrobaric correction method is applied to estimate the accurate frequency of the engine’s vibration. This method can be implemented with a low-cost embedded system estimating the cross-correlation. Test results showed that this method outperformed the traditional vibration-based measurement method.

Citations

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Details

Category:
Articles
Type:
artykuły w czasopismach
Published in:
SENSORS no. 20, pages 1 - 10,
ISSN: 1424-8220
Language:
English
Publication year:
2020
Bibliographic description:
Xuansheng S., Lu T., Wen H., Martinek R., Smulko J.: Analysis of Vibration and Acoustic Signals for Noncontact Measurement of Engine Rotation Speed// SENSORS -Vol. 20,iss. 3 (2020), s.1-10
DOI:
Digital Object Identifier (open in new tab) 10.3390/s20030683
Bibliography: test
  1. Gustafsson, F. Rotational Speed Sensors: Limitations, Pre-processing and Automotive Applications Part 23 in a Series of Tutorials on Instrumentation and Measurement. IEEE Instrum. Meas. Mag. 2010, 13, 16-23. [CrossRef] open in new tab
  2. Arif, S.J.; Asghar, M.S.J.; Sarwar, A. Measurement of Speed and Calibration of Tachometers Using Rotating Magnetic Field. IEEE Trans. Instrum. Meas. 2014, 63, 848-858. [CrossRef] open in new tab
  3. Chicharro, J.M.; Morales, A.L.; Moreno, R.; Nieto, A.J.; Pintado, P. Sensorless automotive engine speed measurement by noise analysis. In Proceedings of the 2009 IEEE International Conference on Mechatronics, Malaga, Spain, 14-17 April 2009; pp. 1-4. open in new tab
  4. Jia-Dong, Z.; Guang-Yao, O.; Hong-Bin, G. Demodulation of instantaneous rotational speed of diesel engine based on Hilbert transform. In Proceedings of the 9th International Conference on Electronic Measurement & Instruments, Beijing, China, 16-19 August 2009; pp. 2-753-2-756. open in new tab
  5. Kepak, S.; Stolarik, M.; Nedoma, J.; Martinek, R.; Kolarik, J.; Pinka, M. Alternative Approaches to Vibration Measurement Due to the Blasting Operation: A Pilot Study. Sensors 2019, 19, 4084. [CrossRef] [PubMed] open in new tab
  6. Nedoma, J.; Stolarik, M.; Kepak, S.; Pinka, M.; Martinek, R.; Frnda, J.; Fridrich, M. Alternative Approaches to Measurement of Ground Vibrations Due to the Vibratory Roller: A Pilot Study. Sensors 2019, 19, 5420. [CrossRef] [PubMed] open in new tab
  7. Santacruz, M.; Felix, M.; Ocampo, J.; Luna, G. Vibration Frequency Peak Detection and Sorting Technique for Passenger Vehicles. In Proceedings of the 2013 IEEE International Instrumentation and Measurement Technology Conference, Minneapolis, MN, USA, 6-9 May 2013; pp. 1353-1357. open in new tab
  8. Amman, S.A.; Das, M. An efficient technique for modeling and synthesis of automotive engine sounds. IEEE Trans. Ind. Electron. 2001, 48, 225-234. [CrossRef] open in new tab
  9. Belouchrani, A.; Amin, M.G. Time-frequency MUSIC. IEEE Signal Process. Lett. 1999, 6, 109-110. [CrossRef] open in new tab
  10. Zhang, J.; Tang, L.; Mingotti, A.; Peretto, L.; Wen, H. Analysis of White Noise on Power Frequency Estimation by DFT-based Frequency Shifting and Filtering Algorithm. IEEE Trans. Instrum. Meas. 2019. [CrossRef] open in new tab
  11. Zhang, J.; Wen, H.; Tang, L. Improved Smoothing Frequency Shifting and Filtering Algorithm for Harmonic Analysis With Systematic Error Compensation. IEEE Trans. Ind. Electron. 2019, 66, 9500-9509. [CrossRef] open in new tab
  12. Marple, S.L. Digital Spectral Analysis With Applications;
  13. Prentice-Hall Inc.: Englewood Cliffs, NJ, USA, 1987; Volume 1. open in new tab
  14. Miao, Q.A.; Cong, L.; Pecht, M. Identification of multiple characteristic components with high accuracy and resolution using the zoom interpolated discrete Fourier transform. Meas. Sci. Technol. 2011, 22, 055701. [CrossRef] open in new tab
  15. Kaminsky, D.; Zidek, J.; Bilik, P. Virtual instrumentation based power quality analyzer. In Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, Prague, Czech Republic, 15-17 September 2011; pp. 184-187. open in new tab
  16. Wen, H.; Li, C.; Yao, W. Power System Frequency hstimation of Sine-Wave Corrupted With Noise by Windowed Three-Point Interpolated DFT. IEEE Trans. Smart Grid 2018, 9, 5163-5172. [CrossRef] open in new tab
  17. Wen, H.; Zhang, J.; Meng, Z.; Guo, S.; Li, F.; Yang, Y. Harmonic Estimation Using Symmetrical Interpolation FFT Based on Triangular Self-Convolution Window. IEEE Trans. Ind. Inform. 2015, 11, 16-26. [CrossRef] open in new tab
  18. Wen, H.; Kish, L.B.; Klappenecker, A.; Peper, F. New noise-based logic representations to avoid some problems with time complexity. Fluct. Noise Lett. 2012, 11. [CrossRef] open in new tab
  19. Lindfors, M.; Hendeby, G.; Gustafsson, F.; Karlsson, R.; IEEE. Vehicle Speed Tracking Using Chassis Vibrations. In Proceedings of the 2016 IEEE Intelligent Vehicles Symposium, Gothenburg, Sweden, 19-22 June 2016; open in new tab
  20. Amarnath, M.; Krishna, I.R.P. Local fault detection in helical gears via vibration and acoustic signals using EMD based statistical parameter analysis. Measurement 2014, 58, 154-164. [CrossRef] open in new tab
  21. Adamczak, S.; Janecki, D.; Makiela, W.; Stepien, K. Quantitative comparison of cylindricity profiles measured with different methods using legendre-fourier coefficients. Metrol. Meas. Syst. 2010, 17, 397-403. [CrossRef] open in new tab
  22. Knapp, C.; Carter, G. The generalized correlation method for estimation of time delay. IEEE Trans. Acoust. Speech Signal Process. 1976, 24, 320-327. [CrossRef] open in new tab
  23. Combet, F.; Gelman, L. An automated methodology for performing time synchronous averaging of a gearbox signal without speed sensor. Mech. Syst. Signal Process. 2007, 21, 2590-2606. [CrossRef] open in new tab
  24. Song, X.; Li, X.; Zhang, W.G.; Zhou, W. The new measurement algorithm of the engine speed base on the basic frequency of vibration signal. In Proceedings of the 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, Changchun, China, 24-26 August 2010; pp. 273-277. open in new tab
  25. Cevher, V.; Chellappa, R.; McClellan, J.H. Vehicle Speed Estimation Using Acoustic Wave Patterns. IEEE Trans. Signal Process. 2009, 57, 30-47. [CrossRef] open in new tab
  26. Oppenheim, A.V.; Willsky, A.S. Signals and Systems; Prentice Hall: Upper Saddle River, NJ, USA, 1983; p. xix+796.
  27. Yan, H.; Joy, D.; Lei, M. Convolution and correlation: A case study of scanning imaging and analysis systems. Scanning 2002, 24, 6-17. [CrossRef] [PubMed] open in new tab
  28. Liu, H.F.; Liu, H.Y.; Zhang, T.T.; Li, J.C. Application of Cross-correlation Algorithm in Radio Weak Signal Detection. In Proceedings of the 7th Annual Communication Networks And Services Research Conference, Moncton, NB, Canada, 11-13 May 2009; pp. 440-442. open in new tab
  29. Offelli, C.; Petri, D. A frequency-domain procedure for accurate real-time signal parameter measurement. IEEE Trans. Instrum. Meas. 1990, 39, 363-368. [CrossRef] open in new tab
  30. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). open in new tab
Verified by:
Gdańsk University of Technology

seen 30 times

Recommended for you

Meta Tags