Concept for an event-triggered wireless sensor network for vibration-based diagnosis in trams

Maik Wolf1 , Mathias Rudolph2 , Olfa Kanoun3

1, 2Leipzig University of Applied Sciences, Leipzig, Germany

3Chemnitz University of Technology, Chemnitz, Germany

1Corresponding author

Vibroengineering PROCEDIA, Vol. 27, 2019, p. 55-60. https://doi.org/10.21595/vp.2019.21033
Received 12 September 2019; accepted 20 September 2019; published 30 September 2019

Copyright © 2019 Maik Wolf, et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract.

Trams are the most durable and resource efficient forms of public transportation. However, because of the varying wear in dependence on their operation mode and load levels, there is a need for condition monitoring and early maintenance. Vibration sensors provide interesting possibilities to monitor the relevant tram drive components. In this contribution we investigate their use under real conditions. On the basis of cable bound vibration measurements, the influence of the crossed track section, the tram speed and the tram condition is shown. Based on the investigation results, a concept is proposed in which a meshed and wireless sensor network, event-triggered, can acquire vibration measurement data, which are suitable for the diagnosis of tram drive components. The proposed concept has the potential to operate the sensor nodes in an energy efficient way through decentralized data evaluation taking place on the sensor node.

Graphical Abstract

Highlights
  • Illustration of the influence from rail and speed on vibration analysis in trams.
  • A concept to trigger a wireless and meshed sensor network by an event.
  • The network has the potential to perform data evaluation in an energy-saving and decentralized manner.

Keywords: vibration diagnosis, mobile machines, tram, wireless sensor network, rail, speed.

References

  1. Minkos A., Dauert U., Feigenspan S., Kessinger S. Air Quality. German Environment Agency Dessau-Roßlau, 2019, p. 6, (in German). [CrossRef]
  2. Schneider A., Cyrys J., Breitner S., Kraus U., Peters A., Diegmann V., Neunhäuserer L. Quantification of environmental illnesses due to exposure to nitrogen dioxide in Germany. German Environment Agency, Dessau-Roßlau, 2018, p. 123, (in German). [CrossRef]
  3. Richard J., Mazur H., Lauenstein D. Manual Noise Action Plans – Recommendations for action for noise-reducing traffic planning. German Environment Agency, Dessau-Roßlau, 2015, p. 101, (in German). [CrossRef]
  4. Wolf M., Hund S., Rudolph M., Kanoun O. Design of a wireless and energy autonomous sensor network for condition monitoring of tram drive components. Designs, 2018, https://doi.org/10.3390/designs2040050. [Publisher]
  5. Wolf M., Hofbauer J., Rudolph M. Diagnostics using self-sufficient wireless sensor network for a condition-based maintenance strategy - strategy for tram bearing diagnostics. 13th International Multi-Conference on Systems, Signals and Devices, Leipzig, Germany, 2016, p. 518-522. [CrossRef]
  6. Mobile Sensor Systems for Maintenance in Transportation. LUST Hybrid Technik GmbH, 2016, https://www.tib.eu/suchen/id/TIBKAT:880572426/, (in German). [CrossRef]
  7. Condition Monitored Maintenance Using Self-Powered Sensors and Vibration Based. 2014, http://www.passenger-rolling-stock-maintenance.com/media/downloads/inline/perpetuum-case-study.1449847586.pdf. [CrossRef]
  8. Mechanical Vibration – Measurement and Evaluation of Machine Vibration – Part 1: General Guidelines (ISO 20816-1:2016). German Institute for Standardization, Beuth Verlag, Berlin, 2017, p. 12, (in German). [CrossRef]
  9. Verordnung über den Bau und Betrieb der Straßenbahnen (Straßenbahn-Bau- und Betriebsordnung – BOStrab). German Federal Regulations on the construction and operation of light rail transit systems, Berlin, 1987, p. 57. [CrossRef]
  10. Wolf M., Rudolph M., Köllner J. Vibration diagnostics of tram drive components – using sensor networks. ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol. 112, Issue 1, 2, p. 62-67, 2017, (in German). [Publisher]
  11. Mori H., Tsunashima H., Koijma T., Matsumoto A., Mizuma T. Condition monitoring of railway track using in-service vehicle. Journal of Mechanical Systems for Transportation and Logistics, Vol. 3, Issue 1, 2010, p. 154-165. [Publisher]
  12. Zimroz R., Urbanek J., Barszcz T., Bartelmus W., Millioz F., Martin N. Measurement of instantaneous shaft speed by advanced vibration signal processing – application to wind turbine gearbox. Metrology and Measurement Systems, Vol. 18, Issue 2011, 4, p. 701-712. [CrossRef]
  13. Vemuri A., Allemang R. J., Phillips A. W. Estimation of Instantaneous Speed for Rotating Systems: New Processing Techniques. Rotating Machinery, Hybrid Test Methods, Vibro-Acoustics and Laser Vibrometry. Proceedings of the 34th Conference and Exposition on Structural Dynamics, 2016. [Publisher]
  14. Aoudia F. A., Gautier M., Magno M., Berder O., Benini L. SNW-MAC: An Asynchonous Protocol Leveraging Wake-Up Receivers for Data Gathering in Star Networks. 7th International Conference on Sensor Systems and Software, Nice, France, 2016. [CrossRef]