Autonomous evaluation of human annoyance rate induced by subway trains using high-sensitivity wireless smart sensors

Wei Zhang, Ke Sun, Huaping Ding, Robin E. Kim, B F Spencer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The operation of subway trains induces secondary structure-borne vibrations in the nearby buildings. The vibration, along with the associated noise, can cause annoyance and adverse physical, physiological, and psychological effects on humans. Traditional tethered instruments restrict the rapid measurement and assessment on such vibration effect. This paper presents a novel approach for Wireless Smart Sensor (WSS)-based autonomous evaluation system for the subway train-induced human annoyance rate. The system was implemented on the MEMSIC's Imote2 platform, using a SHM-H high-sensitivity accelerometer board stacked on top. A new embedded application AnnoyanceRate, which quantitatively determines the adverse vibration impact on human comfort, was added into the Illinois Structural Health Monitoring Project Service Toolsuite. The system was verified in a large underground space, where a nearby subway station is a good source of ground excitation caused by the running subway trains. Using an on-board processor of the Imote2, each sensor calculated the distribution of vibration levels within the testing zone, and sent the distribution of human annoyance rate to the central server via radio to display the information. Also, the raw time-histories and frequency spectrum were retrieved from the WSS leaf nodes. Subsequently, spectral vibration levels in the one-Third octave band, characterizing the vibrating influence of different frequency components on human bodies, was also calculated from each sensor node. Experimental validation demonstrates that the proposed system is efficient for autonomously evaluating the subway train-induced adverse effect on human comfort and the system holds the potential of greatly reducing the laboring of dynamic field testing.

Original languageEnglish (US)
Title of host publicationTransforming the Future of Infrastructure through Smarter Information - Proceedings of the International Conference on Smart Infrastructure and Construction, ICSIC 2016
EditorsAjith K. Parlikad, Jennifer M. Schooling, Kenichi Soga, R.J. Mair, Ying Jin
PublisherICE Publishing
Pages221-226
Number of pages6
ISBN (Electronic)9780727761279
DOIs
StatePublished - Jan 1 2016
Event2016 International Conference on Smart Infrastructure and Construction, ICSIC 2016 - Cambridge, United Kingdom
Duration: Jun 27 2016Jun 29 2016

Publication series

NameTransforming the Future of Infrastructure through Smarter Information - Proceedings of the International Conference on Smart Infrastructure and Construction, ICSIC 2016

Other

Other2016 International Conference on Smart Infrastructure and Construction, ICSIC 2016
CountryUnited Kingdom
CityCambridge
Period6/27/166/29/16

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

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  • Cite this

    Zhang, W., Sun, K., Ding, H., Kim, R. E., & Spencer, B. F. (2016). Autonomous evaluation of human annoyance rate induced by subway trains using high-sensitivity wireless smart sensors. In A. K. Parlikad, J. M. Schooling, K. Soga, R. J. Mair, & Y. Jin (Eds.), Transforming the Future of Infrastructure through Smarter Information - Proceedings of the International Conference on Smart Infrastructure and Construction, ICSIC 2016 (pp. 221-226). (Transforming the Future of Infrastructure through Smarter Information - Proceedings of the International Conference on Smart Infrastructure and Construction, ICSIC 2016). ICE Publishing. https://doi.org/10.1680/tfitsi.61279.221