Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Feasibility study on using crowdsourced smartphones to estimate buildings' natural frequencies during earthquakes

  • Ting-Yu Hsu (Department of Civil and Construction Engineering, National Taiwan University of Science and Technology) ;
  • Yi-Wen Ke (Department of Civil and Construction Engineering, National Taiwan University of Science and Technology) ;
  • Yo-Ming Hsieh (Department of Civil and Construction Engineering, National Taiwan University of Science and Technology) ;
  • Chi-Ting Weng (Department of Civil and Construction Engineering, National Taiwan University of Science and Technology)
  • Received : 2022.04.03
  • Accepted : 2022.10.29
  • Published : 2023.02.25
⟨ Previous Next ⟩

Abstract

After an earthquake, information regarding potential damage to buildings close to the epicenter is very important during the initial emergency response. This study proposes the use of crowdsourced measured acceleration response data collected from smartphones located within buildings to perform system identification of building structures during earthquake excitations, and the feasibility of the proposed approach is studied. The principal advantage of using crowdsourced smartphone data is the potential to determine the condition of millions of buildings without incurring hardware, installation, and long-term maintenance costs. This study's goal is to assess the feasibility of identifying the lowest fundamental natural frequencies of buildings without knowing the orientations and precise locations of the crowds' smartphones in advance. Both input-output and output-only identification methods are used to identify the lowest fundamental natural frequencies of numerical finite element models of a real building structure. The effects of time synchronization and the orientation alignment between nearby smartphones on the identification results are discussed, and the proposed approach's performance is verified using large-scale shake table tests of a scaled steel building. The presented results illustrate the potential of using crowdsourced smartphone data with the proposed approach to identify the lowest fundamental natural frequencies of building structures, information that should be valuable in making emergency response decisions.

Keywords

Acknowledgement

This work was financially supported by the Taiwan Building Technology Center from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education in Taiwan.

References

  1. Borenius, S., Costa-Requena, J., Lehtonen, M. and Kantola, R. (2019), "Providing network time protocol based timing for smart grid measurement and control devices in 5G networks", Proceedings of 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Beijing, China, pp. 1-6.
  2. Brincker, R., Zhang, L. and Andersen P. (2001), "Modal identification of output-only systems using frequency domain decomposition", Smart Mater. Struct., 10(3), 441. https://doi.org/10.1088/0964-1726/10/3/303
  3. Clayton, R.W., Heaton, T., Kohler, M., Chandy, M., Guy, R. and Bunn, J. (2015), "Community seismic network: A dense array to sense earthquake strong motion", Seismol Res. Lett., 86(5), 1354-1363. https://doi.org/10.1785/0220150094
  4. Dashti, S., Bray, J.D., Reilly, J., Glaser, S., Bayen, A. and Mari, E. (2014), "Evaluating the reliability of phones as seismic monitoring instruments", Earthq Spectra, 30(2), 721-742. https://doi.org/10.1193/091711EQS229M
  5. Dong, C.Z., Bas, S. and Catbas, F.N. (2019), "A completely non-contact recognition system for bridge unit influence line using portable cameras and computer vision", Smart Struct. Syst., Int. J., 24(5), 617-630. https://doi.org/10.12989/sss.2019.24.5.617
  6. Elhattab, A., Uddin, N. and Obrien, E. (2019), "Extraction of bridge fundamental frequencies utilizing a smartphone MEMS accelerometer", Sensors, 19, 3143. https://doi.org/10.3390/s19143143
  7. Ewins, D.J. (2000), Modal Testing, (2nd Ed.), Research Studies Press, Baldock.
  8. Faulkner, M., Clayton, R., Heaton, T., Chandy, K.M., Kohler, M., Bunn, J., Guy, R., Liu, A., Olson, M., Cheng, M.H. and Krause, A. (2014), "Community sense and response systems: your phone as quake detector", Commun. ACM, 57, 66-75. https://doi.org/10.1145/2622633
  9. Feng, M., Fukuda, Y., Mizuta, M. and Ozer, E. (2015), "Citizen Sensors for SHM: Use of accelerometer data from smartphones", Sensors, 15, 2980-2998. https://doi.org/10.3390/s150202980
  10. Finazzi, F. (2016), "The earthquake network project: Toward a crowdsourced smartphone-based earthquake early warning system", Bull. Seismol. Soc. Am., 106, 1088. https://doi.org/10.1785/0120150354
  11. Finzi Neto, R.M., Steffen Jr, V., Rade, D.A., Gallo, C.A. and Palomino, L.V. (2010), "A low-cost electromechanical impedance-based SHM architecture for multiplexed piezoceramic actuators", Struct. Health Monitor., 10, 391-402. https://doi.org/10.1177/1475921710379518
  12. Haque, M.E., Zain, M.F.M., Hannan, M.A. and Rahman, M.H. (2015), "Building structural health monitoring using dense and sparse topology wireless sensor network", Smart Struct. Syst., Int. J., 16(4), 607-621. https://doi.org/10.12989/sss.2015.16.4.607
  13. Hsu, T.Y. and Nieh, C.P. (2020), "On-site earthquake early warning using smartphones", Sensors, 20, 2928. https://doi.org/10.3390/s20102928
  14. Hsu, T.Y., Yin, R.C. and Wu, Y.M. (2018), "Evaluating post-earthquake building safety using economical MEMS seismometers", Sensors, 18(5), 1437. https://doi.org/10.3390/s18051437
  15. Hsu, T.Y., Pham, Q.V., Chao, W.C. and Yang, T.S. (2020), "Post-earthquake building safety evaluation using consumer-grade surveillance cameras", Smart Struct. Syst., Int. J., 25(5), 531-541. https://doi.org/10.12989/sss.2020.25.5.531
  16. Hsu, T.Y., Liu, C.Y., Hsieh, Y.M. and Weng, C.T. (2022), "Post-earthquake fast building safety assessment using smartphone-based interstory drifts measurement", Smart Struct. Syst., Int. J., 29(2), 287-299. https://doi.org/10.12989/sss.2022.29.2.287
  17. Kim, R.E., Li, J., Spencer, B.F., Nagayama, T. and Mechitov, K.A. (2016a), "Synchronized sensing for wireless monitoring of large structures", Smart Struct. Syst., Int. J., 18(5), 885-909. https://doi.org/10.12989/sss.2016.18.5.885
  18. Kim, J.M., Han, M., Lim, H.J., Yang, S. and Sohn, H. (2016b), "Operation of battery-less and wireless sensor using magnetic resonance based wireless power transfer through concrete", Smart Struct. Syst., Int. J., 17(4), 631-646. https://doi.org/10.12989/sss.2016.17.4.631
  19. Kohler, M.D., Massari, A., Heaton, T.H., Kanamori, H., Hauksson, E., Guy, R., Clayton, R.W., Bunn, J. and Chandy, K.M. (2016), "Downtown Los Angeles 52-story high-rise and free-field response to an oil refinery explosion", Earthq. Spectra, 32(3), 1793-1820. https://doi.org/10.1193/062315EQS101M
  20. Kong, Q., Allen, R.M. and Schreier, L. (2016a), "Myshake: Initial observations from a global smartphone seismic network", Geophys. Res. Lett., 43, 9588-9594. https://doi.org/10.1002/2016GL070955
  21. Kong, Q., Allen, R.M., Schreier, L. and Kwon, Y.W. (2016b), "MyShake: A smartphone seismic network for earthquake early warning and beyond", Sci. Adv., 2(2), e1501055. https://doi.org/10.1002/2016GL070955
  22. Kong, Q., Allen, R.M., Kohler, M.D., Heaton, T.H. and Bunn, J. (2018), "Structural health monitoring of buildings using smartphone sensors", Seismol. Res. Lett., 89, 594-602. https://doi.org/10.1785/0220170111
  23. Lei, B., Ren, Y., Wang, N., Huo, L. and Song, G. (2020), "Design of a new low-cost unmanned aerial vehicle and vision-based concrete crack inspection method", Struct. Health Monit., 19(6), 1871-1883. https://doi.org/10.1177/1475921719898862
  24. Mills, D.L. (1991), "Internet time synchronization: the network time protocol", IEEE Trans. Commun., 39(10), 1482-1493. https://doi.org/10.1109/26.103043
  25. Miskinis, R., Smirnov, D., Urba, E. and Dzindzeleta, B. (2011), "Timing and synchronization in mobile telecommunication networks. Frequency Control and the European Frequency and Time Forum (FCS)", Proceedings of 2011 Joint Conference of the IEEE International, San Francisco, CA, USA, May, pp. 665-669.
  26. Ozer, E., Feng, M.Q. and Feng, D. (2015), "Citizen sensors for SHM: Towards a crowdsourcing platform", Sensors, 15, 14591-14614. https://doi.org/10.3390/s150614591
  27. Peeters, B. and De Roeck, G. (1999), "Reference-based stochastic subspace identification for output-only modal analysis", Mech. Syst. Signal Process., 13(6), 855-878. https://doi.org/10.1006/mssp.1999.1249
  28. Reynders, E. and De Roeck, G. (2008), "Reference-based combined deterministic-stochastic subspace identification for experimental and operational modal analysis", Mech. Syst. Signal Process., 22(3), 617-637. https://doi.org/10.1016/j.ymssp.2007.09.004
  29. Shen, Y., Fu, W., Luo, Y., Yun, C.B., Liu, D., Yang, P., Yang, G. and Zhou, G. (2021), "Implementation of SHM system for Hangzhou East Railway Station using a wireless sensor network", Smart Struct. Syst., Int. J., 27(1), 19-33. https://doi.org/10.12989/sss.2021.27.1.019
  30. Shrestha, A., Dang, J. and Wang, X. (2018), "Development of a smart-device-based vibration measurement system: Effectiveness examination and application cases to existing structure", Struct. Control Health Monit., 25, e2120. https://doi.org/10.1002/stc.2120
  31. Sun, Z., Krishnan, S., Hackmann, G., Yan, G., Dyke, S.J., Lu, C. and Irfanoglu, A. (2015), "Damage detection on a full-scale highway sign structure with a distributed wireless sensor network", Smart Struct. Syst., Int. J., 16(1), 223-242. https://doi.org/10.12989/sss.2015.16.1.223
  32. Sun, K., Zhang, W., Ding, H., Kim, R.E. and Spencer, B.F. (2017), "Autonomous evaluation of ambient vibration of underground spaces induced by adjacent subway trains using high-sensitivity wireless smart sensors", Smart Struct. Syst., Int. J., 19(1), 1-10. https://doi.org/10.12989/sss.2017.19.1.001
  33. Withers, M., Aster, R., Young, C., Beiriger, J., Harris, M., Moore, S. and Trujillo, J. (1998), "A comparison of select trigger algorithms for automated global seismic phase and event detection", Bull. Seismol. Soc. Am., 88(1), 95-106. https://doi.org/10.1785/BSSA0880010095
  34. Wu, W.H, Wang, S.W., Chen, C.C. and Lai, G. (2017), "Assessment of environmental and nondestructive earthquake effects on modal parameters of an office building based on long-term vibration measurements", Smart Mater. Struct., 26, 055034. https://doi.org/10.1088/1361-665X/aa6ae6
  35. Yu, Y., Han, R., Zhao, X., Mao, X., Hu, W., Jiao, D. and Ou, J. (2015), "Initial validation of mobile-structural health monitoring method using smartphones", Int. J. Distrib. Sensor Networks, 11(2), p.274391. https://doi.org/10.1155/2015/274391
  36. Yu, Q., Guan, B., Shang, T., Liu, X. and Li, Z. (2019), "Flexible camera series network for deformation measurement of large scale structures", Smart Struct. Syst., Int. J., 24(5), 587-595. https://doi.org/10.12989/sss.2019.24.5.587
  37. Zonta, D., Wu, H., Pozzi M., Zanon, P., Ceriotti, M., Mottola, L., Picco, G.P., Murphy, A.L., Guna, S. and Corra, M. (2010), "Wireless sensor networks for permanent health monitoring of historic buildings", Smart Struct. Syst., Int. J., 6(5), 595-618. https://doi.org/10.12989/sss.2010.6.5_6.595