Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Experimental validation of smartphones for measuring human-induced loads

  • Chen, Jun (Department of Structural Engineering, Tongji University) ;
  • Tan, Huan (Department of Structural Engineering, Tongji University) ;
  • Pan, Ziye (Department of Structural Engineering, Tongji University)
  • Received : 2015.05.30
  • Accepted : 2015.08.20
  • Published : 2016.09.25
⟨ Previous Next ⟩

Abstract

The rapid technology developments in smartphones have created a significant opportunity for their use in structural live load measurements. This paper presents extensive experiments conducted in two stages to investigate this opportunity. Shaking table tests were carried out in the first stage using selected popular smartphones to measure the sinusoidal waves of various frequencies, the sinusoidal sweeping, and earthquake waves. Comparison between smartphone measurements and real inputs showed that the smartphones used in this study gave reliable measurements for harmonic waves in both time and frequency domains. For complex waves, smartphone measurements should be used with caution. In the second stage, three-dimensional motion capture technology was employed to explore the capacity of smartphones for measuring the movement of individuals in walking, bouncing and jumping activities. In these tests, reflective markers were attached to the test subject. The markers' trajectories were recorded by the motion capture system and were taken as references. The smartphone measurements agreed well with the references when the phone was properly fixed. Encouraged by these experimental validation results, smartphones were attached to moving participants of this study. The phones measured the acceleration near the center-of-mass of his or her body. The human-induced loads were then reconstructed by the acceleration measurements in conjunction with a biomechanical model. Satisfactory agreement between the reconstructed forces and that measured by a force plate was observed in several instances, clearly demonstrating the capability of smartphones to accurately assist in obtaining human-induced load measurements.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation

References

  1. Araujo, J., Carlos, M. and Brito H.M.B.F. (2009), "Experimental evaluation of synchronization in footbridges due to crowd density", Struct. Eng. Int., 19(3), 298-303. https://doi.org/10.2749/101686609788957784
  2. Brownjohn, J.M.W., Fok, P. and Roche, M. (2004), "Long span steel pedestrian bridge at Singapore Changi Airport-Part 1: prediction of vibration serviceability problems", Struct. Eng., 82(16), 21-27.
  3. Cao, D., Wang, H. and Hu, Y. (2009), "Design and research of remote ECG display system based on smartphone", J. Xihua U: Nat. Sci. Ed., 4, 005.
  4. Chen, J., Zhang, M.S. and Liu, W. (2015), "Vibration serviceability performance of an externally prestressed concrete floor during daily use and under controlled human activities", J. Perform. Constr. Fac.
  5. Chen, J., Zhang, M.S., Zhao, Y.F. and Zhan, H.S. (2014), "Kinematic data smoothing using ensemble empirical mode decomposition", J. Med. Imag. Health Inform., 4(4), 540-546. https://doi.org/10.1166/jmihi.2014.1281
  6. Dierick, F., Penta, M. and Renaut, D. (2004), "A force measuring treadmill in clinical gait analysis", Gait. Posture., 20(3), 299-303. https://doi.org/10.1016/j.gaitpost.2003.11.001
  7. Feng, M., Fukuda, Y., Mizuta, M. et al. (2015), "Citizen sensors for SHM: use of accelerometer data from smartphones", J. Sensors, 15(2), 2980-2998. https://doi.org/10.3390/s150202980
  8. Fujino, Y., Pacheco, B.M., Nakamura, S.I. et al. (1993), "Synchronization of human walking observed during lateral vibration of a congested pedestrian bridge", Earthq. Eng. Struct. D., 22(9), 741-758. https://doi.org/10.1002/eqe.4290220902
  9. Khan, A.M., Lee, Y.K., Lee, S.Y. et al. (2010), "Human activity recognition via an accelerometer-enabled-smartphone using kernel discriminant analysis", Future Information Technology (FutureTech), Busan, Korea, May.
  10. Lau, S.L., Konig I., David, K. et al. (2010), "Supporting patient monitoring using activity recognition with a smartphone", Wireless Communication Systems (ISWCS), 2010 7th International Symposium on. IEEE. 810-814.
  11. Lee, Y. and Cho, S. (2011), "Activity recognition using hierarchical hidden markov models on a smartphone with 3D accelerometer", Hybrid Artificial Intelligent Systems, Wroclaw, Poland, May.
  12. Littler, J.D. (2003), "Frequencies of synchronised human loading from jumping and stamping". Struct. Eng., 81(22), 27-35.
  13. Peng, Y.X., Chen, J. and Ding, G. (2015), "Walking load model for single footfall trace in three dimensions based on gait experiment", Struct. Eng. Mech., 54(5), 937-953. https://doi.org/10.12989/sem.2015.54.5.937
  14. Richards, J.G. (1999), "The measurement of human motion: a comparison of commercially available systems", Hum. Movement. Sci., 18(5), 589-602. https://doi.org/10.1016/S0167-9457(99)00023-8
  15. Spencer, B.F. (2003), "Opportunities and challenges for smart sensing technology", Structural Health Monitoring and Intelligent Infrastructure, Tokyo, Japan, November.
  16. Van Nimmen, K., Lombaert, G., Jonkers, I. et al. (2014), "Characterization of walking loads by 3D inertial motion tracking", J. Sound. Vib., 333(20), 5212-5226. https://doi.org/10.1016/j.jsv.2014.05.022
  17. Wang, L., Chen, J. and Peng Y.X. (2011), "Novel techniques for human-induced loading experiment and data processing", Proceeding of the International Symposium on Innovation & Sustainability of Structures in Civil Engineering, Xiamen, China, October.
  18. Wu, W., Dasgupta, S., Ramirez, E.E. et al. (2012), "Classification accuracies of physical activities using smartphone motion sensors", J. Med. Internet. Res., 14(5), e130. https://doi.org/10.2196/jmir.2208
  19. Yoshida, J., Fujino, Y. and Sugiyama, T. (2007), "Image processing for capturing motions of crowd and its application to pedestrian-induced lateral vibration of a footbridge", Shock. Vib., 14(4), 251-260. https://doi.org/10.1155/2007/763437
  20. Yu, Y., Han, R., Zhao, X. et al. (2015), "Initial validation of mobile-structural health monitoring method using smartphones", Int. J. Distrib.Sens. N..
  21. Zhang M.S., Chen, J., Peng, Y.X. and Wang, L. (2013), "Reproduction and simulation of walking induced load via motion capture technique and inverse dynamics of rigid body models", J. Basic Sci. Eng., 21(5), 961-972 (in Chinese).
  22. Zhang, M., Gong, W., Li, Z. et al. (2007), "Design of remote monitoring system for household appliances and home security based on smart phone", Meas. Control. Tech., 8, 024.

Cited by

  1. Measurements of pedestrian's ioad using smartphones vol.63, pp.6, 2016, https://doi.org/10.12989/sem.2017.63.6.771
  2. Data-Driven Synchronization Analysis of a Bouncing Crowd vol.2019, pp.None, 2016, https://doi.org/10.1155/2019/8528763
  3. Testing Walking-Induced Vibration of Floors Using Smartphones Recordings vol.9, pp.2, 2016, https://doi.org/10.3390/robotics9020037
  4. Structural modal testing using a human actuator vol.221, pp.None, 2016, https://doi.org/10.1016/j.engstruct.2020.111113
  5. Pedestrian-Induced Load Identification from Structural Responses Using Genetic Algorithm with Numerical and Experimental Validation vol.26, pp.3, 2016, https://doi.org/10.1061/(asce)be.1943-5592.0001687
  6. Prediction of floor responses to crowd bouncing loads by response reduction factor and spectrum method vol.24, pp.7, 2016, https://doi.org/10.1177/1369433220975567