Building response analyses recorded by force-balanced and micro-electro mechanical system accelerometers

References

• Y.U. Jun, and T.A.N. Kanghai, Structural behavior of reinforced concrete frames subjected to progressive collapse, ACI Struct. J., vol. 114, no. 1, pp. 63–74, 2017.
   Web of Science ®Google Scholar
• R. Nazanin, K. Gary, and B.G. David, Effect of development and geometry on behavior of concrete deep beams, ACI Struct. J., vol. 116, no. 3, pp. 171–181, 2019.
   Web of Science ®Google Scholar
• J.C. Reyes, W.A. Avila, E. Kalkan, et al., Reducing processing time of nonlinear analysis of symmetric-plan buildings, J. Struct. Eng., vol. 147, no. 6, pp. 1–14, 2021.
   Web of Science ®Google Scholar
• L.I.M. Namyo Salim, K.H. Tan, and C.K. LEE, Effects of rotational capacity and horizontal restraint on development of catenary action in 2-D RC frames, Eng. Struct., vol. 153, pp. 613–627, 2017.
   Web of Science ®Google Scholar
• W. Shan, P. Jun, and K. Shaobo, Evaluation of compressive arch action of reinforced concrete beams and development of design method, Eng. Struct., vol. 191, pp. 479–492, 2019.
   Web of Science ®Google Scholar
• A.N.S. Tiago, R.A.B. Almeida, and A.P.V. Urgueira, On the use of measured rotational responses in structural dynamic analysis, J. Phys. Conf. Ser., vol. 1106, no. 1, pp. 012019–012019, 2018.
   Google Scholar
• X.U. Xiangyang, Augello. Riccardo, and Y. A. N. G. Hao, The generation and validation of a CUF-based FEA model with laser-based experiments, Mech. Adv. Mater. Struct., vol. 28, no. 16, pp. 1–8, 2019.
   Web of Science ®Google Scholar
• H. Ozturk, A. Yashar, and M. Sabuncu, Dynamic stability of cracked multi-bay frame structures, Mech. Adv. Mater. Struct., vol. 23, no. 6, pp. 715–726, 2016. DOI: https://doi.org/10.1080/15376494.2015.1029160.
   Web of Science ®Google Scholar
• S. Beskhyroun, L.M. Wotherspoon, and Q.T. Ma, System identification of a 13-story reinforced concrete building through ambient and forced vibration, In 4th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, 2013. Kos Island, Greece.
   Google Scholar
• C. Marco, C. Giulia, and Z. Fragonara Luca, System identification via fast relaxed vector fitting for the structural health monitoring of masonry bridges, Structures., vol. 30, pp. 277–293, 2021.
   Web of Science ®Google Scholar
• F. Pioldi, and E. Rizzi, Full dynamic compound inverse Method for seismic output-only element-level and input identification: Unitary formulation and extensive validation, Mech. Syst. Sig. Process., vol. 111, pp. 580–614, 2018. DOI: https://doi.org/10.1016/j.ymssp.2018.04.013.
   Web of Science ®Google Scholar
• R. Cardoso, A. Cury, and F. Barbosa, A robust methodology for modal parameters estimation applied to SHM, Mech. Syst. Sig. Process., vol. 95, pp. 24–41, 2017. DOI: https://doi.org/10.1016/j.ymssp.2017.03.021.
   Web of Science ®Google Scholar
• R. Astroza, J.P. Conte, J.I. Restrepo, H. Ebrahimian, and T. Hutchinson, Seismic response analysis and modal identification of a full-scale five-story base-isolated building tested on the NEES@UCSD shake table, Eng. Struct., vol. 238, pp. 112087–112016, 2021. DOI: https://doi.org/10.1016/j.engstruct.2021.112087.
   Web of Science ®Google Scholar
• Z. Jie, L. Hongnan, and L. Chao, Seismic response of large-span spatial structures under multi-support and multidimensional excitations including rotational components, Earthquake Eng. Eng. Vib., vol. 20, no. 1, pp. 141–159, 2021.
   Web of Science ®Google Scholar
• Z. Lei, L. Yiping, and Z. Ge, Analysis of structural responses of bridges based on long-term structural health monitoring, Mech. Adv. Mater. Struct., vol. 25, no. 1, pp. 79–86, 2018.
   Web of Science ®Google Scholar
• A. Bastani, H. Amindavar, M. Shamshirsaz, et al., Adaptive linear prediction damage detection technique in structural health monitoring, Mech. Adv. Mater. Struct., vol. 19, no. 6, pp. 492–498, 2012. DOI: https://doi.org/10.1080/15376494.2011.556838.
   Web of Science ®Google Scholar
• G. Oliveira, F. Magalhaes, A. Cunha, et al., Continuous dynamic monitoring of an onshore wind turbine, Eng. Struct., vol. 164, pp. 22–39, 2018. DOI: https://doi.org/10.1016/j.engstruct.2018.02.030.
   Web of Science ®Google Scholar
• M. Domaneschi, M.P. Limongelli, and L. Martinelli, Damage detection and localization on a benchmark cable-stayed bridge, Earthq. Struct., vol. 8, no. 5, pp. 1113–1126, 2015. DOI: https://doi.org/10.12989/eas.2015.8.5.1113.
   Web of Science ®Google Scholar
• Ganesh. Hegde, and Ravi. Sinha, A technique for placing few sensors on a building for complete modal identification, Mech. Adv. Mat. Struct., vol. 16, no. 3, pp. 248–259, 2009. DOI: https://doi.org/10.1080/15376490902746970.
   Web of Science ®Google Scholar
• C. Hugo, N. Pascal, F. Cécile, et al., A package-less SAW RFID sensor concept for structural health monitoring, Mech. Adv. Mat. Struct., vol. 28, no. 6, pp. 1–8, 2021.
   Web of Science ®Google Scholar
• A. D’Alessandro, S. Scudero, and G. Vitale, A review of the capacitive MEMS for seismology, Sensors., vol. 19, no. 14, pp. 3093, 2019. DOI: https://doi.org/10.3390/s19143093.
   Web of Science ®Google Scholar
• A.V.S. Shaik, R. Chow, K. Mechitov, et al., Development of synchronized high-sensitivity wireless accelerometer for structural health monitoring, Sensors., vol. 20, pp. 4169, 2020.
   Web of Science ®Google Scholar
• X. Hu, X. Wang, B. Chen, et al., Improved resolution and cost performance of low-cost MEMS seismic sensor through parallel acquisition, Sensors., vol. 21, no. 23, pp. 7970, 2021. DOI: https://doi.org/10.3390/s21237970.
   PubMedGoogle Scholar
• L. Jian, K.A. Mechitov, R.E. Kim, et al., Efficient time synchronization for structural health monitoring using wireless smart sensor networks, Struct. Control Health Monit., vol. 22, no. 3, pp. 470–486, 2016.
   Google Scholar
• F. Magalhaes, A. Cunha, and E. Caetano, Vibration based structural health monitoring of an arch bridge: from automated OMA to damage detection, Mech. Syst. Sig. Process., vol. 28, pp. 212–228, 2012. DOI: https://doi.org/10.1016/j.ymssp.2011.06.011.
   Web of Science ®Google Scholar
• M.I. Todorovska, and M.T. Rahmani, System identification of buildings by wave travel time analysis and layered shear beam models-spatial resolution and accuracy, Struct. Control Health Monit., vol. 20, no. 5, pp. 686–702, 2013. DOI: https://doi.org/10.1002/stc.1484.
   Web of Science ®Google Scholar
• J.H. Kuroiwa, Vibration test of a multi-storey building, Ph.D. thesis, 1967. California Institute of Technology.
   Google Scholar
• M.D. Trifunac, Comparisons between ambient and forced vibration experiments, Earthquake Eng. Struct. Dyn., vol. 1, no. 2, pp. 133–150, 1972. DOI: https://doi.org/10.1002/eqe.4290010203.
   Google Scholar
• J. Luco, M. Trifunac, and H. Wong, On the apparent change in dynamic behavior of a 9-story reinforced-concrete building, Bull. Seism. Soc. Am., vol. 77, no. 6, pp. 1961–1963, 1987. DOI: https://doi.org/10.1785/BSSA0770061961.
   Web of Science ®Google Scholar
• R. Snieder, and E. Safak, Extracting the building response using interferometry: theory and applications to the Millikan Library in Pasadena, California. Bull. Seism. Soc. Am., vol. 96, no. 2, pp. 586–598, 2006. DOI: https://doi.org/10.1785/0120050109.
   Web of Science ®Google Scholar
• J.F. Clinton, Modern digital seismology-instrumentation, and small amplitude studies in the engineering world, Ph.D. Thesis, 2004. California Institute of Technology.
   Google Scholar
• T. Jun Hui, O. Zhi Chao, L.C. Lek, et al., Identification of material properties of composite plates using Fourier-generated frequency response functions, Mech. Adv. Mater. Struct., vol. 26, no. 2, pp. 119–128, 2019.
   Web of Science ®Google Scholar
• K. Holschemacher, I. Iskhakov, Y. Ribakov, et al., Laboratory tests of two-layer beams consisting of normal and fibered high strength concrete: ductility and technological aspects, Mech. Adv. Mater. Struct., vol. 19, no. 7, pp. 513–522, 2012. DOI: https://doi.org/10.1080/15376494.2011.556840.
   Web of Science ®Google Scholar
• L. Hui, X. Pengcheng, Z. Tinan, et al., Nonlinear vibration study of fiber-reinforced composite thin plate with strain-dependent property based on strain energy density function method, Mech. Adv. Mater. Struct., vol. 27, no. 9, pp. 761–773, 2020.
   Web of Science ®Google Scholar
• L. Hang, and L. Wenhong, Time delay estimation method used median filter in low signal to noise ratio pulse environment, E3S Web of Conferences, 2021. 252, PP. 02039–02044.
   Google Scholar
• F. Traversaro, W. Legnani, and F.O. Redelico, Influence of the signal to noise ratio for the estimation of Permutation Entropy, Phys. A Stat. Mech. Appl., vol. 553, pp. 124134–124112, 2020. DOI: https://doi.org/10.1016/j.physa.2020.124134.
   Google Scholar