Abstract
Virginia Tech’s Goodwin Hall is instrumented with over 200 highly sensitive, seismic accelerometers. These sensors detect motion from vibration sources inside the building (e.g. footsteps, HVAC equipment, and closing doors) and external (seismic motion and wind loading). The later sources produce much weaker excitations for the sensors and result in lower signal-to-noise ratios. Therefore, it is important to estimate the inherent noise present in the accelerometer signals in order to determine and analyze the actual building vibrations from seismic motion and wind loading. Sources of noise include electrical interference and self-noise in the instrumentation system including the accelerometers, cables, and signal conditioning amplifiers. This paper will examine several techniques for using collocated sensors for estimating the power spectral densities of the noise present in accelerometer measurements. First these estimation techniques are applied to simulated signals corrupted by noise. Then these methods are applied to laboratory data from several accelerometers placed on a vibration isolation table.
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Acknowledgements
The authors are thankful for the support and collaborative efforts provided by our sponsors VTI Instruments; PCB Piezotronics, Inc.; Dytran Instruments, Inc.; and Oregano Systems. The authors would also like to recognize the support from the College of Engineering at Virginia Tech, collaboration efforts with Gilbane, Inc., and financial support from the Student Engineering Council at Virginia Tech.
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Joyce, B.S., Tarazaga, P.A. (2016). Estimating Noise Spectra for Data from an Instrumented Building. In: Atamturktur, S., Schoenherr, T., Moaveni, B., Papadimitriou, C. (eds) Model Validation and Uncertainty Quantification, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-29754-5_9
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DOI: https://doi.org/10.1007/978-3-319-29754-5_9
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