Estimating Noise Spectra for Data from an Instrumented Building
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Virginia Techs 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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Model Validation and Uncertainty Quantification, Volume 3
