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Applications of Smartphone Seismic Data for Rapid Structural Health Assessment
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  • Sarina Patel,
  • Qingkai Kong,
  • Selim Gunay,
  • Richard Allen
Sarina Patel
University of California Berkeley

Corresponding Author:saricpatel@gmail.com

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Qingkai Kong
UC Berkeley
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Selim Gunay
UC Berkeley
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Richard Allen
Univ California Berkeley
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Abstract

The citizen science app, MyShake, represents a new source of global seismic data that can be provided with much higher density sampling than a traditional seismic network, and at a relatively low cost. Because phones are most frequently located in buildings, the signals they record include structural response information in addition to ground shaking. This work explores the capabilities of MyShake as a remote damage detection tool within the field of structural health monitoring. There are several common, empirically determined parameters, such as modal frequency and inter-story drift, which characterize buildings and their response to shaking. Structural damage causes these values to deviate from their ‘healthy’ baseline. Using data collected during smaller excitations, we aim to generate a database of healthy values for buildings in which MyShake users live and work. Then, when a significant earthquake occurs, data from the mainshock and aftershock coda seismic records can be analyzed to detect deviation from this baseline, permitting a rapid, remote diagnosis of damage that could provide critical information to engineers on the ground. To gauge the expected capabilities of MyShake while the system is still relatively new, we compile a database of waveforms collected by the Center for Engineering Strong Motion Data (CESMD), which has instrumented buildings across California. Available CESMD data spans several years, building types, and earthquake magnitudes. After ‘downgrading’ these data to emulate the quality of waveforms collected by MyShake, we determine how big and how close an earthquake needs to be to excite buildings so that key structural health parameters can be determined. These data also inform our expectations for the range of values that typify each building type and size, permitting a gauge for the reasonableness of our results from true phone data. Demonstrative examples from this CESMD-based database in addition to real MyShake examples will be presented.