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Torbol, Marco
Reliability & Risk Assessment Laboratory (R2A lab)
Research Interests
  • Reliability analysis, probabilistic safety assessment, probabilistic risk assessment,structural health monitoring, system identification, damage assessment

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Real-time frequency-domain decomposition for structural health monitoring using general-purpose graphic processing unit

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Title
Real-time frequency-domain decomposition for structural health monitoring using general-purpose graphic processing unit
Author
Torbol, Marco
Keywords
WAVELET NEURAL-NETWORK; SYSTEM-IDENTIFICATION; MODAL IDENTIFICATION; PARAMETER-IDENTIFICATION; DAMAGE IDENTIFICATION; CONTROL-OPTIMIZATION; BIDIAGONAL MATRICES; HIGHRISE BUILDINGS; ALGORITHM; SENSOR
Issue Date
2014-10
Publisher
WILEY-BLACKWELL
Citation
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, v.29, no.9, pp.689 - 702
Abstract
Frequency-domain decomposition (FDD) is used in civil engineering to identify the modal properties of structures by analyzing the data output of structural health monitoring (SHM) systems. However, because FDD is computationally expensive, it prevents CPUs from achieving real-time performance. A CPU takes seconds to perform FDD of 16 input signals but minutes to perform FDD of hundreds of input signals; and the deployed SHM systems are becoming larger and larger. Instead, a supercomputer can achieve real-time performance but it cannot be installed near a civil structure because it is bulky, expensive, and requires constant maintenance. In this study, FDD is performed using general-purpose graphic processor unit (GPGPU). A GPU is capable of massive parallel computing. The developed parallel FDD algorithm is up to hundreds of times faster than its serial version on CPU. For SHM of civil structures, where natural frequencies are less than 20 Hz parallel FDD on a single GPU achieves real-time performance. The use of GPGPU offers many advantages. The modal properties are tracked in real time. A GPU can be installed inside the base station at a structure site. A GPU is energy efficient and does not require the maintenance of a supercomputer.
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DOI
10.1111/mice.12097
ISSN
1093-9687
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UEE_Journal Papers
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