Target-free approach for vision-based structural system identification using consumer-grade cameras

Hyungchul Yoon, Hazem Elanwar, Hajin Choi, Mani Golparvar Fard, B F Spencer

Research output: Contribution to journalArticlepeer-review

Abstract

Recent reports on America's infrastructure have emphasized the importance of structural health monitoring of civil infrastructures. System identification is a key component of many structural health monitoring strategies. Current system identification methods estimate models of a structure by measuring displacements, accelerations, and strains with wired or wireless sensors. However, these methods typically involve installation of a limited number of sensors at discrete locations and require additional data acquisition devices. To overcome these limitations, computer vision-based techniques have been introduced recently that employ high-speed and high-resolution cameras. Such cameras can be quite costly and require tedious installation of targets. This paper investigates the potential of using consumer-grade cameras for structural system identification without the need to install targets. The underlying methods for target-free displacement measurements are introduced, including region of interest selection, feature detection, point tracking, and outlier removal. A set of experiments are conducted to assess the efficacy of the proposed approach by comparing the accuracy of the identified model with one obtained using a conventional wired system. Careful comparison of the results demonstrates the significant potential of the proposed approach.

Original languageEnglish (US)
Pages (from-to)1405-1416
Number of pages12
JournalStructural Control and Health Monitoring
Volume23
Issue number12
DOIs
StatePublished - Dec 1 2016

Keywords

  • computer vision
  • consumer-grade cameras
  • feature tracking
  • structural health monitoring
  • system identification

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Mechanics of Materials

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