Virtual visual sensors and their application in structural health monitoring

Yi-Zhe Song, Chris R. Bowen, Alicia H. Kim, Aydin Nassehi, Julian Padget, Nick Gathercole

Research output: Contribution to journalArticlepeer-review

66 Citations (SciVal)
484 Downloads (Pure)

Abstract

Wireless sensor networks are being increasingly accepted as an effective tool for structural health monitoring. The ability to deploy a wireless array of sensors efficiently and effectively is a key factor in structural health monitoring. Sensor installation and management can be difficult in practice for a variety of reasons: a hostile environment, high labour costs and bandwidth limitations. We present and evaluate a proof-of-concept application of virtual visual sensors to the well-known engineering problem of the cantilever beam, as a convenient physical sensor substitute for certain problems and environments. We demonstrate the effectiveness of virtual visual sensors as a means to achieve non-destructive evaluation. Major benefits of virtual visual sensors are its non-invasive nature, ease of installation and cost-effectiveness. The novelty of virtual visual sensors lies in the combination of marker extraction with visual tracking realised by modern computer vision algorithms. We demonstrate that by deploying a collection of virtual visual sensors on an oscillating structure, its modal shapes and frequencies can be readily extracted from a sequence of video images. Subsequently, we perform damage detection and localisation by means of a wavelet-based analysis. The contributions of this article are as follows: (1) use of a sub-pixel accuracy marker extraction algorithm to construct virtual sensors in the spatial domain, (2) embedding dynamic marker linking within a tracking-by-correspondence paradigm that offers benefits in computational efficiency and registration accuracy over traditional tracking-by-searching systems and (3) validation of virtual visual sensors in the context of a structural health monitoring application.
Original languageEnglish
Pages (from-to)251-264
Number of pages14
JournalStructural Health Monitoring - An International Journal
Volume13
Issue number3
Early online date17 Feb 2014
DOIs
Publication statusPublished - 1 May 2014

Keywords

  • Structural health monitoring
  • non-destructive damage detection
  • computer vision
  • wavelets

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