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Virtual visual sensors and their application in structural health monitoring

Song, Yi-Zhe, Bowen, Chris R, Kim, Alicia, Nassehi, Aydin, Padget, Julian and Gathercole, Nick 2014. Virtual visual sensors and their application in structural health monitoring. Structural Health Monitoring 13 (3) , pp. 251-264. 10.1177/1475921714522841

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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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: SAGE Publications
ISSN: 1475-9217
Date of First Compliant Deposit: 11 December 2018
Date of Acceptance: 3 January 2014
Last Modified: 21 Feb 2019 18:19
URI: http://orca.cf.ac.uk/id/eprint/117573

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