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Proceedings Paper

An autonomous unmanned aerial vehicle sensing system for structural health monitoring of bridges
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Paper Abstract

As civil infrastructure (i.e. bridges, railways, and tunnels) continues to age; the frequency and need to perform inspection more quickly on a broader scale increases. Traditional inspection and monitoring techniques (e.g., visual inspection, mechanical sounding, rebound hammer, cover meter, electrical potential measurements, ultrasound, and ground penetrating radar) may produce inconsistent results, require lane closure, are labor intensive and time-consuming. Therefore, new structural health monitoring systems must be developed that are automated, highly accurate, minimally invasive, and cost effective. Three-dimensional (3D) digital image correlation (DIC) systems have the merits of extracting full-field strain, deformation, and geometry profiles. These profiles can then be stitched together to generate a complete integrity map of the area of interest. Concurrently, unmanned aerial vehicles (UAVs) have emerged as valuable resources for positioning sensing equipment where it is either difficult to measure or poses a risk to human safety. UAVs have the capability to expedite the optical-based measurement process, offer increased accessibility, and reduce interference with local traffic. Within this work, an autonomous unmanned aerial vehicle in conjunction with 3D DIC was developed for monitoring bridges. The capabilities of the proposed system are demonstrated in both laboratory measurements and data collected from bridges currently in service. Potential measurement influences from platform instability, rotor vibration and positioning inaccuracy are also studied in a controlled environment. The results of these experiments show that the combination of autonomous flight with 3D DIC and other non-contact measurement systems provides a valuable and effective civil inspection platform.

Paper Details

Date Published: 22 April 2016
PDF: 9 pages
Proc. SPIE 9804, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, and Civil Infrastructure 2016, 980414 (22 April 2016); doi: 10.1117/12.2218370
Show Author Affiliations
Daniel Reagan, Univ. of Massachusetts Lowell (United States)
Alessandro Sabato, Univ. of Massachusetts Lowell (United States)
Christopher Niezrecki, Univ. of Massachusetts Lowell (United States)
Tzuyang Yu, Univ. of Massachusetts Lowell (United States)
Richard Wilson, Univ. of Massachusetts Lowell (United States)


Published in SPIE Proceedings Vol. 9804:
Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, and Civil Infrastructure 2016
Tzuyang Yu; Andrew L. Gyekenyesi; Peter J. Shull; H. Felix Wu, Editor(s)

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