Development and field testing of a vision-based displacement system using a low cost wireless action camera

Abstract

This paper describes development of a contactless, low cost vision-based system for displacement measurement of civil structures. Displacement measurements provide a valuable insight into the structural condition and service behaviour of bridges under live loading. Conventional displacement gauges or GPS based systems have limitations in terms of access to the infrastructure and accuracy. The system introduced in this paper provides a low cost durable alternative which is rapidly deployable in the field and does not require direct contact or access to the infrastructure or its vicinity. A commercial action camera was modified to facilitate the use of a telescopic lens and paired with the development of robust displacement identification algorithms based on pattern matching. Performance was evaluated first in a series of controlled laboratory tests and validated against displacement measurements obtained using a fibre optic displacement gauge. The efficiency of the system for field applications was then demonstrated by capturing the validated bridge response of two structures under live loading including the iconic peace bridge. Located in the City of Derry, Northern Ireland, the Peace Bridge is a 310m curved self-anchored suspension pedestrian bridge structure. The vision-based results of the field experiment were confirmed against displacements calculated from measured accelerations during a dynamic assessment of the structure under crowd loading. In field applications the developed system can achieve a root mean square error (RMSE) of 0.03mm against verified measurements.

Developing a Workflow for Cloud-based Inspection of Temporary Structures in Construction

“…The third camera is a type of action camera, GoPro. GoPro has already been applied in civil engineering for displacement monitoring [11] and heritage reconstruction [12]. In this paper, GoPro is carried on with a headset by the authors to record the progress of the workflow from data collection to VR display.…”

Measuring Structural Deformations in the Laboratory Environment Using Smartphones

“…Three different image processing algorithms/software are considered and compared: (a) DeforMonit, developed at Nottingham Trent University (Kromanis and Al-Habaibeh, 2017), (b) QUB image processing method (further referred to as QUBDisp), developed at Queen's University Belfast (Del Rincon et al, 2018), and (c) "Video Gauge" (VG) software, a proprietary software built on a patented algorithm (Potter and Setchell, 2014). DeforMonit and QUBDisp are created using available Matlab algorithms.…”

“…These approximations are used in combination with integral images (the sum of pixel values in the image) to encode the distribution of pixel intensity values in the neighborhood of the detected feature. More on QUBDisp can be found in Del Rincon et al (2018).…”

A Low-Cost Robotic Camera System for Accurate Collection of Structural Response

“…Structural response can be accurately measured from image frames (or videos), when analyzed with adequate proprietary or open-source algorithms, which are collected with low-cost cameras such as action cameras, smartphones, and camcorders [10][11][12][13]. Accurate measurements of multiple artificial or natural targets can be obtained [14].…”