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Image-based structural dynamic displacement measurement using different multi-object tracking algorithms
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  • Journal title : Smart Structures and Systems
  • Volume 17, Issue 6,  2016, pp.935-956
  • Publisher : Techno-Press
  • DOI : 10.12989/sss.2016.17.6.935
 Title & Authors
Image-based structural dynamic displacement measurement using different multi-object tracking algorithms
Ye, X.W.; Dong, C.Z.; Liu, T.;
 Abstract
With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.
 Keywords
structural health monitoring;displacement measurement;vision-based system;digital image processing;pattern matching algorithm;mean shift tracking algorithm;
 Language
English
 Cited by
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Reference-Free Displacement Estimation of Bridges Using Kalman Filter-Based Multimetric Data Fusion, Journal of Sensors, 2016, 2016, 1  crossref(new windwow)
3.
Identification of structural dynamic characteristics based on machine vision technology, Measurement, 2017  crossref(new windwow)
4.
A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications, Journal of Sensors, 2016, 2016, 1  crossref(new windwow)
5.
Geotechnical monitoring and analyses on the stability and health of a large cross-section railway tunnel constructed in a seismic area, Measurement, 2017  crossref(new windwow)
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