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. 2017 Jul 8;10(7):770.
doi: 10.3390/ma10070770.

Image Analysis Technique for Material Behavior Evaluation in Civil Structures

Emanuela Speranzini  1 , Roberto Marsili  2 , Michele Moretti  3 , Gianluca Rossi  4
Affiliations

Image Analysis Technique for Material Behavior Evaluation in Civil Structures

Emanuela Speranzini et al. Materials (Basel). .

Abstract

The article presents a hybrid monitoring technique for the measurement of the deformation field. The goal is to obtain information about crack propagation in existing structures, for the purpose of monitoring their state of health. The measurement technique is based on the capture and analysis of a digital image set. Special markers were used on the surface of the structures that can be removed without damaging existing structures as the historical masonry. The digital image analysis was done using software specifically designed in Matlab to follow the tracking of the markers and determine the evolution of the deformation state. The method can be used in any type of structure but is particularly suitable when it is necessary not to damage the surface of structures. A series of experiments carried out on masonry walls of the Oliverian Museum (Pesaro, Italy) and Palazzo Silvi (Perugia, Italy) have allowed the validation of the procedure elaborated by comparing the results with those derived from traditional measuring techniques.

Keywords: civil structures; deformation; digital image correlation; displacement; marker tracking; masonry; monitoring; no-contact measurement; strain field.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Stereo camera calibration checkerboard, (a) left (L) images. (b) right (R) images; (c,d) change in the pattern related to the perspective.
Figure 2
Figure 2
Flow-chart of the schematic representation of the algorithm.
Figure 3
Figure 3
(a,b) Software, loading of the “right” and “left” images and their display. (c) image analysis, chromatic distribution and level filter, the curves represent the three colors RGB (red, green, blue). (d,e) Image binarized.
Figure 4
Figure 4
(a,b) Incongruent enumeration between left “a” and right “b” images. (c) Image regions acquired at different moments containing the same marker.
Figure 5
Figure 5
(a) Map of local cross correlation, from which the displacement vector is extracted; (b,c) Example of displacement applied vectors obtained by means of the method used.
Figure 6
Figure 6
Displacement field.
Figure 7
Figure 7
(a) Sample prepared with the markers and set up on the press for the compression test; (b) equipment for image acquisition.
Figure 8
Figure 8
Displacement measurement with linear variable displacement transducers (LVDT) and the proposed methodology (MT).
Figure 9
Figure 9
(a) The test on a masonry wall inside the Oliverian Museum of Pesaro, (b) Stress-strain diagrams with the flat jack and the proposed technique (MT).
Figure 10
Figure 10
(a) Palazzo Silvi: wall prepared for the Flat Jacks and Marker Tracking tests; (b) The stress-strain diagrams obtained from the cyclic load test for the two techniques.
Figure 11
Figure 11
(a) Stress/strain versus time: stress (right axis), strain (left axis); (b) Measurements with MT (blu line) e deformometer (red line). Black line shows the values of the differences between two measurements (scale in right axis: strain 10−3).
See this image and copyright information in PMC

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