concrete surface roughness testing using nondestructive ... · the results of concrete surface ......

Czech Society for Nondestructive TestingNDE for Safety / DEFEKTOSKOPIE 2012October 30 - November 1, 2012 - Seč u Chrudimi - Czech Republic

DEFEKTOSKOPIE 2012 101

CONCRETE SURFACE ROUGHNESS TESTING USING NONDESTRUCTIVE THREE-DIMENSIONAL OPTICAL

METHOD

Jerzy HOŁA1, Łukasz SADOWSKI1, Jacek REINER2, Maciej STANKIEWICZ2

1Institute of Building Engineering, Wroclaw University of Technology 2 Institute of Machine Technology and Automation, Wroclaw University of Technology

Abstract

In building practice the durability of concrete floors is to a large degree determined by the surface layer’s pull-off adhesion to the structural layer. The strength of the bond between the two layers largely depends on the preparation of the structural layer. Structural layer preparation can be de-scribed by surface roughness parameters. This paper presents results of concrete floor structural layer surface roughness tests done using 3D optical surface scanning. Two differently prepared structural layers were examined in this way. The results show that this method can be successfully used for this purpose. Key words: concrete, roughness, surface topography, bonding surface

1. Introduction

Concrete floors are found in most general and industrial building structures. Owing to their durability they are commonly used in housing and in multi-storey garages. Concrete floors are one of the most prominent elements in the interior finish of such buildings and one of the principal factors having a bearing on the architectural shape of the interiors and the use of the rooms. The durability of concrete floors is to a high degree determined by the pull-off adhe-sion of the surface layer to the structural layer. It should be noted that the proper preparation of the structural layer, describable by surface roughness parameters, has a significant influ-ence on the mutual adhesion of the bonded layers [1].

Roughness is a surface’s characteristic representing its irregularities (convexities and concavi-ties) the height of which is at least one order of magnitude smaller than the size of the ele-ment. It is one of the properties describing a surface’s geometrical structure, i.e. a set of all its irregularities, including shape deviations, waviness and roughness. The latter is regarded to be a major indicator of surface preparation.

The profile method is usually used to measure the roughness of concrete surfaces. In this way two-dimensional surface roughness parameters are determined. In [2], concrete floor surface roughness parameters were determined for five different ways of preparing the surface. The roughness of the surface was described using the parameters determined by the profile method.

A single flat profile does not describe well enough a surface which has a three-dimensional character. Concrete surfaces undoubtedly belong to this category. Even though roughness

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102 DEFEKTOSKOPIE 2012

parameters describing a flat profile are still successfully used in construction [3], recent years have brought a critical re-evaluation of the two-dimensional analysis, and new solutions in its description [4-7]. As a result, the surface method, which enables one to determine roughness parameters in three-dimensionality, has been increasingly used.

Functional volumetric parameters can be useful in the evaluation of the roughness of concrete surfaces. Such parameters are determined on the basis of the Abbott-Firestone curve for a given surface [8]. According to [9], the functional volumetric parameters include: peak ma-terial volume of scale limited surface , core material volume of scale limited surface ,

core void volume of scale limited surface and pit void volume of scale limited surface .It should be noted that the Abbott-Firestone curve represents surface topography structure as a cumulative probability density of the amplitudes of its particular points. In the case of the functional parameters, the volumetric curve is an integral over the examined surface. Hence the position of the surface of a section relative to the highest point of the topography is marked on the Y-axis while the percentage of the material relative to the highest surface point is marked on the X-axis.

The results of concrete surface testing using the three-dimensional optical method and the volumetric parameters are presented below.

2. Description of the surface roughness testing method

The set for the optical testing of surface roughness comprises a laser profile scanner SICK IVC-3D mounted on a linear drive with a guide bar, an encoder and a laptop (fig. 1a). Scan-ning is effected by manually shifting the head above the measuring area during which several surface profiles, separated from one another by a distance of 0.07 mm, are being recorded with a resolution of 0.074 mm. As a result of the scanning one obtains a cloud of points mod-elling the topography of the concrete surface with a vertical resolution of 0.015 mm. The data from the intelligent camera after prefiltration are sent to the laptop to be archived and later processed in order to determine the surface roughness parameters.

Fig. 1. View of: a) measuring set used in optical method, b) testing by nondestructive optical method.

The method of the optical scanning of surface topography is based on triangulation by means of a line of light [10]. It consists in taking photographs at an angle relative to the direction of lighting (fig. 2a). The photographs depict the deformation of the-line-of-light profile caused by the shape of the illuminated object (fig. 2b). Because of its high concentration of energy,

a) b)controller with

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a class II/2M VIS laser equipped with a special optical system is used as the illuminator. In the case of the IVC-3D scanner, a low power (λ=658nm±15nm) diode laser was employed. The recorded image of the line contains information about the 3D geometry of a single section of the scene by a plane of light. For this reason this method is referred to as 2½D, as opposed to the methods capable of activating the full geometry of the whole measuring area (e.g. struc-tural light, stereovision, tomography) [11]. Consequently, it is necessary to effect relative movement, which was achieved by means of the linear drive. During the relative shift of the object being scanned the discrete acquisition of photographs, synchronized by the encoder, takes place. Although the camera system offers a maximum scanning speed of 5000 pro-files/sec., the actual scanning speed is limited by the exposure parameters and the profile line segmentation algorithms. In the case of the setup presented here manual shift is used instead of a controlled electric drive.

Fig. 1. Schematic of laser triangulation method (a) and of triangulation image (b) (1) – camera with lens, (2) – laser line generator, (B) - concrete, (G) – head, (E) – encoder.

In this scanning method only the parts of the scanned surface which are visible from both the camera and laser perspectives are mapped. As the triangulation angle (the angle between the plane of light and the camera’s optical axis) decreases so does the number of invisible areas. But also the measurement resolution along the Z-axis decreases as a result. In the case of the IVC-3D scanner, both the lens and the triangulation angle (53°) have been set by the manu-facturer to strike a balance between occlusion and resolution. The scanning system has been pre-calibrated and ensures constant resolution ∆z=0.015mm along the Z-axis.

For the adopted measuring area of 50mm×50mm the following average resolutions are achieved:

● 0.07mm – along the shift (X-axis),

● 0.074mm – along the laser line (Y-axis),

● 0.015mm – height (Z-axis).

The time of scanning the investigated area did not exceed 2 sec. The measurement data were exported in the csv format to be further processed by the Talymap 3D Analysis Software.



3. Test results

Tests were carried out on two concrete 50×50mm surfaces constituting the structural layer of a concrete floor. The surfaces were made of C30/37 grade, S3 consistency concrete with ratio w/c=0.5 and a maximum aggregate grading of 8 mm. They matured in a natural way in a laboratory at an ambient temperature of +18°C (±3°C) and a relative air humidity of 60%. For the first 7 days they were stored covered with plastic wrap.

The following two ways of concrete surface preparation were used:

- surface I: mechanical grinding and dust removal,

- surface II: no surface preparation, i.e. the surface was left in the after-concreting condi-tion.

Figure 1 shows spatial images (in false colours) of the scanned concrete surface for surface I and II.

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Fig. 1. Spatial image of scanned concrete surface for: a) surface I, b) surface II. 0 10 20 30 40 50 60 70 80 90 100 %

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Vmp = 9.22 ml/m2 Vmc = 277 ml/m2

Vvc = 290 ml/m2 Vvv = 67.0 ml/m2

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Fig. 2. Graphic analysis of volumetric parameters for surface I.



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Vmp = 29.5 ml/m2 Vmc = 619 ml/m2

Vvc = 868 ml/m2 Vvv = 63.1 ml/m2

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Fig. 3. Graphic analysis of volumetric parameters for surface II.

It appears from the graphic analyses of the volumetric parameters for surfaces I and II, shown in figs 2 and 3, that there are differences in the roughness parameters. For surface I the values of Vmp and Vmc are three times lower than for surface II, whereas the values of parameter Vvc

are twice higher for surface II than for surface I, indicating greater surface irregularities of the concrete surface without preparation. It seems that parameter Vv is less useful for the analysis of concrete floor roughness since it does not reveal any differences between surface I and sur-face II.

4. Conclusion

The results of surface roughness tests for a concrete surface constituting the structural layer of a concrete floor, carried out using the 3D optical method have been presented.

Two concrete surfaces differing in the preparation of the structural layer were tested. The tests showed that the parameters: Vmp, Vmc and Vvc are particularly useful for evaluating the degree of roughness of the tested concrete surfaces.

The proposed optical surface scanning method and the SICK IVC-3D sensor used, ensured a resolution sufficient for measuring surface roughness of concrete screeds without any no-ticeable occlusion or speckle effects or disturbances caused by a change in reflectiveness, as noted in [12]. In the designed test setup the motor drive of the head was abandoned and owing to the high scanning speed ensured by the manual shift no profiles were lost. The parallelism between the scanned concrete surface plane and the scanner shift plane was not a critical ac-quisition parameter and it was corrected (through levelling) at the data processing stage.



5. References

1. Siewczyńska M.: Method for determining the parameters of surface roughness by us-age of a 3D scanner, Archives of Civil and Mechanical Engineering, 1-2, p. 83-89 (2012).

2. Franck A, De Belie N.: Concrete floor-bovine claw contact pressures related to floor roughness and deformation of the claw, Journal of Dairy Science, 89, 8 (2006).

3. Erdem S., Dawson A., Thom N.: Impact load-induced micro-structural damage and micro-structure associated mechanical response of concrete made with different sur-face roughness and porosity aggregates, Cement and Concrete Research, 42, s. 291–305 (2012).

4. Grzelka M., Chajda J., Budzik G., Gessner A., Wieczorowski M., Staniek R., GapińskiB., Koteras R., Krasicki P., Marciniak L.: Optical coordinate scanners applied for the inspection of large scale housings produced in foundry technology, Archives of Foun-dry Engineering, 49/1, 255-260 (2010).

5. Mathia T., Pawlus P., Wieczorowski M.: Recent trends in surface metrology, Wear, 271, s. 494–508 (2011).

6. Grzelka M., Majchrowski R., Sadowski Ł.: Investigations of concrete surface rough-ness by means of 3D scanner, Proceedings of Electrotechnical Institute, 16 (2011).

7. Gonzalez-Jorge H., Solla M., Armesto J., Arias P.: Novel method to determine laser scanner accuracy for applications in civil engineering, Optica Applicata, Vol. XLII, No. 1 (2012).

8. Abbott J., Firestone F.: Specifying surface quality: a method based on accurate meas-urement and comparison, Mechanical Engineering, 55, p. 569–572 (1933).

9. ISO 25178: Geometric Product Specifications (GPS) – Surface texture: areal.

10. Kowal J., Sioma A., Active vision system for 3D product inspection: Learn how to construct three-dimensional vision applications by reviewing the measurements pro-cedures, Control Engineering USA; ISSN 0010-8049. vol. 56, pp. 46-48 (2009).

11. Tutsch R., Petz M., and Fischer M., Optical three-dimensional metrology with struc-tured illumination, Optical Engineering, vol. 50, no. 10, p. 101507 (2011).

12. Reiner J., Stankiewicz M., and Wojcik M., Predictive segmentation method for 3D in-spection accuracy and robustness improvement, in Optical Measurement Systems for Industrial Inspection VI, Peter H. Lehmann, Editors, 73890A, Munich (2009).

Acknowledgements

This research was carried out as part of research project “Grant Plus” [POKL 8.2.2] co-funded within the framework of the European Social Fund.


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