CN115290010A - Concrete joint surface roughness detection method and equipment - Google Patents
Concrete joint surface roughness detection method and equipment Download PDFInfo
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- CN115290010A CN115290010A CN202210386849.1A CN202210386849A CN115290010A CN 115290010 A CN115290010 A CN 115290010A CN 202210386849 A CN202210386849 A CN 202210386849A CN 115290010 A CN115290010 A CN 115290010A
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- 238000001514 detection method Methods 0.000 title claims abstract description 35
- 230000003746 surface roughness Effects 0.000 title claims description 20
- 238000000034 method Methods 0.000 claims abstract description 26
- 238000005286 illumination Methods 0.000 claims abstract description 5
- 238000006243 chemical reaction Methods 0.000 claims abstract description 4
- 238000013075 data extraction Methods 0.000 claims abstract description 4
- 230000009466 transformation Effects 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims description 8
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 230000007613 environmental effect Effects 0.000 abstract description 2
- 239000004576 sand Substances 0.000 abstract 1
- 238000010276 construction Methods 0.000 description 7
- 238000000513 principal component analysis Methods 0.000 description 3
- 238000004439 roughness measurement Methods 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
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- 238000013441 quality evaluation Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
Abstract
The invention relates to a method and equipment for detecting the roughness of a concrete joint surface, wherein the method comprises the following steps: collecting joint surface image data and three-dimensional point cloud data in a stable illumination environment, a vertical shooting angle and a proper shooting distance by using a structured light depth camera; obtaining point cloud data in an n multiplied by 3 format in a specified range through data extraction and format conversion; and carrying out coordinate transformation and triangular meshing treatment on the point cloud, and calculating the roughness by a simulated sand piling method. The equipment comprises: the structure light depth camera and the output end of the built-in light source are located on the same side, a stable shooting environment is established through the shading shell and the built-in light source, and a fixed shooting angle and distance are determined through the rigid frame. Compared with the prior art, the invention has the advantages of portability, high efficiency and accuracy, and can ensure stable detection conditions under various environmental conditions.
Description
Technical Field
The invention relates to the technical field of concrete joint surface roughness detection, in particular to a method and equipment for detecting the roughness of a concrete joint surface.
Background
The roughness of the concrete joint surface has important influence on the bonding performance of new and old concrete and is an important control index in the construction process of a concrete structure. At present, the concrete joint surface mostly adopts a rough surface form, but the following defects exist in the joint surface construction process:
(1) The construction process of the joint surface comprises exposed aggregate, napping, chiseling, printing, PE film and the like, the quality of the joint surface adopting different construction processes is uneven, and the construction quality is difficult to ensure.
(2) At present, the joint surface is mainly evaluated by the concave-convex depth, and the rough quality of the joint surface cannot be comprehensively reflected by the index.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide an efficient, reliable, simple and feasible method and equipment for detecting the roughness of a concrete joint surface, which are particularly applied to the construction quality evaluation of the joint surfaces of prefabricated walls, columns, beams, plates and other members and cast-in-place joint surfaces of post-cast strips, construction joints and the like. The purpose of the invention can be realized by the following technical scheme:
a concrete joint surface roughness detection method based on a structured light depth camera comprises the following steps:
a data acquisition step: collecting joint surface image data and three-dimensional point cloud data in a stable illumination environment, a vertical shooting angle and a proper shooting distance by using a structured light camera, wherein the selection range of the proper shooting distance is predetermined;
a data extraction step: selecting a joint surface detection area on the joint surface image, and extracting point cloud data corresponding to the specified joint surface detection area;
and a format conversion step: converting the extracted point cloud data into a point cloud matrix format of n multiplied by 3, wherein each row represents a three-dimensional coordinate of one point in the point cloud;
and (3) coordinate transformation: obtaining an integral point cloud normal vector by adopting a PCA method, wherein the direction of the integral point cloud normal vector is the depth direction of the point cloud, so that the point cloud is rotated, and the z axis of the point cloud represents the depth direction;
triangular gridding step: projecting each point to an xOy plane, establishing a point cloud adjacent relation by adopting a two-dimensional Delaunay triangulation method, and expressing a combined surface as a combination of a series of triangular surfaces;
and (3) roughness calculation: calculating the projection area S of each triangular surface by taking the horizontal plane passing through the highest point as a projection plane i And a volume V enclosed by the triangular surface and the projection surface i Roughness R c ＝∑V i /∑S i 。
Further, the suitable shooting distance is: 200mm and the larger of the minimum working distance of the camera.
Further, the structured light depth camera is packaged in the concrete junction surface roughness detection equipment, the concrete junction surface roughness detection equipment further comprises a built-in light source, a processing module, a battery pack for supplying power to the whole equipment and a rigid frame for supporting the whole equipment, and the output end of the structured light depth camera and the output end of the built-in light source are located on the same side.
Further, the rigid frame is arranged according to the proper shooting distance and the vertical shooting angle of the structured light depth camera, and the proper shooting distance enables the structured light depth camera to acquire point cloud data of at least 2 data points with a single point error smaller than 0.5mm and per square millimeter.
Furthermore, the number of the built-in light sources is multiple, and the multiple built-in light sources are respectively distributed on two sides of the output end of the structured light depth camera.
Further, the processing module comprises a single chip microcomputer and a display screen, and the single chip microcomputer is respectively connected with the display screen, the built-in light source and the structured light depth camera.
Further, the concrete junction surface roughness detection equipment also comprises a shading shell, wherein the shading shell is positioned on the outer side of the concrete junction surface roughness detection equipment, and an ambient light shading surface is formed at the output end of the built-in light source and used for isolating ambient light.
Further, the built-in light source employs a fixed output configuration.
Compared with the prior art, the invention has the following advantages:
(1) The invention provides a concrete joint surface roughness detection method based on a structured light depth camera, and the method has the characteristics of simplicity, convenience and high efficiency. Under certain detection conditions, the method can obtain high-quality point cloud data with high precision and high density, so that the accurate roughness can be calculated. The detection conditions include a stable lighting environment, a vertical shooting angle, and an appropriate shooting distance. In addition, the method is suitable for roughness detection of various concrete joint surfaces and has wide adaptability.
(2) The concrete junction surface roughness detection device provided by the invention is small, exquisite and light, flexible to operate, capable of guaranteeing stable detection conditions under various environmental conditions, capable of realizing detection of various rough surfaces, and suitable for a project junction surface roughness detection scene.
Drawings
Fig. 1 is a front upper right perspective view of an internal structure of a concrete joint surface roughness measurement device according to an embodiment of the present invention;
fig. 2 is a front lower right perspective view of an internal structure of the concrete joint surface roughness measurement device according to the embodiment of the present invention;
FIG. 3 is a cross-sectional view of an internal structure of the concrete joint surface roughness measurement device according to the embodiment of the present invention;
FIG. 4 is a schematic diagram of a structured light depth camera according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a built-in light source according to an embodiment of the present invention;
in the figure, 1, a battery pack; 2. a single chip microcomputer; 3. a structured light depth camera; 4. a built-in light source; 5. a rigid frame; 6. a display screen; 7. a laser projector; 8. a color camera; 9. an infrared camera; 10. an effective imaging area.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings or orientations or positional relationships that the present product is conventionally placed in use, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
Example 1
The embodiment provides a concrete joint surface roughness detection method based on a structured light depth camera, which comprises the following steps:
s1: collecting data, namely collecting joint surface image data and three-dimensional information data in a stable illumination environment, a vertical shooting angle and a proper shooting distance by adopting a structured light depth camera; the method comprises the steps that the shooting distance is related to the shielding condition of a junction surface, the working distance of a camera and the detection precision, data loss caused by shielding of the junction surface or over-small working distance of the camera can occur when the shooting distance is too short, the detection precision can be influenced when the shooting distance is too far, the junction surface characteristic is considered, when the shooting distance is more than 200mm, the influence of shielding of the junction surface can be ignored, and therefore the proper shooting distance is the larger value of 200mm and the minimum working distance of the camera;
s2: data extraction, namely selecting a joint surface detection area on a joint surface image, and automatically extracting point cloud data corresponding to the specified joint surface detection area;
s3: format conversion, namely converting the extracted point cloud data into a point cloud matrix format of n multiplied by 3, wherein each line represents a three-dimensional coordinate of one point in the point cloud;
s4: coordinate transformation, namely acquiring a normal vector (namely the depth direction of the point cloud) of the whole point cloud by adopting a PCA (principal component analysis) method, and rotating the point cloud to enable a z axis of the point cloud to represent the depth direction;
s5: triangularization, namely projecting each point onto an xOy plane, and establishing a point cloud adjacent relation by adopting a two-dimensional Delaunay triangulation method, wherein a joint surface is expressed as a combination of a series of triangular surfaces;
s6: calculating roughness by taking the horizontal plane passing through the highest point as a projection plane and calculating the projection area S of each triangular surface i And a volume V enclosed by the triangular surface and the projection surface i Roughness R c ＝∑V i /∑S i 。
In a preferred embodiment, in S1, the suitable shooting distance is the larger of 200mm and the minimum working distance of the camera.
Example 2
As shown in fig. 1 to 5, the present embodiment provides a concrete joint surface roughness detecting apparatus based on the detecting method of embodiment 1, including: the device comprises a structured light depth camera 3, a built-in light source 4, a processing module, a battery pack 1 for supplying power to the whole device and a rigid frame 5 for supporting the whole device, wherein the acquisition end of the structured light depth camera and the output end of the built-in light source are positioned on the same side;
the structured light depth camera is used for acquiring joint surface image data and three-dimensional point cloud data;
a built-in light source for providing stable and high quality lighting conditions;
the rigid frame is used for fixing the shooting distance and the shooting angle of the camera;
and the battery pack is used for providing power supply.
Optionally, the structured light depth camera adopts a monocular structured light depth camera, and includes a laser projector 7, an infrared camera 9 and a color camera 8, the laser projector is used for projecting structured light to form an effective imaging area 10, the infrared camera is used for collecting a projection image of coded light, and the color camera is used for collecting a color image; the processing module is respectively connected with the built-in light source and the structured light depth camera.
Optionally, the number of the built-in light sources is multiple, and the multiple built-in light sources are respectively distributed on two sides of the output end of the structured light depth camera.
In this embodiment, the processing module includes a single chip microcomputer 2 and a display screen 6, and the single chip microcomputer is connected with the display screen, the built-in light source and the structured light depth camera respectively.
The singlechip is used for processing data and calculating the roughness of a joint surface;
and the display screen is used for displaying the detection result and carrying out interactive operation.
Preferably, the concrete junction surface roughness detection equipment further comprises a shading shell, wherein the shading shell is located on the outer side of the concrete junction surface roughness detection equipment, and forms an ambient light shading surface at the output end of the built-in light source for isolating ambient light.
The detection equipment can acquire joint surface image data under specific conditions, namely the detection equipment performs image acquisition with fixed shooting parameters (such as focal length, exposure time and the like) by adopting the structured light depth camera under the stable illumination condition, acquires joint surface images and three-dimensional point cloud data with stable quality, and can acquire joint surface point cloud data with stable quality and uniform distribution.
The embodiment provides an operation flow based on the detection device, which includes the following steps:
s1: data acquisition, namely placing detection equipment on a concrete joint surface to be detected, acquiring joint surface data (infrared images, color images and three-dimensional point cloud data) by adopting a structured light depth camera, inputting the data into a single chip microcomputer and displaying the joint surface color images on a display screen;
s2: and (3) extracting data, and selecting a range of valid data on the color image, wherein the range of valid data can represent a rectangular area of a joint surface with the side length of 50-200 mm or a circular area with the diameter of 50-200 mm.
S3: and (4) calculating the roughness, namely extracting effective data by the singlechip according to the data range determined in the S2, converting the three-dimensional point cloud data format, and finally calculating the roughness and displaying the roughness on a display screen.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations can be devised by those skilled in the art in light of the above teachings. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (8)
1. A concrete joint surface roughness detection method based on a structured light depth camera is characterized by comprising the following steps:
a data acquisition step: collecting junction surface image data and three-dimensional point cloud data in a stable illumination environment, a vertical shooting angle and a proper shooting distance by using a structured light camera, wherein the selection range of the proper shooting distance is predetermined;
a data extraction step: selecting a joint surface detection area on the joint surface image, and extracting point cloud data corresponding to the specified joint surface detection area;
and a format conversion step: converting the extracted point cloud data into a point cloud matrix format of n multiplied by 3, wherein each row represents a three-dimensional coordinate of one point in the point cloud;
and (3) coordinate transformation: obtaining an integral point cloud normal vector by adopting a PCA method, wherein the direction of the integral point cloud normal vector is the depth direction of the point cloud, so that the point cloud is rotated, and the z axis of the point cloud represents the depth direction;
triangular gridding step: projecting each point to an xOy plane, establishing a point cloud adjacent relation by adopting a two-dimensional Delaunay triangulation network subdivision method, and representing a combined surface as a combination of a series of triangular surfaces;
and (3) roughness calculation: calculating the projection area S of each triangular surface by taking the horizontal plane passing through the highest point as a projection plane i Triangle surface and projection breadVolume V of enclosure i Roughness R c ＝∑V i /∑S i 。
2. The method for detecting the roughness of the concrete joint surface based on the structured light depth camera according to claim 1, wherein the appropriate shooting distance is as follows: 200mm and the larger of the minimum working distance of the camera.
3. The method as claimed in claim 1, wherein the structured light depth camera is packaged in the equipment for detecting the roughness of the concrete junction surface, the equipment for detecting the roughness of the concrete junction surface further comprises a built-in light source, a processing module, a battery pack for supplying power to the whole equipment and a rigid frame for supporting the whole equipment, and the output end of the structured light depth camera and the output end of the built-in light source are located on the same side.
4. The method for detecting the roughness of the concrete junction surface based on the structured light depth camera as claimed in claim 3, wherein the rigid frame is arranged according to a proper shooting distance and a vertical shooting angle of the structured light depth camera, and the proper shooting distance enables the structured light depth camera to obtain point cloud data with a single point error of less than 0.5mm and at least 2 data points per square millimeter.
5. The method for detecting the roughness of the concrete joint surface based on the structured light depth camera according to claim 3, wherein the number of the built-in light sources is multiple, and the multiple built-in light sources are respectively distributed on two sides of the output end of the structured light depth camera.
6. The method for detecting the roughness of the concrete joint surface based on the structured light depth camera as claimed in claim 3, wherein the processing module comprises a single chip microcomputer and a display screen, and the single chip microcomputer is respectively connected with the display screen, the built-in light source and the structured light depth camera.
7. The method for detecting the roughness of the concrete joint surface based on the structured light depth camera according to claim 3, wherein the equipment for detecting the roughness of the concrete joint surface further comprises a shading shell, the shading shell is positioned on the outer side of the equipment for detecting the roughness of the concrete joint surface, and an ambient light shading surface is formed at the output end of the built-in light source and used for isolating ambient light.
8. The structured light depth camera-based concrete joint surface roughness detection method as claimed in claim 3, wherein the built-in light source adopts a fixed output configuration.
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| CN202210386849.1A CN115290010A (en) | 2022-04-13 | 2022-04-13 | Concrete joint surface roughness detection method and equipment |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117553713A (en) * | 2024-01-09 | 2024-02-13 | 南京信瑞智慧建筑科技有限公司 | Method and device for detecting rough quality of joint surface of precast concrete member |
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Patent Citations (5)
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| CN107449378A (en) * | 2017-07-21 | 2017-12-08 | 辽宁科技大学 | A kind of test of rock surface degree of roughness and computational methods based on 3-D view |
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