CN103163136B - Method for distinguishing concrete working degree in real time by virtue of mixing process image - Google Patents

Abstract

The invention discloses a method for judging the concrete workability in real time by using a mixing process image in the technical field of concrete workability detection, which is used for providing decision-making basis for adjusting the mixing ratio during the mixing process. The method comprises: collecting image information of concrete in real time during the mixing process of the mixer; obtaining shape features of the concrete according to the image information of the concrete; and judging workability of the concrete according to the shape features of the concrete. The invention can discriminate the working degree while the concrete is being mixed, improves the efficiency of the mixing proportion design in the laboratory, and reduces the waste of economy and time caused by unqualified concrete working degree on the construction site.

Description

A method of real-time judging concrete working degree by using images of mixing process

technical field

The invention belongs to the technical field of concrete work degree detection, and in particular relates to a method for real-time judging concrete work degree by using a mixing process image.

Background technique

The working performance test of concrete is very important for the mix design of concrete and the guarantee of construction quality. Various workability indicators of concrete (including slump, slump spread, V funnel time, T50 time, etc.) can be tested by slump spread test, V funnel test (or T50 test) and other tests. In addition, there are also various combined concrete work degree measuring instruments to uniformly test concrete and various work properties. Generally speaking, after each tray of concrete is out of the machine (before pouring), it must be inspected for workability.

Although there are various methods to evaluate the workability indexes of concrete, all the measurement methods are to measure the workability indexes by relevant inspectors with corresponding testing instruments after the concrete is discharged from the machine. This brings three types of problems: first, it wastes manpower and time, and interrupts the possible continuous production of concrete; second, it is necessary to provide various testing instruments and a flat site for testing at the construction site; , once the working performance does not meet the requirements, the whole concrete can only be discarded. Therefore, there is an urgent need for a method that can automatically determine the workability of concrete in real time during the mixing process.

Contents of the invention

In order to overcome the deficiencies and defects of the prior art, the purpose of the present invention is to provide a method for judging the workability of concrete, which can judge the workability of concrete in real time while the mixing process is in progress.

In order to achieve the above object, the technical solution proposed by the present invention is a method for real-time discrimination of concrete workability by using images of the mixing process, characterized in that the method includes:

Step 1: Collect image information of concrete in real time during the mixing process of the mixer;

Step 2: Obtain the shape features of the concrete according to the image information of the concrete;

Step 3: Determine the workability of the concrete according to the shape characteristics of the concrete.

The shape feature of the concrete is the inner boundary line of the image information of the concrete and/or the outer boundary line of the image information of the concrete.

The determining the workability of the concrete according to the shape characteristics of the concrete is specifically to determine the workability of the concrete according to the inner boundary line of the image information of the concrete and the outer boundary line of the image information of the concrete.

The determining the workability of the concrete according to the shape characteristics of the concrete is specifically to determine the workability of the concrete according to the inner boundary line of the image information of the concrete or the outer boundary line of the image information of the concrete.

The method proposed by the invention can discriminate the working degree while concrete is being mixed, and on this basis can provide a decision-making basis for the adjustment of the mixing ratio during the mixing process, thereby greatly improving the efficiency of the mixing ratio design in the laboratory and reducing the number of accidents at the construction site. The waste of economy and time caused by unqualified concrete work degree.

Description of drawings

Fig. 1 is the schematic diagram of the image information of real-time collection concrete during the mixer mixing process;

Fig. 2 is a key frame image of the stirring process that image acquisition equipment takes in embodiment 1;

Fig. 3 is to utilize the image in Fig. 2 and its previous frame image to carry out the image subtraction operation to obtain the difference image of two frame images;

Fig. 4 is the binary image obtained by performing global threshold segmentation on Fig. 3;

Figure 5 is an image of the outer boundary line separated from the image information of concrete;

Fig. 6 is an image of an inner boundary line separated from image information of concrete;

Fig. 7 is a schematic diagram of calculating the average height difference between the inner boundary line and the outer boundary line;

Fig. 8 is a key frame image of the mixing process taken by the image acquisition device in embodiment 2;

Fig. 9 is a result diagram obtained by fitting the outer boundary line of the image shown in Fig. 8 by the least square method.

Detailed ways

The preferred embodiments will be described in detail below in conjunction with the accompanying drawings. It should be emphasized that the following description is only exemplary and not intended to limit the scope of the invention and its application.

Embodiment 1: Using the inner boundary line and outer boundary line in the image information of concrete to determine the slump spread of concrete.

The specific implementation steps include:

Step 1: Collect image information of concrete in real time during the mixing process of the mixer.

The image information of the concrete can be collected by setting the collection equipment (such as video camera, camera, infrared camera or other equipment that can obtain the shape characteristics of the concrete in the mixer) above the mixer silo mouth or in the mixer silo, and setting up lighting devices when necessary. At the same time, the shape information of the concrete in the mixer is collected in real time.

Fig. 1 is a schematic diagram of real-time collection of image information of concrete during the mixing process of the mixer. As shown in FIG. 1 , a support 1002 is set beside the concrete mixer 1001 . An image acquisition device 1003 is fixed on the support (if necessary, an illumination source 1004 is provided), so that the image acquisition device can capture images inside the mixer through the silo port of the mixer. The mixer is used to mix the concrete, and while the mixing process is in progress, the real-time image of the mixing process is taken by an image acquisition device and transmitted to the control device (computer) 1005 connected thereto. The control equipment uses the image processing method to judge the working degree of the concrete in the mixer in real time.

Step 2: Obtain the shape features of the concrete according to the image information of the concrete. Acquiring the shape feature of the concrete according to the image information of the concrete specifically includes: separating the inner boundary line and the outer boundary line from the image information of the concrete.

Fig. 2 is a key frame image of the mixing process captured by the image acquisition device. As shown in FIG. 2 , the inner boundary line and the outer boundary line refer to the dividing line between the concrete part stirred by the blade of the concrete mixer during the mixing process and the background. The boundary far away from the mixer axis is the outer boundary line (white solid line in Figure 2), and the boundary close to the mixer axis is the inner boundary line (white dotted line in Figure 2).

(1) Obtain the inner and outer boundary lines of the image information of the concrete.

First, use the image in Figure 3 and its previous frame image to perform an image subtraction operation to obtain the difference Δ between the two frame images, as shown in Figure 3 .

Afterwards, the binary image Δ _B is obtained by using the single-threshold adaptive threshold segmentation method to perform global threshold segmentation on Δ, as shown in Fig. 4 .

Finally, for Δ _B , the highest point of each column in the foreground pixel of the image is taken as the outer boundary, as shown by the white line in Fig. 5 .

(2) Obtain the inner boundary line in the image information of the concrete.

First, the adaptive threshold segmentation with dual thresholds is used to solve the high and low thresholds of the image shown in Figure 2 .

Secondly, use the calculated two thresholds to perform watershed segmentation on the image shown in Fig. 2 .

Finally, the final result of the watershed algorithm is used as the inner boundary line, as shown by the solid line in Figure 6.

Step 3: Determine the slump spread of concrete according to the inner boundary line and outer boundary line.

The slump expansion of concrete is determined by using the inner boundary line and the outer boundary line:

First, calculate the average height difference between the inner and outer boundary lines.

The average height difference between the inner boundary line and the outer boundary line uses the formula:

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; avg</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; A</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

calculate. As shown in Figure 7, A is the area of the enclosing area between the inner boundary line and the outer boundary line, and d is the lateral width of the area.

Then, the slump spread of concrete is calculated from the average height difference between the inner and outer boundary lines. Its formula is as follows:

$\mathrm{<span\; class="notranslate">\; SF</span>}<span\; class="notranslate">\; =</span>\frac{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; avg</span>}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; b</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Among them, H _avg is the average height difference between the inner and outer boundaries obtained by formula (1), and a, b and c are all constants determined by experiments (in this embodiment, a=285, b=0.3011, c=-0.4116) , W/C is the volumetric water-binder ratio of concrete. In this embodiment, the average height difference between the inner and outer boundaries obtained from the image is 208 mm, the slump spread calculated according to formula (2) is 697 mm, and the actual test result obtained by using the slump spread test is 690 mm. If the slump expansion is within the range specified in the code, it can be judged that the slump expansion of the concrete meets the requirements.

Example 2: Using the outer boundary line to determine the V funnel time of concrete.

The specific implementation steps include:

Step 1: Collect image information of concrete in real time during the mixing process of the mixer. The detailed implementation process is described in step 1 of embodiment 1. Fig. 8 is a key frame image of the stirring process taken by the image acquisition device in this embodiment.

Step 2: Obtain the shape features of the concrete according to the image information of the concrete. Acquiring the shape characteristics of concrete according to the image information of concrete is specifically:

Separate the outer boundary line from the image information of the concrete. The detailed implementation process is the same as that described in Step 2 (1) of Example 1.

Step 3: Determine the V funnel time of concrete according to the outer boundary line.

First, use the least squares method to fit the outer boundary line, and calculate the abscissa of the inflection point of the fitted outer boundary line.

Use the Logistic equation to perform least squares regression on the outer boundary, where the Logistic equation is in the following form:

$\mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; b</span>}}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{\mathrm{<span\; class="notranslate">\; wxya</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

a, b, c and d are regression parameters.

For the outer boundary line from Figure 8, the least square method is used to fit a Logistic curve. The fitted curve formula is:

$\mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 546</span>}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 581</span>}}{{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 338</span>}\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 0.00959</span>}\mathrm{<span\; class="notranslate">\; x</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

The fitting results are shown in Figure 9. The dots in the figure represent the point series on the outer boundary line obtained by image processing, and the curve is the Logistic curve obtained by regression.

Secondly, calculate the abscissa of the inflection point of the fitted Logistic curve, the calculation formula is as follows:

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; inf</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; \&CenterDot;</span>\mathrm{<span\; class="notranslate">\; log</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

Among them, X _inf is the abscissa of the inflection point of the fitted outer boundary line, and c and d are the corresponding regression parameters in formula (4). In Fig. 9, the triangle point is the inflection point of the fitted outer boundary curve.

Finally, the V funnel time of concrete is determined according to the abscissa of the inflection point of the fitted outer boundary line.

According to the test results, when X _inf >200, the V funnel time will exceed 25s, that is, exceed the specification requirements. Formula (5) can be used to calculate the abscissa X _inf =607 of the inflection point of the outer boundary in this embodiment. Therefore, it is determined that the V funnel time of the concrete in this embodiment exceeds 25s. The actual test result obtained by using the V funnel test is 76.5s, so the working degree of the concrete exceeds the specification requirement.

It should be noted that, in the above-mentioned embodiments 1 and 2, the process of obtaining the outer boundary line and the inner boundary line in the image information of the concrete is only an example proposed by the present invention, and the outer boundary line and the inner boundary line in the image information of the concrete are obtained and Not limited to the above process. In addition, the method for measuring the slump spread and V funnel time used in the present invention is based on the "Technical Regulations for the Application of Self-Compacting Concrete" (CECS203:2006) formulated by China Engineering Construction Standardization Association.

The beneficial effects of the method provided by the invention are:

1. A method of analyzing the working degree of concrete mixing by using shape information is proposed, which has the characteristics of real-time, automation and non-contact.

2. The method of judging the workability of concrete by using the shape information of the inner and outer boundary lines of the concrete stirred by the mixer blade can replace the traditional concrete workability detection test and be applied to engineering sites and laboratory tests.

3. The concrete working degree discrimination method proposed by the present invention simplifies the detection procedure, can save a lot of manpower and time, and provides a basis for the automation and continuity of concrete production in the true sense.

4. The method for discriminating the working degree of concrete proposed by the present invention can discriminate the working degree while the concrete is mixing. On this basis, it can provide a decision-making basis for the adjustment of the mixing ratio in the mixing process, and can greatly improve the accuracy of the mixing ratio design in the laboratory. Efficiency and reduce the waste of economy and time caused by unqualified concrete work on the construction site.

The above is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of changes or modifications within the technical scope disclosed in the present invention. Replacement should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims (1)

1. a method for procedural image real time discriminating concrete work degree is mixed and stirred in utilization, and it is characterized in that, described method comprises:

Step 1: mix and stir the concrete image information of Real-time Collection in process at stirring machine;

Step 2: according to the concrete shape facility of concrete image information acquisition;

Described concrete shape facility is the inner edge boundary line of concrete image information and/or the boundary line, outside of concrete image information;

Step 3: differentiate concrete workability according to concrete shape facility, be specially: utilize inner edge boundary line and boundary line, outside jointly to judge concrete slump flow test, or judge the concrete V funnel time according to boundary line, outside;

Inner edge boundary line and boundary line, outside is utilized jointly to judge that concrete slump flow test comprises:

1) according to formula calculate the average height difference between inner edge boundary line and boundary line, outside; A is the area of enclosing region between inner edge boundary line and boundary line, outside, and d is region transverse width for this reason;

2) calculate concrete slump flow test according to the average height difference between inner edge boundary line and boundary line, outside, its formula is: h _avgfor inner and outer boundary line average height difference, a, b and c are the constant tested and determine, W/C is concrete volume water-cement ratio;

Judge that the concrete V funnel time comprises according to boundary line, outside:

1) the external boundary line of least square method is utilized to carry out matching;

2) the flex point horizontal ordinate X in the boundary line, outside after digital simulation _inf;

3) the concrete V funnel time is judged according to boundary line, the outside flex point horizontal ordinate after matching.