Concrete wet curing method and device and storage medium

Abstract

The invention provides a concrete wet curing method and device and a storage medium. The method comprises the following steps that image collection is conducted on a concrete surface needing wet curing after pouring operation is completed; the collected images are preprocessed; performing color space conversion on the preprocessed image, and substituting a characteristic value obtained after conversion into a color difference expression to calculate a color difference value; and judging whether the color difference value reaches a spraying threshold value or not, if yes, spraying the area, and if not, repeating the above steps. According to the method, monitoring, color difference calculation and automatic spraying form scientific linkage control, so that full-intelligent concrete wet curing is realized; the problems that in the prior art, on-time and accurate spraying cannot be achieved according to the hardening condition of concrete, the curing difficulty of part of construction sites is large, and the concrete curing quality is difficult to guarantee are solved, site construction operation is more refined and scientific, the wet curing quality is improved, and good social benefits and technical benefits are achieved.

Description

Technical Field

[0001] The present invention relates to the field of target detection technology, and more specifically to a concrete wet curing method, device and storage medium. Background Art

[0002] With the rapid development of expressway construction in my country, the requirements for highway and bridge construction are increasing day by day, and the standardization and regularization requirements for various on-site processes are becoming more stringent. The quality of concrete construction is a key factor affecting the durability and safety of the project. Therefore, the requirements for concrete wet curing construction have also been raised to a new level. During construction, concrete will undergo hydration and heat dissipation during the strength formation process. At this time, it needs to absorb water and retain moisture. If the maintenance is not in place or timely, the concrete will have insufficient strength and poor appearance, and may even cause cracks on the concrete surface, causing great quality risks. The commonly used wet curing method is still mainly completed through manual sprinkling. The quality of this traditional maintenance method usually depends on the quality awareness and sense of responsibility of the on-site workers. Because the maintenance time is generally long, the on-site workers cannot spray on time and accurately according to the hardening of the concrete. Not only that, during the bridge construction process, as the construction pouring height of the suspended grouting bridge-building machine increases, the difficulty of artificial wet curing is also increasing, and the quality of concrete curing is difficult to guarantee. Summary of the invention

[0003] In view of the above defects or improvement needs of the prior art, the present invention provides a concrete wet curing method, device and storage medium, which solve the problems in the prior art that it is impossible to spray concrete on time and accurately according to the hardening condition of concrete, and that some construction sites are difficult to maintain and the quality of concrete curing is difficult to guarantee.

[0004] According to an embodiment of the present invention, a concrete wet curing method comprises the following steps:

[0005] S1. Capture images of concrete surfaces that require wet curing after pouring.

[0006] S2, preprocessing the collected images;

[0007] S3, performing color space conversion on the preprocessed image, and substituting the characteristic value obtained after the conversion into the color difference expression to calculate the color difference value;

[0008] S4, judging whether the color difference value reaches the spraying threshold, if so, spraying the area, otherwise repeating steps S1-S4.

[0009] Furthermore, the following method is used for preprocessing in step S2:

[0010] An RGB color space model is constructed, and bilateral filtering algorithm is used to perform image denoising on each component of R, G, and B. The pixel value of a point is introduced into the image, and the domain kernel is determined according to the distance between this pixel value and the neighboring pixel values. The range kernel is determined according to the grayscale value of this pixel value and the neighboring pixel values. The weight coefficient is determined according to the domain kernel and the range kernel. The pixel value of the new output image at this point is obtained by weighting the introduced pixel value.

[0011] Furthermore, the bilateral filtering calculation method in step S2 is as follows:

[0012] S2.1, bring in the center point (i, j) of the image and a point (k, 1) in the neighborhood, then the domain kernel is defined as:

[0013]

[0014] Among them, σ d represents the smoothing parameter;

[0015] S2.2, bring in the center point (i, j) of the image and a point (k, 1) in the neighborhood, then the range kernel is:

[0016]

[0017] Among them, σ t is the smoothing parameter;

[0018] S2.3, Substitute into the definition domain d(i,j,k,l) ​​and r(i,j,k,l), and get the weight coefficient w(i,j,k,l):

[0019]

[0020] S2.4, bring in the neighborhood pixel value f(k,l) for weighting, then bring in the output pixel value g(i,j) of the image center point (i,j) as:

[0021]

[0022] Furthermore, the step S3 further includes the following sub-steps:

[0023] S3.1, mapping the RGB color space to the CIELAB color space;

[0024] S3.2, let the area to be sprayed be numbered 1 and the standard area be numbered 2, and calculate the brightness difference, chroma difference, hue angle difference, and hue difference between the area to be sprayed and the standard area respectively;

[0025] S3.3. Calculate the color difference value.

[0026] Furthermore, the corresponding calculation method of step S3.1 is as follows:

[0027]

[0028] Where L * Indicates psychological brightness, a * , b * Indicates psychological chromaticity, X, Y, and Z indicate the three stimulus values ​​of the object color. n , Y n , Z n Indicates the tristimulus values ​​of the CIE standard light source.

[0029] Furthermore, the calculation method of step S3.2 is as follows:

[0030] The brightness difference between the spray area and the standard area ΔL * for:

[0031]

[0032] in Respectively represent the brightness of the area to be sprayed and the standard area;

[0033] The color saturation of the spraying area and the standard area and color difference They are:

[0034]

[0035] where a * represents the red and green characteristic components of the region, b * Represents the yellow-blue characteristic component of the region, Respectively represent the chroma of the area to be sprayed and the standard area;

[0036] The hue angle between the spray area and the standard area is The hue angle difference is They are:

[0037]

[0038] Among them, h1 and h2 represent the hue angles of the area to be sprayed and the standard area respectively;

[0039] The hue angle difference between the area to be sprayed and the standard area is ΔH * for:

[0040]

[0041] Furthermore, the color difference value is calculated as follows:

[0042] The color difference value for:

[0043]

[0044] Where ΔL * Indicates the brightness difference between the area to be sprayed and the standard area. Indicates the color difference between the area to be sprayed and the standard area. Indicates the hue difference between the area to be sprayed and the standard area, S L , S C , S H They respectively represent the color difference correction values ​​determined by the brightness, chroma and hue of the standard area.

[0045] Furthermore, the step S4 further includes the following sub-steps:

[0046] S4.1. Set the spraying threshold, and determine whether to spray based on whether the color difference value reaches the spraying threshold;

[0047] S4.2: If the spraying threshold is reached, spraying is performed; if the spraying threshold is not reached, the steps S1 to S4 are repeated.

[0048] Furthermore, another aspect of the embodiment of the present invention further provides a concrete wet curing device, the device comprising:

[0049] An image acquisition unit, wherein the image acquisition unit comprises an industrial camera and is used to acquire images;

[0050] An analysis unit, connected to the image acquisition unit, configured to receive an image signal and analyze the image signal using the above method, and output a control signal;

[0051] The spray unit is connected to the analysis unit and is used to receive an input control signal and start spraying clean water on the concrete.

[0052] Furthermore, another aspect of the embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] The present invention realizes fully intelligent wet curing of concrete by forming scientific linkage control of monitoring, color difference calculation and automatic spraying. It can achieve real-time monitoring and accurately replenish water according to the dry and wet conditions of the concrete surface at any time, thereby reducing labor costs, eliminating quality risks of manual curing, and improving the quality of wet curing of concrete. At the same time, it makes on-site construction operations more refined and scientific, can be applied to different concrete curing pavements, is not affected by construction conditions, and has good applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1It is a flow chart of a method for intelligent wet curing of concrete provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0057] like Figure 1 As shown, the embodiment of the present invention provides a concrete wet curing method, comprising the following steps:

[0058] S1. Capture images of concrete surfaces that require wet curing after pouring.

[0059] S2. Preprocess the collected images.

[0060] Furthermore, in step S2, the following method is used for preprocessing:

[0061] Construct an RGB color space model, and use a bilateral filtering algorithm for image denoising for each component of R, G, and B. The bilateral filter regards the filtering calculation of each pixel as the median of adjacent pixels, and Gaussian weights the spatial distance and intensity distance, which can smooth the image and retain edge information. The specific method is: introduce a pixel value of a point through the image, determine the domain kernel according to the distance between this pixel value and the neighboring pixel values, determine the range kernel according to the grayscale value of this pixel value and the neighboring pixel values, determine the weight coefficient according to the domain kernel and the range kernel, and obtain the pixel value of the new output image at this point by weighting the introduced pixel value.

[0062] Furthermore, the bilateral filtering calculation method in step S2 is as follows:

[0063] S2.1, bring in the center point (i, j) of the image and a point (k, 1) in the neighborhood, then the domain kernel is defined as:

[0064]

[0065] Among them, σ d represents the smoothing parameter;

[0066] S2.2, bring in the center point (i, j) of the image and a point (k, 1) in the neighborhood, then the range kernel is:

[0067]

[0068] Among them, σ t is the smoothing parameter;

[0069] S2.3, Substitute into the definition domain d(i,j,k,l) ​​and r(i,j,k,l), and get the weight coefficient w(i,j,k,l):

[0070]

[0071] S2.4, bring in the neighborhood pixel value f(k,l) for weighting, then bring in the output pixel value g(i,j) of the image center point (i,j) as:

[0072]

[0073] This filtering method takes into account both the spatial domain and the range weights, and can remove noise without smoothing the edges.

[0074] S3. Perform color space conversion on the preprocessed image, and substitute the characteristic value obtained after the conversion into the color difference expression to calculate the color difference value.

[0075] Furthermore, step S3 also includes the following sub-steps:

[0076] S3.1, mapping the RGB color space to the CIELAB color space;

[0077] S3.2, let the area to be sprayed be numbered 1 and the standard area be numbered 2, and calculate the brightness difference, chroma difference, hue angle difference, and hue difference between the area to be sprayed and the standard area respectively;

[0078] S3.3. Calculate the color difference value.

[0079] S3.1. To better describe color and provide more accurate and stable color representation, the RGB color space is mapped to the CIELAB color space through the CIEXYZ color space. The calculation method is as follows:

[0080]

[0081] Where L * Indicates psychological brightness, a * , b * Indicates psychological chromaticity, X, Y, and Z indicate the three stimulus values ​​of the object color. n , Y n , Z n It represents the tristimulus value of CIE standard light source, the above formula is X / X n 、Y / Y n and Z / Z n The value of must be greater than 0.008856. If it is less than 0.008856, it means that the color is extremely dark, and the use of the above formula will cause distortion of the color space.

[0082] S3.2, let the area to be sprayed be numbered 1 and the standard area be numbered 2, then the brightness difference between the area to be sprayed and the standard area ΔL * for:

[0083]

[0084] in Respectively represent the brightness of the area to be sprayed and the standard area;

[0085] The color saturation of the spraying area and the standard area and color difference They are:

[0086]

[0087] where a * represents the red and green characteristic components of the region, b * Represents the yellow-blue characteristic component of the region, Respectively represent the chroma of the area to be sprayed and the standard area;

[0088] The hue angle between the spray area and the standard area is The hue angle difference is They are:

[0089]

[0090] Among them, h1 and h2 represent the hue angles of the area to be sprayed and the standard area respectively;

[0091] The hue angle difference between the area to be sprayed and the standard area is ΔH * for:

[0092]

[0093] S3.3, the CMC (l:c) color difference formula is used to calculate the color difference value, then the color difference value for:

[0094]

[0095] Where ΔL * Indicates the brightness difference between the area to be sprayed and the standard area. Indicates the color difference between the area to be sprayed and the standard area. Indicates the hue difference between the area to be sprayed and the standard area, S L , S C , S H Respectively represent the color difference correction value determined by the lightness, chroma and hue of the standard area. Preferably, the lightness weight factor l is selected as 2 and the chroma weight factor c is selected as 1, so that the color difference allowable range is larger and the selectable color range is wider. The CMC (l:c) color difference formula is usually used in color quality control detection. The formula introduces lightness and chroma weight factors, and the calculated result is closer to the human eye's perception of color.

[0096] S4, judging whether the color difference value reaches the spraying threshold, if so, spraying the area, otherwise repeating steps S1-S4.

[0097] Furthermore, step S4 also includes the following sub-steps:

[0098] S4.1. Set the spraying threshold, and determine whether to spray based on whether the color difference value reaches the spraying threshold;

[0099] S4.2: If the spraying threshold is reached, spraying is performed; if the spraying threshold is not reached, the steps S1 to S4 are repeated.

[0100] The present invention realizes fully intelligent wet curing of concrete by forming scientific linkage control of monitoring, color difference calculation and automatic spraying. It can achieve real-time monitoring and accurately replenish water according to the dry and wet conditions of the concrete surface at any time, thereby reducing labor costs, eliminating quality risks of manual curing, and improving the quality of wet curing of concrete. At the same time, it makes on-site construction operations more refined and scientific, can be applied to different concrete curing pavements, is not affected by construction conditions, and has good applicability.

[0101] Furthermore, another aspect of the embodiment of the present invention further provides a concrete wet curing device, which can implement the above concrete wet curing method, and the device includes:

[0102] An image acquisition unit, wherein the image acquisition unit comprises an industrial camera and is used to acquire images;

[0103] An analysis unit, connected to the image acquisition unit, configured to receive image signals and analyze them using the above concrete wet curing method, and output a control signal;

[0104] The spray unit is connected to the analysis unit and is used to receive an input control signal and start spraying clean water on the concrete.

[0105] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0106] Furthermore, another aspect of the embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned concrete wet curing method is implemented.

[0107] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for wet curing of concrete, characterized in that: The following steps are involved: S1. Capture images of concrete surfaces that require wet curing after pouring. S2, preprocessing the collected images; S3, performing color space conversion on the preprocessed image, and substituting the characteristic value obtained after the conversion into the color difference expression to calculate the color difference value; S4, judging whether the color difference value reaches the spraying threshold, if so, spraying the area, otherwise repeating steps S1-S4.

2. A concrete wet curing method as claimed in claim 1, characterized in that: In step S2, the following method is used for preprocessing: An RGB color space model is constructed, and bilateral filtering algorithm is used to perform image denoising on each component of R, G, and B. The pixel value of a point is introduced into the image, and the domain kernel is determined according to the distance between this pixel value and the neighboring pixel values. The range kernel is determined according to the grayscale value of this pixel value and the neighboring pixel values. The weight coefficient is determined according to the domain kernel and the range kernel. The pixel value of the new output image at this point is obtained by weighting the introduced pixel value.

3. A concrete wet curing method as claimed in claim 2, characterized in that: The bilateral filtering calculation method in step S2 is as follows: S2.1, bring in the center point (i, j) of the image and a point (k, 1) in the neighborhood, then the domain kernel is defined as: Among them, σ d represents the smoothing parameter; S2.2, bring in the center point (i, j) of the image and a point (k, 1) in the neighborhood, then the range kernel is: Among them, σ r is the smoothing parameter; S2.3, Substitute into the definition domain d(i,j,k,l) ​​and r(i,j,k,l), and get the weight coefficient w(i,j,k,l): S2.4, bring in the neighborhood pixel value f(k,l) for weighting, then bring in the output pixel value g(i,j) of the image center point (i,j) as:

4. A method for wet curing concrete according to claim 1, characterized in that: The step S3 further comprises the following sub-steps: S3.1, mapping the RGB color space to the CIELAB color space; S3.2, let the area to be sprayed be numbered 1 and the standard area be numbered 2, and calculate the brightness difference, chroma difference, hue angle difference, and hue difference between the area to be sprayed and the standard area respectively; S3.

3. Calculate the color difference value.

5. A method for wet curing concrete as claimed in claim 4, characterized in that: The corresponding calculation method of step S3.1 is as follows: Where L * Indicates psychological brightness, a * , b * Indicates psychological chromaticity, X, Y, and Z indicate the three stimulus values ​​of the object color. n , Y n , Z n Indicates the tristimulus values ​​of the CIE standard light source.

6. A method for wet curing concrete as claimed in claim 4, characterized in that: The calculation method of step S3.2 is as follows: The brightness difference between the spray area and the standard area ΔL * for: in Respectively represent the brightness of the area to be sprayed and the standard area; The color saturation of the spraying area and the standard area and color difference They are: where a * represents the red and green characteristic components of the region, b * Represents the yellow-blue characteristic component of the region, Respectively represent the chroma of the area to be sprayed and the standard area; The hue angle between the spray area and the standard area is The hue angle difference is They are: Among them, h1 and h2 represent the hue angles of the area to be sprayed and the standard area respectively; The hue angle difference between the area to be sprayed and the standard area is ΔH * for:

7. A method for wet curing concrete as claimed in claim 4, characterized in that: The color difference value is calculated as follows: Color difference value for: Where ΔL * Indicates the brightness difference between the area to be sprayed and the standard area. Indicates the color difference between the area to be sprayed and the standard area. Indicates the hue difference between the area to be sprayed and the standard area, S L , S C , S H They respectively represent the color difference correction values ​​determined by the brightness, chroma and hue of the standard area.

8. A method for wet curing concrete according to claim 1, characterized in that: The step S4 also includes the following sub-steps: S4.

1. Set the spraying threshold, and determine whether to spray based on whether the color difference value reaches the spraying threshold; S4.2, if the spraying threshold is reached, spraying is performed; if the spraying threshold is not reached, steps S1 to S4 are repeated.

9. A concrete wet curing device, characterized in that: The device comprises: An image acquisition unit, wherein the image acquisition unit comprises an industrial camera and is used to acquire images; An analysis unit connected to the image acquisition unit, configured to receive an image signal and analyze the image signal by the method according to any one of claims 1 to 8, and output a control signal; The spray unit is connected to the analysis unit and is used to receive an input control signal and start spraying clean water on the concrete.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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