Intelligent concrete surface finishing and plastering control method and device

Abstract

The invention discloses an intelligent concrete surface finishing and plastering control method and device, and the method comprises the steps: obtaining and preprocessing a concrete surface image, extracting image feature parameters from the concrete surface image, analyzing and screening the image feature parameters, and determining key feature parameters affecting concrete surface finishing and plastering; the state of each key feature parameter is evaluated to determine the state level of the key feature parameter; and according to the state grade, setting a collecting and plastering control instruction corresponding to the collecting and plastering equipment, and carrying out collecting and plastering treatment on the concrete surface based on the instruction. According to the method, deep analysis and processing are carried out on the surface image of the concrete, the key characteristic parameters influencing the concrete surface plastering can be accurately determined, the state of the concrete surface is evaluated to determine the state grade, the state of the concrete surface corresponding to each key characteristic parameter can be accurately reflected, and the concrete surface plastering accuracy is improved. And the working parameters of the collecting and plastering equipment are adjusted according to the state, so that accurate collecting and plastering treatment on the concrete surface is realized, and the quality and the performance of the concrete surface are improved.

Description

Technical Field

[0001] The invention relates to the technical field of construction, and in particular to an intelligent concrete surface finishing control method and device. Background Art

[0002] Concrete surface finishing refers to the use of special finishing equipment to finish the concrete surface after concrete construction to achieve a certain degree of flatness and smoothness. This process is usually carried out after the initial setting of the concrete. It aims to improve the quality and appearance of the concrete surface and ensure the engineering performance and aesthetics of the concrete structure.

[0003] However, traditional methods usually rely on the experience and skills of operators, lack objective analysis and quantification of concrete surface characteristics, and are easily affected by human factors. Traditional methods are usually unable to adjust the working conditions of finishing equipment in real time, and have difficulty coping with changes and unevenness in concrete surface characteristics, resulting in uneven finishing quality. At the same time, traditional methods find it difficult to achieve fine control of the concrete surface, and cannot make targeted adjustments based on the fine features of the concrete surface, which affects the improvement of finishing quality. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides an intelligent concrete surface finishing control method and device, comprising:

[0005] Acquire the surface image of concrete and pre-process the surface image;

[0006] Extract image feature parameters of the pre-processed surface image, analyze and screen the image feature parameters, and determine the key feature parameters that affect the finishing of the concrete surface;

[0007] Evaluate the status of each key characteristic parameter, and determine the status level of each key characteristic parameter based on the evaluation result;

[0008] The finishing control instructions corresponding to the finishing equipment are set according to the state level of each key characteristic parameter, and the finishing treatment is performed on the concrete surface based on the finishing control instructions.

[0009] Furthermore, the step of obtaining the surface image of the concrete and preprocessing the surface image includes:

[0010] Acquire the surface image of the concrete, extract the surface image for grayscale processing, and obtain a surface grayscale image;

[0011] Extract all pixels in the surface grayscale image and obtain the grayscale value of each pixel;

[0012] The grayscale values ​​of each pixel are clustered based on the k-means clustering algorithm, the number of cluster centers is determined according to the area of ​​the surface image, and the surface grayscale image is partitioned according to the clustering results;

[0013] The grayscale values ​​of the pixels in the partition are adjusted to the grayscale values ​​of the cluster centers corresponding to the partitions, and several surface grayscale area images are obtained;

[0014] The detail level of each surface grayscale region image is analyzed, and based on the judgment of the detail level, it is determined whether to perform enhancement processing on the surface grayscale region image.

[0015] Further, analyzing the detail of each surface grayscale region image and determining whether to perform enhancement processing on the surface grayscale region image based on the judgment of the detail, includes:

[0016] Obtaining the contrast value of each pixel in each surface grayscale region image, and calculating the average contrast value of all pixels in each surface grayscale region image;

[0017] Determine the number of pixels in each surface grayscale region image that exceed the average contrast value, and determine the detail of each surface grayscale region image based on the number of pixels and the average contrast value;

[0018] If the detail of the surface grayscale area image is greater than or equal to the preset detail threshold, there is no need to enhance the surface grayscale area image;

[0019] If the detail of the surface grayscale area image is less than a preset detail threshold, it is necessary to perform enhancement processing on the surface grayscale area image.

[0020] Furthermore, the detail of each surface grayscale area image is calculated according to the following formula:

[0021] L = exp(P-P0) / (S-S0),

[0022] Wherein, L is the detail of each surface grayscale area image, S is the total number of pixels of all pixels in each surface grayscale area image, S0 is the number of pixels exceeding the average contrast value in each surface grayscale area image, P is the standard contrast value, P0 is the average contrast value of all pixels in each surface grayscale area image, and exp is the natural exponential function.

[0023] Furthermore, the extraction of image feature parameters of the pre-processed surface image, and analysis and screening of the image feature parameters to determine key feature parameters affecting the finishing of the concrete surface include:

[0024] The pre-processed surface image is subjected to feature extraction through image processing technology to determine the image feature parameters;

[0025] The difference between each image feature parameter and the corresponding standard requirement is analyzed, and the image feature parameters whose difference exceeds the corresponding preset value are screened out and determined as the key feature parameters affecting the finishing of the concrete surface.

[0026] Furthermore, the analysis of the difference between each image feature parameter and the corresponding standard requirement includes:

[0027] Obtaining the value of each image feature parameter and the value required by the corresponding standard, and calculating the difference between the value of each image feature parameter and the value required by the corresponding standard;

[0028] The numerical difference is taken as the degree of difference between each image feature parameter and the corresponding standard requirement.

[0029] Further, the step of evaluating the state of each key characteristic parameter and determining the state level of each key characteristic parameter based on the evaluation result includes:

[0030] Obtain the degree of difference between each key characteristic parameter and the corresponding standard requirements, and evaluate and value the degree of difference to obtain the evaluation value of each key characteristic parameter;

[0031] Each key feature parameter is scored by the expert assignment method, and the score is used as the weight coefficient of each key feature parameter;

[0032] Multiply the evaluation value of each key characteristic parameter by the corresponding weight coefficient to obtain the state evaluation value of each key characteristic parameter;

[0033] A state level-state evaluation value interval correspondence relationship is preset, and the state level-state evaluation value interval correspondence relationship is associated with a corresponding state level for each state evaluation value interval to which the state evaluation value belongs;

[0034] The state evaluation value of the key characteristic parameter is obtained, and based on the mapping relationship between the state evaluation value interval to which the state evaluation value belongs and the state level-state evaluation value interval corresponding relationship, the state level corresponding to the key characteristic parameter is determined.

[0035] Furthermore, the step of setting the corresponding wiping control instruction of the wiping device according to the state level of each key characteristic parameter includes:

[0036] Obtain the status level of each key characteristic parameter, and select the preset adjustment coefficient of the collection and wiping equipment according to the status level;

[0037] The preset working conditions corresponding to the closing and wiping equipment are adjusted through the preset adjustment coefficient to obtain the closing and wiping control instructions corresponding to the closing and wiping equipment.

[0038] The present invention also provides an intelligent concrete surface finishing control device, comprising:

[0039] An acquisition module is used to acquire a surface image of concrete and pre-process the surface image;

[0040] An extraction module is used to extract image feature parameters of the preprocessed surface image, analyze and screen the image feature parameters, and determine key feature parameters that affect the finishing of the concrete surface;

[0041] An evaluation module, used to evaluate the status of each key characteristic parameter and determine the status level of each key characteristic parameter based on the evaluation result;

[0042] The control module is used to set the finishing control instructions corresponding to the finishing equipment according to the state level of each key characteristic parameter, and perform finishing processing on the concrete surface based on the finishing control instructions.

[0043] Compared with the prior art, the intelligent concrete surface finishing control method and device according to the embodiment of the present invention have the following beneficial effects:

[0044] The present invention can accurately determine the key characteristic parameters that affect the finishing of the concrete surface by conducting in-depth analysis and processing of the surface image of concrete, and can also evaluate its state to determine the state level, and can accurately reflect the state of the concrete surface corresponding to each key characteristic parameter, and adjust the working parameters of the finishing equipment according to the state to achieve precise finishing of the concrete surface, thereby improving the quality and performance of the concrete surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the flow structure of the intelligent concrete surface finishing and plastering control method in an embodiment of the present invention;

[0046] Figure 2 It is a schematic diagram of the composition of the intelligent concrete surface finishing control device in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0048] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship are the orientation or position relationship shown in the accompanying drawings, which are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0049] The terms "second" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined with "second" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "multiple" means two or more.

[0050] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0051] like Figure 1 As shown, in an embodiment of the present application, an intelligent concrete surface finishing control method is provided, including: S100: acquiring a surface image of concrete, and preprocessing the surface image; S100: extracting image feature parameters of the preprocessed surface image, and analyzing and screening the image feature parameters to determine key feature parameters that affect the finishing of the concrete surface; S100: evaluating the state of each key feature parameter, and determining the state level of each key feature parameter based on the evaluation result; S100: setting a finishing control instruction corresponding to a finishing device according to the state level of each key feature parameter, and finishing the concrete surface based on the finishing control instruction.

[0052] Specifically, the image data of the concrete surface is acquired, and the image is preprocessed, including denoising, grayscale, edge detection, scale transformation and other operations, so as to facilitate subsequent feature extraction and analysis; image processing and computer vision technology are used to extract the characteristic parameters of the preprocessed surface image, such as texture features, color features, morphology features, etc., and then these characteristic parameters are analyzed and screened to determine which features are related to the finishing performance of the concrete surface; through analysis and screening, the key characteristic parameters affecting the finishing of the concrete surface are determined, including flatness, roughness, slope and surface defects; a state assessment is performed on each key characteristic parameter, and according to the state level of each key characteristic parameter, a corresponding finishing control instruction is set for the finishing equipment, which may involve adjusting the working speed, rotation angle, tool pressure and other parameters of the finishing equipment, and the concrete surface is finished according to the set finishing control instruction to achieve precise control of the concrete surface.

[0053] In an embodiment of the present application, a method for controlling the finishing of an intelligent concrete surface is provided, wherein the method of obtaining a surface image of the concrete and preprocessing the surface image comprises: obtaining a surface image of the concrete, and extracting the surface image for grayscale processing to obtain a surface grayscale image; extracting all pixels in the surface grayscale image, and obtaining a grayscale value of each pixel; clustering the grayscale value of each pixel based on a k-means clustering algorithm, determining the number of clustering centers according to the area of ​​the surface image, and partitioning the surface grayscale image according to the clustering result; adjusting the grayscale value of the pixel in the partition to the grayscale value of the cluster center corresponding to the partition, and obtaining a plurality of surface grayscale area images; analyzing the detail of each surface grayscale area image, and determining whether to perform enhancement processing on the surface grayscale area image based on the judgment of the detail.

[0054] Specifically, an image of the concrete surface is obtained, and the original color image is converted into a grayscale image; all pixels in the surface grayscale image are extracted, and the grayscale value of each pixel is obtained. In the grayscale image, the grayscale value of each pixel represents the brightness of the point, which can be achieved by accessing the pixels one by one and obtaining their grayscale values; the grayscale values ​​of each pixel are clustered based on the k-means clustering algorithm, and the grayscale values ​​of the concrete surface are clustered using the k-means clustering algorithm to find the center of the grayscale value, and the number of clustering centers is determined according to the area of ​​the surface image, and the table is clustered according to the clustering results. The surface grayscale image is partitioned. By determining the area of ​​the surface image, the number of cluster centers can be determined, and then the surface grayscale image is partitioned according to the clustering result; the grayscale value of the pixel point in the partition is adjusted to the grayscale value of the cluster center corresponding to the partition, and a number of surface grayscale area images are obtained. For the pixel point in each partition, its grayscale value is adjusted to the grayscale value of the corresponding cluster center, thereby obtaining a number of surface grayscale area images; the detail of each surface grayscale area image is analyzed, and based on the judgment of the detail, it is determined whether to enhance the surface grayscale area image.

[0055] In an embodiment of the present application, a method for controlling the finishing of an intelligent concrete surface is provided, wherein the detail of each surface grayscale area image is analyzed, and based on the judgment of the detail, whether to perform enhancement processing on the surface grayscale area image is determined, including: obtaining the contrast value of each pixel in each surface grayscale area image, and calculating the average contrast value of all pixels in each surface grayscale area image; determining the number of pixels in each surface grayscale area image that exceed the average contrast value, and determining the detail of each surface grayscale area image based on the number of pixels and the average contrast value; if the detail of the surface grayscale area image is greater than or equal to a preset detail threshold, there is no need to perform enhancement processing on the surface grayscale area image; if the detail of the surface grayscale area image is less than the preset detail threshold, it is necessary to perform enhancement processing on the surface grayscale area image.

[0056] Specifically, the contrast value of each pixel in each surface grayscale area image is obtained, and the average contrast value of all pixels in each surface grayscale area image is calculated. For each pixel in each surface grayscale area image, the contrast value of the surrounding pixels is calculated; the number of pixels in each surface grayscale area image that exceed the average contrast value is determined, and the detail of each surface grayscale area image is determined based on the number of pixels and the average contrast value, the number of pixels that exceed the average contrast value is counted, and the detail of each surface grayscale area image is determined in combination with the average contrast value, and the richness of the details in the image is judged; if the detail of the surface grayscale area image is greater than or equal to a preset detail threshold, there is no need to enhance the surface grayscale area image; if the detail of the surface grayscale area image is less than the preset detail threshold, it is necessary to enhance the surface grayscale area image.

[0057] In an embodiment of the present application, a smart concrete surface finishing control method is provided, and the detail degree of each surface grayscale area image is calculated according to the following formula:

[0058] L = exp(P-P0) / (S-S0),

[0059] Wherein, L is the detail of each surface grayscale area image, S is the total number of pixels of all pixels in each surface grayscale area image, S0 is the number of pixels exceeding the average contrast value in each surface grayscale area image, P is the standard contrast value, P0 is the average contrast value of all pixels in each surface grayscale area image, and exp is the natural exponential function.

[0060] In an embodiment of the present application, a smart concrete surface finishing control method is provided, wherein the image feature parameters of the preprocessed surface image are extracted, and the image feature parameters are analyzed and screened to determine the key feature parameters that affect the finishing of the concrete surface, including: extracting features of the preprocessed surface image by image processing technology to determine the image feature parameters; analyzing the degree of difference between each image feature parameter and the corresponding standard requirement, and screening out the image feature parameters whose degree of difference exceeds the corresponding preset value, and determining them as the key feature parameters that affect the finishing of the concrete surface.

[0061] Specifically, the feature extraction of the pre-processed surface image is performed through image processing technology to determine the image feature parameters. Various image processing technologies are used to extract the feature parameters of the concrete surface image, which include the flatness, roughness, slope, surface defects, etc. of the concrete surface; the difference between each image feature parameter and the corresponding standard requirements is analyzed, and the extracted image feature parameters are compared with the standard requirements to analyze the difference between them; the image feature parameters whose difference exceeds the corresponding preset value are screened out and determined as the key feature parameters affecting the finishing of the concrete surface; according to the preset difference threshold, the image feature parameters whose difference with the standard requirements exceeds the preset value are screened out. These feature parameters can be determined as the key feature parameters affecting the finishing of the concrete surface because their deviation from the standard requirements exceeds the expected range.

[0062] In an embodiment of the present application, a smart concrete surface finishing control method is provided, wherein the analysis of the degree of difference between each image feature parameter and the corresponding standard requirement includes: obtaining the numerical value of each image feature parameter and the numerical value of the corresponding standard requirement, and calculating the numerical difference between the numerical value of each image feature parameter and the numerical value of the corresponding standard requirement; and using the numerical difference as the degree of difference between each image feature parameter and the corresponding standard requirement.

[0063] Specifically, each image feature parameter is clearly defined, and its corresponding standard requirement is determined; for each feature parameter, a specific numerical value is extracted; the difference between the numerical value of each image feature parameter and the numerical value of the corresponding standard requirement is calculated. For each feature parameter, the difference between its numerical value and the numerical value of the corresponding standard requirement can be calculated, and the numerical difference is used as the degree of difference between each image feature parameter and the corresponding standard requirement, which helps to quantify the degree of difference between each feature parameter and the standard requirement, so that these differences can be more intuitively understood and compared.

[0064] In an embodiment of the present application, a method for controlling the finishing of an intelligent concrete surface is provided, wherein the state of each key feature parameter is evaluated, and the state level of each key feature parameter is determined based on the evaluation result, including: obtaining the degree of difference between each key feature parameter and the corresponding standard requirement, and evaluating and taking values ​​of the degree of difference to obtain the evaluation value of each key feature parameter; scoring each key feature parameter by an expert assignment method, and using the scored score as the weight coefficient of each key feature parameter; multiplying the evaluation value of each key feature parameter by the corresponding weight coefficient to obtain the state evaluation value of each key feature parameter; presetting a state level-state evaluation value interval correspondence relationship, and the state level-state evaluation value interval correspondence relationship is associated with a corresponding state level for each state evaluation value interval to which the state evaluation value belongs; obtaining the state evaluation value of the key feature parameter, and determining the state level corresponding to the key feature parameter based on the mapping relationship between the state evaluation value interval to which the state evaluation value belongs within the state level-state evaluation value interval correspondence relationship.

[0065] Specifically, the degree of difference between each key feature parameter and the corresponding standard requirements is obtained, and the degree of difference is evaluated and valued to obtain the evaluation value of each key feature parameter. The evaluation value is evaluated and valued according to the degree of difference between each key feature parameter and the standard requirements to obtain the evaluation value of each feature parameter; each key feature parameter is scored by the expert assignment method, and the score is used as the weight coefficient of each key feature parameter. Experts score each key feature parameter and then use the score as the weight coefficient. The expert assignment method usually includes experts assigning weights to each feature parameter based on their experience and knowledge; the evaluation value of each key feature parameter is multiplied by the corresponding weight coefficient to obtain the state evaluation value of each key feature parameter, which helps to take into account different Importance of characteristic parameters; a state level-state assessment value interval correspondence is preset, and each state assessment value interval to which the state assessment value belongs is associated with a corresponding state level, and a correspondence between state levels and state assessment value intervals is predefined to help map the state assessment value to the state level; the state assessment value of the key characteristic parameter is obtained, and based on the mapping relationship between the state assessment value interval to which the state assessment value belongs within the state level-state assessment value interval correspondence, the state level corresponding to the key characteristic parameter is determined; according to the state assessment value of each key characteristic parameter and the preset state level-state assessment value interval correspondence, the state level to which each key characteristic parameter belongs is determined.

[0066] In an embodiment of the present application, a method for controlling the finishing and plastering of an intelligent concrete surface is provided, wherein the finishing and plastering control instructions corresponding to the finishing and plastering equipment are set according to the status level of each key characteristic parameter, including: obtaining the status level of each key characteristic parameter, and selecting a preset adjustment coefficient of the finishing and plastering equipment according to the status level; adjusting the preset working conditions corresponding to the finishing and plastering equipment by the preset adjustment coefficient to obtain the finishing and plastering control instructions corresponding to the finishing and plastering equipment.

[0067] Specifically, for each state level of key characteristic parameters, corresponding preset adjustment coefficients are predefined; the preset working conditions corresponding to the finishing equipment are adjusted through the preset adjustment coefficients; once the preset adjustment coefficients are determined, these coefficients are applied to the preset working conditions of the finishing equipment, such as vibration frequency, vibration amplitude, scraper pressure, etc. These adjustments can be made for the state level of each key characteristic parameter; after applying the preset adjustment coefficients, you will get the adjusted working conditions of the finishing equipment, so as to generate corresponding finishing control instructions, which can be used to control the operation of the finishing equipment to ensure that the finishing quality of the concrete surface meets the requirements, and help to dynamically adjust the working conditions of the finishing equipment according to the state level of the key characteristic parameters to adapt to different surface characteristics, improve production efficiency, and ensure that the quality of the concrete surface meets the requirements.

[0068] like Figure 2 As shown, in an embodiment of the present application, an intelligent concrete surface finishing control device is provided, including: an acquisition module, used to acquire a surface image of concrete and preprocess the surface image; an extraction module, used to extract image feature parameters of the preprocessed surface image, and analyze and screen the image feature parameters to determine key feature parameters that affect the finishing of the concrete surface; an evaluation module, used to evaluate the state of each key feature parameter, and determine the state level of each key feature parameter based on the evaluation result; a control module, used to set a finishing control instruction corresponding to the finishing device according to the state level of each key feature parameter, and finish the concrete surface based on the finishing control instruction.

[0069] In summary, the embodiments of the present invention provide an intelligent concrete surface finishing control method and device, which includes: acquiring and preprocessing the surface image of the concrete, and extracting image feature parameters therefrom, analyzing and screening them, and determining the key feature parameters that affect the finishing of the concrete surface; evaluating the state of each key feature parameter to determine its state level; setting the finishing control instructions corresponding to the finishing equipment according to the state level, and finishing the concrete surface based on the instructions. The present invention can accurately determine the key feature parameters that affect the finishing of the concrete surface by performing in-depth analysis and processing on the surface image of the concrete, and also evaluate its state to determine the state level, which can accurately reflect the state of the concrete surface corresponding to each key feature parameter, and adjust the working parameters of the finishing equipment according to the state to achieve accurate finishing of the concrete surface, thereby improving the quality and performance of the concrete surface.

[0070] Finally, it should be noted that it is obvious that those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0071] The above is only an example of implementation of the present invention, but it cannot be used to limit the scope of the present invention. Any structural changes made according to the present invention, as long as they do not lose the essence of the present invention, should be regarded as falling within the scope of protection of the present invention and being restricted. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process and related instructions of the platform described above can refer to the corresponding process in the aforementioned platform embodiment, and will not be repeated here.

[0072] The term "comprises" or any other similar term is intended to cover a non-exclusive inclusion such that a process, platform, article, or apparatus / platform that includes a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, platform, article, or apparatus / platform.

[0073] So far, the technical solutions of the present invention have been described in conjunction with the further embodiments shown in the accompanying drawings, but it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0074] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A method for controlling the surface finishing of intelligent concrete, characterized in that: include: Acquire the surface image of concrete and pre-process the surface image; Extract image feature parameters of the pre-processed surface image, analyze and screen the image feature parameters, and determine the key feature parameters that affect the finishing of the concrete surface; Evaluate the status of each key characteristic parameter, and determine the status level of each key characteristic parameter based on the evaluation result; The finishing control instructions corresponding to the finishing equipment are set according to the state level of each key characteristic parameter, and the finishing treatment is performed on the concrete surface based on the finishing control instructions.

2. The intelligent concrete surface finishing control method according to claim 1 is characterized in that: The step of obtaining a surface image of the concrete and preprocessing the surface image comprises: Acquire the surface image of the concrete, extract the surface image for grayscale processing, and obtain a surface grayscale image; Extract all pixels in the surface grayscale image and obtain the grayscale value of each pixel; The grayscale values ​​of each pixel are clustered based on the k-means clustering algorithm, the number of cluster centers is determined according to the area of ​​the surface image, and the surface grayscale image is partitioned according to the clustering results; The grayscale values ​​of the pixels in the partition are adjusted to the grayscale values ​​of the cluster centers corresponding to the partitions, and several surface grayscale area images are obtained; The detail level of each surface grayscale region image is analyzed, and based on the judgment of the detail level, it is determined whether to perform enhancement processing on the surface grayscale region image.

3. The intelligent concrete surface finishing control method according to claim 2 is characterized in that: The analyzing the detail of each surface grayscale region image and determining whether to perform enhancement processing on the surface grayscale region image based on the judgment of the detail, comprises: Obtaining the contrast value of each pixel in each surface grayscale region image, and calculating the average contrast value of all pixels in each surface grayscale region image; Determine the number of pixels in each surface grayscale region image that exceed the average contrast value, and determine the detail of each surface grayscale region image based on the number of pixels and the average contrast value; If the detail of the surface grayscale area image is greater than or equal to the preset detail threshold, there is no need to enhance the surface grayscale area image; If the detail of the surface grayscale area image is less than a preset detail threshold, it is necessary to perform enhancement processing on the surface grayscale area image.

4. The intelligent concrete surface finishing control method according to claim 3 is characterized in that: The detail of each surface grayscale area image is calculated according to the following formula: L = exp(P-P0) / (S-S0), Wherein, L is the detail of each surface grayscale area image, S is the total number of pixels of all pixels in each surface grayscale area image, S0 is the number of pixels exceeding the average contrast value in each surface grayscale area image, P is the standard contrast value, P0 is the average contrast value of all pixels in each surface grayscale area image, and exp is the natural exponential function.

5. The intelligent concrete surface finishing control method according to claim 2 is characterized in that: The image characteristic parameters of the pre-processed surface image are extracted, and the image characteristic parameters are analyzed and screened to determine the key characteristic parameters that affect the finishing of the concrete surface, including: The image processing technology is used to extract features from the pre-processed surface image and determine the image feature parameters; The difference between each image feature parameter and the corresponding standard requirement is analyzed, and the image feature parameters whose difference exceeds the corresponding preset value are screened out and determined as the key feature parameters affecting the finishing of the concrete surface.

6. The intelligent concrete surface finishing control method according to claim 5 is characterized in that: The analyzing the difference between each image feature parameter and the corresponding standard requirement includes: Obtaining the value of each image feature parameter and the value required by the corresponding standard, and calculating the difference between the value of each image feature parameter and the value required by the corresponding standard; The numerical difference is taken as the degree of difference between each image feature parameter and the corresponding standard requirement.

7. The intelligent concrete surface finishing control method according to claim 6 is characterized in that: The step of evaluating the status of each key characteristic parameter and determining the status level of each key characteristic parameter based on the evaluation result includes: Obtain the degree of difference between each key characteristic parameter and the corresponding standard requirements, and evaluate and value the degree of difference to obtain the evaluation value of each key characteristic parameter; Each key feature parameter is scored by the expert assignment method, and the score is used as the weight coefficient of each key feature parameter; Multiply the evaluation value of each key characteristic parameter by the corresponding weight coefficient to obtain the state evaluation value of each key characteristic parameter; A state level-state evaluation value interval correspondence relationship is preset, and the state level-state evaluation value interval correspondence relationship is associated with a corresponding state level for each state evaluation value interval to which the state evaluation value belongs; The state evaluation value of the key characteristic parameter is obtained, and based on the mapping relationship between the state evaluation value interval to which the state evaluation value belongs and the state level-state evaluation value interval corresponding relationship, the state level corresponding to the key characteristic parameter is determined.

8. The intelligent concrete surface finishing control method according to claim 7 is characterized in that: The step of setting the corresponding wiping control instruction of the wiping device according to the state level of each key characteristic parameter includes: Obtain the status level of each key characteristic parameter, and select the preset adjustment coefficient of the collection and wiping equipment according to the status level; The preset working conditions corresponding to the closing and wiping equipment are adjusted through the preset adjustment coefficient to obtain the closing and wiping control instructions corresponding to the closing and wiping equipment.

9. An intelligent concrete surface finishing control device, characterized in that: include: An acquisition module is used to acquire a surface image of concrete and pre-process the surface image; An extraction module is used to extract image feature parameters of the preprocessed surface image, analyze and screen the image feature parameters, and determine key feature parameters that affect the finishing of the concrete surface; An evaluation module, used to evaluate the status of each key characteristic parameter and determine the status level of each key characteristic parameter based on the evaluation result; The control module is used to set the finishing control instructions corresponding to the finishing equipment according to the state level of each key characteristic parameter, and perform finishing processing on the concrete surface based on the finishing control instructions.

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