Method and device for analyzing anti-segregation performance of fresh self-compacting concrete

Abstract

The present application provides a method and device for analyzing the anti-segregation performance of fresh self-compacting concrete, the method comprising: determining the basic index value of the anti-segregation performance of fresh self-compacting concrete according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake; wherein the basic index value comprises: a length index value, an area index value and a volume index value; determining the derived index value of the anti-segregation performance of the fresh self-compacting concrete according to the basic index value; wherein the derived index value comprises: a water seepage index, a mortar-wrapped coarse aggregate degree index and an intermediate stone accumulation index; analyzing the anti-segregation performance of the fresh self-compacting concrete according to the derived index value and a preset analysis threshold value of the anti-segregation performance of the fresh self-compacting concrete. The present application can analyze the anti-segregation performance of fresh self-compacting concrete.

Description

Technical Field

[0001] The present application relates to the technical field of concrete working performance detection, and specifically to a method and device for analyzing the anti-segregation performance of freshly mixed self-compacting concrete. Background Art

[0002] With the rapid development of modern science and technology and economy, various types of buildings are constantly emerging, and high-rise and super-high-rise buildings are increasing. Concrete has become one of the most widely used civil engineering materials. With the popularization of concrete admixtures, fresh self-compacting concrete has been more and more widely used, and the convenience of construction has been greatly improved. The types of concrete have also shifted from plastic and dry hard concrete to fluid and high fluidity concrete. However, as the fluidity of concrete increases, its homogeneity becomes more difficult to control. The homogeneity of fresh self-compacting concrete has a significant impact on its performance after hardening. Therefore, controlling the homogeneity of fresh self-compacting concrete is of great significance for the quality assurance of buildings built with fresh self-compacting concrete.

[0003] At present, in actual construction, in order to meet the high fluidity of fresh self-compacting concrete, people often ignore its cohesiveness, causing segregation. Concrete segregation is caused by insufficient cohesion between the components of concrete, which is usually manifested as the separation of coarse aggregate and mortar. Coarse aggregate with larger particle size sinks under self-weight or vibration conditions, resulting in different volume fractions of coarse aggregate contained in the upper and lower concrete layers. Segregation not only affects the homogeneity and pumpability of concrete, but also greatly reduces the strength of fresh self-compacting concrete, seriously affecting the bearing capacity of fresh self-compacting concrete structures and reducing the safety of structures. At present, there is no unified standard for the evaluation of the anti-segregation performance of fresh self-compacting concrete at home and abroad. The existing evaluation methods have the following disadvantages: First, the existing quantitative indicators cannot describe the anti-segregation performance well, and manual assistance is required for observation and qualitative description; second, the existing quantitative indicators need to be measured one by one in the sieve test or the jump table test, the measurement process is cumbersome, and the indicator stability is also poor. Therefore, a method is needed in practical engineering to quickly, real-time and accurately evaluate the anti-segregation performance of fresh self-compacting concrete. Summary of the invention

[0004] In response to the problems in the prior art, the present application provides a method and device for analyzing the anti-segregation performance of freshly mixed self-compacting concrete, which can analyze the anti-segregation performance of freshly mixed self-compacting concrete by determining the basic index value of the anti-segregation performance of freshly mixed self-compacting concrete, and then determine the derived index value of the anti-segregation performance of freshly mixed self-compacting concrete.

[0005] In order to solve the above technical problems, this application provides the following technical solutions:

[0006] In a first aspect, the present application provides a method for analyzing the anti-segregation performance of fresh self-compacting concrete, comprising:

[0007] Determine the basic index value of the anti-segregation performance of the fresh self-compacting concrete according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake; wherein the basic index value includes: a length index value, an area index value and a volume index value;

[0008] Determining the derived index value of the anti-segregation performance of the fresh self-compacting concrete according to the basic index value; wherein the derived index value includes: water seepage index, mortar coating coarse aggregate index and intermediate stone accumulation index;

[0009] The anti-segregation performance of the fresh self-compacting concrete is analyzed according to the derived index value and a preset analysis threshold value of the anti-segregation performance of the fresh self-compacting concrete.

[0010] Furthermore, the length index value includes the maximum diameter of the cake, the minimum diameter of the cake, the maximum height of the cake, the maximum diameter of the center-clustered aggregate, the minimum diameter of the center-clustered aggregate and the maximum height of the center-clustered aggregate; the basic index value of the anti-segregation performance of the fresh self-compacting concrete is determined according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake, including:

[0011] Obtaining the maximum diameter of the cake, the minimum diameter of the cake and the maximum height of the cake of the slump spread cake; wherein the maximum diameter of the cake includes the maximum diameter of the water-containing area and the maximum diameter of the non-water-containing area; the minimum diameter of the cake includes the minimum diameter of the water-containing area and the minimum diameter of the non-water-containing area;

[0012] The maximum diameter of the centrally clustered aggregate, the minimum diameter of the centrally clustered aggregate, and the maximum height of the centrally clustered aggregate of the slump spread cake are obtained.

[0013] Furthermore, the area index value includes the bleeding area, the coarse aggregate area not covered by mortar, the non-bleeding area and the center aggregate area. The basic index value of the anti-segregation performance of the fresh self-compacting concrete is determined according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake, including:

[0014] Correcting the image corresponding to the slump spread cake to obtain a front view thereof;

[0015] Draw the area boundaries corresponding to each area index in the area index value in the front view to obtain each area region;

[0016] The areas within each of the area regions are summed up respectively to obtain the area index values ​​corresponding to the slump spread cake.

[0017] Furthermore, the area boundaries corresponding to the area indicators in the area indicator values ​​are drawn in the front view to obtain the area regions, including:

[0018] The image semantic segmentation is performed using a pre-trained image semantic segmentation machine learning model to obtain the area boundary corresponding to each area indicator in the area indicator value.

[0019] Furthermore, the steps of training the image semantic segmentation machine learning model include:

[0020] Correcting the training image corresponding to the slump spread cake to obtain a training front view;

[0021] Annotating the training front view to obtain label data;

[0022] The data training set consisting of the training front view and the label data is input into the original machine learning model for training to obtain an image semantic segmentation machine learning model.

[0023] Further, the volume index value includes the total volume of coarse aggregate, the volume of coarse aggregate not wrapped by mortar, the volume of the leaked part of coarse aggregate not wrapped by mortar, the volume of water body and the volume of central aggregate, the total volume of fresh self-compacting concrete, the volume of mortar in fresh self-compacting concrete and the water equivalent volume; the basic index value of the anti-segregation performance of fresh self-compacting concrete determined according to the physical parameters of fresh self-compacting concrete and the geometric parameters of the slump spread cake includes:

[0024] Determining the total volume of the coarse aggregate according to the total mass and density of the coarse aggregate in the fresh self-compacting concrete;

[0025] Determining the volume of the coarse aggregate not wrapped by the mortar according to the mass of the coarse aggregate not wrapped by the mortar in the fresh self-compacting concrete and the density;

[0026] The semantic 3D reconstruction method is used to determine the volume of the coarse aggregate that is not covered by mortar, the volume of the seepage water body, and the volume of the central aggregate.

[0027] Determining the total volume of the fresh self-compacting concrete and the volume of mortar in the fresh self-compacting concrete;

[0028] The water equivalent volume is determined based on the concrete mix ratio and the total volume of the fresh self-compacting concrete.

[0029] In a second aspect, the present application provides a device for analyzing the anti-segregation performance of freshly mixed self-compacting concrete, comprising:

[0030] A basic index determination unit is used to determine the basic index value of the anti-segregation performance of the fresh self-compacting concrete according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake; wherein the basic index value includes: a length index value, an area index value and a volume index value;

[0031] A derived index determination unit is used to determine a derived index value of the anti-segregation performance of the fresh self-compacting concrete according to the basic index value; wherein the derived index value includes: a water seepage index, a mortar coating coarse aggregate degree index and an intermediate stone accumulation index;

[0032] The segregation performance analysis unit is used to analyze the anti-segregation performance of the fresh self-compacting concrete according to the derived index value and a preset analysis threshold value of the anti-segregation performance of the fresh self-compacting concrete.

[0033] Furthermore, the length index value includes the maximum diameter of the cake, the minimum diameter of the cake, the maximum height of the cake, the maximum diameter of the central clustered aggregate, the minimum diameter of the central clustered aggregate and the maximum height of the central clustered aggregate; the basic index determination unit includes:

[0034] The cake index acquisition module is used to obtain the maximum cake diameter, the minimum cake diameter and the maximum cake height of the slump spread cake; wherein the maximum cake diameter includes the maximum diameter of the water-containing area and the maximum diameter of the non-water-containing area; the minimum cake diameter includes the minimum diameter of the water-containing area and the minimum diameter of the non-water-containing area;

[0035] The aggregate index acquisition module is used to obtain the maximum diameter of the central aggregate, the minimum diameter of the central aggregate and the maximum height of the central aggregate of the slump spread cake.

[0036] Furthermore, the area index value includes the seepage area, the area of ​​coarse aggregate not wrapped by mortar, the non-seepage area and the area of ​​central aggregate. The basic index determination unit includes:

[0037] A correction module, used for correcting the image corresponding to the slump spread cake to obtain a front view thereof;

[0038] An area drawing module, used for drawing the area boundaries corresponding to each area index in the area index value in the front view to obtain each area region;

[0039] The summing module is used to sum the areas in each of the area regions to obtain the area index values ​​corresponding to the slump spread cake.

[0040] Furthermore, the area drawing module is specifically used to perform image semantic segmentation using a pre-trained image semantic segmentation machine learning model to obtain area boundaries corresponding to each area indicator in the area indicator value.

[0041] Furthermore, the device for analyzing the anti-segregation performance of freshly mixed self-compacting concrete further comprises:

[0042] A training correction unit, used for correcting the training image corresponding to the slump spread cake to obtain a training front view;

[0043] A data labeling unit, used for labeling the training front view to obtain label data;

[0044] The model generation unit is used to input the data training set consisting of the training front view and the label data into the machine learning original model for training to obtain the image semantic segmentation machine learning model.

[0045] Furthermore, the volume index value includes the total volume of coarse aggregate, the volume of coarse aggregate not wrapped by mortar, the volume of the leaked part of coarse aggregate not wrapped by mortar, the volume of water body and the volume of central aggregate, the total volume of fresh self-compacting concrete, the volume of mortar in fresh self-compacting concrete and the water equivalent volume; the basic index determination unit includes:

[0046] A first volume determination module, configured to determine the total volume of the coarse aggregate according to the total mass and density of the coarse aggregate in the fresh self-compacting concrete;

[0047] A second volume determination module, configured to determine the volume of the coarse aggregate not wrapped by the mortar according to the mass of the coarse aggregate not wrapped by the mortar in the fresh self-compacting concrete and the density;

[0048] The third volume determination module is used to determine the volume of the leaked part of the coarse aggregate not wrapped by the mortar, the volume of the bleeding water body and the volume of the central aggregate by using the semantic three-dimensional reconstruction method;

[0049] a fourth volume determination module, configured to determine the total volume of the fresh self-compacting concrete and the volume of mortar in the fresh self-compacting concrete;

[0050] The fifth volume determination module is used to determine the water equivalent volume according to the concrete mix ratio and the total volume of the fresh self-compacting concrete.

[0051] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for analyzing the anti-segregation performance of freshly mixed self-compacting concrete are implemented.

[0052] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for analyzing the anti-segregation performance of fresh self-compacting concrete.

[0053] In response to the problems in the prior art, the present application provides a method and device for analyzing the anti-segregation performance of freshly mixed self-compacting concrete, which can integrate artificial intelligence technology to determine the basic index value of the anti-segregation performance of freshly mixed self-compacting concrete, and then determine the derived index value of the anti-segregation performance of freshly mixed self-compacting concrete, and analyze the anti-segregation performance of freshly mixed self-compacting concrete. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 Flow chart of the method for analyzing the anti-segregation performance of fresh self-compacting concrete in the embodiment of the present application;

[0055] Figure 2 One of the flowcharts for determining the basic index value in the embodiment of the present application;

[0056] Figure 3 Flow chart 2 of determining the basic index value in the embodiment of the present application;

[0057] Figure 4 Flow chart of training an image semantic segmentation machine learning model in an embodiment of the present application;

[0058] Figure 5 Flow chart 3 of determining basic index value in the embodiment of the present application;

[0059] Figure 6 One of the structural diagrams of the device for analyzing the anti-segregation performance of fresh self-compacting concrete in the embodiment of the present application;

[0060] Figure 7 One of the basic indicator determination units in the embodiment of the present application;

[0061] Figure 8 The second basic indicator determination unit in the embodiment of the present application;

[0062] Fig. 9 The second structural diagram of the device for analyzing the anti-segregation performance of fresh self-compacting concrete in the embodiment of the present application;

[0063] Fig.10 The third basic indicator determination unit in the embodiment of the present application;

[0064] Fig.11 A schematic diagram of the structure of an electronic device in an embodiment of the present application;

[0065] Fig.12 Schematic diagram of length index values ​​in an embodiment of the present application. DETAILED DESCRIPTION

[0066] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0067] See also Figure 1 In order to determine the basic index value of the anti-segregation performance of fresh self-compacting concrete, and then determine the derived index value of the anti-segregation performance of fresh self-compacting concrete, the anti-segregation performance of fresh self-compacting concrete is analyzed. This application provides a method for analyzing the anti-segregation performance of fresh self-compacting concrete, including:

[0068] S101: determining basic index values ​​of anti-segregation performance of fresh self-compacting concrete according to physical parameters of the fresh self-compacting concrete and geometric parameters of the slump spread cake; wherein the basic index values ​​include: length index value, area index value and volume index value;

[0069] It is understandable that in actual engineering, when the method described in this application is needed to analyze the anti-segregation performance of fresh self-compacting concrete, a slump expansion test can be first performed on the fresh self-compacting concrete to obtain a slump expansion cake. Then, the geometric parameters of the slump expansion cake are measured using conventional measuring tools such as a ruler, and these parameters include but are not limited to the cake diameter and cake height. In addition, fresh self-compacting concrete has its inherent physical parameters, and these parameters include but are not limited to the volume and density of coarse aggregate in fresh self-compacting concrete. According to the physical parameters of fresh self-compacting concrete and the geometric parameters of the slump expansion cake, the basic index values ​​of the anti-segregation performance of fresh self-compacting concrete can be determined. These basic index values ​​reflect the length characteristics, area characteristics and volume characteristics of fresh self-compacting concrete.

[0070] Specifically, the length index values ​​include the maximum diameter D1 of the cake, the minimum diameter D2 of the cake, the maximum height H1 of the cake, the maximum diameter D3 of the center-clustered aggregate, the minimum diameter D4 of the center-clustered aggregate and the maximum height H2 of the center-clustered aggregate; the area index values ​​include the seepage area S1, the area S2 of coarse aggregate not wrapped by mortar, the non-seepage area S3 and the area S4 of the center-clustered aggregate; the volume index values ​​include the total volume V1 of coarse aggregate, the volume V2 of coarse aggregate not wrapped by mortar, the volume V3 of the leaked part of coarse aggregate not wrapped by mortar, the volume V6 of seepage water and the volume V7 of the center-clustered aggregate, the total volume V4 of freshly mixed self-compacting concrete, the volume V5 of mortar in freshly mixed self-compacting concrete and the water equivalent volume V8.

[0071] S102: Determine a derived index value of the anti-segregation performance of the fresh self-compacting concrete according to the basic index value; wherein the derived index value includes: a water seepage index, a mortar coating coarse aggregate index, and an intermediate stone accumulation index;

[0072] It is understandable that in order to better analyze the anti-segregation performance of fresh self-compacting concrete, the present application also proposes a plurality of derived index values. These derived index values ​​can be determined by the above-mentioned basic index values, reflecting the degree of water seepage, the degree of mortar covering coarse aggregate and the degree of stone accumulation in the middle of the fresh self-compacting concrete. Those skilled in the art know that the anti-segregation performance of fresh self-compacting concrete is better when there is no water seepage at the edge of the slump expansion cake, when the mortar completely covers the coarse aggregate, and when there is no stone accumulation in the middle of the slump expansion cake.

[0073] In the derived index value proposed in this application, the or It can characterize the degree of water bleeding of fresh self-compacting concrete; or It can characterize the degree of mortar covering coarse aggregate; or Can characterize the degree of intermediate stone accumulation; or It can characterize the degree of mortar covering coarse aggregate; or It can characterize the degree of mortar covering coarse aggregate; or or It can characterize the degree of water bleeding of fresh self-compacting concrete; or Can characterize the degree of intermediate stone accumulation; or It can characterize the degree of mortar covering coarse aggregate. Among them, D11 and D21 represent the maximum diameter and minimum diameter of the area containing seepage water, respectively.

[0074] S103: Analyze the anti-segregation performance of the fresh self-compacting concrete according to the derived index value and a preset analysis threshold value of the anti-segregation performance of the fresh self-compacting concrete.

[0075] It is understandable that the anti-segregation performance analysis method of fresh self-compacting concrete provided in the present application can preset the analysis threshold of the anti-segregation performance of fresh self-compacting concrete, see Table 1 to Table 8. The following thresholds can correspond to the calculation results corresponding to the various degree indicators described in S102.

[0076] Table 1

[0077]

[0078]

[0079] Table 2

[0080]

[0081] Table 3

[0082]

[0083] Table 4

[0084]

[0085] Table 5

[0086]

[0087] Table 6

[0088]

[0089] Table 7

[0090]

[0091] Table 8

[0092]

[0093] From the above description, it can be seen that the anti-segregation performance analysis method of freshly mixed self-compacting concrete provided in the present application can determine the basic index value of the anti-segregation performance of freshly mixed self-compacting concrete, and then determine the derived index value of the anti-segregation performance of freshly mixed self-compacting concrete, and analyze the anti-segregation performance of freshly mixed self-compacting concrete.

[0094] See also Figure 2 When the basic index value is the length index value, the basic index value of the anti-segregation performance of fresh self-compacting concrete is determined according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump expansion cake, including:

[0095] S201: Obtaining the maximum diameter D1, the minimum diameter D2 and the maximum height H1 of the slump spread cake; wherein the maximum diameter D1 of the cake includes the maximum diameter D11 of the bleeding area and the maximum diameter D12 of the non-bleeding area; the minimum diameter D2 of the cake includes the minimum diameter D21 of the bleeding area and the minimum diameter D22 of the non-bleeding area;

[0096] S202: Obtain the maximum diameter D3 of the central aggregate, the minimum diameter D4 of the central aggregate, and the maximum height H2 of the central aggregate of the slump spread cake.

[0097] Understandably, see Fig.12The above basic index values ​​can be actually measured by conventional measuring tools such as rulers to obtain various parameters.

[0098] From the above description, it can be seen that the anti-segregation performance analysis method of fresh self-compacting concrete provided in this application can determine the basic index value of the anti-segregation performance of fresh self-compacting concrete according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake.

[0099] See also Figure 3 When the basic index value is the area index value, the basic index value of the anti-segregation performance of the fresh self-compacting concrete is determined according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump expansion cake, including:

[0100] S301: Correcting the image corresponding to the slump spread cake to obtain a front view thereof;

[0101] It is understandable that the embodiment of the present application first uses the Canny edge detection operator to perform edge detection on the slump spread image, thereby drawing the area boundary corresponding to each area index in the area index value. During the detection process, all objects in the slump spread image can be hollowed out, leaving only the edges, thereby obtaining the edge contour image of all objects. Since the fresh self-compacting concrete needs to be placed on a base plate for testing when the slump spread test is carried out, a base plate will be included in the slump spread image. Generally speaking, compared with other objects in the slump spread image, the edge contour of the base plate is the largest, so the edge contour of the base plate can be easily found by using the functions findcounter and drawcounter in the cross-platform computer vision and machine learning software library OpenCV, and the edge contour of the base plate is drawn in a clockwise direction. In this way, since the base plate is usually a square, the four corner points of the base plate can be determined by the lines drawn by the points. Generally speaking, the coordinates of the points that make up the edge contour of the base plate can be stored in a one-dimensional array, and each element in the array represents the coordinate information of a point in the edge contour, and is stored in a clockwise direction along the contour. The smallest horizontal coordinate X in the array min and the minimum ordinate Y min The corresponding point is the upper left corner of the base plate, and the largest horizontal coordinate X in the array max and the minimum ordinate Y min The corresponding point is the upper right corner of the base plate, and the smallest horizontal coordinate X in the array min and the maximum ordinate Y max The corresponding point is the lower left corner of the base plate, and the largest horizontal coordinate X in the array max and the maximum ordinate Y maxThe corresponding point is the lower right corner of the base. The coordinate values ​​of these four corner points are necessary parameters of the perspective transformation model, which corresponds to the function getPerspectiveTransform in the cross-platform computer vision and machine learning software library OpenCV. The perspective transformation model can realize the correction of the base of the slump spread image in the video, so that the crooked base in the natural shooting state is converted into a front view, that is, the Mask image of the slump spread image. Obviously, after the base is adjusted to the front view, the slump spread cake on the base will also present the front view direction.

[0102] When calculating coordinates, the actual value of the slump spread cake can be used for positioning calculations, or the pixel value of each point in the slump spread image can be used for positioning calculations. The conversion formula between pixel value and actual value is as follows:

[0103]

[0104] Where p is the pixel size of the target length, d is the bit depth of the slump spread image, l is the actual size of the target length, and 2.54 is the conversion from inches to centimeters. This formula can be used to convert the actual size of the slump spread cake into pixel size, which is convenient for perspective transformation of the slump spread cake.

[0105] S302: Draw the area boundaries corresponding to each area index in the area index value in the front view to obtain each area region;

[0106] In the embodiment of the present application, the corrected slump spread image is loaded into the background elimination model to remove the background in the slump spread image, which includes but is not limited to the base plate, so as to obtain a mask image containing only fresh self-compacting concrete, that is, a front view of the slump spread image. Among them, the background elimination model can separate objects in motion in the video. The embodiment of the present application adopts the function BackgroundSubtractorKNN in the cross-platform computer vision and machine learning software library OpenCV.

[0107] Then, the watershed algorithm is used to continue edge detection and contour recognition of the above-mentioned Mask image, and the area boundary corresponding to each area index in the area index value can be drawn to obtain each area region. At this time, the function Threshold in the cross-platform computer vision and machine learning software library OpenCV is used. The watershed algorithm is an image region segmentation method. During the segmentation process, the grayscale value of each pixel in the image is first obtained, and then the similarity between each pixel is calculated based on the grayscale value of each pixel, so that the pixels with similar spatial positions and similar grayscale values ​​are connected to each other to form a closed contour, and finally the contour recognition of the corrected slump spread image is completed, so as to obtain the area boundary corresponding to each area index and obtain each area region.

[0108] S303: summing up the areas in each area region respectively to obtain the area index values ​​corresponding to the slump spread cake.

[0109] From the above description, it can be seen that the anti-segregation performance analysis method of fresh self-compacting concrete provided in this application can determine the basic index value of the anti-segregation performance of fresh self-compacting concrete according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake.

[0110] In one embodiment, the area boundaries corresponding to the area indicators in the area indicator value are drawn in the front view to obtain the area regions, including:

[0111] The image semantic segmentation is performed using a pre-trained image semantic segmentation machine learning model to obtain the area boundary corresponding to each area indicator in the area indicator value.

[0112] It is understandable that there are various image semantic segmentation machine learning models, and the present application is not limited thereto. Those skilled in the art know that commonly used image semantic segmentation machine learning models can be trained based on convolutional neural networks (CNN) or fully convolutional neural networks (FCN). The trained image semantic segmentation machine learning model can perform image semantic segmentation on each object in the image to obtain the area boundary required by the embodiment of the present application.

[0113] From the above description, it can be seen that the anti-segregation performance analysis method of fresh self-compacting concrete provided in the present application can draw the area boundaries corresponding to each area index in the area index value in the front view to obtain each area region.

[0114] See also Figure 4 , the steps to train a machine learning model for image semantic segmentation include:

[0115] S401: Correcting the training image corresponding to the slump spread cake to obtain a training front view;

[0116] S402: Annotate the training front view to obtain label data;

[0117] It is understandable that the training image corresponding to the slump spread cake can be corrected by the method described in S301 to S302 to obtain a training front view. Data annotation of the training front view can obtain label data representing the degree of segregation.

[0118] S403: Input the data training set consisting of the training front view and the label data into the original machine learning model for training to obtain an image semantic segmentation machine learning model.

[0119] From the above description, it can be seen that the anti-segregation performance analysis method of fresh self-compacting concrete provided in this application can complete the training of the image semantic segmentation machine learning model.

[0120] See also Figure 5 When the basic index value is a volume index value, the basic index value of the anti-segregation performance of fresh self-compacting concrete is determined according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump expansion cake, including:

[0121] S501: Determine the total volume of coarse aggregate according to the total mass and density of coarse aggregate in the fresh self-compacting concrete;

[0122] It is understood that the fresh self-compacting concrete can be weighed before being mixed to obtain the total mass of the coarse aggregate in the fresh self-compacting concrete. Since the density of the coarse aggregate in the fresh self-compacting concrete is a known quantity, the total volume of the coarse aggregate can be obtained.

[0123] S502: Determine the volume of the coarse aggregate not wrapped by the mortar according to the mass and density of the coarse aggregate not wrapped by the mortar in the freshly mixed self-compacting concrete;

[0124] It can be understood that the coarse aggregate not covered by mortar can be picked out from the slump expansion cake, the surface slurry can be washed off, and then dried and weighed to obtain the mass of the coarse aggregate not covered by mortar. Combined with the density of the coarse aggregate in the freshly mixed self-compacting concrete, the volume of the coarse aggregate not covered by mortar can be obtained.

[0125] S503: using a semantic 3D reconstruction method to determine the volume of the leaked portion of the coarse aggregate not wrapped by the mortar, the volume of the seepage water body, and the volume of the central aggregate;

[0126] It is understandable that the common methods for obtaining a three-dimensional model are:

[0127] First, use traditional geometric modeling tools such as AutoCDA or 3D Studio Max for manual modeling.

[0128] Second, based on multiple images taken at different angles, point cloud recognition is performed using computer vision theory, and 3D modeling is performed using the recognized point cloud. This method is image-based 3D reconstruction. Specifically, image-based 3D reconstruction mainly includes sparse point cloud reconstruction and dense point cloud reconstruction. Sparse point cloud reconstruction includes feature point detection and matching and SFM reconstruction. Currently, the more mature algorithms include SURF (Speeded Up Robust Features), FAST (Features from Accelerated Segment Test), ORB (Oriented FAST and Rotated BRIEF), SLAM (simultaneous localization and mapping), and DSO (Direct Sparse Odometry).

[0129] Third, use a 3D scanning device to scan the target and then reconstruct the 3D model of the target. This method is point cloud-based 3D reconstruction.

[0130] Specifically, first, SLAM point cloud recognition is performed on the collapse degree cake, and the steps are: 1) a two-dimensional image or video is obtained for the collapse degree cake; 2) the device is calibrated for the image corresponding to the obtained image or video, such as camera calibration; 3) based on the image corresponding to the obtained image or video and the calibration parameters, SLAM point cloud recognition is performed to finally obtain a surface three-dimensional point cloud map of the collapse degree cake;

[0131] Alternatively, a three-dimensional laser radar is used to obtain a point cloud, and the steps are: 1) using a laser scanner to acquire data and scan the slump spread cake from different angles; 2) aligning the point clouds corresponding to the slump spread cakes scanned at different angles in the same coordinate system to obtain a three-dimensional point cloud map of the slump spread cake.

[0132] Then, a machine learning algorithm is used to perform two-dimensional semantic segmentation on the image corresponding to the acquired two-dimensional image or video, and the steps are: 1) establishing a semantic segmentation dataset for the collapse spread cake; 2) using the pre-established semantic segmentation dataset to train the selected machine learning model; 3) using the trained model to perform semantic segmentation on the image corresponding to the acquired two-dimensional image or video of the collapse spread cake; 4) assigning the two-dimensional semantics obtained by the semantic segmentation to the corresponding three-dimensional point cloud, and finally obtaining a three-dimensional point cloud with semantic attributes.

[0133] Finally, various spatial volumes are calculated based on the obtained three-dimensional point cloud with semantic attributes. These spatial volumes include but are not limited to the volume of the leaked part of the coarse aggregate, the volume of the seepage water body and the volume of the central aggregate.

[0134] S504: Determine the total volume of the fresh self-compacting concrete and the volume of the mortar in the fresh self-compacting concrete;

[0135] It is understood that for the slump flow test, the total volume of fresh self-compacting concrete is fixed and can be obtained directly. The volume of mortar in fresh self-compacting concrete can be determined by V4-V1-V6 calculation.

[0136] S505: Determine the water equivalent volume based on the concrete mix ratio and the total volume of the fresh self-compacting concrete.

[0137] From the above description, it can be seen that the anti-segregation performance analysis method of fresh self-compacting concrete provided in the present application can determine the basic index value of the anti-segregation performance of fresh self-compacting concrete according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake.

[0138] Based on the same inventive concept, the embodiments of the present application also provide a device for analyzing the anti-segregation performance of fresh self-compacting concrete, which can be used to implement the method described in the above embodiments, as described in the following embodiments. Since the principle of solving the problem by the device for analyzing the anti-segregation performance of fresh self-compacting concrete is similar to the method for analyzing the anti-segregation performance of fresh self-compacting concrete, the implementation of the device for analyzing the anti-segregation performance of fresh self-compacting concrete can refer to the implementation of the method for determining the software performance benchmark, and the repeated parts will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. Although the system described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0139] See also Figure 6 The present application provides a device for analyzing the anti-segregation performance of freshly mixed self-compacting concrete, comprising:

[0140] A basic index determination unit 601 is used to determine the basic index value of the anti-segregation performance of the fresh self-compacting concrete according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake; wherein the basic index value includes: a length index value, an area index value and a volume index value;

[0141] The derived index determination unit 602 is used to determine the derived index value of the anti-segregation performance of the fresh self-compacting concrete according to the basic index value; wherein the derived index value includes: a water seepage index, a mortar coating coarse aggregate degree index and an intermediate stone accumulation index;

[0142] The segregation performance analysis unit 603 is used to analyze the anti-segregation performance of the fresh self-compacting concrete according to the derived index value and a preset analysis threshold value of the anti-segregation performance of the fresh self-compacting concrete.

[0143] See also Figure 7 The length index value includes the maximum diameter of the cake, the minimum diameter of the cake, the maximum height of the cake, the maximum diameter of the center-clustered aggregate, the minimum diameter of the center-clustered aggregate and the maximum height of the center-clustered aggregate; the basic index determination unit 601 includes:

[0144] The cake index acquisition module 701 is used to obtain the maximum cake diameter, the minimum cake diameter and the maximum cake height of the slump spread cake; wherein the maximum cake diameter includes the maximum diameter of the water bleeding area and the maximum diameter of the non-water bleeding area; the minimum cake diameter includes the minimum diameter of the water bleeding area and the minimum diameter of the non-water bleeding area;

[0145] The aggregate index acquisition module 702 is used to obtain the maximum diameter of the central aggregate, the minimum diameter of the central aggregate and the maximum height of the central aggregate of the slump spread cake.

[0146] See also Figure 8 The area index value includes the bleeding area, the coarse aggregate area not covered by mortar, the non-bleeding area and the center aggregate area. The basic index determination unit 601 includes:

[0147] A correction module 801 is used to correct the image corresponding to the slump spread cake to obtain its front view;

[0148] An area drawing module 802 is used to draw the area boundaries corresponding to each area index in the area index value in the front view to obtain each area region;

[0149] The summing module 803 is used to sum the areas in each of the area regions to obtain the area index values ​​corresponding to the slump spread cake.

[0150] In one embodiment, the area drawing module is specifically used to perform image semantic segmentation using a pre-trained image semantic segmentation machine learning model to obtain area boundaries corresponding to each area indicator in the area indicator value.

[0151] See also Fig. 9 , the anti-segregation performance analysis device for freshly mixed self-compacting concrete also includes:

[0152] A training correction unit 901 is used to correct the training image corresponding to the slump spread cake to obtain a training front view;

[0153] A data labeling unit 902 is used to label the training front view to obtain label data;

[0154] The model generation unit 903 is used to input the data training set consisting of the training front view and the label data into the original machine learning model for training to obtain an image semantic segmentation machine learning model.

[0155] See also Fig.10 The volume index value includes the total volume of coarse aggregate, the volume of coarse aggregate not covered by mortar, the volume of the leaked part of coarse aggregate not covered by mortar, the volume of water body and the volume of central aggregate, the total volume of fresh self-compacting concrete, the volume of mortar in fresh self-compacting concrete and the water equivalent volume; the basic index determination unit 601 includes:

[0156] The first volume determination module 1001 is used to determine the total volume of the coarse aggregate according to the total mass and density of the coarse aggregate in the fresh self-compacting concrete;

[0157] A second volume determination module 1002 is used to determine the volume of the coarse aggregate not wrapped by the mortar according to the mass of the coarse aggregate not wrapped by the mortar in the fresh self-compacting concrete and the density;

[0158] The third volume determination module 1003 is used to determine the volume of the coarse aggregate leaking out of the mortar, the volume of the bleeding water body and the volume of the central aggregate by using the semantic 3D reconstruction method;

[0159] A fourth volume determination module 1004 is used to determine the total volume of the fresh self-compacting concrete and the volume of mortar in the fresh self-compacting concrete;

[0160] The fifth volume determination module 1005 is used to determine the water equivalent volume according to the concrete mix ratio and the total volume of the fresh self-compacting concrete.

[0161] From the hardware level, in order to determine the basic index value of the anti-segregation performance of fresh self-compacting concrete, and then determine the derived index value of the anti-segregation performance of fresh self-compacting concrete, the anti-segregation performance of fresh self-compacting concrete is analyzed. The present application provides an embodiment of an electronic device for implementing all or part of the contents of the anti-segregation performance analysis method of fresh self-compacting concrete, and the electronic device specifically includes the following contents:

[0162] Processor, memory, communication interface and bus; wherein the processor, memory and communication interface communicate with each other through the bus; the communication interface is used to realize information transmission between the fresh self-compacting concrete anti-segregation performance analysis device and related devices such as core business systems, user terminals and related databases; the logic controller can be a desktop computer, a tablet computer and a mobile terminal, etc., and the present embodiment is not limited thereto. In the present embodiment, the logic controller can be implemented with reference to the embodiment of the fresh self-compacting concrete anti-segregation performance analysis method and the embodiment of the fresh self-compacting concrete anti-segregation performance analysis device in the embodiment, and the contents thereof are incorporated herein, and the repeated parts are not repeated.

[0163] It is understandable that the user terminal may include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a personal digital assistant (PDA), a vehicle-mounted device, a smart wearable device, etc. Among them, the smart wearable device may include smart glasses, a smart watch, a smart bracelet, etc.

[0164] In practical applications, part of the method for analyzing the anti-segregation performance of fresh self-compacting concrete can be executed on the electronic device side as described above, or all operations can be completed in the client device. The selection can be made based on the processing capability of the client device and the limitations of the user's usage scenario. This application does not limit this. If all operations are completed in the client device, the client device may also include a processor.

[0165] The client device may have a communication module (i.e., a communication unit) that can communicate with a remote server to achieve data transmission with the server. The server may include a server on the task scheduling center side, and other implementation scenarios may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, or a server cluster consisting of multiple servers, or a server structure of a distributed device.

[0166] Fig.11 FIG. 9 is a schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. Fig.11 As shown, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. It is worth noting that Fig.11 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0167] In one embodiment, the function of the analysis method for the anti-segregation performance of fresh self-compacting concrete can be integrated into the central processing unit 9100. The central processing unit 9100 can be configured to perform the following control:

[0168] S101: determining basic index values ​​of anti-segregation performance of fresh self-compacting concrete according to physical parameters of the fresh self-compacting concrete and geometric parameters of the slump spread cake; wherein the basic index values ​​include: length index value, area index value and volume index value;

[0169] S102: Determine a derived index value of the anti-segregation performance of the fresh self-compacting concrete according to the basic index value; wherein the derived index value includes: a water seepage index, a mortar coating coarse aggregate index, and an intermediate stone accumulation index;

[0170] S103: Analyze the anti-segregation performance of the fresh self-compacting concrete according to the derived index value and a preset analysis threshold value of the anti-segregation performance of the fresh self-compacting concrete.

[0171] From the above description, it can be seen that the anti-segregation performance analysis method of freshly mixed self-compacting concrete provided in the present application can determine the basic index value of the anti-segregation performance of freshly mixed self-compacting concrete, and then determine the derived index value of the anti-segregation performance of freshly mixed self-compacting concrete, and analyze the anti-segregation performance of freshly mixed self-compacting concrete.

[0172] In another embodiment, the device for analyzing the anti-segregation performance of freshly mixed self-compacting concrete can be configured separately from the central processing unit 9100. For example, the data composite transmission device for analyzing the anti-segregation performance of freshly mixed self-compacting concrete can be configured as a chip connected to the central processing unit 9100, and the function of the method for analyzing the anti-segregation performance of freshly mixed self-compacting concrete can be realized through the control of the central processing unit.

[0173] like Fig.11 As shown, the electronic device 9600 may also include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily have to include Fig.11 In addition, the electronic device 9600 may also include Fig.11 For components not shown, reference may be made to the prior art.

[0174] like Fig.11 As shown, the central processing unit 9100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor device and / or logic device. The central processing unit 9100 receives input and controls the operation of various components of the electronic device 9600.

[0175] The memory 9140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The CPU 9100 may execute the program stored in the memory 9140 to implement information storage or processing, etc.

[0176] The input unit 9120 provides input to the central processing unit 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used to display display objects such as images and texts. The display may be, for example, an LCD display, but is not limited thereto.

[0177] The memory 9140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142, which is used to store application programs and function programs or processes for executing the operation of the electronic device 9600 through the central processor 9100.

[0178] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various drivers for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0179] The communication module 9110 is a transmitter / receiver 9110 that sends and receives signals via an antenna 9111. The communication module (transmitter / receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0180] Based on different communication technologies, multiple communication modules 9110 may be provided in the same electronic device, such as a cellular network module, a Bluetooth module and / or a wireless LAN module. The communication module (transmitter / receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide an audio output via the speaker 9131 and receive an audio input from the microphone 9132, thereby realizing a common telecommunication function. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 9130 is also coupled to the central processor 9100, so that recording can be performed on the local machine through the microphone 9132, and the sound stored on the local machine can be played through the speaker 9131.

[0181] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps of the method for analyzing the anti-segregation performance of fresh self-compacting concrete in the above embodiments, the execution subject of which is a server or a client. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all the steps of the method for analyzing the anti-segregation performance of fresh self-compacting concrete in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0182] S101: determining basic index values ​​of anti-segregation performance of fresh self-compacting concrete according to physical parameters of the fresh self-compacting concrete and geometric parameters of the slump spread cake; wherein the basic index values ​​include: length index value, area index value and volume index value;

[0183] S102: Determine a derived index value of the anti-segregation performance of the fresh self-compacting concrete according to the basic index value; wherein the derived index value includes: a water seepage index, a mortar coating coarse aggregate index, and an intermediate stone accumulation index;

[0184] S103: Analyze the anti-segregation performance of the fresh self-compacting concrete according to the derived index value and a preset analysis threshold value of the anti-segregation performance of the fresh self-compacting concrete.

[0185] From the above description, it can be seen that the anti-segregation performance analysis method of freshly mixed self-compacting concrete provided in the present application can determine the basic index value of the anti-segregation performance of freshly mixed self-compacting concrete, and then determine the derived index value of the anti-segregation performance of freshly mixed self-compacting concrete, and analyze the anti-segregation performance of freshly mixed self-compacting concrete.

[0186] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0187] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0188] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0189] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0190] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for analyzing the anti-segregation performance of fresh self-compacting concrete, characterized in that: include: Determine the basic index value of the anti-segregation performance of the fresh self-compacting concrete according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump expansion cake; wherein the basic index value includes: length index value, area index value, volume index value; wherein the length index value includes the maximum diameter D1 of the cake body, the minimum diameter D2 of the cake body, the maximum height H1 of the cake body, the maximum diameter D3 of the center clustered aggregate, the minimum diameter D4 of the center clustered aggregate, and the maximum height H2 of the center clustered aggregate; the area index value includes the seepage area S1, the area S2 of the coarse aggregate not wrapped by the mortar, the non-seepage area S3, and the area S4 of the center clustered aggregate; the volume index value includes the total volume V1 of the coarse aggregate, the volume V2 of the coarse aggregate not wrapped by the mortar, the volume V3 of the leaked part of the coarse aggregate not wrapped by the mortar, the volume V6 of the seepage water body, the volume V7 of the center clustered aggregate, the total volume V4 of the fresh self-compacting concrete, the volume V5 of the mortar in the fresh self-compacting concrete, and the water equivalent volume V8; Determine the derived index value of the anti-segregation performance of the fresh self-compacting concrete according to the basic index value; wherein the derived index value includes: water seepage index, mortar coating coarse aggregate index, intermediate stone accumulation index; wherein, in the derived index value, use or Characterize the degree of bleeding of fresh self-compacting concrete; or Characterize the degree of mortar encapsulation of coarse aggregate; or Characterize the degree of intermediate stone accumulation; use or Characterize the degree of mortar encapsulation of coarse aggregate; or Characterize the degree of mortar encapsulation of coarse aggregate; or or Characterize the degree of bleeding of fresh self-compacting concrete; or Characterize the degree of intermediate stone accumulation; use or Characterizes the degree of mortar encapsulation of coarse aggregate; among them, D 11 , D 21 They represent the maximum diameter of the area containing bleeding water and the minimum diameter of the area containing bleeding water respectively; The anti-segregation performance of the fresh self-compacting concrete is analyzed according to the derived index value and a preset analysis threshold value of the anti-segregation performance of the fresh self-compacting concrete.

2. The method for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 1, characterized in that: The basic index value of the anti-segregation performance of the fresh self-compacting concrete is determined according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake, including: Obtaining the maximum diameter of the cake, the minimum diameter of the cake and the maximum height of the cake of the slump spread cake; wherein the maximum diameter of the cake includes the maximum diameter of the water-containing area and the maximum diameter of the non-water-containing area; the minimum diameter of the cake includes the minimum diameter of the water-containing area and the minimum diameter of the non-water-containing area; The maximum diameter of the centrally clustered aggregate, the minimum diameter of the centrally clustered aggregate, and the maximum height of the centrally clustered aggregate of the slump spread cake are obtained.

3. The method for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 1, characterized in that: The basic index value of the anti-segregation performance of the fresh self-compacting concrete is determined according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake, including: Correcting the image corresponding to the slump spread cake to obtain a front view thereof; Draw the area boundaries corresponding to each area index in the area index value in the front view to obtain each area region; The areas within each of the area regions are summed up respectively to obtain the area index values ​​corresponding to the slump spread cake.

4. The method for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 3, characterized in that: The step of drawing the area boundaries corresponding to the area indicators in the area indicator values ​​in the front view to obtain the area regions includes: The image semantic segmentation is performed using a pre-trained image semantic segmentation machine learning model to obtain the area boundary corresponding to each area indicator in the area indicator value.

5. The method for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 4, characterized in that: The steps to train a machine learning model for image semantic segmentation include: Correcting the training image corresponding to the slump spread cake to obtain a training front view; Annotating the training front view to obtain label data; The data training set consisting of the training front view and the label data is input into the original machine learning model for training to obtain an image semantic segmentation machine learning model.

6. The method for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 1, characterized in that: The basic index value of the anti-segregation performance of the fresh self-compacting concrete is determined according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake, including: Determining the total volume of the coarse aggregate according to the total mass and density of the coarse aggregate in the fresh self-compacting concrete; Determining the volume of the coarse aggregate not wrapped by the mortar according to the mass of the coarse aggregate not wrapped by the mortar in the fresh self-compacting concrete and the density; The semantic 3D reconstruction method is used to determine the volume of the coarse aggregate that is not covered by mortar, the volume of the seepage water body, and the volume of the central aggregate. Determining the total volume of the fresh self-compacting concrete and the volume of mortar in the fresh self-compacting concrete; The water equivalent volume is determined based on the concrete mix ratio and the total volume of the fresh self-compacting concrete.

7. A device for analyzing the anti-segregation performance of fresh self-compacting concrete, characterized in that: include: The basic index determination unit is used to determine the basic index value of the anti-segregation performance of the fresh self-compacting concrete according to the physical parameters of the fresh self-compacting concrete and the geometric parameters of the slump spread cake; wherein the basic index value includes: length index value, area index value, volume index value; wherein the length index value includes the maximum diameter D1 of the cake body, the minimum diameter D2 of the cake body, the maximum height H1 of the cake body, the maximum diameter D3 of the center clustered aggregate, the minimum diameter D4 of the center clustered aggregate, and the maximum height H2 of the center clustered aggregate. H2; the area index values ​​include the seepage area S1, the area of ​​coarse aggregate not covered by mortar S2, the non-seepage area S3, and the area of ​​central aggregate S4; the volume index values ​​include the total volume of coarse aggregate V1, the volume of coarse aggregate not covered by mortar V2, the volume of the leaked part of coarse aggregate not covered by mortar V3, the volume of seepage water V6, the volume of central aggregate V7, the total volume of fresh self-compacting concrete V4, the volume of mortar in fresh self-compacting concrete V5, and the water equivalent volume V8; A derived index determination unit is used to determine the derived index value of the anti-segregation performance of the fresh self-compacting concrete according to the basic index value; wherein the derived index value includes: water seepage index, mortar coating coarse aggregate index, and intermediate stone accumulation index; wherein, in the derived index value, the derived index value is determined by using or Characterize the degree of bleeding of fresh self-compacting concrete; or Characterize the degree of mortar encapsulation of coarse aggregate; or Characterize the degree of intermediate stone accumulation; use or Characterize the degree of mortar encapsulation of coarse aggregate; or Characterize the degree of mortar encapsulation of coarse aggregate; or or Characterize the degree of bleeding of fresh self-compacting concrete; or Characterize the degree of intermediate stone accumulation; use or Characterizes the degree of mortar encapsulation of coarse aggregate; among them, D 11 , D 21 They represent the maximum diameter of the area containing bleeding water and the minimum diameter of the area containing bleeding water respectively; The segregation performance analysis unit is used to analyze the anti-segregation performance of the fresh self-compacting concrete according to the derived index value and a preset analysis threshold value of the anti-segregation performance of the fresh self-compacting concrete.

8. The device for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 7, characterized in that: The basic indicator determination unit includes: The cake index acquisition module is used to obtain the maximum cake diameter, the minimum cake diameter and the maximum cake height of the slump spread cake; wherein the maximum cake diameter includes the maximum diameter of the water-containing area and the maximum diameter of the non-water-containing area; the minimum cake diameter includes the minimum diameter of the water-containing area and the minimum diameter of the non-water-containing area; The aggregate index acquisition module is used to obtain the maximum diameter of the central aggregate, the minimum diameter of the central aggregate and the maximum height of the central aggregate of the slump spread cake.

9. The device for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 7, characterized in that: The basic indicator determination unit includes: A correction module, used for correcting the image corresponding to the slump spread cake to obtain a front view thereof; An area drawing module, used for drawing the area boundaries corresponding to each area index in the area index value in the front view to obtain each area region; The summing module is used to sum the areas in each of the area regions to obtain the area index values ​​corresponding to the slump spread cake.

10. The device for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 9, characterized in that: The area drawing module is specifically used to perform image semantic segmentation using a pre-trained image semantic segmentation machine learning model to obtain area boundaries corresponding to each area indicator in the area indicator value.

11. The device for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 10, characterized in that: Also includes: A training correction unit, used for correcting the training image corresponding to the slump spread cake to obtain a training front view; A data labeling unit, used for labeling the training front view to obtain label data; The model generation unit is used to input the data training set consisting of the training front view and the label data into the machine learning original model for training to obtain the image semantic segmentation machine learning model.

12. The device for analyzing the anti-segregation performance of fresh self-compacting concrete according to claim 7, characterized in that: The basic indicator determination unit includes: A first volume determination module, configured to determine the total volume of the coarse aggregate according to the total mass and density of the coarse aggregate in the fresh self-compacting concrete; A second volume determination module, configured to determine the volume of the coarse aggregate not wrapped by the mortar according to the mass of the coarse aggregate not wrapped by the mortar in the fresh self-compacting concrete and the density; The third volume determination module is used to determine the volume of the leaked part of the coarse aggregate not wrapped by the mortar, the volume of the bleeding water body and the volume of the central aggregate by using the semantic three-dimensional reconstruction method; a fourth volume determination module, configured to determine the total volume of the fresh self-compacting concrete and the volume of mortar in the fresh self-compacting concrete; The fifth volume determination module is used to determine the water equivalent volume according to the concrete mix ratio and the total volume of the fresh self-compacting concrete.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for analyzing the anti-segregation performance of fresh self-compacting concrete according to any one of claims 1 to 6 are implemented.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for analyzing the anti-segregation performance of fresh self-compacting concrete according to any one of claims 1 to 6 are implemented.

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