Intelligent detection method for compactness of ultra-high performance concrete structure

Abstract

The invention relates to an intelligent detection method for the compactness of an ultra-high performance concrete structure, which comprises the following steps: 1, preparing UHPC (Ultra High Performance Concrete), and uniformly cutting the UHPC into n layers in a layered manner; 2, performing image recognition processing on each sub-layer, and determining the porosity of each sub-layer; 3, for the u group of steel fiber UHPC and the p group of polymer fiber UHPC, calculating the porosity average value and the porosity dispersion degree of each sub-layer surface respectively, and calculating the porosity average value and the porosity dispersion degree of the overall structure respectively; 4, on the basis of the UHPC surface layer porosity and the discrete degree data of the UHPC surface layer porosity, a UHPC overall structure porosity average value fitting equation and a UHPC overall structure porosity discrete degree fitting equation of u groups of steel fiber UHPC and p groups of polymer fiber UHPC are obtained respectively; 5, in combination with the fitting equation, establishing a UHPC structure compactness judgment rule; and 6, intelligent detection of the compactness of the UHPC overall structure is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of building construction, and particularly relates to an intelligent detection method for the density of ultra-high performance concrete structures. Background Art

[0002] Ultra-high performance concrete (UHPC) has been increasingly widely used in many fields such as municipal engineering, architecture, and wind power due to its excellent workability, mechanical properties, and durability. Traditional methods for detecting the density of ultra-high performance concrete mainly include ultrasonic detection method, core drilling method, etc.

[0003] The ultrasonic detection method mainly uses the propagation characteristics of ultrasonic waves in concrete to evaluate the density, which has the characteristics of non-destructive testing, but has the following deficiencies: 1) It relies on a large number of measurement points and multiple repeated operations because this method only measures the density within the axial range between two measurement points each time and has certain requirements for the surface state of the concrete, and it is impossible to quickly and effectively identify the overall density of the concrete; 2) It has high requirements for testing equipment and operators, with large human operation errors and large discreteness of test results.

[0004] The core drilling method detects whether there are defects such as air holes and cracks inside the concrete by drilling concrete core samples, but has the following deficiencies: 1) It belongs to random sampling detection, with large detection randomness and insufficient representativeness, and it is impossible to reflect the overall density state of the concrete; 2) It belongs to destructive testing, which will cause local damage to the structure and will affect the structural safety to a certain extent.

[0005] Therefore, how to provide an intelligent detection method for the density of ultra-high performance concrete structures is a technical problem that needs to be urgently solved by those skilled in the art. Summary of the Invention

[0006] In view of the problems that traditional methods for detecting the density of ultra-high performance concrete are either destructive testing or have low accuracy of test results, the present invention proposes an intelligent detection method for the density of ultra-high performance concrete structures.

[0007] To solve the above technical problems, the present invention includes the following technical solutions: An intelligent detection method for the density of ultra-high performance concrete structures, comprising the following steps: Step S1, prepare UHPC components with different strength grades under the same mixing ratio conditions corresponding to the actual project, and the structural dimensions of all components are kept the same, wherein, it includes u-group steel fiber UHPC and p-group polymer fiber UHPC; Step S2, evenly cut and layer the structure of each UHPC component; Step S3: Use a high-resolution industrial camera to take pictures of the split surfaces after each UHPC component is cut and layered, obtaining images of each split surface to ensure that the images are clear and have sufficient details; Step S4: Use image recognition software to process the images of each split surface, identify the pore regions, and calculate the porosity of each split surface of the steel fiber and polymer fiber UHPC structures, denoted as N and M respectively; Step S5: Denote the average porosity of each split surface of the UHPC structure as K, where the steel fiber UHPC corresponds to Ku and the polymer fiber UHPC corresponds to Kp; Denote the degree of dispersion of the porosity of each split surface of the UHPC structure as R, characterized by the standard deviation formula, where the steel fiber UHPC corresponds to Ru and the polymer fiber UHPC corresponds to Rp; Step S6: For the u groups of steel fiber UHPC, calculate the average porosity Ku1, Ku2,..., Kun of each split surface from layer 1 to layer n, and the degree of dispersion Ru1, Ru2,..., Run of the porosity of each split surface from layer 1 to layer n; For the p groups of polymer fiber UHPC, calculate the average porosity Kp1, Kp2,..., Kpn of each split surface from layer 1 to layer n, and the degree of dispersion Rp1, Rp2,..., Rpn of the porosity of each split surface from layer 1 to layer n; Step S7: Denote the average porosity of the overall UHPC structure as , where the steel fiber UHPC corresponds to , and the polymer fiber UHPC corresponds to ; Denote the degree of dispersion of the porosity of the overall UHPC structure as , where the steel fiber UHPC corresponds to , and the polymer fiber UHPC corresponds to ; Step S8: Respectively obtain the fitting equations for the average porosity and the degree of dispersion of the overall UHPC structure through Matlab equation fitting, and according to the probability statistics theory, take the confidence level as 90%, and obtain the corresponding Z-score value of 1.645 from the Z-table to establish the determination rule for the compactness of the UHPC structure: 1) When , it indicates that the UHPC structure is compact; 2) When , it indicates that the UHPC structure is relatively compact; 3) When , it indicates that the UHPC structure is not compact.

[0008] Furthermore, the step S4 includes: Denote the porosity of each split surface of the first group of steel fiber UHPC structures as N 11 , N 12 , N 13 …, N 1n ; The porosity of each split surface of the second group of steel fiber UHPC structures is N21 , N 22 , N 23 …, N 2n ; And so on, the porosity of each sub - layer of the u - th group of steel fiber UHPC structure is N u1 , N u2 , N u3 …, N un ; Similarly, denote the porosity of each sub - layer of the first group of polymer fiber UHPC structure as M 11 , M 12 , M 13 …, M 1n ; The porosity of each sub - layer of the second group of polymer fiber UHPC structure is M 21 , M 22 , M 23 …, M 2n ; And so on, the porosity of each sub - layer of the p - th group of polymer fiber UHPC structure is M p1 , M p2 , M p3 …, M pn .

[0009] Furthermore, the step S6 includes: For the u - group of steel fiber UHPC, the average porosity of the first layer is denoted as K u1 =(N 11 +N 21 +…+N u1 )÷u, and the dispersion degree of the porosity of the first layer is denoted as R u1 = ; For the p - group of polymer fiber UHPC, the average porosity of the first layer is denoted as K p1 =(M 11 +M 21 +…+M p1 )÷p, and the dispersion degree of the porosity of the first layer is denoted as R p1 = ; For the u - group of steel fiber UHPC, the average porosity of the second layer is denoted as K u2 =(N 12 +N 22 +…+N u2 )÷u, and the dispersion degree of the porosity of the second layer is denoted as R u2 = ; For the p - group of polymer fiber UHPC, the average porosity of the second layer is denoted as K p2 =(M 12 +M 22 +…+Mp2 )÷p, the porosity dispersion degree of the second layer is denoted as R p2 = ; For u groups of steel fiber UHPC, the average porosity of the nth layer is denoted as Kun = (N 1n + N 2n + … + N un )÷u, the porosity dispersion degree of the nth layer is denoted as ; For p groups of polymer fiber UHPC, the average porosity of the nth layer is denoted as K pn = (M 1n + M 2n + … + M pn )÷p, the porosity dispersion degree of the nth layer is denoted as .

[0010] Furthermore, the step S8 includes: For u groups of steel fiber UHPC, the average porosity of the overall structure of UHPC from the 1st to the nth layer , the porosity dispersion degree of the overall structure of UHPC from the 1st to the nth layer ; For p groups of polymer fiber UHPC, the average porosity of the overall structure of UHPC from the 1st to the nth layer , the porosity dispersion degree of the overall structure of UHPC from the 1st to the nth layer ; For u groups of steel fiber UHPC, obtained by fitting with Matlab equations, the fitting equation of the average porosity of the overall structure of UHPC from the 1st to the nth layer and the average porosity of the surface layer is denoted as: ; The fitting equation of the porosity dispersion degree of the overall structure of UHPC from the 1st to the nth layer and the porosity dispersion degree of the surface layer is denoted as: ; For p groups of polymer fiber UHPC, obtained by fitting with Matlab equations, the fitting equation of the average porosity of the overall structure of UHPC from the 1st to the nth layer and the average porosity of the surface layer is denoted as: = ; The fitting equation of the porosity dispersion degree of the overall structure of UHPC from the 1st to the nth layer and the porosity dispersion degree of the first layer (surface layer) is denoted as: = .

[0011] Furthermore, for different types of UHPC structures, by using image recognition or other related technologies to obtain the basic data of the porosity of the surface layer of the UHPC structure, the average value and the degree of dispersion of the porosity of the overall UHPC structure can be accurately calculated. Combining with the determination rule of the compactness of the UHPC structure, the non-destructive determination of the compactness of the overall UHPC structure can be realized.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides an intelligent detection method for the compactness of ultra-high performance concrete structures, including: First, preparing an ultra-high performance concrete (UHPC) structure and uniformly cutting the UHPC structure into n layers; Second, performing image recognition processing on each sub-layer surface of each structure to determine the porosity of each sub-layer surface; Third, denoting the average value of the porosity of each sub-layer surface of the UHPC structure as K and the degree of dispersion of the porosity of each sub-layer surface as R; Fourth, for u groups of steel fiber UHPC, calculating K u1 , K u2 , …, K un and R u1 , R u2 , …, R un ; for p groups of polymer fiber UHPC, calculating K p1 , K p2 , …, K pn and R p1 , R p2 , …, R pn ; Fifth, denoting the average value of the porosity of the overall UHPC structure as , and the degree of dispersion of the porosity of the overall structure as ; Sixth, for u groups of steel fiber UHPC, calculating and ; for p groups of polymer fiber UHPC, calculating and ; Seventh, for u groups of steel fiber UHPC, the fitting equation for the average value of the porosity of the overall UHPC structure is , and the fitting equation for the degree of dispersion of the porosity of the overall UHPC structure is , for p groups of polymer fiber UHPC, the fitting equation for the average value of the porosity of the overall UHPC structure is ; the fitting equation for the degree of dispersion of the porosity of the overall UHPC structure is ; VIII. Combine the above fitting equations to establish a judgment rule for the compactness of the UHPC structure; IX. Realize the intelligent detection of the compactness of the overall UHPC structure. The intelligent detection method for the compactness of the ultra-high performance concrete structure of the present invention establishes fitting equations for the average porosity and its dispersion degree of different types of overall UHPC structures. At the same time, a judgment rule for the compactness of the UHPC structure is also established. Based on this, for different types of UHPC structures, technicians only need to use image recognition or related technologies to obtain the basic data of the porosity of the UHPC structure surface layer, and then can accurately calculate the average porosity and its dispersion degree of the overall UHPC structure, and realize the intelligent, efficient, accurate and non-destructive judgment of the compactness of the overall UHPC structure, meeting the urgent needs of engineering practice for the quality control of concrete structures and helping the high-quality development of the industry. The application of the technical method of the present invention can not only greatly improve the accuracy and reliability of the detection of the compactness of concrete structures, ensure the safety of concrete structures, but also has a simple and easy operation process, low detection cost, high degree of digitization and intelligence, and wide applicability. Therefore, it has a broad market promotion and application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic flow chart of the intelligent detection method for the compactness of the ultra-high performance concrete structure in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] The following further details a kind of intelligent detection method for the compactness of the ultra-high performance concrete structure provided by the present invention in conjunction with the drawings and specific embodiments. According to the following description, the advantages and features of the present invention will be clearer.

[0015] Embodiment 1 The following combines Figure 1 to detail the intelligent detection method for the compactness of the ultra-high performance concrete structure of the present invention.

[0016] An intelligent detection method for the compactness of the ultra-high performance concrete structure includes the following steps: Step S1: Prepare UHPC components with different strength grades under the same mixing ratio conditions corresponding to the actual project. The structural sizes of all components are kept the same, including u groups of steel fiber UHPC and p groups of polymer fiber UHPC. Specifically, for different strength grades (such as 120 - 140 MPa) of ultra-high performance concrete (UHPC) structures, there are w groups (w = u + p), among which, u groups (such as 30 - 50 groups) of steel fiber UHPC are prepared, and p groups (such as 30 - 50 groups) of polymer fiber UHPC are prepared; the structural sizes of all are kept the same, for example, they are all cuboid structures of 100 mm × 100 mm × 400 mm or cube structures of 150 mm × 150 mm × 150 mm.

[0017] Step S2: Uniformly cut and layer the structure of each UHPC component, specifically: divide the overall structure into the first layer (surface layer), the second layer (cutting layer), the third layer (cutting layer), …, the nth layer (cutting layer); Step S3: Use a high-resolution industrial camera to photograph the divided surfaces of each UHPC component after cutting and layering to obtain images of each divided surface, ensuring that the images are clear and have sufficient details; Step S4: Use image recognition software to process the images of each divided surface, identify the pore regions and calculate the porosity of each divided surface of the steel fiber and polymer fiber UHPC structures, denoted as N and M respectively; Step S5: Denote the average porosity of each divided surface of the UHPC structure as K, where Ku corresponds to steel fiber UHPC and Kp corresponds to polymer fiber UHPC; Denote the degree of dispersion of the porosity of each divided surface of the UHPC structure as R, characterized by the standard deviation formula, where Ru corresponds to steel fiber UHPC and Rp corresponds to polymer fiber UHPC; Step S6: For u groups of steel fiber UHPC, calculate the average porosity Ku1, Ku2, …, Kun of each divided surface from the 1st to the nth layer, and the degree of dispersion Ru1, Ru2, …, Run of the porosity of each divided surface from the 1st to the nth layer; For p groups of polymer fiber UHPC, calculate the average porosity Kp1, Kp2, …, Kpn of each divided surface from the 1st to the nth layer, and the degree of dispersion Rp1, Rp2, …, Rpn of the porosity of each divided surface from the 1st to the nth layer; Step S7: Denote the average porosity of the overall UHPC structure as , where it corresponds to steel fiber UHPC as , and it corresponds to polymer fiber UHPC as ; Denote the degree of dispersion of the porosity of the overall UHPC structure as , where it corresponds to steel fiber UHPC as , and it corresponds to polymer fiber UHPC as ; Step S8: Respectively obtain the fitting equations of the average porosity and the fitting equation of the degree of dispersion of the overall UHPC structure through Matlab equation fitting, and according to the probability statistics theory, take the confidence level as 90%, obtain the corresponding Z-score value of 1.645 from the Z-table, and establish the UHPC structure density determination rule: 1) When , it indicates that the UHPC structure is dense; 2) When , it indicates that the UHPC structure is relatively dense; 3) When , it indicates that the UHPC structure is not dense.

[0018] In this embodiment, more preferably, step S4 includes: Denote the porosity of each sub-layer of the first group of steel fiber UHPC structures as N 11 , N 12 , N 13 …, N 1n ; Denote the porosity of each sub-layer of the second group of steel fiber UHPC structures as N 21 , N 22 , N 23 …, N 2n ; And so on, denote the porosity of each sub-layer of the u-th group of steel fiber UHPC structures as N u1 , N u2 , N u3 …, N un ; Similarly, denote the porosity of each sub-layer of the first group of polymer fiber UHPC structures as M 11 , M 12 , M 13 …, M 1n ; Denote the porosity of each sub-layer of the second group of polymer fiber UHPC structures as M 21 , M 22 , M 23 …, M 2n ; And so on, denote the porosity of each sub-layer of the p-th group of polymer fiber UHPC structures as M p1 , M p2 , M p3 …, M pn .

[0019] In this embodiment, more preferably, step S6 includes: For the u groups of steel fiber UHPC, denote the average porosity of the first layer as K u1 = (N 11 + N 21 + … + N u1 ) ÷ u, and denote the dispersion degree of the porosity of the first layer as R u1 = ; For the p groups of polymer fiber UHPC, denote the average porosity of the first layer as K p1 = (M 11 + M 21 + … + M p1 ) ÷ p, and denote the dispersion degree of the porosity of the first layer as R p1 = ; For the u groups of steel fiber UHPC, denote the average porosity of the second layer as K u2 = (N 12 + N 22 + … + N u2( )÷u, the porosity dispersion degree of the second layer is denoted as R u2 = ; For p groups of polymer fiber UHPC, the average porosity of the second layer is denoted as K p2 =(M 12 +M 22 +…+M p2 )÷p, the porosity dispersion degree of the second layer is denoted as R p2 = ; For u groups of steel fiber UHPC, the average porosity of the nth layer is denoted as Kun=(N 1n +N 2n +…+N un )÷u, the porosity dispersion degree of the nth layer is denoted as ; For p groups of polymer fiber UHPC, the average porosity of the nth layer is denoted as K pn =(M 1n +M 2n +…+M pn )÷p, the porosity dispersion degree of the nth layer is denoted as .

[0020] In this embodiment, more preferably, the step S8 includes: For u groups of steel fiber UHPC, the average porosity of the overall structure of UHPC from layer 1 to layer n , the porosity dispersion degree of the overall structure of UHPC from layer 1 to layer n ; For p groups of polymer fiber UHPC, the average porosity of the overall structure of UHPC from layer 1 to layer n , the porosity dispersion degree of the overall structure of UHPC from layer 1 to layer n ; For u groups of steel fiber UHPC, obtained by fitting with Matlab equation, the fitting equation of the average porosity of the overall structure of UHPC from layer 1 to layer n and the average porosity of the surface layer is denoted as: ; The fitting equation of the porosity dispersion degree of the overall structure of UHPC from layer 1 to layer n and the porosity dispersion degree of the surface layer is denoted as: ; For p groups of polymer fiber UHPC, obtained by fitting with Matlab equation, the fitting equation of the average porosity of the overall structure of UHPC from layer 1 to layer n and the average porosity of the surface layer is denoted as: = ; The fitting equation for the porosity dispersion degree of the 1~n layer UHPC overall structure and the porosity dispersion degree of the first layer (surface layer) is denoted as: = 。

[0021] Specifically, the specific coefficients of the above fitting equation are shown in Table 1 and Table 2 below.

[0022] Table 1 Fitting equation for the average porosity of the overall structure of steel fiber and polymer fiber UHPC

[0023] Table 2 Fitting equation for the porosity dispersion degree of the overall structure of steel fiber and polymer fiber UHPC

[0024] In this embodiment, more preferably, for different types of UHPC structures, by using image recognition or other related technologies to obtain the basic data of the porosity of the surface layer of the UHPC structure, the average value of the porosity of the UHPC overall structure and its dispersion degree can be accurately calculated, and combined with the UHPC structure density determination rule, the non-destructive determination of the density of the UHPC overall structure can be realized.

[0025] Specifically, an intelligent detection method for the density of a ultra-high performance concrete structure of the present invention includes: First, prepare a ultra-high performance concrete (UHPC) structure and evenly cut the UHPC structure into n layers; Second, perform image recognition processing on each sub-layer surface of each structure to determine the porosity of each sub-layer surface; Third, record the average value of the porosity of each sub-layer surface of the UHPC structure as K, and the porosity dispersion degree of each sub-layer surface as R; Fourth, for u groups of steel fiber UHPC, calculate K u1 ,K u2 ,…,K un and R u1 ,R u2 ,…,R un ; for p groups of polymer fiber UHPC, calculate K p1 ,K p2 ,…,K pn and R p1 ,R p2 ,…,R pn ; Fifth, record the average value of the porosity of the UHPC overall structure as ,and the porosity dispersion degree of the overall structure as ; Sixth, for u groups of steel fiber UHPC, calculate and ; for p groups of polymer fiber UHPC, calculate and ; VII. For the u-group steel fiber UHPC, the fitting equation for the average porosity of the overall UHPC structure is , and the fitting equation for the dispersion degree of the porosity of the overall UHPC structure is . For the p-group polymer fiber UHPC, the fitting equation for the average porosity of the overall UHPC structure is ; the fitting equation for the dispersion degree of the porosity of the overall UHPC structure is ; VIII. Combining the above fitting equations, a judgment rule for the compactness of the UHPC structure is established; IX. Realize the intelligent detection of the compactness of the overall UHPC structure. The intelligent detection method for the compactness of the ultra-high performance concrete structure of the present invention establishes the fitting equations for the average porosity and its dispersion degree of the overall structure of different types of UHPC. At the same time, a judgment rule for the compactness of the UHPC structure is also established. Based on this, for different types of UHPC structures, technicians only need to obtain the basic data of the porosity of the surface layer of the UHPC structure by using image recognition or related technologies, and then can accurately calculate the average porosity and its dispersion degree of the overall UHPC structure, and realize the intelligent, efficient, accurate and non-destructive judgment of the compactness of the overall UHPC structure, meeting the urgent needs of engineering practice for the quality control of concrete structures and helping the high-quality development of the industry.

[0026] The above examples are the preferred embodiments of the present invention, but the embodiments of the present invention are not limited by the above examples. The above embodiments only represent several embodiments of the present invention, and their descriptions are relatively specific and detailed, but they cannot be construed as limiting the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the invention patent shall be subject to the appended claims.

Claims

1. An intelligent detection method for the compactness of ultra-high performance concrete structures, characterized in that It includes the following steps: Step S1: Prepare UHPC components with different strength grades under the same mixing ratio conditions corresponding to the actual engineering. The structural dimensions of all components are kept the same. Among them, it includes u-group steel fiber UHPC and p-group polymer fiber UHPC; Step S2: Uniformly cut and layer the structure of each UHPC component; Step S3: Use a high-resolution industrial camera to photograph the split surfaces of each UHPC component after cutting and layering to obtain the images of each split surface; Step S4: Use image recognition software to process the images of each split surface, identify the pore regions, and calculate the porosity of each split surface of the steel fiber and polymer fiber UHPC structures, denoted as N and M respectively; Step S5: Denote the average porosity of each split surface of the UHPC structure as K, where the steel fiber UHPC is correspondingly denoted as Ku, and the polymer fiber UHPC is correspondingly denoted as Kp; Denote the degree of dispersion of the porosity of each split surface of the UHPC structure as R, which is characterized by the standard deviation formula, where the steel fiber UHPC is correspondingly denoted as Ru, and the polymer fiber UHPC is correspondingly denoted as Rp; Step S6: For the u-group steel fiber UHPC, calculate the average porosity Ku1, Ku2,..., Kun of each split surface from layer 1 to layer n, and the degree of dispersion Ru1, Ru2,..., Run of the porosity of each split surface from layer 1 to layer n; For the p-group polymer fiber UHPC, calculate the average porosity Kp1, Kp2,..., Kpn of each split surface from layer 1 to layer n, and the degree of dispersion Rp1, Rp2,..., Rpn of the porosity of each split surface from layer 1 to layer n; Step S7: Denote the average porosity of the UHPC overall structure as , where the steel fiber UHPC is correspondingly denoted as , and the polymer fiber UHPC is correspondingly denoted as ; Denote the dispersion degree of the porosity of the UHPC overall structure as , where the steel fiber UHPC is correspondingly denoted as , and the polymer fiber UHPC is correspondingly denoted as ; Step S8: Obtain the fitting equations for the average porosity of the UHPC overall structure and its dispersion degree through Matlab equation fitting respectively. According to the probability statistics theory, with a confidence level of 90%, the corresponding Z - score value of 1.645 is obtained from the Z - table, and the determination rule for the compactness of the UHPC structure is established: 1) When Then it indicates that the UHPC structure is compact; 2) When Then it indicates that the UHPC structure is relatively compact; 3) When Then it indicates that the UHPC structure is not compact.

2. The method according to claim 1, characterized in that The step S4 includes: recording the porosity of each sub-layer of the first group of steel fiber UHPC structures as N 11 , N 12 , N 13 …, N 1n ; the porosity of each sub-layer of the second group of steel fiber UHPC structures as N 21 , N 22 , N 23 …, N 2n ; and so on, the porosity of each sub-layer of the u-th group of steel fiber UHPC structures as N u1 , N u2 , N u3 …, N un ; Similarly, denote the porosity of each sub-layer of the first group of polymer fiber UHPC structure as M 11 , M 12 , M 13 …, M 1n ; denote the porosity of each sub-layer of the second group of polymer fiber UHPC structure as M 21 , M 22 , M 23 …, M 2n ; and so on, denote the porosity of each sub-layer of the p-th group of polymer fiber UHPC structure as M p1 , M p2 , M p3 …, M pn .

3. The method according to claim 1, characterized in that, The said Step S6 includes: For the u-group steel fiber UHPC, denote the average porosity of the first layer as K u1 = (N 11 + N 21 + … + N u1 ) ÷ u, the porosity dispersion degree of the first layer is denoted as R u1 = ; For p groups of polymer fiber UHPC, the average porosity of the first layer is denoted as K p1 = (M 11 + M 21 + … + M p1 ) ÷ p, the porosity dispersion degree of the first layer is denoted as R p1 = ; For u groups of steel fiber UHPC, the average porosity of the second layer is denoted as K u2 = (N 12 + N 22 + … + N u2 ) ÷ u, and the dispersion degree of the porosity of the second layer is denoted as R u2 = ; For p groups of polymer fiber UHPC, the average porosity of the second layer is denoted as K p2 = (M 12 + M 22 + … + M p2 ) ÷ p, and the porosity dispersion degree of the second layer is denoted as R p2 = ; For the u-group steel fiber UHPC, denote the average porosity of the nth layer as Kun = (N 1n + N 2n + … + N un ) ÷ u, and the porosity dispersion degree of the nth layer is denoted as ; For p groups of polymer fiber UHPC, the average porosity of the nth layer is denoted as K pn = (M 1n + M 2n + … + M pn ) ÷ p, and the degree of dispersion of the porosity of the nth layer is denoted as 。 4. The method according to claim 1, characterized in that The said Step S8 includes: For the u-group steel fiber UHPC, the average porosity of the overall structure of the UHPC in layers 1 to n , the degree of dispersion of the porosity of the overall structure of the UHPC in layers 1 to n ; for the p-group polymer fiber UHPC, the average porosity of the overall structure of the UHPC in layers 1 to n , the degree of dispersion of the porosity of the overall structure of the UHPC in layers 1 to n ; For the u-group steel fiber UHPC, obtain the fitting equation of the average porosity of the overall UHPC structure from layer 1 to layer n and the average porosity of the surface layer through Matlab equation fitting, denoted as: ； The fitting equation of the degree of dispersion of the porosity of the overall UHPC structure from layer 1 to layer n and the degree of dispersion of the porosity of the surface layer, denoted as: ； For p groups of polymer fiber UHPC, the fitting equation of the average porosity of the overall structure of UHPC from layer 1 to layer n and the average porosity of the surface layer is obtained by Matlab equation fitting, denoted as: = ; The fitting equation of the degree of dispersion of the porosity of the overall UHPC structure from layer 1 to layer n and the degree of dispersion of the porosity of the first layer (surface layer), denoted as: = 。 5. The method according to claim 1, wherein For different types of UHPC structures, by using image recognition or other related technologies to obtain the basic data of the surface layer porosity of the UHPC structure, the average value and the degree of dispersion of the porosity of the overall UHPC structure can be accurately calculated, and combined with the UHPC structure density determination rule, the non-destructive determination of the density of the overall UHPC structure can be realized.

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