Method for measuring compressive strength of vibratory stirring high-strength concrete based on rebound apparatus

Abstract

Compared with the prior art, the method for measuring the compressive strength of the vibration stirring high-strength concrete based on the rebound apparatus has the advantages that the compressive strength of the vibration stirring high-strength concrete is measured by combining the rebound apparatus measurement and the heat source test; and accurate prediction of the compressive strength of the vibratory stirring high-strength concrete is realized. Compared with the prior art, the device and the method have the advantages that the concrete strength can be non-destructively and quickly measured, and the device and the method can adapt to concrete parts with different raw material ratios and thicknesses.

Description

Technical Field

[0001] The invention relates to the technical field of concrete strength testing, and in particular to a method for measuring the compressive strength of vibration-mixed high-strength concrete based on a rebound hammer. Background Art

[0002] On-site testing of concrete strength includes core drilling method, pull-out method, indentation method, shooting method, rebound method, ultrasonic method, rebound ultrasonic comprehensive method, ultrasonic attenuation comprehensive method, ray method, falling ball method, etc. Among them, the rebound method has become the most widely used method for on-site concrete strength testing due to its mature technology, simple operation, fast detection and no damage to the structure, especially in highway construction projects. However, the rebound method is currently mainly applicable to concrete strength testing below 50MPa. Due to the limited scope of application of medium-sized rebound testers, the relative error of rebound data in the detection of high-strength concrete in the range of 50.0-60.0MPa is large, which is difficult to meet actual needs. In addition, vibration mixing technology has shown significant performance in improving concrete strength, and the compressive strength can be increased by about 10% under the same mix conditions. Therefore, the ordinary strength measurement curve relied on by the traditional rebound method can no longer meet the requirements of high-strength concrete detection after the optimization of vibration mixing technology.

[0003] The experimental team has been browsing and studying a large number of relevant records and materials on the relevant technologies of vibration mixing high-strength concrete detection for a long time. At the same time, relying on relevant resources and conducting a large number of relevant experiments, after a large number of searches, it was found that there are existing technologies such as CN116539463B, CN103792120B, CN112082873B, and CN116539463B disclosed in the prior art. For example, a concrete strength detection method disclosed in the prior art includes: step S1, strength rebound tester for each test point on the concrete Strength is tested; step S2, the heavy hammer in the strength rebound tester hits each of the test points in turn and records the rebound distance of the heavy hammer after hitting each test point; step S3, calculates multiple variances for the test points to determine whether to replace the spring with a corresponding elastic coefficient for driving the heavy hammer; step S4, when the strength of the test point does not meet the preset standard, determines whether to correct the preset rebound distance or reselect the test point according to the measured average rebound distance for the test point; step S5, outputs the test result for the concrete strength.

[0004] Existing concrete strength testing technology faces many limitations: the concrete materials currently used are significantly different from the representative materials used when the unified strength curve was formulated ten years ago, resulting in a significant reduction in the reference value of the strength curve, making it difficult to accurately reflect the actual strength of the project. The existing rebound method is mainly applicable to concrete with a strength below 50MPa, while in high-strength concrete in the range of 50.0 to 60.0MPa, due to the limited application range of the medium-sized rebound tester, the relative error of the test data is large and cannot meet the accuracy requirements of high-strength concrete.

[0005] In order to solve the common problems in this field, the present invention proposes a method for estimating the actual strength of vibration-mixed high-strength concrete based on a rebound hammer. Through the exclusive strength measurement curve of vibration-mixed high-strength concrete, the detection accuracy is significantly improved, so that it is adapted to the characteristics of current materials and vibration-mixed high-strength concrete, and meets the actual engineering needs of high-strength concrete, thus making the present invention. Summary of the invention

[0006] The purpose of the present invention is to propose a method for measuring the compressive strength of vibration-mixed high-strength concrete based on a rebound hammer in view of the shortcomings existing in the current field.

[0007] In order to overcome the shortcomings of the prior art, the present invention adopts the following technical solutions:

[0008] A method for measuring the compressive strength of high-strength concrete by vibration stirring based on a rebound tester, the method comprising the following steps:

[0009] S101: pouring vibrating high-strength concrete of target mix ratio to obtain m standard cube-shaped specimens, where m∈{1,2,3…10};

[0010] S102: Apply constant load to each specimen in turn to measure the rebound strength and collect the average rebound value Rm of each specimen i ;

[0011] S103: Perform uniaxial compression tests on each specimen in turn to obtain the compressive strength fa of each specimen i ;

[0012] S104: Obtain the average rebound value Rm of each specimen i and compressive strength fa i After that, the average rebound value Rm of the specimen i and compressive strength fa i The Allometric function is fitted based on the change of , so as to obtain the preliminary compressive strength prediction formula of high-strength concrete under vibration mixing, and the preliminary predicted strength of the actual test piece is obtained through the preliminary compressive strength prediction formula:

[0013] f ex1 =a×R b Among them, f ex1 is the preliminary predicted strength of the actual sample, a is the first parameter obtained by fitting, b is the second parameter obtained by fitting, and R is the rebound strength measurement value obtained by a single test of the actual test piece through the rebound device, and the actual test sample at least includes walls, beams, columns and slabs made of vibration-mixed high-strength concrete with different mix ratios;

[0014] S105: performing a heat source test on the actual test piece to obtain an internal density distribution parameter PDI of the test piece;

[0015] S106: Further calculate and obtain the final predicted strength value f of the vibration-mixed high-strength concrete corresponding to the actual test piece ex2 .

[0016] Furthermore, the method for obtaining the standard cube-shaped specimen in step S101 is: pouring the target mix of vibrating high-strength concrete in a volume of 150 mm × 150 mm × 150 mm, and curing the poured specimen in a concrete room at a temperature of 18-22° C. and a relative humidity of 95% for 28 days.

[0017] Furthermore, the specific steps of applying a constant load to each test piece in turn to measure the rebound strength in step S102 include:

[0018] S1021: Support the bottom surface of the specimen and apply a 30kN constant load to the top surface of the specimen;

[0019] S1022: Select N measurement areas on the outer surface of each specimen, and N ≥ 5. Divide the matrix on each measurement area into 16 measurement points, where the area of ​​each measurement area does not exceed 0.04 square meters, the spacing between adjacent measurement areas does not exceed 2 meters, the distance between the measurement area and the edge of the specimen or the construction joint should be maintained at 0.2 meters to 0.5 meters, and the spacing between the measurement points in the same measurement area is uniform to ensure that the measurement points cover different positions of the measurement area. The surface of the measurement area should be the original concrete slurry surface, and the measurement areas should be evenly arranged on the four sides of the specimen;

[0020] S1023: Use a rebound hammer to measure the rebound strength at 16 measuring points in each measuring area in turn. Keep the rebound hammer perpendicular to the surface of the measuring point during measurement, and record the rebound strength value of each measuring point.

[0021] S1024: Data cleaning is performed on the rebound strength values ​​of the 16 measuring points in the same measuring area, and the 3 maximum and 3 minimum rebound strength values ​​of the 16 measuring points are eliminated. The mean rebound strength value VN of the 10 measuring points after data cleaning in the same measuring area is calculated to eliminate the influence of abnormal data. The middle 10 rebound strength values ​​in the measuring area are retained, and the average rebound value Rm of the vibration-mixed high-strength concrete is calculated. i :

[0022]

[0023] Among them, VN i，j is the VN value of the jth measurement area of ​​the i-th specimen, i∈{1,2,3…m},j∈

[0024] {1,2,3…N},Rm i The calculation is accurate to 0.1, Rm i is the average rebound value of the i-th specimen.

[0025] Furthermore, in step S103, the specific steps of performing uniaxial compression tests on each specimen in turn to obtain the compressive strength fa of the specimen are as follows:

[0026] S1031: Use a compression testing machine to perform uniaxial compression tests on each specimen in turn;

[0027] S1032: The compression tester applies pressure to the specimen at a constant loading rate until the specimen breaks;

[0028] S1033: Record the maximum stress fa applied by the compression testing machine to the specimen displayed on the display screen of the compression testing machine when the specimen ruptures, and record the maximum stress fa applied by the compression testing machine to the specimen in terms of fa i It is expressed as the maximum stress value of the i-th specimen.

[0029] Furthermore, the specific implementation steps of step S104 are as follows:

[0030] S1041: Collect the average rebound value Rm of each specimen i and compressive strength fa i data,

[0031] S1042: Collect the data in Rm i is the horizontal axis, fa i As the vertical axis, draw a scatter plot to show the relationship between rebound strength and compressive strength.

[0032] S1043: Select Allometric function fa=a×R m b As a fitting model, a nonlinear regression method is used to fit the data in the scatter plot to solve the first parameter a and the second parameter b in the model parameters.

[0033] S1044: Determine the initial compressive strength prediction formula for high-strength concrete under vibration mixing:

[0034] f ex1 =a×R b , where f ex1 is the preliminary predicted strength of the actual sample, a is the first parameter obtained by fitting, b is the second parameter obtained by fitting, and R is the rebound strength measurement value of the vibration-mixed high-strength concrete obtained by the rebound device test.

[0035] Furthermore, the specific steps for implementing step S105 are as follows:

[0036] S1051: Using two oppositely disposed side surfaces of the actual test piece as the first test surface and the second test surface respectively, evenly arranging a number of L×D electric heating plates on the first test surface of the actual test piece, where L and D are the number of rows and columns of the electric heating plates arranged in a matrix, respectively. The electric heating plates are arranged in a matrix to form a uniform heating grid to ensure that the first test surface of the actual test piece is evenly heated, starting the electric heating plates, and setting the heating temperature Yb of the heating plates.

[0037] S1052: A plurality of temperature sensors are arranged in a matrix on the second test surface of the actual test piece. The matrix distribution of the temperature sensors on the second test surface corresponds to the matrix distribution of the electric heating plates on the first test surface, ensuring that each temperature sensor is in the same position as the corresponding electric heating plate.

[0038] S1053: Maintaining a constant heating temperature Yb of the electric heating plate on the first test surface of the actual test piece, and recording the temperature values ​​monitored by each temperature sensor at each time.

[0039] S1054: When the temperature sensor detects When the temperature is 0, the heating time of the electric heater is recorded as the reference time of the temperature sensor, and the reference time at the matrix coordinate position (x, y) is represented as Tb (x，y) , x∈{1, 2, 3…L}, y∈{1, 2, 3…D},

[0040] S1055: Calculate the reference time average VT of the temperature sensor:

[0041]

[0042] S1056: Calculate the reference time distribution difference of the temperature sensor б:

[0043]

[0044] S1057: Obtain the internal density distribution parameter PDI of the actual test piece:

[0045]

[0046] c1 is the control parameter used to normalize VT, λ is the weight used to adjust the influence of б on PDI, max Tb(x，y) is the maximum reference time of all temperature sensors, min Tb(x，y) is the minimum reference time among all temperature sensors, and c2 is the correction coefficient used to adjust the maximum reference time difference.

[0047] The specific implementation steps of step S106 are as follows:

[0048]

[0049] Wherein, PDI is the PDI value of the actual test piece obtained through a heat source test on the actual test piece, M is the thickness between the first test surface and the second test surface of the actual test piece, Mr is a thickness reference value used to reflect the thickness of the actual test piece, μ1 is a first strength correction coefficient related to the internal density distribution of the test piece, μ2 is a second strength correction coefficient related to the thickness of the test piece, and e is a natural base.

[0050] The beneficial effects achieved by the present invention are:

[0051] 1. Non-destructive testing, reducing material waste and construction interference: The present invention combines heat source testing with a rebound tester to non-destructively detect the internal density distribution of concrete, thereby effectively evaluating its strength. This method does not cause any damage to the concrete specimen, avoids the problem of cutting or destroying the specimen in traditional testing, and greatly reduces material waste and interference in the construction process.

[0052] 2. Efficient and real-time prediction of concrete strength: Combining the rebound value, internal density distribution PDI and thickness correction, the present invention provides a method for quickly and accurately predicting concrete strength. By acquiring relevant data in real time, the compressive strength of concrete can be quickly determined, reducing the bottleneck of long waiting time for strength test results in traditional test methods, and is suitable for real-time monitoring and quality assessment of construction sites.

[0053] 3. Wide application scope and enhanced concrete quality control capability: The present invention is not only applicable to walls, beams, columns and slabs made of vibrating high-strength concrete with different proportions and thicknesses, but can also provide accurate strength predictions based on actual test pieces of different thicknesses. Through machine learning optimization model, the prediction accuracy is higher, and it can adapt to various complex construction environments and structural forms, thus enhancing the ability of engineering quality control. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0055] Figure 1 The present invention is a schematic flow chart of a method for measuring the compressive strength of high-strength concrete by vibration stirring based on a rebound tester.

[0056] Figure 2 It is a scatter diagram of the test piece of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention is further described in detail in combination with its embodiments below; it should be pointed out that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present case. For those skilled in the art, after reviewing the following detailed description, other systems, methods and / or features of this embodiment will become apparent. And the terms describing the positional relationship in the accompanying drawings are only used for illustrative purposes and cannot be understood as limitations on this patent. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to the specific circumstances.

[0058] Embodiment 1: Combining with the attached Figure 1 and attached Figure 2 This embodiment constructs a method for measuring the compressive strength of high-strength concrete by vibration stirring based on a rebound tester. The method for measuring the compressive strength of high-strength concrete by vibration stirring based on a rebound tester comprises the following steps:

[0059] S101: pouring vibrating high-strength concrete of target proportion to obtain m standard cube-shaped specimens,

[0060] where m∈{1,2,3…10};

[0061] S102: Apply constant load to each specimen in turn to measure the rebound strength and collect the average rebound value Rm of each specimen i ;

[0062] S103: Perform uniaxial compression tests on each specimen in turn to obtain the compressive strength fa of each specimen i ;

[0063] S104: Obtain the average rebound value Rm of each specimen i and compressive strength fa i After that, the average rebound value Rm of the specimen i and compressive strength fa iThe Allometric function is fitted based on the change of , so as to obtain the preliminary compressive strength prediction formula of high-strength concrete under vibration mixing, and the preliminary predicted strength of the actual test piece is obtained through the preliminary compressive strength prediction formula:

[0064] f ex1 =a×R b , where f ex1 is the preliminary predicted strength of the actual sample, a is the first parameter obtained by fitting, b is the second parameter obtained by fitting, and R is the rebound strength measurement value obtained by a single test of the actual test piece through the rebound device, and the actual test sample at least includes walls, beams, columns and slabs made of vibration-mixed high-strength concrete with different mix ratios;

[0065] S105: performing a heat source test on the actual test piece to obtain an internal density distribution parameter PDI of the test piece;

[0066] S106: Further calculate and obtain the final predicted strength value f of the vibration-mixed high-strength concrete corresponding to the actual test piece ex2 .

[0067] The method for obtaining the standard cube-shaped test piece in step S101 is: pouring the target mix of vibrating high-strength concrete in a volume of 150 mm×150 mm×150 mm, and curing the poured test piece in a concrete room at a temperature of 18-22° C. and a relative humidity of 95% for 28 days.

[0068] The specific steps of applying a constant load to each test piece in turn to measure the rebound strength in step S102 include:

[0069] S1021: Support the bottom surface of the specimen and apply a 30kN constant load to the top surface of the specimen;

[0070] S1022: Select N measurement areas on the outer surface of each specimen, and N ≥ 5. Divide the matrix on each measurement area into 16 measurement points, where the area of ​​each measurement area does not exceed 0.04 square meters, the spacing between adjacent measurement areas does not exceed 2 meters, the distance between the measurement area and the edge of the specimen or the construction joint should be maintained at 0.2 meters to 0.5 meters, and the spacing between the measurement points in the same measurement area is uniform to ensure that the measurement points cover different positions of the measurement area. The surface of the measurement area should be the original concrete slurry surface, and the measurement areas should be evenly arranged on the four sides of the specimen;

[0071] S1023: Use a rebound hammer to measure the rebound strength at 16 measuring points in each measuring area in turn. Keep the rebound hammer perpendicular to the surface of the measuring point during measurement, and record the rebound strength value of each measuring point.

[0072] S1024: Data cleaning is performed on the rebound strength values ​​of the 16 measuring points in the same measuring area, and the 3 maximum and 3 minimum rebound strength values ​​of the 16 measuring points are eliminated. The mean rebound strength value VN of the 10 measuring points after data cleaning in the same measuring area is calculated to eliminate the influence of abnormal data. The middle 10 rebound strength values ​​in the measuring area are retained, and the average rebound value Rm of the vibration-mixed high-strength concrete is calculated. i :

[0073]

[0074] Among them, VN i，j is the VN value of the jth measurement area of ​​the i-th specimen, i∈{1,2,3…m},j∈

[0075] {1,2,3…N},Rm i The calculation is accurate to 0.1, Rm i is the average rebound value of the i-th specimen.

[0076] In step s103, the specific steps of performing uniaxial compression tests on each specimen in turn to obtain the compressive strength fa of the specimen are as follows:

[0077] S1031: Use a compression testing machine to perform uniaxial compression tests on each specimen in turn;

[0078] S1032: The compression tester applies pressure to the specimen at a constant loading rate until the specimen breaks;

[0079] S1033: Record the maximum stress fa applied by the compression testing machine to the specimen displayed on the display screen of the compression testing machine when the specimen ruptures, and record the maximum stress fa applied by the compression testing machine to the specimen in terms of fa i It is expressed as the maximum stress value of the i-th specimen.

[0080] The specific implementation steps of step S104 are as follows:

[0081] S1041: Collect the average rebound value Rm of each specimen i and compressive strength fa i data,

[0082] S1042: Collect the data in Rm i is the horizontal axis, fa i As the vertical axis, draw a scatter diagram to show the relationship between rebound strength and compressive strength;

[0083] S1043: Select Allometric function fa=a×(R m ) b As a fitting model, a nonlinear regression method is used to fit the data in the scatter plot to solve the first parameter a and the second parameter b in the model parameters;

[0084] S1044: Determine the initial compressive strength prediction formula for high-strength concrete under vibration mixing:

[0085] f ex1 =a×(R) b , where fex1 is the preliminary predicted strength of the actual specimen, a is the first parameter obtained by fitting, b is the second parameter obtained by fitting, and R is the rebound strength measurement value obtained by the vibration-mixed high-strength concrete through the rebound device test.

[0086] The vibration-mixed high-strength concrete compressive strength measurement method based on the rebound hammer of the present invention is non-destructive, efficient and has strong engineering applicability. A prediction model is quickly established through the correlation between the rebound value and the compressive strength. The data processing is accurate, outliers are eliminated and the fitting formula is dynamically optimized. The prediction accuracy is further improved by combining the density distribution parameters and the machine learning algorithm. The method is easy to operate and the results are reliable. The conversion table can be quickly generated to provide an accurate and efficient strength assessment method for the engineering site, which significantly reduces the test time and material loss. At the same time, the method aims at the excellent effect of vibration mixing technology on improving the strength of concrete, and makes up for the insufficient applicability of ordinary rebound curves in concrete above 50MPa. Considering that there are significant differences between current concrete materials and the representative materials of the strength test curve ten years ago, the method provides a more scientific and practical reference basis for the strength assessment of engineering structures by formulating an exclusive strength test curve that conforms to the characteristics of modern materials and processes.

[0087] Embodiment 2: Combining with Figure 1 and attached Figure 2 In addition to the contents of the above embodiments, the specific steps for implementing step S105 are as follows:

[0088] S1051: using two oppositely disposed side surfaces of the actual test piece as the first test surface and the second test surface respectively, evenly arranging a number of L×D electric heating plates on the first test surface of the actual test piece, where L and D are the number of rows and columns of the electric heating plates arranged in a matrix, respectively, and the electric heating plates are arranged in a matrix to form a uniform heating grid to ensure that the first test surface of the actual test piece is evenly heated, starting the electric heating plates, and setting the heating temperature Yb of the heating plates;

[0089] S1052: a plurality of temperature sensors are arranged in a matrix on the second test surface of the actual test piece, and the matrix distribution of the temperature sensors on the second test surface corresponds to the matrix distribution of the electric heating plates on the first test surface, ensuring that each temperature sensor is in the same position as the corresponding electric heating plate;

[0090] S1053: maintaining a constant heating temperature Yb of the electric heating plate on the first test surface of the actual test piece, and recording the temperature value monitored by each temperature sensor at each time;

[0091] S1054: When the temperature sensor detects When the temperature is 0, the heating time of the electric heater is recorded as the reference time of the temperature sensor, and the reference time at the matrix coordinate position (x, y) is represented as Tb (x，y) , x∈{1, 2, 3…L}, y∈{1, 2, 3…D};

[0092] S1055: Calculate the reference time average VT of the temperature sensor:

[0093]

[0094] S1056: Calculate the reference time distribution difference of the temperature sensor б:

[0095]

[0096] S1057: Obtain the internal density distribution parameter PDI of the actual test piece:

[0097]

[0098] c1 is the control parameter used to normalize VT, λ is the weight used to adjust the influence of б on PDI, max Tb(x，y) is the maximum reference time of all temperature sensors, min Tb(x，y) is the minimum reference time among all temperature sensors, and c2 is the correction coefficient used to adjust the maximum reference time difference.

[0099] Among them, PDI is used to reflect the density distribution inside the actual test piece. The values ​​of c1, λ, and c2 are derived from the following:

[0100] The initial values ​​of c1, λ and c2 are set by technical personnel in this field based on historical experience. Then, through a large number of heat source tests and combined with the actual density distribution of different specimens, the correlation and deviation between the PDI of the specimen and the actual density distribution are analyzed, and the values ​​of c1, λ and c2 are dynamically adjusted to make the PDI more accurately reflect the density distribution inside the specimen. Finally, the optimal c1, λ and c2 values ​​are determined through verification experiments to ensure that the PDI can accurately reflect the actual density distribution of the specimen, thereby improving the reliability and accuracy of the subsequent prediction of the compressive strength of vibrated high-strength concrete.

[0101] A higher PDI value indicates that the actual test piece has a higher overall density and is evenly distributed, and the compressive strength of the test piece is higher. On the contrary, a lower PDI value indicates that the actual test piece may have uneven density or local anomalies, and the compressive strength may be lower.

[0102] Among them, the internal density distribution parameter is a quantification of the uniformity of the internal density distribution of the actual test piece, which represents the influence of factors such as the pore distribution and particle accumulation inside the concrete. Concrete with uneven density distribution may have more local voids or uneven particles.

[0103] The specific implementation steps of step S106 include: based on the preliminary predicted strength value and PDI value of the actual test piece, further calculating and obtaining the final predicted strength value f of the vibration-mixed high-strength concrete corresponding to the actual test piece ex2 :

[0104]

[0105] Wherein, PDI is the PDI value of the actual test piece obtained by the heat source test on the actual test piece, wherein M is the thickness between the first test surface and the second test surface of the actual test piece, Mr is the thickness reference value used to reflect the thickness of the actual test piece, μ1 is the first strength correction coefficient related to the internal density distribution of the test piece, μ2 is the second strength correction coefficient related to the thickness of the test piece, μ1×e PDI It reflects the nonlinear effect of uneven density distribution on strength. Mr is determined by technical personnel in this field based on the average thickness of vibration-mixed concrete specimens under different target mix ratios. e is the natural base, Mr∈[100mm,300mm].

[0106] The values ​​of u1 and u2 are derived from the following: To train the formula, a large number of specimens will be trained by a technician in the field by performing a large number of repeated tests to obtain the rebound strength measurement values ​​R and the preliminary predicted strength f corresponding to a large number of specimens. ex1 , internal density distribution parameter PDI, thickness M and maximum stress value fa are substituted into the training formula, and μ1 and μ2 are further optimized through regression analysis or machine learning model deep neural network and support vector machine. During the optimization training process, the final predicted strength value f is minimized. ex2 The error between the maximum stress value fa and the final correction coefficients μ1 and μ2 are obtained, thereby improving the prediction accuracy of the final predicted strength value of the specimen.

[0107] In construction projects, the mix ratio of concrete needs to be adjusted according to project requirements. Changes in mix ratio will directly affect the strength of concrete. Through this method, the strength of actual test samples of vibrating stirred high-strength concrete with different mix ratios can be predicted. The advantages of the heat source test in the prediction of concrete strength through the present invention are mainly reflected in its non-destructiveness, rapidity, real-time monitoring and high efficiency. The heat source test provides strong data support for concrete quality detection, making the detection process more comprehensive and accurate, and can analyze the density distribution inside the concrete without destroying the test piece. Therefore, it is very suitable for quickly and non-destructively obtaining relevant data on the density distribution inside the concrete during the construction process or when detecting existing structures.

[0108] The present invention combines non-destructive testing methods, density distribution data obtained from heat source tests, thickness correction, rebound value and machine learning optimization, which not only improves the accuracy of prediction results, but also can be widely applied to concrete components of different types and thicknesses. The method of the present invention can significantly reduce the time and cost required for traditional strength testing, and provide real-time and reliable data support for engineering quality control. Therefore, the method has broad application prospects, and is particularly suitable for online monitoring and early warning of concrete strength.

[0109] Although the present invention has been described above with reference to various embodiments, it should be understood that many changes and modifications may be made without departing from the scope of the present invention. That is, the methods, systems and devices discussed above are examples. Various configurations may appropriately omit, replace or add various processes or components. For example, in alternative configurations, the method may be performed in an order different from that described, and / or various components may be added, omitted and / or combined. Moreover, the features described with respect to certain configurations may be combined in various other configurations, such as different aspects and elements of the configuration may be combined in a similar manner. In addition, as technology develops, the elements therein may be updated, i.e., many elements are examples and do not limit the scope of the present disclosure or claims. And it should be understood that after reading the contents of the record of the present invention, the technician may make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. A method for measuring the compressive strength of vibration-mixed high-strength concrete based on a rebound tester, characterized in that: The method for measuring the compressive strength of vibration-mixed high-strength concrete based on a rebound tester comprises the following steps: S101: pouring vibrating high-strength concrete of target mix ratio to obtain m standard cube-shaped specimens, where m∈{1,2,3…10}; S102: Apply constant load to each specimen in turn to measure the rebound strength and collect the average rebound value Rm of each specimen i ; S103: Perform uniaxial compression tests on each specimen in turn to obtain the compressive strength fa of each specimen i ; S104: Obtain the average rebound value Rm of each specimen i and compressive strength fa i After that, the average rebound value Rm of the specimen i and compressive strength fa i The Allometric function is fitted based on the change of , so as to obtain the preliminary compressive strength prediction formula of high-strength concrete under vibration mixing, and the preliminary predicted strength of the actual test piece is obtained through the preliminary compressive strength prediction formula: f ex1 =a×R b , where f ex1 is the preliminary predicted strength of the actual sample, a is the first parameter obtained by fitting, b is the second parameter obtained by fitting, and R is the rebound strength measurement value obtained by a single test of the actual test piece through the rebound device, and the actual test sample at least includes walls, beams, columns and slabs made of vibration-mixed high-strength concrete with different mix ratios; S105: performing a heat source test on the actual test piece to obtain an internal density distribution parameter PDI of the test piece; S106: Further calculate and obtain the final predicted strength value f of the vibration-mixed high-strength concrete corresponding to the actual test piece ex2 .

2. The method for measuring the compressive strength of vibrating stirred high-strength concrete according to claim 1, characterized in that: The method for obtaining the standard cube-shaped test piece in step S101 is: pouring the target mix of vibrating high-strength concrete in a volume of 150 mm×150 mm×150 mm, and curing the poured test piece in a concrete room at a temperature of 18-22° C. and a relative humidity of 95% for 28 days.

3. The method for measuring the compressive strength of vibrating stirred high-strength concrete according to claim 2, characterized in that: The specific steps of applying a constant load to each test piece in turn to measure the rebound strength in step S102 include: S1021: Support the bottom surface of the specimen and apply a 30kN constant load to the top surface of the specimen; S1022: Select N measurement areas on the outer surface of each specimen, and N ≥ 5. Divide the matrix on each measurement area into 16 measurement points, where the area of ​​each measurement area does not exceed 0.04 square meters, the spacing between adjacent measurement areas does not exceed 2 meters, the distance between the measurement area and the edge of the specimen or the construction joint should be maintained at 0.2 meters to 0.5 meters, and the spacing between the measurement points in the same measurement area is uniform to ensure that the measurement points cover different positions of the measurement area. The surface of the measurement area should be the original concrete slurry surface, and the measurement areas should be evenly arranged on the four sides of the specimen; S1023: Use a rebound hammer to measure the rebound strength at 16 measuring points in each measuring area in turn. Keep the rebound hammer perpendicular to the surface of the measuring point during measurement, and record the rebound strength value of each measuring point. S1024: Data cleaning is performed on the rebound strength values ​​of the 16 measuring points in the same measuring area, and the 3 maximum and 3 minimum rebound strength values ​​of the 16 measuring points are eliminated. The mean rebound strength value VN of the 10 measuring points after data cleaning in the same measuring area is calculated to eliminate the influence of abnormal data. The middle 10 rebound strength values ​​in the measuring area are retained, and the average rebound value Rm of the vibration-mixed high-strength concrete is calculated. i : Among them, VN i，j is the VN value of the jth measurement area of ​​the i-th specimen, i∈{1,2,3…m},j∈ {1,2,3…N},Rm i The calculation is accurate to 0.1, Rm i is the average rebound value of the i-th specimen.

4. The method for measuring the compressive strength of vibrating stirred high-strength concrete according to claim 3, characterized in that: In step S103, the specific steps of performing uniaxial compression tests on each specimen in turn to obtain the compressive strength fa of the specimen are as follows: S1031: Use a compression testing machine to perform uniaxial compression tests on each specimen in turn; S1032: The compression tester applies pressure to the specimen at a constant loading rate until the specimen breaks; S1033: Record the maximum stress fa applied by the compression testing machine to the specimen displayed on the display screen of the compression testing machine when the specimen ruptures, and record the maximum stress fa applied by the compression testing machine to the specimen in terms of fa i It is expressed as the maximum stress value of the i-th specimen.

5. The method for measuring the compressive strength of vibrating stirred high-strength concrete according to claim 4, characterized in that: The specific implementation steps of step S104 are as follows: S1041: Collect the average rebound value Rm of each specimen i and compressive strength fa i data, S1042: Collect the data in Rm i is the horizontal axis, fa i As the vertical axis, draw a scatter plot to show the relationship between rebound strength and compressive strength. S1043: Select Allometric function fa=a×R m b As a fitting model, a nonlinear regression method is used to fit the data in the scatter plot to solve the first parameter a and the second parameter b in the model parameters. S1044: Determine the initial compressive strength prediction formula for high-strength concrete under vibration mixing: f ex1 =a×R b , where f ex1 is the preliminary predicted strength of the actual specimen, a is the first parameter obtained by fitting, b is the second parameter obtained by fitting, and R is the rebound strength measurement value obtained by a single test of the actual test piece through the rebound device.

6. The method for measuring the compressive strength of vibrating stirred high-strength concrete according to claim 5, characterized in that: The specific steps for implementing step S105 are as follows: S1051: Using two oppositely disposed side surfaces of the actual test piece as the first test surface and the second test surface respectively, evenly arranging a number of L×D electric heating plates on the first test surface of the actual test piece, where L and D are the number of rows and columns of the electric heating plates arranged in a matrix, respectively. The electric heating plates are arranged in a matrix to form a uniform heating grid to ensure that the first test surface of the actual test piece is evenly heated, starting the electric heating plates, and setting the heating temperature Yb of the heating plates. S1052: A plurality of temperature sensors are arranged in a matrix on the second test surface of the actual test piece. The matrix distribution of the temperature sensors on the second test surface corresponds to the matrix distribution of the electric heating plates on the first test surface, ensuring that each temperature sensor is in the same position as the corresponding electric heating plate. S1053: Maintaining a constant heating temperature Yb of the electric heating plate on the first test surface of the actual test piece, and recording the temperature values ​​monitored by each temperature sensor at each time. S1054: When the temperature sensor detects When the temperature is 0, the heating time of the electric heater is recorded as the reference time of the temperature sensor, and the reference time at the matrix coordinate position (x, y) is expressed as Tb (x，y) , x∈{1, 2, 3…L}, y∈{1, 2, 3…D}, S1055: Calculate the reference time average VT of the temperature sensor: S1056: Calculate the reference time distribution difference of the temperature sensor б: S1057: Obtain the internal density distribution parameter PDI of the actual test piece: c1 is the control parameter used to normalize VT, λ is the weight used to adjust the influence of б on PDI, max Tb(x，y) is the maximum reference time of all temperature sensors, min Tb(x，y) is the minimum reference time among all temperature sensors, and c2 is the correction coefficient used to adjust the maximum reference time difference.

7. The method for measuring the compressive strength of vibrating stirred high-strength concrete according to claim 6, characterized in that: The specific implementation steps of step S106 are as follows: Wherein, PDI is the PDI value of the actual test piece obtained through a heat source test on the actual test piece, M is the thickness between the first test surface and the second test surface of the actual test piece, Mr is a thickness reference value used to reflect the thickness of the actual test piece, μ1 is a first strength correction coefficient related to the internal density distribution of the test piece, μ2 is a second strength correction coefficient related to the thickness of the test piece, and e is a natural base.

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