A concrete single-side CT detection method based on surface wave

Abstract

The application discloses a concrete single-face CT detection method based on surface waves, and innovatively utilizes surface waves to perform single-face CT scanning on a concrete structure, fills the gap of related technologies at home and abroad, and solves the problem that currently, in the internal defects of a concrete structure, only the double-channel SASW surface wave method can draw the dispersion curve of the concrete in the surface wave measurement area, and is used for simply evaluating the layering and quality of the concrete structure, the result is not intuitive and the test stability is poor, and therefore the effect is poor in actual application.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology for concrete, specifically to a single-sided CT testing method for concrete based on surface waves. Background Technology

[0002] In the field of non-destructive testing (NDT) of concrete, elastic waves are a highly effective testing medium. Methods derived from elastic waves, such as impact-echo analysis and elastic wave CT, are also very effective. Elastic wave CT requires at least two test surfaces for tomographic imaging, providing intuitive results. Impact-echo analysis, on the other hand, can be performed on a single surface, but is generally only suitable for thin-plate structures and requires prior knowledge of the structural thickness; it is also effective for thin-plate structures. Therefore, for concrete structures with unknown or significant thickness and only a single test surface, there is currently a lack of effective NDT techniques.

[0003] Currently, the only method for detecting surface waves in concrete structures using the dual-channel SASW surface wave method is the surface wave method, which can plot the dispersion curve (two-dimensional curve) of the concrete in the surface wave test area and is used to simply evaluate the delamination and quality of the concrete structure. However, the results are not intuitive and the test stability is poor, so the effect is not good in practical applications. Summary of the Invention

[0004] In response to the problems raised in the background technology, the present invention aims to provide a single-sided CT detection method for concrete based on surface waves. This method solves the problem that currently, only the dual-channel SASW surface wave method can plot the dispersion curve of concrete in the surface wave test area for internal defects of concrete structures, and is used to simply evaluate the delamination and quality of concrete structures. However, the results are not intuitive and the test stability is poor, so the method is not effective in practical applications.

[0005] This invention is achieved through the following technical solution:

[0006] This invention provides a single-sided CT inspection method for concrete based on surface waves, comprising the following steps:

[0007] Step S1: Arrange multi-channel sensors on the concrete test surface and use vibrating hammers of different diameters to strike the concrete to obtain multi-hammer impact data and single-hammer impact data.

[0008] Step S2: The dispersion curve of the multi-hammer striking data is extracted using the sliding window point selection method to generate a dispersion curve graph, and the dispersion curve of the single-hammer striking data is extracted using the narrowband filtering method to generate a dispersion curve graph.

[0009] Step S3: Use the improved simultaneous iterative method to perform inversion imaging on the dispersion curve to obtain a tomographic profile.

[0010] In the above technical solution, the surface wave component of the elastic wave signal exhibits dispersion characteristics, meaning its influence depth is related to the signal frequency; low-frequency signals have a deeper influence depth, while high-frequency signals have a shallower influence depth, typically 0.75 times the surface wave wavelength. This characteristic allows for the testing of wave velocities at different depths in concrete, and the obtained wave velocities reflect the internal quality of the concrete. In this step, a multi-channel sensor is used, and corresponding dispersion curve extraction techniques are matched to different data acquisition methods. Multi-hammer impact data is analyzed using a sliding window point selection method, while single-hammer data can be analyzed using narrowband filtering point selection techniques to generate dispersion curves. By analyzing the dispersion curves, wave velocity values ​​of concrete at different depths in each channel are obtained, and finally, a tomographic (CT) profile is obtained. The tomographic profile reflects the internal quality of the tested concrete structure.

[0011] In one optional embodiment, the dispersion curve extraction and generation of a dispersion curve graph from the multi-hammer impact data using the sliding window point selection method includes:

[0012] Step S21: Perform fast Fourier transform spectrum analysis on the elastic wave data D0, D1, D2, and D3 of each channel, and extract the main frequencies f0, f1, f2, and f3 of the signal.

[0013] Step S22: Set the range, start point, and end point of the first wave of the data surface wave in elastic wave data D0;

[0014] Step S23: Calculate the correlation array by using the Pearson correlation coefficient on the adjacent channel data, and calculate the wave velocity V by taking the maximum value point of the correlation array. 0～1 V 1～2、 V 2～3 ;

[0015] Step S24: Calculate the wave velocity V respectively. 0～1 V 1～2、 V 2～3 The corresponding frequencies are determined, and a dispersion curve is plotted.

[0016] In one optional embodiment, the Pearson correlation coefficient is used to calculate the correlation array for adjacent channel data, resulting in:

[0017] xgx 0-1 (j)=r(D0[iq:jz],D1[iq+j:jz+j])

[0018] In the above formula, xgx 0-1 Let iq be the correlation array, jz be the starting point and j be the ending point, j be the array range from 0 to 255, and r be the function of the Pearson correlation coefficient.

[0019] In one optional embodiment, the wave velocity V is calculated separately.0～1 V 1～2、 V 2～3 The corresponding frequencies include:

[0020] f 0～1 = 0.5 × (f0 × f1)

[0021] f 1～2 = 0.5 × (f1 × f2)

[0022] f 2～3 = 0.5 × (f2 × f3)

[0023] In the above formula, f 0～1 Wave speed V 0～1 The corresponding frequency, f 1～2 Wave speed V 1～2 The corresponding frequency, f 2～3 Wave speed V 1～2 The corresponding frequency.

[0024] In one optional embodiment, the process of extracting dispersion curves from the aforementioned single-hammer striking data using narrowband filtering to generate a dispersion curve graph includes:

[0025] Step S25: Set the frequency nodes f of the desired dispersion curve. bpf0 f bpf1 f bpf2 f bpf3 f bpf4 f bpf5 ;

[0026] Step S26: Perform bandpass filtering on the elastic wave data D0, D1, D2, and D3 of each channel according to the frequency nodes to obtain the filtered data D. bpf0 D bpf1 D bpf2 D bpf3 ;

[0027] Step S27 executes steps S22 to S23 on the filtered data to obtain the wave velocity values ​​between adjacent sensors at each frequency node;

[0028] Step S28: Draw a dispersion curve based on the frequency nodes of the required dispersion curve and the wave velocity values ​​between adjacent sensors at each frequency node.

[0029] In one alternative embodiment, the inversion mesh generation includes:

[0030] Step S31: Divide the vertical lines of the inversion grid based on the multi-channel sensor, and divide the horizontal lines of the inversion grid to take into account the influence of the surface wave signal.

[0031] Step S32: Arrange the dispersion points in the dispersion curve graph in descending order of frequency value to obtain frequency data f. bpf0 f bpf1 f bpf2 f bpf3 f bpf4 and its corresponding wave velocity value V bpf0 V bpf1 V bpf2 V bpf3 V bpf4 ;

[0032] Step S33: Using the frequency data f bpf0 f bpf1 f bpf2 f bpf3 f bpf4 and its corresponding wave velocity value V bpf0 V bpf1 V bpf2 V bpf3 V bpf4 Depth is calculated using average wave velocity and laterally segmented coordinates;

[0033] Step S34: The grid partitions are numbered according to the coordinates of the horizontal and vertical dividing lines to obtain the slowness value of each partition.

[0034] In an alternative embodiment, via the frequency data f bpf0 f bpf1 f bpf2 f bpf3 f bpf4 and its corresponding wave velocity value V bpf0 V bpf1 V bpf2 V bpf3 V bpf4 Depth calculations using average wave velocity and lateral segmentation coordinates include:

[0035]

[0036]

[0037] In the above formula, For depth, use the average wave velocity, C i The coordinates are for the horizontal dividing line.

[0038] In one alternative embodiment, tomographic inversion includes:

[0039] Step S35: Construct the surface wave tomography inversion matrix based on the grid divided in step S31;

[0040] Step S36: Solve for the slowness value in the surface wave tomography inversion matrix using a simultaneous iterative algorithm;

[0041] Step S37: Plot the inversion results using contour lines to generate a tomographic profile.

[0042] In one optional embodiment, the surface wave tomography inversion matrix includes:

[0043] In one alternative embodiment, the pixel value wave velocity range in the simultaneous iterative algorithm is limited to between 1 km / s and 3 km / s.

[0044] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0045] 1. Innovatively utilizes surface waves to perform single-sided CT scanning of concrete structures, filling a gap in related technologies both domestically and internationally;

[0046] 2. This invention can detect structures of unknown thickness, with an effective testing range from 1 cm to several meters;

[0047] 3. This invention can perform tomographic imaging of the interior of concrete, and the results are intuitive and reliable. Attached Figure Description

[0048] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0049] Figure 1 This is a schematic diagram of a multi-channel surface wave test provided in an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of a single-sided CT result provided in an embodiment of the present invention;

[0051] Figure 3 A schematic flowchart of a single-sided CT inspection method for concrete based on surface waves provided in an embodiment of the present invention;

[0052] Figure 4 The model of the excitation hammer provided in the embodiments of the present invention;

[0053] Figure 5 This is a scatter plot of the dispersion curves of each measurement point provided in the embodiments of the present invention;

[0054] Figure 6 This is a schematic diagram of single-sided CT network segmentation provided in an embodiment of the present invention;

[0055] Figure 7 This is a single-sided CT contour map provided in an embodiment of the present invention;

[0056] Figure 8 This is a ground-penetrating radar result image provided in an embodiment of the present invention;

[0057] Figure 9 The image shows the test results of the impact echo acoustic method provided in the embodiment of the present invention;

[0058] Figure 10 This is a single-sided CT result image provided in an embodiment of the present invention. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0060] Example

[0061] Figure 3 A flowchart illustrating a single-sided CT inspection method for concrete based on surface waves, as provided in an embodiment of the present invention, is shown below. Figure 3 As shown, a single-sided CT inspection method for concrete based on surface waves includes the following steps:

[0062] Step S1: Arrange multi-channel sensors on the concrete test surface and use vibrating hammers of different diameters to strike the concrete to obtain multi-hammer impact data and single-hammer impact data.

[0063] It should be noted that the surface wave component in elastic wave signals exhibits dispersion characteristics, meaning its signal influence depth is related to the signal frequency; low-frequency signals have a deeper influence depth, while high-frequency signals have a shallower influence depth, typically 0.75 times the surface wave wavelength. This characteristic can be used to test the wave velocity at different depths of concrete, and the obtained wave velocity can reflect the internal quality of the concrete. The sensor used in this step is a multi-channel sensor, and the data collected by the multi-channel sensor is as follows: Figure 1 As shown.

[0064] Furthermore, the spacing between the sensors can be any value between 0.2m and 0.5m. In this embodiment, the spacing between the sensors is 0.5m, meaning the tapping point is 0.5m away from the nearest sensor.

[0065] Model of vibratory hammer, such as Figure 4 As shown, steel ball hammers with diameters of 10mm, 17mm, 30mm and 50mm are included. Different diameter vibratory hammers or a single model of vibratory hammer can be selected for data collection by impact.

[0066] Step S2: The dispersion curve of the multi-hammer striking data is extracted using the sliding window point selection method to generate a dispersion curve graph, and the dispersion curve of the single-hammer striking data is extracted using the narrowband filtering method to generate a dispersion curve graph.

[0067] It should be noted that different dispersion curve extraction techniques are matched to different data acquisition methods. Multi-hammer impact data is analyzed using the sliding window point selection method, while single-hammer data can be analyzed using the narrowband filtering point selection technique.

[0068] In one optional embodiment, the dispersion curve extraction and generation of a dispersion curve graph from the multi-hammer impact data using the sliding window point selection method includes:

[0069] Step S21: Perform fast Fourier transform spectrum analysis on the elastic wave data D0, D1, D2, and D3 of each channel, and extract the main frequencies f0, f1, f2, and f3 of the signal.

[0070] Step S22: Set the range, start point, and end point of the first wave of the data surface wave in elastic wave data D0;

[0071] Step S23: Calculate the correlation array by using the Pearson correlation coefficient on the adjacent channel data, and calculate the wave velocity V by taking the maximum value point of the correlation array. 0～1 V 1～2、 V 2～3 ;

[0072] Step S24: Calculate the wave velocity V respectively. 0～1 V 1～2、 V 2～3 The corresponding frequencies are determined, and a dispersion curve is plotted.

[0073] It should be noted that in this embodiment, the subscripts correspond to the sensor serial numbers. The maximum value of the correlation array is the data interval between two adjacent channels, from which the wave velocity of two adjacent channels can be calculated.

[0074] In one optional embodiment, the Pearson correlation coefficient is used to calculate the correlation array for adjacent channel data, resulting in:

[0075] xgx 0-1 (j)=r(D0[iq:jz],D1[iq+j:jz+j])

[0076] In the above formula, xgx 0-1 Let iq be the correlation array, jz be the starting point and j be the ending point, j be the array range from 0 to 255, and r be the function of the Pearson correlation coefficient.

[0077] It should be noted that the purpose of step S23 is to perform sliding window point selection. In this embodiment, the process is as follows: Array j: 0~255, calculated using the Pearson correlation coefficient (function r) method:

[0078] xgx 0-1 (j)=r(D0[iq:jz],D1[iq+j:jz+j])

[0079] Obtain the correlation array xgx 0-1 The maximum value point of this array is m1, which is the data interval point of channel 0 to 1. From this, the wave velocity V can be calculated. 0～1 Similarly, a sliding window is used to select points on the remaining adjacent channel data to obtain the wave velocity V. 0～1 V 1～2、 V 2～3 .

[0080] In one optional embodiment, the wave velocity V is calculated separately. 0～1 V 1～2、 V 2～3 The corresponding frequencies include:

[0081] f 0～1 = 0.5 × (f0 × f1)

[0082] f 1～2 = 0.5 × (f1 × f2)

[0083] f 2～3 = 0.5 × (f2 × f3)

[0084] In the above formula, f 0～1 Wave speed V 0～1 The corresponding frequency, f 1～2 Wave speed V 1～2 The corresponding frequency, f 2～3 Wave speed V 1～2 The corresponding frequency.

[0085] In one optional embodiment, the process of extracting dispersion curves from the aforementioned single-hammer striking data using narrowband filtering to generate a dispersion curve graph includes:

[0086] Step S25: Set the frequency nodes f of the desired dispersion curve. bpf0 f bpf1 f bpf2 f bpf3 f bpf4 f bpf5 ;

[0087] Step S26: Perform bandpass filtering on the elastic wave data D0, D1, D2, and D3 of each channel according to the frequency nodes to obtain the filtered data D. bpf0 Dbpf1 D bpf2 D bpf3 ;

[0088] Step S27 executes steps S22 to S23 on the filtered data to obtain the wave velocity values ​​between adjacent sensors at each frequency node;

[0089] Step S28: Draw a dispersion curve based on the frequency nodes of the required dispersion curve and the wave velocity values ​​between adjacent sensors at each frequency node.

[0090] It should be noted that, in order to analyze the data of a single type of hammer and extract the surface wave velocity at different frequencies, a narrowband filtering method was developed in this invention to extract the dispersion curve. The scatter plot of the dispersion curve at each measuring point is shown below. Figure 5 As shown.

[0091] In this embodiment, the elastic wave data D0, D1, D2, and D3 of each channel are bandpass filtered according to the set frequency nodes. For example, if the main frequency is set to f... bpf0 At that time, the low-pass filter was 1.25f. bpf0 The high-pass value is 0.75f. bpf0 The filtered data D is obtained. bpf0 D bpf1 D bpf2 D bpf3 .

[0092] Step S3: Use the improved simultaneous iterative method to perform inversion imaging on the dispersion curve to obtain a tomographic profile.

[0093] In one alternative embodiment, an improved simultaneous iterative method is used to invert the dispersion curve to obtain a tomographic profile including inversion mesh division and tomographic inversion.

[0094] In one alternative embodiment, the inversion mesh generation includes:

[0095] Step S31: Divide the vertical lines of the inversion grid based on the multi-channel sensor, and divide the horizontal lines of the inversion grid to take into account the influence of the surface wave signal.

[0096] Step S32: Arrange the dispersion points in the dispersion curve graph in descending order of frequency value to obtain frequency data f. bpf0 f bpf1 f bpf2 f bpf3 f bpf4 and its corresponding wave velocity value V bpf0 V bpf1 V bpf2 V bpf3 V bpf4 ;

[0097] Step S33: Using the frequency data f bpf0 f bpf1 f bpf2 f bpf3 f bpf4 and its corresponding wave velocity value V bpf0 V bpf1 V bpf2 V bpf3 V bpf4 Depth is calculated using average wave velocity and laterally segmented coordinates;

[0098] Step S34: The grid partitions are numbered according to the coordinates of the horizontal and vertical dividing lines to obtain the slowness value of each partition.

[0099] In one alternative embodiment, via the frequency data f bpf0 f bpf1 f bpf2 f bpf3 f bpf4 and its corresponding wave velocity value V bpf0 V bpf1 V bpf2 V bpf3 V bpf4 Depth calculations using average wave velocity and lateral segmentation coordinates include:

[0100]

[0101]

[0102] In the above formula, For depth, use the average wave velocity, C i The coordinates are for the horizontal dividing line.

[0103] It should be noted that the grid partitions are numbered i (horizontal division line coordinates) and j (vertical division line coordinates), and the slowness value of each partition is Z. ij The schematic diagram of single-sided CT mesh division is shown below. Figure 6 As shown.

[0104] In one alternative embodiment, tomographic inversion includes:

[0105] Step S35: Construct the surface wave tomography inversion matrix based on the grid divided in step S31;

[0106] Step S36: Solve for the slowness value in the surface wave tomography inversion matrix using a simultaneous iterative algorithm;

[0107] Step S37: Plot the inversion results using contour lines to generate a tomographic profile.

[0108] In one optional embodiment, the surface wave tomography inversion matrix includes:

[0109]

[0110] In one alternative embodiment, the pixel value wave velocity range in the simultaneous iterative algorithm is limited to between 1 km / s and 3 km / s.

[0111] It should be noted that the inversion results are plotted as contour lines. The contour line result of a single-sided CT scan is shown below. Figure 7 As shown in the figure. Testing was conducted using a multi-channel sensor, and the wave velocity values ​​of concrete at different depths between channels were analyzed. Finally, a tomographic (CT) cross-sectional image was obtained, as shown in the figure. Figure 2 As shown, where, Figure 2 The colors in the image are used to distinguish wave velocities. The internal quality of the tested concrete structure is reflected in the tomographic cross-section.

[0112] The present invention has the following advantages and beneficial effects:

[0113] 1. Innovatively utilizes surface waves to perform single-sided CT scanning of concrete structures, filling a gap in related technologies both domestically and internationally;

[0114] 2. This invention can detect structures of unknown thickness, with an effective testing range from 1 cm to several meters;

[0115] 3. This invention can perform tomographic imaging of the interior of concrete, and the results are intuitive and reliable.

[0116] To illustrate the effectiveness of this invention, this embodiment uses a reinforced concrete model (3m long, 2m wide, 0.4m thick, with internal defects) from a university as an example for testing. We compare and contrast the ground-penetrating radar method, the impact echo acoustic method, and the single-sided CT method of this invention. Comparing the data from the same survey line, there are two defects with a burial depth of approximately 30cm, filled with sand. The ground-penetrating radar results are shown in the figure below. Figure 8 As shown, no defects are visible in the ground-penetrating radar results image; the shock echo acoustic test results image is as follows. Figure 9 As shown, the impact echo acoustic method does not clearly reflect the second defect. The single-sided CT result is shown in the image below. Figure 10 As shown in the figure, it can be seen that the two defects detected by the single-sided CT detection method of concrete based on surface waves provided by the present invention are obvious and the coordinates match.

[0117] The comparative test shows that the single-sided CT test in this invention has the best results.

[0118] Example

[0119] Based on the above embodiments, this embodiment provides an electronic device including a processor, a memory, an input device, and an output device; the number of processors in the computer device can be one or more, taking one processor as an example; the processor, memory, input device, and output device in the electronic device can be connected by a bus or other means, taking bus connection as an example.

[0120] Memory, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules. The processor executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the memory, thereby implementing the surface wave-based single-sided CT detection method for concrete described in the above embodiment.

[0121] The memory may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data created based on the use of the terminal. Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory, or other non-volatile solid-state storage device. In some instances, the memory may further include memory remotely located relative to the processor 21, which can be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0122] The input device can be used to receive user input such as passwords. The output device is used to output the network distribution page.

[0123] Example

[0124] Based on the above embodiments, this invention also provides a computer-readable storage medium, wherein the computer-executable instructions, when executed by a computer processor, are used to implement a single-sided CT detection method for concrete based on surface waves as provided in the above embodiments.

[0125] The storage medium containing computer-executable instructions provided in the embodiments of the present invention is not limited to the method operations provided in the above embodiments, but can also perform related operations in the concrete single-sided CT detection method based on surface waves provided in any embodiment of the present invention.

[0126] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A single-sided CT inspection method for concrete based on surface waves, characterized in that, Includes the following steps: Step S1: Arrange multi-channel sensors on the concrete test surface and use vibrating hammers of different diameters to strike the concrete to obtain multi-hammer impact data and single-hammer impact data. Step S2: Extract dispersion curves from the multi-hammer striking data using the sliding window point selection method to generate a dispersion curve graph; and extract dispersion curves from the single-hammer striking data using the narrowband filtering method to generate a dispersion curve graph. The extraction of dispersion curves from the multi-hammer striking data using the sliding window point selection method includes: Step S21: Perform fast Fourier transform spectrum analysis on the elastic wave data D0, D1, D2, and D3 of each channel, and extract the signal main frequencies ƒ0, ƒ1, ƒ2, and ƒ3. Step S22: Set the range, start point, and end point of the first wave of the data surface wave in elastic wave data D0; Step S23: Calculate the correlation array by using the Pearson correlation coefficient on the adjacent channel data, and calculate the wave velocity V by taking the maximum value point of the correlation array. 0~1 V 1~2、 V 2~3 ; Step S24: Calculate the wave velocity V respectively. 0~1 V 1~2、 V 2~3 The corresponding frequencies are determined, and dispersion curves are plotted. The dispersion curves of the above single hammer impact data are extracted using narrowband filtering to generate dispersion curve diagrams, including: Step S25: Set the frequency nodes ƒ of the desired dispersion curve bpf0 、ƒ bpf1 、ƒ bpf2 、ƒ bpf3 、ƒ bpf4 、ƒ bpf5 ; Step S26: Perform bandpass filtering on the elastic wave data D0, D1, D2, and D3 of each channel according to the frequency nodes to obtain the filtered data D. bpf0 D bpf1 D bpf2 D bpf3 ; Step S27 executes steps S22 to S23 on the filtered data to obtain the wave velocity values ​​between adjacent sensors at each frequency node; Step S28: Draw a dispersion curve based on the frequency nodes of the required dispersion curve and the wave velocity values ​​between adjacent sensors at each frequency node. Step S3: The dispersion curve is inverted using the improved simultaneous iterative method to obtain a tomographic profile; wherein, the inversion mesh division includes: Step S31: Divide the vertical lines of the inversion grid based on the multi-channel sensor, and divide the horizontal lines of the inversion grid to take into account the influence of the surface wave signal. Step S32: Arrange the dispersion points in the dispersion curve graph in descending order of frequency value to obtain frequency data ƒ bpf0 、ƒ bpf1 、ƒ bpf2 、ƒ bpf3 、ƒ bpf4 and its corresponding wave velocity value V bpf0 V bpf1 V bpf2 V bpf3 V bpf4 ; Step S33: Using the frequency data ƒ bpf0 、ƒ bpf1 、ƒ bpf2 、ƒ bpf3 、ƒ bpf4 and its corresponding wave velocity value V bpf0 V bpf1 V bpf2 V bpf3 V bpf4 Depth is calculated using average wave velocity and laterally segmented coordinates; Step S34: The grid partitions are numbered according to the coordinates of the horizontal and vertical dividing lines to obtain the slowness value of each partition; Tomographic inversion includes: Step S35: Construct the surface wave tomography inversion matrix based on the grid divided in step S31; Step S36: Solve for the slowness value in the surface wave tomography inversion matrix using a simultaneous iterative algorithm; Step S37: Plot the inversion results using contour lines to generate a tomographic profile.

2. The method for single-sided CT inspection of concrete based on surface waves according to claim 1, characterized in that, The correlation array is obtained by calculating the correlation coefficient between adjacent channels using the Pearson correlation coefficient: In the above formula, This is a correlation array. Starting from, The endpoint is given by array j: 0~255, and r is a function of the Pearson correlation coefficient.

3. The method for single-sided CT inspection of concrete based on surface waves according to claim 2, characterized in that, Calculate the wave speed V respectively 0~1 V 1~2、 V 2~3 The corresponding frequencies include: ƒ 0~1 =0.5×(ƒ0׃1) ƒ 1~2 =0.5×(ƒ1׃2) ƒ 2~3 =0.5×(ƒ2׃3) In the above formula, ƒ 0~1 Wave speed V 0~1 The corresponding frequency, ƒ 1~2 Wave speed V 1~2 The corresponding frequency, ƒ 2~3 Wave speed V 1~2 The corresponding frequency.

4. The method for single-sided CT inspection of concrete based on surface waves according to claim 1, characterized in that, Through the frequency data ƒ bpf0 、ƒ bpf1 、ƒ bpf2 、ƒ bpf3 、ƒ bpf4 and its corresponding wave velocity value V bpf0 V bpf1 V bpf2 V bpf3 V bpf4 Depth calculations using average wave velocity and lateral segmentation coordinates include: In the above formula, The average wave velocity is used for depth. The coordinates are for the horizontal dividing line.

5. The method for single-sided CT inspection of concrete based on surface waves according to claim 1, characterized in that, Surface wave tomography inversion matrices include: .

6. The method for single-sided CT inspection of concrete based on surface waves according to claim 1, characterized in that, The pixel value wave velocity range in the simultaneous iterative algorithm is limited to between 1 km / s and 3 km / s.

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