Methods for locating the void between the asphalt pavement surface layer and the base layer

Abstract

This invention discloses a method for locating the void between the surface layer and base layer of an asphalt pavement, belonging to the field of pavement inspection technology. The method includes: scanning the pavement with ground-penetrating radar to obtain radar data; performing horizontal filtering on the radar data; and applying an improved back projection imaging algorithm to the horizontally filtered radar data to obtain the true location of the void. This invention performs horizontal filtering on the acquired radar data to reduce the influence of reflected waves from the surface layer and base layer interface on void identification, minimizing the influence of direct waves and interface reflections. This invention only superimposes radar signals adjacent to grid points, greatly reducing the computational load, and can accurately locate the void position.

Description

Technical Field

[0001] This invention relates to the field of road surface testing technology, and in particular to a method for locating the void between the asphalt pavement surface layer and the base layer. Background Technology

[0002] Voiding occurs when uneven settlement of the subgrade, along with factors such as soil consolidation, temperature, humidity, load, and materials, leads to discontinuous contact in the semi-rigid base asphalt pavement structure. This type of defect can reduce the road's load-bearing capacity, and if not addressed promptly, can result in pumping, cracking, and other pavement problems. Identifying and treating voids in existing roads can significantly extend their service life, meeting the requirements of environmental protection, economic efficiency, and sustainable development in highway construction. It also avoids periodic reconstruction, reduces maintenance frequency, greatly alleviates traffic congestion caused by pavement reconstruction, and ensures traffic safety.

[0003] The most commonly used non-destructive testing method for finding voids is ground-penetrating radar (GPR). However, the electromagnetic waves reflected by voids between the asphalt pavement surface layer and the base layer are often masked by the reflection at the interface between the surface layer and the base layer, and it is difficult to accurately locate the size and position of the voids. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for locating the void between the asphalt pavement surface layer and the base layer, so as to accurately locate the void.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] A method for locating the void between the asphalt pavement surface layer and the base layer includes:

[0007] Ground-penetrating radar is used to scan the road surface to obtain radar data;

[0008] The radar data is then horizontally filtered.

[0009] The radar data after horizontal filtering is offset using an improved backward projection imaging algorithm to obtain the true location of the gap.

[0010] The present invention has the following beneficial effects:

[0011] This invention performs horizontal filtering on the collected radar data to reduce the impact of reflected waves from the surface layer and the base layer interface on the identification of voids, and minimizes the influence of direct waves and interface reflections. This invention only performs superposition processing on radar signals that are close to the grid points, which greatly reduces the amount of computation. Furthermore, this invention can accurately locate the void position. Attached Figure Description

[0012] Figure 1This is a flowchart illustrating the method for locating the void between the asphalt pavement surface layer and the base layer according to the present invention.

[0013] Figure 2 This is a schematic diagram of the road surface structure model in an embodiment of the present invention;

[0014] Figure 3 This is a schematic diagram of the raw data from the ground-penetrating radar in an embodiment of the present invention;

[0015] Figure 4 This is a schematic diagram of ground-penetrating radar data after horizontal filtering in an embodiment of the present invention;

[0016] Figure 5 This is a schematic diagram of a certain grid point in the grid and its neighboring radar receiving points in an embodiment of the present invention;

[0017] Figure 6 This is a schematic diagram of the improved back projection imaging processing result in an embodiment of the present invention;

[0018] Figure 7 This is a single-channel waveform diagram of the ground-penetrating radar in an embodiment of the present invention. Detailed Implementation

[0019] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0020] This invention provides a method for locating the void between the asphalt pavement surface layer and the base layer, such as... Figure 1 As shown, it includes:

[0021] Step 101: Use ground-penetrating radar to scan the road surface and obtain radar data;

[0022] Ground penetrating radar is a conventional technology in this field. In the specific implementation of this step, the center frequency of the ground penetrating radar antenna can be 3 GHz, the sampling window can be 6 nanoseconds, and each channel can consist of 1273 sampling points. Figure 2 A pavement structure model is presented, assuming an asphalt layer (dielectric constant ε1 = 6) at depths of 0–0.07 m and a cement-stabilized crushed stone layer (dielectric constant ε2 = 9) at depths of 0.07–0.15 m. T is the transmitting antenna, R is the receiving antenna, and the transmit / receive distance is 0.002 m. An air-filled void exists at depths of 0.064–0.07 m.

[0023] right Figure 2 The road surface structure model shown is scanned. The starting positions of the transmitting antenna T and the receiving antenna R can be 0.04m and 0.042m respectively. The transmitting antenna and the receiving antenna move to the right 79 times at a time interval of 0.002m. Figure 3The radar detection results are shown. Due to the strong amplitude of the direct wave, the reflected signal in the medium is suppressed, and the reflected signal is not obvious in the image. In addition, when the void location is at the layer boundary, the reflection of the interface will greatly affect the reflected signal of the void area. To solve the above problems, a horizontal filtering method is used here (see subsequent step 102) to minimize the influence of the direct wave and interface reflection.

[0024] Step 102: Perform horizontal filtering on the radar data;

[0025] In this step, the radar data is horizontally filtered to reduce the impact of reflected waves from the surface layer and the base layer interface on clearance identification. Horizontal filtering can employ various filtering algorithms in the art, such as average value filtering. That is, horizontal filtering of the radar data (step 102) may include:

[0026] The average of multiple (N) data points at the same depth point in the distance direction is calculated, and then the average value is subtracted to obtain the filtered data for that point.

[0027] N represents the window size during the filtering process. A larger N value results in a smoother filtered signal, but lower sensitivity (potentially masking useful signal features); conversely, a smaller N value leads to poorer smoothing but better sensitivity. The window size should be determined based on the actual signal and noise characteristics. To ensure good sensitivity, the principle for choosing the window size is to highlight anomalous signals (such as...). Figure 4 As shown in the figure, specifically, it is preferable to first open the window to the maximum size, and then gradually reduce the window size, selecting the window size when the relative energy of the abnormal signal is the strongest as the window size in the filtering process.

[0028] Figure 4 The result is obtained after horizontal filtering. As shown in the figure, the influence of the direct wave and the reflected wave from the horizontal interface is greatly reduced, and the reflected wave signal from the void region is highlighted. However, due to... Figure 4 It is difficult to determine the extent and depth of the vacuolated area. Therefore, a backward projection imaging technique (see subsequent step 103) is used here to obtain the extent and depth of the vacuolated area.

[0029] Step 103: The radar data after horizontal filtering is offset using an improved backward projection imaging algorithm to obtain the true location of the gap.

[0030] Back projection imaging is an imaging method that processes time-domain echo data. It references the concept of "delay-superposition," matching the echo signal with a reference point signal to obtain a range-compressed signal, upon which the back projection imaging algorithm is executed. However, the back projection imaging algorithm also has significant drawbacks: its computational data is large, exhibiting redundancy, which directly leads to low computational efficiency and excessively long waiting times during imaging. To improve computational efficiency, this application proposes an improved back projection imaging algorithm. Traditional back projection imaging methods require calculating the time delay from each grid point in the segmented region to all radar transmission positions, and then obtaining the energy superposition of the reflected signals from that grid point based on the time delay, which requires a large computational load. Radar signals experience power attenuation during propagation in the medium; as the propagation distance increases, the radar reflection amplitude decreases rapidly. Therefore, radar transmission points far from the grid point receive weak, even negligible, radar reflection signals from that grid point. Therefore, this application only performs superposition processing on radar signals adjacent to the grid point, thus significantly reducing the computational load.

[0031] Therefore, as an optional embodiment, the step of offsetting the horizontally filtered radar data using an improved backward projection imaging algorithm to obtain the true location of the gap (step 103) may include:

[0032] Step 1031: Divide the imaging area into a grid and obtain the coordinates of all grid points;

[0033] Step 1032: For a certain grid point A(i,j) in the grid, the improved backward projection imaging algorithm only cares about the radar received signals of n radar receiving points within a preset distance range from A(i,j), and calculates the two-way travel time t1 from A(i,j) to the first radar receiving point R1 among the n radar receiving points.

[0034] In this step, for a point A(i,j) in the mesh, the improved backward projection imaging algorithm only cares about the n radar received signals that are adjacent to A(i,j) (within a preset distance range) (see...). Figure 5 The amplitude of the reflected signal received by the other radars from A(i,j) is very weak and can be ignored. Assuming the distance from A(i,j) to R1 is S1, then the two-way travel time t1 can be expressed as:

[0035]

[0036] Where c represents the speed of light and ε represents the dielectric constant of the underground medium.

[0037] Preferably, the preset distance range is 10-20 times the thickness of the road surface layer.

[0038] Step 1033: Interpolate the time series of the reflected wave signal received at the first radar receiving point R1 to find the radar reflected signal amplitude value A1 at time t1. Use the same method to obtain the amplitude values ​​A1 of all reflected signals at A(i,j) for the n radar receiving points. i (i = 1, 2, ..., n), then the value obtained at A(i, j) by the improved back projection imaging algorithm is

[0039] Step 1034: Traverse all mesh points and obtain the calculation results for all mesh points;

[0040] In this step, steps 1032-1033 above can be repeated to obtain the calculation results for all mesh points.

[0041] Step 1035: Based on the calculation results, obtain the actual location of the void.

[0042] As an optional embodiment, obtaining the true location of the detachment based on the calculation results (step 1035) may include:

[0043] Step 10351: Based on the calculation results, generate a radar waveform diagram;

[0044] Step 10352: Locate the region on the radar waveform that first shows a strong positive amplitude followed by a strong negative amplitude; this region is the decoupling region. In other words, the location of this region (its depth from the ground) is the location of the decoupling region, and the width of this region is the width of the decoupling region.

[0045] The principle is explained as follows:

[0046] Each received record forms a radar waveform. When electromagnetic waves propagate through underground media, their path, electromagnetic field strength, and waveform change according to the dielectric properties and geometry of the medium they pass through. When the electromagnetic wave reaches a location where the dielectric constant differs, a reflection signal is immediately generated. The reflection coefficient can be expressed as:

[0047]

[0048] Where ε1 is the dielectric constant of the medium above the reflecting interface, and ε2 is the dielectric constant of the medium below the reflecting interface.

[0049] The greater the difference in dielectric constants on both sides of the reflecting interface, the greater the reflected amplitude. When an electromagnetic wave moves from a medium with a lower dielectric constant to a medium with a higher dielectric constant, R < 0, the phase changes (the wave crest becomes the wave trough, and the wave trough becomes the wave crest); conversely, the waveform remains unchanged.

[0050] The dielectric constant of air is 1, while the dielectric constant of asphalt pavement is greater than 1. The electromagnetic wave used in this application is a Ricker wavelet (approximately...). Figure 7 (The waveform in the region shown by the ellipse) has a reflection coefficient less than 0 at the interface between the air and the asphalt layer, where the electromagnetic wave phase is reversed. At the interface between the asphalt layer and the voided region, the reflection coefficient is greater than 0, and the phase remains unchanged. Figure 7 The area shown by the rectangle is the reflected signal of the de-energized region, which is out of phase with the original Ricker wavelet and appears on the image as a strong positive amplitude followed by a strong negative amplitude.

[0051] Figure 6 In the diagram, white represents positive amplitude and black represents negative amplitude. Only the area enclosed by the ellipse shows strong amplitude, with the white positive amplitude appearing first, followed by the black negative amplitude. Therefore, the area within the ellipse is the calculated void region. The white box in the diagram represents... Figure 2 The actual location of the empty area in the model is basically consistent with the white box and the elliptical area.

[0052] Figure 6 The imaging results show that the predicted gap size and depth are basically consistent with the actual situation, verifying the effectiveness and feasibility of the method proposed in this application. Furthermore, testing shows that the method used in this application has an accuracy rate of over 90% in calculating the size and location of the gap; compared with traditional methods, the method used in this application reduces the computation time by 50%, significantly shortening the computation time and improving computational efficiency.

[0053] In summary, the method for locating the void between the surface layer and base layer of asphalt pavement according to the present invention first uses ground-penetrating radar to scan the pavement to obtain radar data. Then, the radar data is horizontally filtered. Finally, the horizontally filtered radar data is offset using an improved backward projection imaging algorithm to obtain the true location of the void. Thus, the present invention performs horizontal filtering on the acquired radar data, reducing the influence of reflected waves from the surface layer and base layer interface on void identification, minimizing the influence of direct waves and interface reflections. The present invention only superimposes radar signals adjacent to grid points, greatly reducing the computational load, and can accurately locate the void position.

[0054] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for locating the void between the surface layer and the base layer of an asphalt pavement, characterized in that, include: Ground-penetrating radar is used to scan the road surface to obtain radar data; Horizontal filtering of the radar data includes: The average of multiple channels of data at the same depth point in the distance direction is calculated, and then the average value is subtracted to obtain the filtered data for that point. The horizontally filtered radar data is then offset using an improved back projection imaging algorithm to obtain the true location of the gap, including: The imaging area is divided into grids, and the coordinates of all grid points are obtained; For a certain grid point A(i,j) in the grid, the improved backward projection imaging algorithm only cares about the radar received signals of n radar receiving points within a preset distance range from A(i,j), and calculates the two-way travel time t1 from A(i,j) to the first radar receiving point R1 among the n radar receiving points. Interpolate the time series of the reflected wave signal received at the first radar receiving point R1 to find the radar reflected signal amplitude value A1 at time t1. Use the same method to obtain the amplitude values ​​A1 of all reflected signals at A(i,j) for the n radar receiving points. i If i = 1, 2, ..., n, then the value obtained at A(i,j) by the improved back projection imaging algorithm is... ; Traverse all mesh points to obtain the calculation results for all mesh points; Based on the calculation results, the actual location of the void is obtained.

2. The method according to claim 1, characterized in that, For the selection of window size during the filtering process, the window is first opened to the maximum, and then the window is gradually reduced. The window size when the relative energy of the anomalous signal is the strongest is selected as the window size during the filtering process.

3. The method according to claim 1, characterized in that, The formula for calculating the two-way travel time t1 is: Where S1 is the distance from A(i,j) to R1, c represents the speed of light, and ε represents the dielectric constant of the underground medium.

4. The method according to claim 1, characterized in that, The preset distance range is 10-20 times the thickness of the road surface layer.

5. The method according to claim 1, characterized in that, Based on the calculation results, the actual location of the detachment is obtained, including: Based on the calculation results, a radar waveform diagram is generated; Find the region on the radar waveform diagram where a strong positive amplitude appears first, followed by a strong negative amplitude; this region is the decoupling region.

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