Pavement structure strength evaluation method based on high-speed deflectometer

Abstract

The invention discloses a pavement structure strength evaluation method based on a high-speed deflectometer. According to the method, the deflection slope is obtained by calculating the ratio of the road surface deformation speed to the vehicle speed in the vehicle running process, on the basis, the first-order change rate and the second-order change rate are introduced, multi-scale smooth filtering and strict data screening are combined, and a set of layered strength index system capable of finely evaluating the surface layer, the base layer, the subbase layer and the roadbed is established. In addition, the invention further provides a layered strength degradation rate index to quantify the structural degradation degree, and high-precision inversion from the surface response to the structural layer modulus is realized by combining finite element simulation with a machine learning model. According to the method, the recognition sensitivity of early damage of the road surface is improved, the anti-noise capability is enhanced, the layering bearing capacity and damage evolution characteristics of the road surface can be efficiently and accurately reflected, and the method is particularly suitable for network-level rapid detection and project-level refined evaluation of various roads in a complex environment.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of rapid nondestructive testing of road engineering, and particularly relates to a pavement structure strength evaluation method based on a high-speed deflectometer. BACKGROUND

[0002] With the highway network of China entering a new stage of large-scale maintenance, how to quickly and accurately evaluate the pavement, especially the layered structure strength of semi-rigid base asphalt pavement, has become an urgent technical problem. Traditional detection methods, such as the falling weight deflectometer, have been difficult to adapt to the large-scale and efficient maintenance management needs of the modern highway network due to their low efficiency. Under this background, the high-speed laser dynamic deflectometer (TSD) that can continuously measure at normal vehicle speed has emerged and gradually become an important tool for road structure evaluation. However, the existing TSD data analysis methods mostly rely on finding the extreme points of the deflection slope basin to calculate the structure modulus, which is not only complex in physical interpretation, but also very sensitive to data noise and vehicle speed fluctuations. More importantly, it is difficult to effectively reflect the damage evolution and performance degradation trend of the pavement structure under the influence of long-term use and environmental factors. SUMMARY

[0003] To solve the above technical problems, the application embodiment provides a pavement structure strength evaluation method based on a high-speed deflectometer, including the following steps:

[0004] Collecting the deformation velocity (Vy) and vehicle driving speed (Vx) of the pavement in the vehicle driving process by using the high-speed deflectometer;

[0005] Calculating the pavement deflection slope by the formula S=Vy / Vx, and forming a deflection slope curve;

[0006] Performing data processing on the deflection slope curve to extract feature parameters;

[0007] Based on the deflection slope and / or its derivative index, establishing a pavement layered structure strength evaluation system to evaluate the strength of at least one structure layer in the surface layer, base layer, subbase layer and roadbed.

[0008] Further, the vehicle driving speed (Vx) ranges from 20-100km / h, and the collected data needs to be screened before calculating the deflection slope to eliminate the data of the vehicle starting, accelerating and braking deceleration stages.

[0009] Further, the data screening needs to meet at least one of the following stability conditions:

[0010] The instantaneous vehicle speed is not less than 30km / h;

[0011] The absolute value of acceleration is not greater than 0.5m / s²;

[0012] The standard deviation of the speed within the sliding window is not greater than 1.5 km / h.

[0013] Further, the data processing step includes smoothing the deflection slope curve using a moving average method.

[0014] Further, the layered structure strength evaluation system characterizes the strength of different structure layers through the deflection slope indicators of different distance measuring points.

[0015] Further, the layered structure strength evaluation system includes:

[0016] The deflection slope (S10) at a distance of 10 cm from the load center is used to represent the surface layer structure strength.

[0017] The deflection slope (S30) at a distance of 30 cm from the load center is used to represent the base layer structure strength.

[0018] The deflection slope (S90) at a distance of 90 cm from the load center is used to represent the subbase layer structure strength.

[0019] The deflection slope (S150) at a distance of 150 cm from the load center is used to represent the subgrade structure strength.

[0020] Further, the evaluation system also includes the first order change rate (gradient) and / or the second order change rate (curvature) of the deflection slope, wherein the gradient is used to reflect the sudden change of the structure layer strength, and the curvature is used to represent the sensitivity of the structure damage.

[0021] Further, the evaluation system also includes calculating the "layered strength degradation rate" to quantitatively evaluate the degree of deterioration of the road segment structure strength.

[0022] Further, the layered strength degradation rate is calculated by comparing the deflection slope indicators of the measured road segment with the deflection slope reference values of the reference road segment, wherein the reference road segment is a hard shoulder or a road segment repaired after structural maintenance.

[0023] Further, the deflection slope and / or its derivative indicators are included as input features, and the structure layer modulus inversion is performed through a machine learning model, wherein the mapping relationship between the deflection slope and the structure layer modulus is established and calibrated by combining laboratory tests, finite element simulations, and regression modeling.

[0024] The beneficial effects of the present application are:

[0025] The application provides a pavement structure strength evaluation method based on a high-speed deflection instrument.

[0026] The application establishes a high-precision mapping relationship between evaluation indexes and actual moduli of structure layers by combining finite element simulation, indoor tests and artificial intelligence models, and has dynamic calibration capability, so as to ensure the adaptability and accuracy of evaluation results under different engineering and environmental conditions. BRIEF DESCRIPTION OF DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0028] Figure 1 It is a schematic diagram of high-speed deflection instrument data acquisition;

[0029] Figure 2 It is a measured deflection slope graph of high-speed deflection instrument;

[0030] Figure 3 It is S10 data of different lanes of a measured road section;

[0031] Figure 4 It is S30 data of different lanes of a measured road section. DETAILED DESCRIPTION

[0032] In order to make the application purposes, features and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings of the embodiments of the present application. Obviously, the following described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0033] The application will be further illustrated in combination with the drawings and specific embodiments.

[0034] Embodiment 1

[0035] The embodiment provides a pavement structure strength evaluation method based on a high-speed deflection instrument, and the specific method is as follows:

[0036] The road surface was inspected using a high-speed deflectometer. To ensure data quality, key equipment parameters were set, including a sampling frequency of no less than 100kHz for the laser vibrometer, to guarantee sufficient spatiotemporal resolution to identify the responses of different structural layers. During the inspection, the system synchronously acquired two core data streams in real time: the instantaneous road surface deformation velocity Vy at each laser vibrometer measuring point, and the instantaneous vehicle speed Vx.

[0037] To ensure the accuracy of subsequent calculations, the collected raw data must be screened to remove interfering data generated during unstable driving conditions (such as starting, acceleration, braking, and deceleration). This screening process is achieved by establishing a mathematical model that must simultaneously satisfy the following three stability conditions:

[0038] Speed ​​limit condition: The instantaneous vehicle speed Vx must not be lower than a preset threshold, such as 30 km / h.

[0039] Acceleration constraints: Calculate the instantaneous acceleration using first-order difference and ensure that its absolute value is within the allowable range, for example, not exceeding 0.5 m / s².

[0040] Speed ​​fluctuation conditions: A sliding window is used to perform standard deviation analysis on the speed data to identify and eliminate sections with localized severe fluctuations. For example, the standard deviation of speed within the window is required to be no greater than 1.5 km / h.

[0041] For the selected valid data points, the deflection slope S of the pavement at that measuring point is calculated using the physical formula S=Vy / Vx. Connecting the deflection slope values ​​of consecutive measuring points forms a deflection slope curve. To suppress the interference of random noise on the identification of structural strength change trends, the curve needs to be smoothed. This embodiment uses the moving average method, and this processing is accomplished by setting an appropriate window size. The specific method is as follows:

[0042]

[0043] Where N is the window size, and in this invention, N is 10.

[0044] Based on the above data processing results, this embodiment further constructs a layered strength evaluation system based on the deflection slope index of fixed measuring points. This system utilizes the physical principle that the deflection response depth varies at measuring points at different distances to correlate the deflection slope index at a specific location with the strength of a specific structural layer.

[0045] S10 (deflection slope at 10cm from the load center): used to characterize the structural strength of the asphalt surface layer;

[0046] S30 (deflection slope at 30cm from load center): used to represent the structural strength of semi-rigid base;

[0047] S90 (deflection slope at 90cm from load center): used to represent the structural strength of sub-base;

[0048] S150 (deflection slope at 150cm from load center): used to represent the structural strength of subgrade.

[0049] It should be noted that these index parameters are optimized by finite element simulation and sensitivity analysis, and the larger the value, the worse the corresponding structural layer strength.

[0050] To more comprehensively evaluate the pavement structure state, the first and second order change rates are introduced on the basis of the deflection slope:

[0051] Deflection slope gradient (first order change rate) : used to identify spatial mutations of structural layer strength, which can effectively locate the boundaries of structural weak points or potential diseases;

[0052] Deflection slope curvature (second order change rate) : this index is more sensitive to structural damage, and can be used to represent the sensitivity and development trend of structural damage.

[0053] In addition, the concept of "layered strength degradation rate" is introduced, which compares the indicators of the measured road section with the reference values of a state-perfect reference road section (such as a hard shoulder or a newly repaired road section), so as to quantitatively evaluate the deterioration degree of each structural layer. The layered strength degradation rate is specifically represented as:

[0054]

[0055] Wherein is the deflection slope reference value of the reference road section.

[0056] The above deflection slope index (Si), gradient index (Gi) and curvature index (Ci) are used as input characteristic variables, and are applied to a structure modulus inversion model based on machine learning or artificial neural network. The model is calibrated by combining the material parameters obtained from laboratory tests, the theoretical responses calculated by finite element simulation, and the regression modeling technology, so as to realize high-precision mapping from surface response index to internal structure layer modulus.

[0057] The following gives a plurality of groups of embodiments, which aims to verify that the method proposed in the present application can effectively distinguish and evaluate the structural strength difference between different lanes on the same road section caused by traffic load difference.

[0058] Example 2:

[0059] The pavement structure of the test section is 18 cm asphalt surface layer (4 cm modified SMA-13 + 6 cm modified SUP-20 + 8 cm ordinary SUP-25), 40 cm cement stabilized gravel base, 20 cm lime-soil stabilized soil bottom base, high-speed deflection meter 70 km / h stable driving, A, B, C three sections are hard shoulder, one lane, two lanes respectively, the length of the section is 200 m, and the deflection slope index (0.01 mm / m) is as follows:

[0060] Table 1: Comparison table of deflection slope index of different lanes

[0061] Surface course structure strength index S10 (0.01 mm / m) Base course structure strength index S30 (0.01 mm / m) Subbase course structure strength index S90 (0.01 mm / m) Subgrade course structure strength index S150 (0.01 mm / m) A 2.122 1.883 1.316 0.981 B 3.561 2.771 1.923 0.852 C 4.867 3.823 1.856 0.766

[0062] It can be seen that the strength of the hard shoulder pavement structure is good, and the two-lane structure is weaker than the one-lane structure due to the frequent driving of heavy vehicles.

[0063] Example 3:

[0064] The pavement structure of the test section is 18 cm asphalt surface layer (4 cm modified SMA-13 + 6 cm modified SUP-20 + 8 cm ordinary AC-25I), 38 cm cement stabilized gravel base, 20 cm lime-soil stabilized soil bottom base, high-speed deflection meter 80 km / h stable driving, A, B two sections are crack dense section and crack non-dense section respectively, the length of the section is 800 m, and the deflection slope index (0.01 mm / m) is as follows:

[0065] Table 2: Comparison table of deflection slope index of different pavement conditions

[0066] Surface course structure strength index S10 (0.01 mm / m) Base course structure strength index S30 (0.01 mm / m) Subbase course structure strength index S90 (0.01 mm / m) Subgrade course structure strength index S150 (0.01 mm / m) A 5.231 2.337 1.215 0.897 B 2.368 2.132 1.343 0.916

[0067] It can be seen that the surface layer structure strength index S10 can better distinguish the bearing capacity of the surface layer structure, and the surface layer structure strength index of the crack dense section is much larger than that of the non-crack dense section, and the structure strength is poor, and the structure strength of the remaining layers is similar.

[0068] Example 4:

[0069] The pavement structure of the detection section A is 18 cm asphalt surface layer (4 cm modified AK-13A + 6 cm modified AC-20I + 8 cm ordinary AC-25I), 40 cm water-stable macadam, and 20 cm lime-soil bottom base; the pavement structure of the detection section B is 10 cm asphalt surface layer (4 cm SMA-13 + 6 cm AC-20), 26 cm continuously reinforced cement concrete pavement, 20 cm water-stable base, and 20 cm lime-soil bottom base; and the pavement structure of the detection section C is 18 cm asphalt surface layer (4 cm SMA-13 + 6 cm AC-20 + 8 cm AC-25), 18 cm ATB-25 + 9 cm rich-oil asphalt fatigue layer + 16 cm graded gravel bottom base. The lengths of the three sections A, B and C are all 600 m, and the deflection slope indices (0.01 mm / m) thereof are as shown in the following table:

[0070] Table 3: Comparison table of deflection slope indices of different pavement structures

[0071] Surface course structure strength index S10 (0.01 mm / m) Base course structure strength index S30 (0.01 mm / m) Subbase course structure strength index S90 (0.01 mm / m) Subgrade course structure strength index S150 (0.01 mm / m) A 2.158 1.987 1.315 0.787 B 3.216 1.132 1.241 0.826 C 2.236 3.651 1.982 0.963

[0072] It can be seen that the base structure strength index S30 can better distinguish different pavement structures, and the flexible base has a larger S30 value and relatively weak structure strength.

[0073] The above description is only the preferred embodiment of the present application, and is not intended to limit the present application in other forms. Any skilled person in the art can modify or change the above disclosed technical content into equivalent embodiments. However, any simple modification, equivalent change and modification made according to the technical essence of the present application to the above embodiments, without departing from the technical scheme of the present application, still falls within the protection scope of the present application.

Claims

1. A method for evaluating strength of a pavement structure based on a high-speed deflection meter, characterized by, The method comprises the following steps: Collecting the deflection velocity (Vy) and vehicle speed (Vx) of the road surface during vehicle driving by using a high-speed deflectometer; Calculating the deflection slope of the road surface according to the formula S=Vy / Vx, and forming a deflection slope curve; Processing the deflection slope curve to extract characteristic parameters; Based on the deflection slope and / or its derivative index, an evaluation system of the strength of the layered structure of the road surface is established to evaluate the strength of at least one structural layer in the surface layer, base layer, subbase layer and roadbed.

2. The method of claim 1, wherein, The vehicle driving speed (Vx) ranges from 20 to 100 km / h, and before calculating the deflection slope, the collected data needs to be screened to eliminate the data of the vehicle starting, accelerating and decelerating stages.

3. The method of claim 2, wherein, The data screening needs to meet at least one of the following stability conditions: The instantaneous vehicle speed is not less than 30 km / h; The absolute value of the acceleration is not greater than 0.5 m / s²; The speed standard deviation in the sliding window is not greater than 1.5 km / h.

4. The method of claim 1, wherein, The data processing step includes smoothing the deflection slope curve by using a moving average method.

5. The method of claim 1, wherein, The layered structure strength evaluation system represents the strength of different structural layers through the deflection slope indexes of different distance measuring points.

6. The method of claim 5, wherein, The layered structure strength evaluation system comprises: The deflection slope (S10) at a distance of 10 cm from the load center is used to represent the strength of the surface layer structure; The deflection slope (S30) at a distance of 30 cm from the load center is used to represent the strength of the base layer structure; The deflection slope (S90) at a distance of 90 cm from the load center is used to represent the strength of the subbase layer structure; The deflection slope (S150) at a distance of 150 cm from the load center is used to represent the strength of the roadbed structure.

7. The method according to claim 1 or 5, characterized in that, The evaluation system also includes the first-order change rate (gradient) and / or the second-order change rate (curvature) of the deflection slope, wherein the gradient is used to reflect the sudden change of the structural layer strength, and the curvature is used to represent the sensitivity of the structural damage.

8. The method of claim 1, wherein, The evaluation system also includes calculating the "layered strength degradation rate" to quantitatively evaluate the degree of deterioration of the structural strength of the road section.

9. The method of claim 8, wherein, The layered strength degradation rate is calculated by comparing the deflection slope index of the measured road section with the deflection slope benchmark value of the reference road section, wherein the reference road section is a hard shoulder or a road section repaired by structural maintenance.

10. The method of claim 1, wherein, The method also includes using the deflection slope and / or its derivative index as input features to perform structural layer modulus inversion through a machine learning model, wherein the mapping relationship between the deflection slope and the structural layer modulus is established and calibrated by combining laboratory tests, finite element simulations and regression modeling.

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