A method, equipment, and medium for detecting the development degree of asphalt pavement bulging cracking.

Abstract

This invention discloses a method, equipment, and medium for detecting the development degree of asphalt pavement arching cracking, relating to the field of road maintenance. The method includes: acquiring deflection basin data at different test points on the road section to be tested; obtaining the subgrade modulus of each test point using the inertial point method based on the deflection basin data of each test point; inverting the base course modulus of each test point based on the deflection basin data and the subgrade modulus of each test point; and comprehensively calculating the base course modulus of each test point to obtain a representative value of the base course modulus used to characterize the development degree of arching cracking in the road section to be tested. This invention, based on deflection basin data, uses the inertial point method to apply the deflection basin data to the inversion of the pavement structural layer modulus, realizing the detection of the development degree of asphalt pavement arching cracking. The detection results can be used to guide the treatment of arching cracking and pavement maintenance, reducing maintenance costs.

Description

Technical Field

[0001] This invention relates to the field of road maintenance, and in particular to a method, equipment and medium for detecting the degree of development of asphalt pavement arching and cracking. Background Technology

[0002] The arid and temperature-varying geographical and climatic conditions lead to frequent arching and cracking defects in semi-rigid base asphalt pavements, placing enormous pressure on road maintenance departments. These defects mainly occur in sections with long base layers, manifesting as overall arching and damage from the base layer to the surface layer. The significant arching height and density affect driving comfort and pose a serious safety threat to vehicles traveling at high speeds.

[0003] Current research on bulging cracking in asphalt pavements mainly focuses on the development mechanism of bulging cracking, the investigation and analysis of its causes, and prevention and treatment measures. Studies indicate that bulging cracking in semi-rigid base asphalt pavements primarily originates from the bulging of the base layer, ultimately leading to bulging and cracking of the surface layer. Regarding the investigation and analysis of the causes of bulging cracking, research points out that the main factors influencing bulging cracking in asphalt pavements include temperature changes, high strength of the water-stabilized base layer, salt expansion, construction techniques, and the construction season. In the research on prevention and treatment measures, bulging cracking prevention mainly involves measures taken before road paving is completed, involving pavement materials, pavement structure design, and pavement construction plans. For cases already affected by bulging cracking, treatment measures generally include a combination of methods such as cutting, excavation, and milling.

[0004] However, arch cracking originates from the base course and is considered a hidden structural layer defect before it develops to the asphalt surface layer. Damage to this hidden structural layer cannot be directly observed with the naked eye, making it impossible to visually detect and assess arch cracking in its early stages. Furthermore, surface cracking caused by arching exhibits similar characteristics to surface cracking caused by other factors; therefore, even if surface cracking occurs in the early stages of arch cracking, it is impossible to determine whether the cracking is due to base course arching. Current research has not established a complete evaluation system for the development degree of arch cracking, making accurate detection in its early stages impossible. This also hinders the timely implementation of preventative maintenance to prevent further deterioration of arch cracking. Therefore, there is an urgent need to develop a method to detect the development degree of arch cracking in asphalt pavements, enabling the implementation of preventative maintenance measures at appropriate times to accurately guide the treatment and maintenance of arch cracking, effectively reducing maintenance costs. Summary of the Invention

[0005] The purpose of this invention is to provide a method, equipment, and medium for detecting the development degree of asphalt pavement bulging cracking, which can realize the detection of the development degree of asphalt pavement bulging cracking, so as to guide the treatment of bulging cracking and pavement maintenance, and reduce maintenance costs.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A method for detecting the development degree of bulging cracking in asphalt pavement, the method comprising:

[0008] Acquire deflection basin data at different detection points on the road section to be tested;

[0009] Based on the deflection basin data at each test point, the soil modulus at each test point is obtained using the inertia point method.

[0010] Based on the deflection basin data and subgrade modulus of each test point, the base course modulus of each test point is obtained by inversion.

[0011] The base modulus of each test point is comprehensively calculated to obtain a representative value of the base modulus used to characterize the degree of arching and cracking disease development in the road section under test.

[0012] Optionally, the deflection basin data at any detection point includes: n average deflection data, wherein the i-th average deflection data is obtained by averaging the deflection data measured by the i-th deflection sensor configured in the falling weight deflectometer when the falling weight deflectometer performs the second to the Mth falling weight at the detection point, i = 1, 2, ..., n, where n is the number of deflection sensors configured in the falling weight deflectometer.

[0013] Optionally, based on the deflection basin data at each testing point, the inertial point method is used to obtain the soil modulus at each testing point, specifically including:

[0014] Based on the deflection basin data of each detection point, a deflection curve is constructed for each detection point; the deflection curve is a curve relating distance information and deflection, where the distance information is the distance between the deflection sensor and the detection point;

[0015] Based on the deflection curve of each test point and the regression equation of the inertia point, the subgrade modulus of the road section to be tested is solved by the iterative method.

[0016] Optionally, the regression equation for the inertial point is:

[0017] R c = f(H, E0);

[0018] D c =g(H,E0);

[0019] Among them, R cD is the distance from the inert point to the detection point. c Let H be the deflection at the inertial point, H be the subgrade thickness of the road section to be tested, E0 be the subgrade modulus, f() be the distance regression equation at the inertial point, and g() be the deflection regression equation at the inertial point.

[0020] Optionally, based on the deflection curve of each detection point and the regression equation of the inertia point, the subgrade modulus of the road section to be tested is solved using an iterative method, specifically including:

[0021] An iterative optimization algorithm is used to determine the soil modulus corresponding to the inertial point closest to the deflection curve of the detection point as the soil modulus of the detection point.

[0022] Optionally, based on the deflection basin data and subgrade modulus of each testing point, the base course modulus of each testing point can be obtained by inversion, specifically including:

[0023] With the goal of minimizing the root mean square error, the base modulus of each test point is optimized and solved based on the deflection basin data and subgrade modulus of each test point.

[0024] The function for calculating the root mean square error is:

[0025]

[0026] Among them, D i，实测 Let D be the i-th average deflection data in the deflection basin data. i，计算 The distance detection point d is calculated based on the modulus calculation formula. i The deflection value at d i The distance between the i-th deflection sensor configured for the falling weight deflectometer and the detection point.

[0027] Optionally, the base modulus of each test point is comprehensively calculated to obtain a representative value of the base modulus used to characterize the degree of arching cracking in the tested road section, specifically including:

[0028] The average value of the base modulus at each test point is calculated using the following formula, and is used as the representative value of the base modulus of the road section to be tested.

[0029]

[0030] Among them, E 2代表值 E represents the base modulus of the road section to be tested. 2k Let K be the base modulus of the k-th detection point in the road segment to be tested, where K is the number of detection points in the road segment to be tested.

[0031] Optionally, the base modulus of each test point is comprehensively calculated to obtain a representative value of the base modulus used to characterize the degree of arching cracking in the road section under test. This also includes:

[0032] Based on the range of the representative value of the base modulus used to characterize the degree of arching cracking in the road section under test, a maintenance strategy for the road section under test is formulated.

[0033] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.

[0034] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0035] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0036] This invention provides a method, equipment, and medium for detecting the development degree of asphalt pavement arching cracking. The method includes: acquiring deflection basin data at different test points on the road section to be tested; obtaining the subgrade modulus of each test point using the inertial point method based on the deflection basin data; inverting the base course modulus of each test point based on the deflection basin data and the subgrade modulus; and comprehensively calculating the base course modulus of each test point to obtain a representative value of the base course modulus used to characterize the development degree of arching cracking in the road section to be tested. This invention utilizes the inertial point method based on deflection basin data to invert the modulus of the pavement structural layers, thus realizing the detection of the development degree of asphalt pavement arching cracking. The detection results can be used to guide the treatment of arching cracking and pavement maintenance, reducing maintenance costs. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 A flowchart of a method for detecting the development degree of asphalt pavement bulging cracking disease provided in an embodiment of the present invention;

[0039] Figure 2 A schematic diagram illustrating the principle of a method for detecting the development degree of asphalt pavement arching cracking defects according to an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of the road surface structure provided in an embodiment of the present invention;

[0041] Figure 4This is a schematic diagram of the base modulus test results for road section 1 provided in an embodiment of the present invention;

[0042] Figure 5 This is a schematic diagram of the base modulus test results for road section 2 provided in an embodiment of the present invention;

[0043] Figure 6 This is a schematic diagram of the base modulus test results for road segment 3 provided in an embodiment of the present invention;

[0044] Figure 7 This is a schematic diagram of the base modulus test results for road section 4 provided in an embodiment of the present invention;

[0045] Figure 8 This is a schematic diagram of the base modulus test results for road segment 5 provided in an embodiment of the present invention;

[0046] Figure 9 A schematic diagram illustrating the maintenance strategy provided in an embodiment of the present invention;

[0047] Figure 10 An internal structural diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] The purpose of this invention is to provide a method, equipment, and medium for detecting the development degree of asphalt pavement bulging cracking, which can realize the detection of the development degree of asphalt pavement bulging cracking, so as to guide the treatment of bulging cracking and pavement maintenance, and reduce maintenance costs.

[0050] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0051] Example 1

[0052] like Figure 1 and Figure 2 As shown in Example 1, this method provides a method for detecting the degree of development of asphalt pavement arching cracking, the method comprising:

[0053] Step 101: Obtain deflection basin data at different detection points on the road section to be tested.

[0054] In this embodiment of the invention, the deflection basin data at any detection point includes: n average deflection data, wherein the i-th average deflection data is obtained by averaging the deflection data measured by the i-th deflection sensor configured in the falling weight deflectometer when the falling weight deflectometer performs the second to the Mth falling weight at the detection point, i = 1, 2, ..., n, where n is the number of deflection sensors configured in the falling weight deflectometer.

[0055] For example, a fully automatic falling weight deflectometer is used to detect the surface deflection basin of the road section under inspection, with a detection length of no less than 1 km. A detection point is established every 20 to 50 meters; the specific spacing can be adjusted flexibly according to the actual situation. The falling weight deflectometer should be equipped with at least 5 deflection sensors, and the sensors should be in good working order and the detection data should be normal. Record the diameter of the bearing plate and the specific distance of each deflection sensor from the center of the bearing plate. At the same detection point, four falling weight operations are required. The first operation is a test, and no deflection data is recorded. For the next three falling weight operations, the deflection data of each sensor should be recorded separately. The average of the three measurements from each sensor is taken to obtain the deflection basin value for that detection point.

[0056] Step 102: Based on the deflection basin data of each test point, the soil modulus of each test point is obtained using the inertial point method.

[0057] Based on the collected pavement structure information of the inspected road section, the pavement structure layers are determined, such as... Figure 3 As shown, it can generally be divided into surface layer, base layer and subgrade. For the same pavement structure, the larger the modulus of the surface layer and base layer, the flatter the deflection basin; conversely, the steeper the deflection basin, so the two deflection basins will inevitably intersect at a point. At this intersection point, the deflection is equal and is independent of the modulus of the surface layer and base layer, and this point is defined as the inertia point. The inertia point is only related to the pavement thickness and the subgrade modulus. Therefore, in the deflection basin curve, the distance from the inertia point to the load center (i.e., the test point) and the deflection at the inertia point can be represented by equations (1) and (2).

[0058] R c =f(H,E0) (1)

[0059] D c =g(H,E0) (2)

[0060] Among them, R c D is the distance from the inert point to the detection point. c Let H be the deflection at the inertial point, H be the subgrade thickness of the road section to be tested, E0 be the subgrade modulus, f() be the distance regression equation at the inertial point, and g() be the deflection regression equation at the inertial point.

[0061] Based on the collected pavement structure information, the pavement thickness is obtained, and equations (1) and (2) can be simplified to:

[0062] R c =f(E0) (3)

[0063] D c =g(E0) (4)

[0064] The soil modulus E0 is changed by using an iterative method, so that the calculated deflection D c The measured deflection (the value at the corresponding position on the deflection curve) is equal to the measured deflection. The soil modulus obtained under this condition is the inversion value of the soil modulus corresponding to this test point.

[0065] In this embodiment of the invention, step 102 specifically includes:

[0066] Based on the deflection basin data of each detection point, a deflection curve is constructed for each detection point; the deflection curve is a curve about distance information and deflection, and the distance information is the distance between the deflection sensor and the detection point; based on the deflection curve of each detection point and the regression equation of the inert point, the subgrade modulus of the road section to be tested is solved by the iterative method, and the regression equation includes formulas (3) and (4).

[0067] For example, the specific form of the regression equation can be obtained by function fitting or training on existing data.

[0068] In the process of solving the subgrade modulus of the road section to be tested using an iterative method based on the deflection curve of each test point and the regression equation of the inertial point, this embodiment of the invention uses an iterative optimization algorithm to determine the subgrade modulus corresponding to the inertial point closest to the deflection curve of the test point as the subgrade modulus of the test point. This iterative optimization algorithm can be a particle swarm optimization algorithm.

[0069] Step 103: Based on the deflection basin data and subgrade modulus of each test point, the base course modulus of each test point is obtained by inversion.

[0070] In this embodiment of the invention, firstly, the trial calculation range E of the initial simulated surface layer is determined. a1 ~E a2 The trial calculation range at the grassroots level is E. b1 ~E b2 By adjusting the surface layer modulus and the base layer modulus, the root mean square error (RMSE) of the theoretically calculated deflection and the measured deflection at the test point is minimized. The calculation method of the root mean square error is shown in Equation (5). The point with the smallest RMSE corresponds to E a and E b These are the surface layer modulus and base layer modulus obtained through inversion.

[0071]

[0072] Where RMSE is the root mean square error, D i，实测Let D be the i-th average deflection data in the deflection basin data. i，计算 The distance detection point d is calculated based on the modulus calculation formula. i The deflection value at d i The distance between the i-th deflection sensor configured for the falling weight deflectometer and the detection point, where n is the number of deflection sensors configured for the falling weight deflectometer.

[0073] Based on the theory of elastic layered systems, the distance d from the center axis of the load-bearing surface is calculated using formulas (6) and (7). i The formula for calculating the deflection, or modulus, at a given point is:

[0074]

[0075] Among them, D i,计算 The distance detection point d is calculated based on the modulus calculation formula. i The deflection values ​​at the points, p,δ are the tire contact pressure and equivalent circle radius under standard axle load, h1,h2,…,h m-1 Let E0, E1, E2, E3, ..., E be the thickness of each structural layer. m-1 The modulus of each structural layer, Let d be the distance to the detection point. i The deflection coefficient at point f is an integral containing the Bessel function.

[0076] In formulas (6) and (7), the calculated deflection is unknown, the tire ground pressure and equivalent circle radius of the standard axle load are known, the thickness of each structural layer is known, and the f() function is known. Based on formula (7), the deflection coefficient can be obtained through the surface layer modulus and the base layer modulus, and then the calculated deflection value can be obtained through formula (6).

[0077] Step 104: Perform a comprehensive calculation on the base modulus of each test point to obtain a representative value of the base modulus used to characterize the degree of arching and cracking disease development in the road section under test.

[0078] The surface layer modulus and base layer modulus of each test point are obtained using the above method. The average value of the base layer modulus of each test point is then used to obtain the representative value of the base layer modulus of the tested road section, as shown in equation (8).

[0079]

[0080] Among them, E 2代表值 E represents the base modulus of the road section to be tested. 2k Let K be the base modulus of the k-th detection point in the road segment to be tested, where K is the number of detection points in the road segment to be tested.

[0081] The method of the present invention further includes:

[0082] Step 105: Based on the range of the representative value of the base modulus used to characterize the degree of arching cracking disease development in the road section to be tested, formulate a maintenance strategy for the road section to be tested.

[0083] The degree of asphalt pavement arching cracking is evaluated by using the representative value of the base modulus of the test section obtained from the back calculation of the road surface deflection basin. Arching is accompanied by crack formation. Based on the characteristics of arching, including the spacing and height of the arches and the spacing of the cracks, the degree of arching cracking is classified into four levels: no arching, slight arching, moderate arching, and severe arching. The classification of arching cracking at each level is shown in Table 1.

[0084] Table 1. Classification and Judgment Methods for the Degree of Arch Development

[0085]

[0086]

[0087] The representative value of the base modulus of the tested road section is used as an evaluation index to determine the degree of arching crack development. The specific determination method is as follows:

[0088] When the representative value of the base modulus is less than 20,000 MPa, it indicates that the pavement condition is good, and the degree of asphalt pavement arching and cracking development is determined to be no arching; when the representative value of the base modulus is between 20,000 MPa and 30,000 MPa, the degree of asphalt pavement arching and cracking development is determined to be slight arching; when the representative value of the base modulus is between 30,000 MPa and 40,000 MPa, the degree of asphalt pavement arching and cracking development is determined to be moderate arching; when the representative value of the base modulus is greater than or equal to 40,000 MPa, the degree of asphalt pavement arching and cracking development is determined to be severe arching.

[0089] Maintenance strategies for asphalt pavement bulging cracking:

[0090] Maintenance strategies are determined based on the evaluation results of the development degree of asphalt pavement bulging and cracking. When the bulging and cracking development degree is determined to be no bulging, normal pavement maintenance is performed; when the bulging and cracking development degree is determined to be slight bulging, preventive maintenance is performed; when the bulging and cracking development degree is determined to be moderate bulging, targeted maintenance is performed; and when the bulging and cracking development degree is determined to be severe bulging, major overhaul of the pavement structure is required. The specific measures for normal pavement maintenance, preventive maintenance, targeted maintenance, and major overhaul of the pavement structure are as follows.

[0091] Routine maintenance: cleaning up road surface pollution, handling snowfall in winter, etc.

[0092] Preventive maintenance: A pre-cut joint scheme is adopted for treatment. Pre-cut joints are set every 50m to 100m, and the joints are filled with asphalt sand.

[0093] Targeted maintenance: Milling is used to treat the arched parts to ensure that the road surface is smooth after treatment.

[0094] Major overhaul of the road structure: The asphalt surface layer within 1.5m on both sides of the damaged area was removed; the water-stabilized base course within 1m on both sides of the damaged area was removed; the surface of the subbase was cleaned and moistened; 4cm thick polystyrene boards were placed on both sides of the base course; water-stabilized gravel was filled in 2-3 layers; asphalt sand was used to fill the joints; and finally, the surface course was repaved to ensure road thickness and smoothness. This comprehensive maintenance strategy effectively ensured the stability and smoothness of the road surface.

[0095] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0096] 1. In practical engineering applications, fully automatic falling weight deflectometers are generally only used to detect the surface deflection of structural layers, resulting in low utilization of the information from the test results. This invention, however, builds upon this by fully utilizing the test results of multi-point deflection to obtain deflection basin data at the test location. It then employs a combination of the inertial point method and the deflection matching method to apply the deflection basin data to the modulus inversion of the pavement structural layer. This fully utilizes the information from the test results, effectively improving testing time and efficiency, and providing a more accurate and effective means for pavement quality assessment.

[0097] 2. The evaluation of the development degree of arching cracking in asphalt pavement based on the representative value of the base modulus fills the gap in the evaluation method of arching cracking development degree and solves the problem of not being able to accurately identify arching cracking in the hidden structural layer.

[0098] 3. By assessing the degree of asphalt pavement arching and cracking development, the maintenance needs of the pavement can be determined. This allows for effective preventative maintenance of pavement arching and cracking defects, significantly reducing pavement maintenance and repair costs.

[0099] To illustrate the implementation process and effects of the method of the present invention, the embodiments of the present invention also provide the following examples:

[0100] Example 1

[0101] First, the road sections to be inspected are identified, and pavement structure information is collected, including the material and thickness of each structural layer. In this example, two road sections, section 1 and section 2, are selected for inspection within the range of K1418-K1498 of the Xinjiang Kashi-Yemo Expressway. Through on-site investigation and data collection, the structural layer information of the pavement to be inspected is obtained as follows: Figure 3 As shown.

[0102] Secondly, a fully automatic falling weight deflectometer was used to perform surface deflection basin tests on the tested road sections. Before testing, the road surface was cleaned to ensure flatness; during testing, traffic was directed to ensure the safety of testing personnel and vehicles. A testing point was established every 50 meters. Four falling weight tests were performed at the same testing point. The first test was a pre-test, and no deflection data was recorded. The subsequent three tests recorded the deflection data from each sensor. The average of the three sets of data was used as the final deflection basin test data for that testing point. In this example, the deflection basin test used a Beijing Luxing falling weight automatic deflectometer, model FWD-150, with nine sensors. The distances of each sensor from the center of the bearing plate were 0cm, 30cm, 45cm, 60cm, 90cm, 123cm, 156cm, 188cm, and 221cm, respectively, and the radius of the bearing plate was 15cm. The tested deflection data for road sections 1 and 2 are shown in Tables 2 and 3.

[0103] Table 2 shows the measured deflection results of section 1 of the road.

[0104]

[0105]

[0106]

[0107] Table 3 shows the measured deflection results of section 2 of the road.

[0108]

[0109]

[0110]

[0111] Secondly, based on the pavement deflection basin test data, the modulus of each pavement structural layer and the subgrade is back-calculated. During the back-calculation of the modulus of each structural layer, according to... Figure 3 The pavement structure information is used to divide the inspected pavement into three layers: surface layer, base layer, and subgrade. Based on the surface deflection basin data and the regression equation of the inertial points, the subgrade modulus E0 is obtained using an iterative method. The trial calculation range for the asphalt layer and base layer moduli is then determined. By adjusting the surface layer and base layer moduli, the root mean square error (RMSE) between the theoretically calculated and measured deflection values ​​at each inspection point is minimized. The surface layer and base layer moduli corresponding to the point with the smallest RMS error are the inverted surface layer and base layer moduli.

[0112] Figure 4 and Figure 5The base modulus is calculated based on the deflection at each monitoring point in road segment 1 and road segment 2. The average base modulus of all monitoring points in each road segment is calculated to obtain the representative values ​​of the base modulus of road segment 1 and road segment 2 as 16520.7MPa and 16231.8MPa, respectively.

[0113] Furthermore, the representative value of the base modulus was used to evaluate the degree of bulging cracking in asphalt pavement. Based on bulging and crack characteristics, the degree of bulging cracking in asphalt pavement was divided into four levels: no bulging, slight bulging, moderate bulging, and severe bulging. Corresponding maintenance strategies were determined based on the degree of bulging cracking development in each road segment. The classification, discrimination method, and corresponding maintenance strategies for the degree of bulging cracking development are shown in Table 4. From the representative values ​​of the base modulus of road segments 1 and 2, it can be concluded that the degree of bulging cracking development in both road segments belongs to the no-bulging stage.

[0114] Table 4. Classification and identification methods of arch development degree and corresponding maintenance strategies

[0115]

[0116] The maintenance process includes: Regular road surface maintenance (cleaning up road surface contamination, snow removal in winter, etc.); Preventative maintenance (pre-cut joints are installed every 50m-100m, with asphalt sand filling the joints); Targeted maintenance (milling up bulges to ensure a smooth road surface); Major road structure overhaul (removing the asphalt surface layer within 1.5m on both sides of the affected area, removing the water-stabilized base course within 1m on both sides of the affected area, cleaning and moistening the subbase surface, placing 4cm thick polystyrene boards on both sides of the base course, filling with water-stabilized gravel in 2-3 layers, filling the joints with asphalt sand, and finally repaving the surface course to ensure road thickness and smoothness).

[0117] Finally, the pavement maintenance strategy was determined based on the assessment results of the degree of arching and cracking development. Table 4 shows that normal pavement maintenance is sufficient for sections 1 and 2. The assessment results were compared with the survey results, and the comparison results are as follows: Figure 8 As shown in the figure. The comparison results show that the assessment of the degree of pavement arching cracking development based on the representative value of the modulus matches the actual degree of arching cracking development.

[0118] Example 2

[0119] To verify the above-mentioned method for evaluating the development degree of asphalt pavement bulging cracking, the same testing equipment as in Example 1 was used to conduct deflection basin tests on the Xinjiang Kayemo Expressway K1418-K1420 (section 3). Information on each pavement structural layer is as follows: Figure 2 As shown.

[0120] Based on the surface deflection basin test data, the back calculation of the modulus of each structural layer of the pavement and the subgrade is performed. Figure 6 The base modulus is calculated based on the deflection at each monitoring point in section 3. The average value of the base modulus at all monitoring points in section 3 is averaged to obtain a representative value of 24053 MPa for the base modulus of section 3.

[0121] The representative value of the base modulus was used to evaluate the degree of bulging cracking in asphalt pavement. According to the bulging cracking development degree discrimination method in Table 4, the bulging cracking development degree of section 3 can be judged to be in the slight bulging stage. Actual survey results show that there is no bulging on the surface of this section, only a few cracks. Core drilling revealed that the asphalt surface core sample was generally intact, the base layer at the bulging area was broken, the adhesion between the cement-stabilized crushed stone upper and lower base layers was poor, and the cement-stabilized crushed stone lower base layer was broken.

[0122] The pavement maintenance strategy was determined based on the assessment results of the degree of arching and cracking development. Table 4 shows that section 3 requires preventative maintenance, which will be addressed using a pre-cut joint scheme. Pre-cut joints will be installed every 50m to 100m, and the joints will be filled with asphalt sand. This example demonstrates that for minor arching and cracking defects, there is no difference between the surface cracking and normal pavement cracking, making it impossible to determine whether arching has occurred. However, evaluating the degree of arching and cracking development based on the modulus representative value can effectively determine if arching has occurred in the base layer, facilitating early treatment of pavement arching and cracking and significantly reducing maintenance costs.

[0123] Example 3

[0124] The same testing equipment as in Example 1 was used to conduct deflection basin testing on the Xinjiang Kayemo Expressway from K1465 to K1463 (section 4). Information on each pavement structural layer is as follows: Figure 3 As shown.

[0125] Based on the surface deflection basin test data, the back calculation of the modulus of each structural layer of the pavement and the subgrade is performed. Figure 7 The base modulus is calculated based on the deflection at each monitoring point in section 4. The average value of the base modulus at all monitoring points in section 4 is calculated, and the representative value of the base modulus of section 4 is 32223.5 MPa.

[0126] The representative value of the base modulus was used to evaluate the degree of bulging cracking in asphalt pavement. According to the bulging cracking development degree discrimination method in Table 4, the bulging cracking development degree of section 4 can be judged to be in the medium bulging stage. Actual survey results show that the bulging height of section 4 is 1.5 cm, the average bulging spacing is 100 m, and transverse cracks penetrate the entire pavement. This assessment result is consistent with the actual survey results.

[0127] The pavement maintenance strategy was determined based on the assessment results of the degree of arching and cracking development. Table 4 shows that section 4 requires targeted maintenance, using milling to treat the arched parts and ensure a smooth pavement surface after treatment. This measure effectively prevents further aggravation of arching and cracking.

[0128] Example 4

[0129] The same testing equipment as in Example 1 was used to conduct deflection basin testing on the K1497-K1498 (section 5) of the Kayemo Expressway. The information of each pavement structural layer is as follows: Figure 3 As shown.

[0130] Based on the surface deflection basin test data, the back calculation of the modulus of each structural layer of the pavement and the subgrade is performed. Figure 8 The base modulus is calculated based on the deflection at each monitoring point in section 5. The average value of the base modulus at all monitoring points in section 5 is calculated, and the representative value of the base modulus of section 5 is 45033 MPa.

[0131] The representative value of the base modulus was used to evaluate the degree of bulging cracking in asphalt pavement. According to the bulging cracking development degree judgment method in Table 4, the bulging cracking development degree of section 5 can be judged to be in the severe bulging stage. Actual survey results show that the surface bulging height of section 5 is approximately 7.5 cm, and the average bulging spacing is approximately 10 m. This judgment result is consistent with the actual survey results.

[0132] The pavement maintenance strategy was determined based on the assessment results of the degree of arching and cracking development. Table 4 shows that section 5 requires major pavement structural repair. This involves removing the asphalt surface layer within 1.5m on both sides of the affected area, removing the water-stabilized base course within 1m on both sides of the affected area, cleaning and wetting the subbase surface, placing 4cm thick polystyrene boards on both sides of the base course, filling with water-stabilized gravel in 2-3 layers, filling the joints with asphalt sand, and finally repaving the surface course to ensure pavement thickness and smoothness. This maintenance strategy effectively ensures the stability and smoothness of the pavement.

[0133] Table 5. Results of the application of evaluation methods and maintenance strategies for the development degree of asphalt pavement bulging disease.

[0134]

[0135] Table 5 shows the results of using the evaluation method and maintenance strategy for the development degree of asphalt pavement bulging disease. In summary, this invention proposes a method for evaluating the development degree of asphalt pavement bulging cracking disease and corresponding maintenance strategies. In the embodiments, non-destructive testing technology was applied to collect deflection basin data from five different sections of the Xinjiang Kashi-Yemo Expressway, and modulus back-calculation was performed using the inertial point method and deflection matching method, successfully obtaining representative values ​​of the base modulus for each tested section. Figure 9The results show that the base modulus data obtained from the deflection basin back-calculation for sections with no or slight caving are relatively stable with low dispersion. However, the base modulus for sections with moderate or severe caving exhibits greater dispersion. Significant differences exist in the representative values ​​of base modulus for caving cracking defects of different developmental stages. The representative values ​​of base modulus can effectively evaluate the developmental stage of caving cracking in asphalt pavements and determine corresponding maintenance strategies. The evaluation method and maintenance strategy proposed in this invention can accurately identify caving cracking defects in hidden structural layers and implement preventative maintenance measures, thereby significantly reducing pavement maintenance costs.

[0136] Example 2

[0137] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method in Embodiment 1.

[0138] The internal structure diagram of this computer device can be as follows: Figure 10 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores pending transactions. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the asphalt pavement arching cracking disease development degree detection method in Example 1.

[0139] Example 3

[0140] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method in Embodiment 1.

[0141] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this invention are all information and data authorized by the object or fully authorized by all parties.

[0142] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided by this invention may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided by this invention may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0143] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0144] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for detecting the degree of development of bulging cracking in asphalt pavement, characterized in that, The method includes: Acquire deflection basin data at different detection points on the road section to be tested; Based on the deflection basin data at each test point, the soil modulus at each test point is obtained using the inertia point method. Based on the deflection basin data and subgrade modulus of each test point, the base course modulus of each test point is obtained by inversion. The base modulus of each test point is comprehensively calculated to obtain a representative value of the base modulus used to characterize the degree of development of arching cracking in the road section under test; Based on the deflection basin data at each testing point, the soil modulus at each testing point is obtained using the inertia point method, specifically including: Based on the deflection basin data of each detection point, a deflection curve is constructed for each detection point; the deflection curve is a curve relating distance information and deflection, where the distance information is the distance between the deflection sensor and the detection point; Based on the deflection curve of each detection point and the regression equation of the inertia point, the subgrade modulus of the road section to be tested is solved by iterative method. Based on the deflection basin data and subgrade modulus of each testing point, the base course modulus of each testing point is obtained by inversion, specifically including: With the goal of minimizing the root mean square error, the base modulus of each test point is optimized and solved based on the deflection basin data and subgrade modulus of each test point. The function for calculating the root mean square error is: ； in, The root mean square error, This represents the i-th average deflection data point in the deflection basin data. The distance detection point d is calculated based on the modulus calculation formula. i The deflection value at d i The distance between the i-th deflection sensor configured for the falling weight deflectometer and the detection point, where n is the number of deflection sensors configured for the falling weight deflectometer. The base modulus of each testing point is comprehensively calculated to obtain a representative value of the base modulus used to characterize the degree of arching cracking in the tested road section. This value includes: The average value of the base modulus at each test point is calculated using the following formula, and is used as the representative value of the base modulus of the road section to be tested. ； in, This represents the base modulus of the road section to be tested. The first section of the road to be tested k The base modulus at each testing point K This represents the number of testing points in the road section to be tested.

2. The method for detecting the degree of asphalt pavement bulging cracking as described in claim 1, characterized in that, The deflection basin data at any detection point includes: n average deflection data, where the i-th average deflection data is obtained by averaging the deflection data measured by the i-th deflection sensor configured in the falling weight deflectometer when the falling weight deflectometer performs the second to the Mth falling weight at the detection point, i=1,2,...,n, where n is the number of deflection sensors configured in the falling weight deflectometer.

3. The method for detecting the degree of asphalt pavement bulging cracking as described in claim 1, characterized in that, The regression equation for inertia points is: ； ； in, R c The distance from the inert point to the detection point. D c For the deflection at the inertia point, H The soil thickness of the road section to be tested. E 0 represents the soil modulus, f() represents the distance regression equation for the inert point, and g() represents the deflection regression equation for the inert point.

4. The method for detecting the degree of asphalt pavement bulging cracking as described in claim 3, characterized in that, Based on the deflection curve of each detection point and the regression equation of the inertia point, the subgrade modulus of the road section under test is solved using an iterative method, specifically including: An iterative optimization algorithm is used to determine the soil modulus corresponding to the inertial point closest to the deflection curve of the detection point as the soil modulus of the detection point.

5. The method for detecting the degree of asphalt pavement bulging cracking as described in claim 1, characterized in that, The base modulus of each testing point is comprehensively calculated to obtain a representative value of the base modulus used to characterize the degree of arching and cracking defects in the tested road section. This calculation also includes: Based on the range of the representative value of the base modulus used to characterize the degree of arching cracking in the road section under test, a maintenance strategy for the road section under test is formulated.

6. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the method according to any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method described in any one of claims 1-5.

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