Rebound deflection identification method and device for roadbed and pavement and computer equipment

Abstract

The invention relates to a rebound deflection identification method and device for a roadbed and a pavement and computer equipment. The method comprises the following steps: acquiring vehicle detection data of a test vehicle and road surface association information of a roadbed and a road surface, and identifying test preparation information of the roadbed and the road surface based on the vehicle detection data and the road surface association information; based on the test preparation information, identifying each test data of the roadbed and the pavement through a pavement test strategy, and based on the test preparation information, identifying a target rebound deflection algorithm adapted to the roadbed and the pavement; and calculating target rebound deflection information of the roadbed and the road surface through the target rebound deflection algorithm based on the test data. By adopting the method, the rebound deflection measurement efficiency can be improved.

Description

Technical Field

[0001] This application relates to the technical fields of data measurement and data calculation, and particularly relates to a method, device, and computer equipment for identifying the resilient deflection of subgrade and pavement. Background Art

[0002] With the rapid development of the transportation industry, the requirements for highway quality are constantly increasing. The resilient deflection of subgrade and pavement, as a key indicator for evaluating its bearing capacity and service performance, its accurate measurement is crucial. Therefore, how to improve the measurement accuracy of the resilient deflection of subgrade and pavement is the current research focus.

[0003] The traditional measurement method of resilient deflection is to identify the measurement value of resilient deflection by manually reading the dial gauge. However, there are large subjectivity and errors in manually reading the indication of the dial gauge, which are easily affected by factors such as the experience of operators and the environment, resulting in poor recognition accuracy of test results. Moreover, for large-scale highway construction, a large amount of resilient deflection data needs to be obtained. Manual identification has poor timeliness and high costs, thus leading to low measurement efficiency of resilient deflection. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium, and computer program product for identifying the resilient deflection of subgrade and pavement in view of the above technical problems.

[0005] In a first aspect, this application provides a method for identifying the resilient deflection of subgrade and pavement, including:

[0006] Obtain the vehicle detection data of the test vehicle and the pavement correlation information of the subgrade and pavement, and identify the test preparation information of the subgrade and pavement based on the vehicle detection data and the pavement correlation information;

[0007] Based on the test preparation information, identify each test data of the subgrade and pavement through a pavement test strategy, and identify the target resilient deflection algorithm suitable for the subgrade and pavement based on the test preparation information;

[0008] Based on each of the test data, calculate the target resilient deflection information of the subgrade and pavement through the target resilient deflection algorithm.

[0009] Optionally, the identifying the test preparation information of the subgrade and pavement based on the vehicle detection data and the pavement correlation information includes:

[0010] Based on the vehicle detection data, identify the vehicle parameter values of each vehicle parameter type of the test vehicle;

[0011] Based on the road surface association information, identify the road surface condition data for each road surface condition, and use the vehicle parameter values of each vehicle parameter type and the road surface condition data of each road surface condition as the test preparation information for the subgrade and road surface.

[0012] Optionally, based on the test preparation information, identify each test data of the subgrade and road surface through a road surface test strategy, including:

[0013] Collect the road surface test strategy of the subgrade and road surface based on the road surface condition data of each road surface condition;

[0014] Based on the vehicle parameter values of each vehicle parameter type and the road surface test strategy, identify the test process of the test vehicle and the test requirement information of the test vehicle, and generate the test control process of the subgrade and road surface based on the test process of the test vehicle and the test requirement information of the test vehicle;

[0015] Perform test processing on the subgrade and road surface through the test control process to obtain each test data of the subgrade and road surface.

[0016] Optionally, collecting the road surface test strategy of the subgrade and road surface based on the road surface condition data of each road surface condition includes:

[0017] Based on the road surface condition data of each road surface condition, identify the road surface type of the subgrade and road surface and the road surface state of the subgrade and road surface;

[0018] Based on the road surface type of the subgrade and road surface, query each initial road surface test strategy corresponding to the subgrade and road surface in the test database;

[0019] Identify the road surface condition data range of each road surface condition corresponding to each initial road surface test strategy, and based on the road surface state of the subgrade and road surface and the road surface condition data range of each road surface condition corresponding to each initial road surface test strategy, screen the road surface test strategy suitable for the subgrade and road surface from each initial road surface test strategy.

[0020] Optionally, identifying the target rebound deflection algorithm suitable for the subgrade and road surface based on the test preparation information includes:

[0021] Obtain the algorithm correction target of each rebound deflection algorithm, and query the target condition information corresponding to each algorithm correction target in the algorithm database;

[0022] Based on the target condition information and the road surface condition data of each road surface condition, match the target rebound deflection algorithm suitable for the subgrade and road surface through an algorithm adaptation network.

[0023] Optionally, calculating the target resilient deflection information of the roadbed and pavement based on each of the test data through the target resilient deflection algorithm includes:

[0024] Identifying the test data distribution information of each test type based on each of the test data;

[0025] Identifying the target measured data of each of the test types based on the test data distribution information of each test type, and calculating the associated resilient deflection values based on the target measured data of each of the test types through the target resilient deflection algorithm;

[0026] Taking each of the associated resilient deflection values as the target resilient deflection information of the roadbed and pavement.

[0027] In a second aspect, the present application further provides a resilient deflection identification device for a roadbed and pavement, including:

[0028] An acquisition module, configured to acquire the vehicle detection data of a test vehicle and the pavement associated information of the roadbed and pavement, and identify the test preparation information of the roadbed and pavement based on the vehicle detection data and the pavement associated information;

[0029] An identification module, configured to identify each test data of the roadbed and pavement through a pavement test strategy based on the test preparation information, and identify the target resilient deflection algorithm adapted to the roadbed and pavement based on the test preparation information;

[0030] A calculation module, configured to calculate the target resilient deflection information of the roadbed and pavement based on each of the test data through the target resilient deflection algorithm.

[0031] Optionally, the acquisition module is specifically configured to:

[0032] Identify the vehicle parameter values of each vehicle parameter type of the test vehicle based on the vehicle detection data;

[0033] Identify the pavement condition data of each pavement condition based on the pavement associated information, and take the vehicle parameter values of each vehicle parameter type and the pavement condition data of each pavement condition as the test preparation information of the roadbed and pavement.

[0034] Optionally, the identification module is specifically configured to:

[0035] Collect the pavement test strategy of the roadbed and pavement based on the pavement condition data of each pavement condition;

[0036] Based on the vehicle parameter values of each of the vehicle parameter types and the road surface test strategy, identify the test process of the test vehicle and the test requirement information of the test vehicle, and generate the test control process of the subgrade and road surface based on the test process of the test vehicle and the test requirement information of the test vehicle;

[0037] Through the test control process, perform test processing on the subgrade and road surface to obtain various test data of the subgrade and road surface.

[0038] Optionally, the identification module is specifically configured to:

[0039] Based on the road surface condition data of each of the road surface conditions, identify the road surface type of the subgrade and road surface and the road surface state of the subgrade and road surface;

[0040] Based on the road surface type of the subgrade and road surface, query each initial road surface test strategy corresponding to the subgrade and road surface in the test database;

[0041] Identify the road surface condition data range of each road surface condition corresponding to each initial road surface test strategy, and based on the road surface state of the subgrade and road surface and the road surface condition data range of each road surface condition corresponding to each initial road surface test strategy, screen the road surface test strategy suitable for the subgrade and road surface from each of the initial road surface test strategies.

[0042] Optionally, the identification module is specifically configured to:

[0043] Obtain the algorithm correction target of each rebound deflection algorithm, and query the target condition information corresponding to each algorithm correction target in the algorithm database;

[0044] Based on the target condition information and the road surface condition data of each of the road surface conditions, match the target rebound deflection algorithm suitable for the subgrade and road surface through the algorithm adaptation network.

[0045] Optionally, the calculation module is specifically configured to:

[0046] Based on each of the test data, identify the test data distribution information of each test type;

[0047] Based on the test data distribution information of each test type, identify the target measured data of each of the test types, and based on the target measured data of each of the test types, calculate the associated rebound deflection values through the target rebound deflection algorithm;

[0048] Use each of the associated rebound deflection values as the target rebound deflection information of the subgrade and road surface.

[0049] In a third aspect, the present application provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the method according to any one of the first aspect are implemented.

[0050] In a fourth aspect, the present application provides a computer-readable storage medium. A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the method according to any one of the first aspect are implemented.

[0051] In a fifth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of the first aspect are implemented.

[0052] The above-mentioned resilient deflection identification method, device and computer device for subgrade and pavement obtain vehicle detection data of a test vehicle and pavement correlation information of the subgrade and pavement, and identify test preparation information of the subgrade and pavement based on the vehicle detection data and the pavement correlation information; based on the test preparation information, identify each test data of the subgrade and pavement through a pavement test strategy, and identify a target resilient deflection algorithm suitable for the subgrade and pavement based on the test preparation information; based on each test data, calculate the target resilient deflection information of the subgrade and pavement through the target resilient deflection algorithm. In this solution, by combining the vehicle detection data of the test vehicle and the vehicle state information, and collecting the pavement correlation information of the subgrade and pavement, a pavement test strategy for each subgrade and pavement is generated, so that different pavement tests are carried out for different subgrades and pavements, thereby ensuring the test accuracy for different subgrades and pavements. Then, in this solution, by screening a target resilient deflection algorithm suitable for each subgrade and pavement and calculating each test data, the original data collected can be intelligently analyzed and processed, the data quality and the calculation accuracy of the test data are improved. Finally, through the above solution, the problem of large subjectivity and error in manually reading the indication of the dial gauge is avoided, so that the accuracy of the target resilient deflection information of the subgrade and pavement obtained is higher. Moreover, when calculating and analyzing the test data, different resilient deflection algorithms are adapted to different subgrades and pavements, so that the target resilient deflection information of different subgrades and pavements in a large range of subgrades and pavements can be accurately and efficiently obtained, thereby comprehensively improving the measurement efficiency of the resilient deflection. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] To more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for the description of the embodiments or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0054] Figure 1 It is a schematic structural diagram of a Benkelman beam in an embodiment;

[0055] Figure 2 It is a schematic diagram of a dial indicator and a dial indicator stand in an embodiment;

[0056] Figure 3 It is a schematic flowchart of a method for identifying the resilient deflection of subgrade and pavement in an embodiment;

[0057] Figure 4 It is a schematic flowchart of an example for identifying the resilient deflection of subgrade and pavement in an embodiment;

[0058] Figure 5 It is a structural block diagram of a device for identifying the resilient deflection of subgrade and pavement in an embodiment;

[0059] Figure 6 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0060] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the following further details the present application in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0061] The method for identifying the resilient deflection of subgrade and pavement provided by the embodiments of the present application can be used in the application environment for identifying the resilient deflection of subgrade and pavement. Among them, as Figure 1 shown, it is the Benkelman beam applied when conducting subgrade tests for the above-mentioned scheme. Among them, this Benkelman beam: is made of alloy aluminum, has a spirit level on it, and the ratio of the length of its front arm to the rear arm is 2:1. The Benkelman beam is divided into two types according to length: a 5.4m (3.6m + 1.8m) beam and a 3.6m (2.4m + 1.2m) beam. The Benkelman beam with a length of 5.4m is suitable for testing the resilient deflection of various types of pavement structures; the Benkelman beam with a length of 3.6m is suitable for testing the resilient deflection of flexible base asphalt pavements. As Figure 2As shown, it is a dial indicator and a dial indicator stand, which are used to read various test data of subgrade and pavement tests. This method can be applied to a terminal, a server, or a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Among them, the terminal can be, but is not limited to, various personal computers, laptop computers, medium-sized computers, etc. Among them, the terminal combines the vehicle detection data of the test vehicle and the vehicle status information, and collects the pavement-related information of the subgrade and pavement, so as to generate a pavement test strategy for each subgrade and pavement, so as to perform different pavement tests for different subgrades and pavements, thereby ensuring the test accuracy of different subgrades and pavements. Then, this solution calculates each test data by screening the target rebound deflection algorithm adapted to each subgrade and pavement, so that the original data collected can be intelligently analyzed and processed, improving the data quality and the calculation accuracy of the test data. Finally, through the above solution, the problem of large subjectivity and error in manually reading the indication value of the dial indicator is avoided, so that the accuracy of the target rebound deflection information of the subgrade and pavement obtained is higher. Moreover, when calculating and analyzing the test data, different rebound deflection algorithms are adapted for different subgrades and pavements, so as to accurately and efficiently obtain the target rebound deflection information of different subgrades and pavements in multiple large-scale subgrades and pavements, thereby comprehensively improving the measurement efficiency of the rebound deflection.

[0062] In an exemplary embodiment, as Figure 3 shown, a method for identifying the rebound deflection of subgrade and pavement is provided. Taking the application of this method to a terminal as an example, it includes the following steps S301 to S303. Among them:

[0063] Step S301: Obtain the vehicle detection data of the test vehicle and the pavement-related information of the subgrade and pavement, and identify the test preparation information of the subgrade and pavement based on the vehicle detection data and the pavement-related information.

[0064] In this embodiment, the terminal correspondingly obtains the vehicle detection data of the test vehicle and the pavement-related information of the subgrade and pavement according to the information upload operation of the staff. Among them, the test vehicle is a loading vehicle, which is a load-carrying vehicle with a single rear axle and a single-side double-wheel group. The double-wheel gap should be able to meet the requirement of freely inserting the Beckmann beam probe. The technical parameters such as the axle load and tire pressure should meet the requirements of Table 1.

[0065] Table 1: Parameter requirements of the loading vehicle

[0066] Standard axle load of rear axle P (kN) 100±1 Single-sided dual-wheel load (kN) 50±0.5 Tire pressure (MPa) 0.7±0.05 <![CDATA[Equivalent circle area of single-wheel pressure transmission surface (mm 2 )]]> <![CDATA[(3.56±0.20)*10 4 >

[0067] Among them, the vehicle detection data of the test vehicle is the detection data obtained by performing a structural inspection on the vehicle. Among them, the road surface related information of the subgrade and pavement is pavement detection data. For example, pavement detection data such as the type of pavement structural material, the designed thickness of the pavement, the average air temperature, etc. Then, the terminal identifies the test preparation information of the subgrade and pavement based on the vehicle detection data and the road surface related information. The specific identification process will be described in detail later.

[0068] Step S302: Based on the test preparation information, through the pavement test strategy, identify each test data of the subgrade and pavement, and based on the test preparation information, identify the target rebound deflection algorithm suitable for the subgrade and pavement.

[0069] In this embodiment, the terminal identifies each test data of the subgrade and pavement through the pavement test strategy based on the test preparation information, and identifies the target rebound deflection algorithm suitable for the subgrade and pavement based on the test preparation information. Among them, the pavement test strategy is a strategy for testing the subgrade and pavement by a test vehicle. Specifically, this strategy includes the test process of the test vehicle (i.e., the loading vehicle). For example,

[0070] (1) Park the loading vehicle at the test position of the test section. Generally, the rear wheels should be placed on the road wheel tracks. Insert the Benkelman beam into the wheel gap of the rear wheel of the loading vehicle, in the same direction as the driving direction of the loading vehicle, and the beam arm shall not touch the tire. Place the Benkelman beam measuring head at the measuring point (30 - 50) mm in front of the center of the wheel gap. Measure and record the road surface temperature near the measuring point with a road surface thermometer. Two Benkelman beams can be used to simultaneously perform rebound deflection tests on both side wheel tracks.

[0071] (2) Install the dial gauge on the gauge rack, and place the measuring head of the dial gauge on the top surface of the measuring rod of the Benkelman beam. Gently tap the Benkelman beam to ensure that the dial gauge returns to its normal position.

[0072] (3) Command the loading vehicle to move forward slowly, with a speed of about 5 km / h. The dial gauge reading continuously increases with the pavement deformation. When the reading is the largest, quickly read the initial reading I. The loading vehicle continues to move forward, and the reading starts to change in the reverse direction. After the loading vehicle drives out of the deflection influence range (about 3 m or more) and the dial gauge reading stabilizes, read the final reading L2.

[0073] (4) Command the loading vehicle to move forward along the wheel track and drive to the next test position, repeating steps (1) - (3) to complete the test process. The specific identification process will be described in detail later.

[0074] Step S303: Based on each test data, calculate the target rebound deflection information of the subgrade and pavement through the target rebound deflection algorithm.

[0075] In this embodiment, the terminal calculates the target resilient deflection information of the roadbed and pavement based on each test data through the target resilient deflection algorithm. Among them, the resilient deflection value algorithm includes the resilient deflection value algorithm of pavement measuring points, the resilient deflection value algorithm that needs to correct the deflection meter fulcrum deformation, the temperature correction resilient deflection value algorithm when the asphalt thickness is too large, etc. For different roadbeds and pavements, the corresponding resilient deflection algorithms are different, and the specific identification process will be described in detail later.

[0076] Based on the above solution, by combining the vehicle detection data of the test vehicle and the vehicle status information, and collecting the road surface related information of the roadbed and pavement, a road surface test strategy for each roadbed and pavement is generated, so that different road surface tests are carried out for different roadbeds and pavements, thereby ensuring the test accuracy of different roadbeds and pavements. Then, in this solution, by screening the target resilient deflection algorithm suitable for each roadbed and pavement and calculating each test data, the original data collected can be analyzed and processed intelligently, the data quality and the calculation accuracy of the test data can be improved. Finally, through the above solution, the problem of large subjectivity and error in manually reading the indication value of the dial gauge is avoided, so that the accuracy of the target resilient deflection information of the roadbed and pavement obtained is higher. Moreover, when calculating and analyzing the test data, different resilient deflection algorithms are adapted to different roadbeds and pavements, so as to accurately and efficiently obtain the target resilient deflection information of different roadbeds and pavements in multiple large-scale roadbeds and pavements, thereby comprehensively improving the measurement efficiency of the resilient deflection.

[0077] Optionally, based on the vehicle detection data and the road surface related information, the test preparation information of the roadbed and pavement is identified, including: based on the vehicle detection data, identifying the vehicle parameter values of each vehicle parameter type of the test vehicle; based on the road surface related information, identifying the road surface condition data of each road surface condition, and taking the vehicle parameter values of each vehicle parameter type and the road surface condition data of each road surface condition as the test preparation information of the roadbed and pavement.

[0078] In this embodiment, the terminal identifies the vehicle parameter values of each vehicle parameter type of the test vehicle based on the vehicle detection data. Among them, the vehicle parameter type includes but is not limited to the type of rear axle standard axle load P (KN), the type of single-side double-wheel load (kN), the type of tire pressure (MPa), and the type of equivalent circle area of single-wheel pressure transmission surface (mm2).

[0079] Then, the terminal identifies the road surface condition data of each road surface condition based on the road surface related information, and takes the vehicle parameter values of each vehicle parameter type and the road surface condition data of each road surface condition as the test preparation information of the roadbed and pavement. Among them, the road surface conditions include but are not limited to road surface design thickness, road surface layers, types of structural materials of each road surface layer, etc.

[0080] Based on the above solution, by identifying the types of vehicle parameters of the test vehicle, the test preparation information of the roadbed and pavement is obtained, which improves the accuracy of identifying the basic information of the roadbed and pavement and the basic information of the test vehicle, and also improves the judgment efficiency of whether the test measurement meets the screening of the test vehicle for the roadbed and pavement.

[0081] Optionally, based on the test preparation information, through the road surface test strategy, various test data of the roadbed and pavement are identified, including: road surface condition data based on various road surface conditions, and the road surface test strategy for collecting the roadbed and pavement is obtained; based on the vehicle parameter values of various vehicle parameter types and the road surface test strategy, the test process of the test vehicle and the test requirement information of the test vehicle are identified, and based on the test process of the test vehicle and the test requirement information of the test vehicle, the test control process of the roadbed and pavement is generated; through the test control process, the roadbed and pavement are tested to obtain various test data of the roadbed and pavement.

[0082] In this embodiment, the terminal collects the road surface test strategy of the roadbed and pavement based on the road surface condition data of various road surface conditions. Among them, different road surface condition data of various road surface conditions correspond to different road surface test strategies, and the corresponding relationship between different road surface condition data of various road surface conditions and the road surface test strategy is preset in the terminal. The specific collection process will be described in detail later.

[0083] The terminal identifies the test process of the test vehicle and the test requirement information of the test vehicle based on the vehicle parameter values of various vehicle parameter types and the road surface test strategy, and generates the test control process of the roadbed and pavement based on the test process of the test vehicle and the test requirement information of the test vehicle. Among them, the test requirement information of the vehicle is the information that needs to be adjusted by the test vehicle in different steps of the test process. For example,

[0084] (1) Park the loading vehicle at the test position on the test section. Generally, the rear wheels should be placed on the road wheel track. Insert the Benkelman beam into the wheel gap of the rear wheel of the loading vehicle, in the same direction as the driving direction of the loading vehicle, and the beam arm shall not touch the tire. Place the Benkelman beam probe at the measuring point (30 - 50) mm in front of the center of the wheel gap. Measure and record the road surface temperature near the measuring point with a road surface thermometer. Two Benkelman beams can be used to simultaneously conduct rebound deflection tests on both-sided wheel tracks. (Among them, the test requirement information is the test position requirement of the test vehicle, the setting requirement of the Benkelman beam and the loading vehicle, etc.).

[0085] (2) Install the dial indicator on the dial indicator stand, and place the probe of the dial indicator on the top surface of the measuring rod of the Benkelman beam. Gently tap the Benkelman beam to ensure that the dial indicator returns to its normal position.

[0086] (3) Command the loading vehicle to move forward slowly at a speed of about 5 km / h. The reading of the percentage indicator continuously increases with the deformation of the road surface. When the reading is the largest, quickly read the initial reading L1. The loading vehicle continues to move forward, and the reading starts to change in the reverse direction. After the loading vehicle drives out of the deflection influence range (about 3 m or more) and the reading of the percentage indicator stabilizes, read the final reading L2. (Among them, the test requirement information includes the speed of the loading vehicle, control method, etc.).

[0087] (4) Command the loading vehicle to move forward along the wheel track and drive to the next test position, repeating the steps in (1)-(3) to complete the test process. (Among them, the test requirement information includes the forward route of the loading vehicle, etc.).

[0088] Finally, the terminal performs test processing on the subgrade and pavement through the test control process to obtain various test data of the subgrade and pavement.

[0089] Based on the above scheme, after identifying the pavement test strategy of the subgrade and pavement, the test process of the test vehicle and the test requirement information are identified, improving the test accuracy of the subgrade and pavement.

[0090] Optionally, based on the pavement condition data of each pavement condition, collect the pavement test strategy of the subgrade and pavement, including: based on the pavement condition data of each pavement condition, identify the pavement type of the subgrade and pavement and the pavement state of the subgrade and pavement; based on the pavement type of the subgrade and pavement, query each initial pavement test strategy corresponding to the subgrade and pavement in the test database; identify the pavement condition data range of each pavement condition corresponding to each initial pavement test strategy, and based on the pavement state of the subgrade and pavement and the pavement condition data range of each pavement condition corresponding to each initial pavement test strategy, screen the pavement test strategy suitable for the subgrade and pavement among each initial pavement test strategy.

[0091] In this embodiment, the terminal identifies the pavement type of the subgrade and pavement and the pavement state of the subgrade and pavement based on the pavement condition data of each pavement condition. Among them, the pavement type is the material type of each structural layer of the pavement, and the pavement state of the subgrade and pavement is the state data such as the temperature, radian, and angle of the pavement.

[0092] Then, the terminal queries each initial pavement test strategy corresponding to the subgrade and pavement in the test database based on the pavement type of the subgrade and pavement. Among them, each pavement type corresponds to one or more pavement test strategies.

[0093] Subsequently, the terminal identifies the range of pavement condition data for each pavement condition corresponding to each initial pavement test strategy, and based on the pavement condition data for each pavement condition and the range of pavement condition data for each pavement condition corresponding to each initial pavement test strategy, screens out the pavement test strategies suitable for the subgrade pavement among the initial pavement test strategies. Among them, each pavement test strategy uses a pavement state range. The terminal identifies the pavement state range corresponding to each initial pavement test strategy within the range of pavement condition data for each pavement condition, and based on the pavement state of the subgrade pavement, screens out the initial pavement test strategy corresponding to the range of pavement condition data that includes the pavement state of the subgrade pavement within the range of pavement condition data for each pavement condition as the pavement test strategy suitable for the subgrade pavement.

[0094] Based on the above solution, by using the pavement condition data for each pavement condition, the pavement type and pavement state of the subgrade pavement are identified, thereby screening out the pavement test strategies suitable for the subgrade pavement, improving the accuracy and adaptability of the subgrade pavement test.

[0095] Optionally, based on the test preparation information, identifying the target rebound deflection algorithm suitable for the subgrade pavement includes: obtaining the algorithm correction target for each rebound deflection algorithm, and querying the target condition information corresponding to each algorithm correction target in the algorithm database; based on the target condition information and the pavement condition data for each pavement condition, matching the target rebound deflection algorithm suitable for the subgrade pavement through the algorithm adaptation network.

[0096] In this embodiment, the terminal obtains the algorithm correction target for each rebound deflection algorithm and queries the target condition information corresponding to each algorithm correction target in the algorithm database. Specifically, each rebound deflection algorithm is:

[0097] Data processing

[0098] The rebound deflection value of the pavement measuring point is calculated according to formula (T0951-1). 4.1

[0099] l t =(L1 - L2)*2

[0100] In the formula:

[0101] l t -- The rebound deflection value at the average temperature of the asphalt surface layer (0.0lmm);

[0102] L1 -- The maximum reading of the dial gauge when the wheel center is near the Beckmann beam probe (0.01mm);

[0103] L2 -- The final reading after the loading vehicle drives out of the deflection influence radius and the dial gauge stabilizes (0.01mm). When the deflection correction of the deflectometer fulcrum needs to be carried out, the rebound deflection value of the pavement measuring point is calculated according to the above formula.

[0104] When the deformation correction of the fulcrum of the deflectometer is required, the rebound deflection value of the pavement measuring point shall be calculated according to the following formula.

[0105] l t =(L1 - L2)*2+(L3 - L4)*6

[0106] In the formula:

[0107] L3--The maximum reading of the Benkelman beam for inspection when the center of the loading vehicle is near the measuring head of the Benkelman beam (0.01 mm);

[0108] L4--The final reading of the Benkelman beam for inspection after the loading vehicle drives out of the deflection influence radius (0.01 mm).

[0109] Note: This formula is applicable to the situation where there is deformation at the support of the Benkelman beam used for measurement, but there is no deformation on the pavement at the dial gauge support.

[0110] When the thickness of the asphalt surface layer is greater than 50 mm, the rebound deflection value shall be corrected according to the average temperature of the asphalt surface layer. Proceed as follows.

[0111] (1) Calculate the average temperature of the asphalt surface layer during measurement according to the following formula

[0112] t=(t 25 +t m +t e ) / 3

[0113] In the formula:

[0114] t--The average temperature of the asphalt surface layer during measurement (°C);

[0115] t 25 --The temperature at 25 mm below the road surface (°C);

[0116] t m --The temperature at the middle depth of the asphalt surface layer (°C);

[0117] t e --The temperature at the bottom of the asphalt surface layer (°C);

[0118] to--The sum of the road surface temperature during measurement and the average value of the daily average air temperatures in the previous 5 days (°C), and the daily average air temperature is the average value of the daily highest air temperature and the lowest air temperature.

[0119] (2) When the average temperature of the asphalt surface layer is (20 + 2)°C, the temperature correction coefficient K - 1. When the average temperature of the asphalt surface layer is other temperatures, the temperature correction coefficient K of the rebound deflection value of the asphalt pavement with different bases shall be obtained from the currently collected data according to the thickness of the asphalt surface layer.

[0120] (3) Calculate the corrected rebound deflection value of the asphalt pavement according to the following formula

[0121] l 20 = l t * K

[0122] In the formula:

[0123] K--Temperature correction coefficient;

[0124] l 20 --Rebound deflection value of the asphalt pavement after correction (0.0lmm)

[0125] Finally, based on the above algorithm, the average value of the rebound deflection is calculated, and then the standard deviation and the representative value are calculated to obtain the target rebound deflection information of the subgrade and pavement.

[0126] Subsequently, based on the target condition information and the pavement condition data of each pavement condition, the terminal matches the target rebound deflection algorithm suitable for the subgrade and pavement through the algorithm adaptation network. Among them, the algorithm adaptation network is a neural network based on reinforcement learning, which can match the target rebound deflection algorithm suitable for the subgrade and pavement based on each target condition information and the pavement condition data of each pavement condition.

[0127] Based on the above solution, by identifying the target condition information of each target rebound algorithm, the target rebound deflection algorithm suitable for the subgrade and pavement is matched, thereby improving the calculation accuracy of the target rebound deflection value of the subgrade and pavement.

[0128] Optionally, based on each test data, the target rebound deflection information of the subgrade and pavement is calculated through the target rebound deflection algorithm, including: based on each test data, identifying the test data distribution information of each test type; based on the test data distribution information of each test type, identifying the target measured data of each test type, and based on the target measured data of each test type, calculating each rebound deflection correlation value through the target rebound deflection algorithm; using each rebound deflection correlation value as the target rebound deflection information of the subgrade and pavement.

[0129] In this embodiment, the terminal identifies the test data distribution information of each test type based on each test data. Among them, the test data distribution information of each test type is the distribution information obtained after sorting the test data of each test type in the test data. Subsequently, the terminal identifies the target measured data of each test type based on the test data distribution information of each test type, and calculates each rebound deflection correlation value through the target rebound deflection algorithm based on the target measured data of each test type. Among them, the target measured data of each test type are the parameter values of each parameter in each rebound deflection algorithm. And the rebound deflection correlation value includes values such as the average value of the rebound deflection, the standard deviation, and the representative value.

[0130] Finally, use the associated resilient deflection values as the target resilient deflection information for the roadbed and pavement.

[0131] Based on the above solution, after arranging and distributing the test data according to each test type, identify the target measured data for each test type, and then calculate the associated resilient deflection values of the roadbed and pavement, improving the calculation accuracy and efficiency of the associated resilient deflection values.

[0132] This application also provides an example for identifying the resilient deflection of the roadbed and pavement, as Figure 4 shown. The specific processing process includes the following steps:

[0133] Step S401: Obtain the vehicle detection data of the test vehicle and the pavement associated information of the roadbed and pavement.

[0134] Step S402: Based on the vehicle detection data, identify the vehicle parameter values of each vehicle parameter type of the test vehicle.

[0135] Step S403: Based on the pavement associated information, identify the pavement condition data of each pavement condition, and use the vehicle parameter values of each vehicle parameter type and the pavement condition data of each pavement condition as the test preparation information for the roadbed and pavement.

[0136] Step S404: Based on the pavement condition data of each pavement condition, identify the pavement type of the roadbed and pavement and the pavement state of the roadbed and pavement.

[0137] Step S405: Based on the pavement type of the roadbed and pavement, query the initial pavement test strategies corresponding to the roadbed and pavement in the test database.

[0138] Step S406: Identify the pavement condition data ranges of each pavement condition corresponding to each initial pavement test strategy, and based on the pavement state of the roadbed and pavement and the pavement condition data ranges of each pavement condition corresponding to each initial pavement test strategy, screen the pavement test strategies suitable for the roadbed and pavement from the initial pavement test strategies.

[0139] Step S407: Based on the vehicle parameter values of each vehicle parameter type and the pavement test strategy, identify the test process of the test vehicle and the test requirement information of the test vehicle, and based on the test process of the test vehicle and the test requirement information of the test vehicle, generate the test control process for the roadbed and pavement.

[0140] Step S408: Through the test control process, perform test processing on the roadbed and pavement to obtain the test data of the roadbed and pavement.

[0141] Step S409: Obtain the algorithm correction target for each rebound deflection algorithm, and query the target condition information corresponding to each algorithm correction target in the algorithm database.

[0142] Step S410: Based on the target condition information and the pavement condition data of each pavement condition, match the target rebound deflection algorithm adapted to the subgrade and pavement through the algorithm adaptation network.

[0143] Step S411: Based on each test data, identify the test data distribution information of each test type.

[0144] Step S412: Based on the test data distribution information of each test type, identify the target measured data of each test type, and based on the target measured data of each test type, calculate each rebound deflection related value through the target rebound deflection algorithm.

[0145] Step S413: Use each rebound deflection related value as the target rebound deflection information of the subgrade and pavement.

[0146] It should be understood that although the steps in the flowcharts involved in the above-mentioned embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0147] Based on the same inventive concept, an embodiment of the present application also provides a device for identifying the rebound deflection of subgrade and pavement for implementing the above-mentioned method for identifying the rebound deflection of subgrade and pavement. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the device for identifying the rebound deflection of subgrade and pavement provided below can refer to the limitations on the method for identifying the rebound deflection of subgrade and pavement in the above text, and will not be repeated here.

[0148] In an exemplary embodiment, as Figure 5 shown, a device for identifying the rebound deflection of subgrade and pavement is provided, including: an acquisition module 510, an identification module 520, and a calculation module 530, where:

[0149] Optionally, the acquisition module 510 is specifically configured to:

[0150] Identify the vehicle parameter values of each vehicle parameter type of the test vehicle based on the vehicle detection data;

[0151] Identify the road surface condition data of each road surface condition based on the road surface association information, and use the vehicle parameter values of each vehicle parameter type and the road surface condition data of each road surface condition as the test preparation information of the subgrade and road surface.

[0152] Optionally, the identification module 520 is specifically configured to:

[0153] Collect the road surface test strategy of the subgrade and road surface based on the road surface condition data of each road surface condition;

[0154] Identify the test process of the test vehicle and the test requirement information of the test vehicle based on the vehicle parameter values of each vehicle parameter type and the road surface test strategy, and generate the test control process of the subgrade and road surface based on the test process of the test vehicle and the test requirement information of the test vehicle.

[0155] Perform test processing on the subgrade and road surface through the test control process to obtain each test data of the subgrade and road surface.

[0156] Optionally, the identification module 520 is specifically configured to:

[0157] Identify the road surface type of the subgrade and road surface and the road surface state of the subgrade and road surface based on the road surface condition data of each road surface condition;

[0158] Query each initial road surface test strategy corresponding to the subgrade and road surface in the test database based on the road surface type of the subgrade and road surface;

[0159] Identify the road surface condition data range of each road surface condition corresponding to each initial road surface test strategy, and screen the road surface test strategy suitable for the subgrade and road surface from each initial road surface test strategy based on the road surface state of the subgrade and road surface and the road surface condition data range of each road surface condition corresponding to each initial road surface test strategy.

[0160] Optionally, the identification module 520 is specifically configured to:

[0161] Obtain the algorithm correction target of each rebound deflection algorithm, and query the target condition information corresponding to each algorithm correction target in the algorithm database;

[0162] Match the target rebound deflection algorithm suitable for the subgrade and road surface through the algorithm adaptation network based on the target condition information and the road surface condition data of each road surface condition.

[0163] Optionally, the calculation module 530 is specifically configured to:

[0164] Based on each piece of the test data, identify the test data distribution information of each test type;

[0165] Based on the test data distribution information of each test type, identify the target measured data of each test type, and based on the target measured data of each test type, calculate the associated resilient deflection values through the target resilient deflection algorithm;

[0166] Use each of the associated resilient deflection values as the target resilient deflection information of the subgrade and pavement.

[0167] Each module in the above-mentioned resilient deflection identification device for subgrade and pavement can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor of the computer device in hardware form or be independent of it, or be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0168] In an exemplary embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 6 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used for the processor to exchange information with external devices. The communication interface of the computer device is used for wired or wireless communication with external terminals, and the wireless method can be implemented through WIFI, mobile cellular networks, NFC (Near Field Communication), or other technologies. The computer program, when executed by the processor, implements a method for identifying the resilient deflection of subgrade and pavement. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the outer shell of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0169] Those skilled in the art can understand, Figure 6The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0170] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps corresponding to the rebound deflection identification method for subgrade and pavement are implemented.

[0171] In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps corresponding to the rebound deflection identification method for subgrade and pavement are implemented.

[0172] In an embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps corresponding to the rebound deflection identification method for subgrade and pavement are implemented.

[0173] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0174] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. 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), magnetoresistive 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 be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0175] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, 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, it should be considered as the scope recorded in this specification.

[0176] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for identifying rebound deflection of roadbed and pavement, characterized in that: The method comprises: Acquire vehicle detection data of the test vehicle and road surface related information of the roadbed and road surface, and identify test preparation information of the roadbed and road surface based on the vehicle detection data and the road surface related information; Based on the test preparation information, identifying various test data of the roadbed and road surface through a road surface test strategy, and based on the test preparation information, identifying a target rebound deflection algorithm adapted for the roadbed and road surface; Based on each of the test data, the target rebound deflection information of the roadbed and pavement is calculated using the target rebound deflection algorithm.

2. The method according to claim 1, characterized in that The step of identifying the test preparation information of the roadbed and road surface based on the vehicle detection data and the road surface associated information includes: Based on the vehicle detection data, identifying vehicle parameter values ​​of each vehicle parameter type of the test vehicle; Based on the road surface associated information, road surface condition data of each road surface condition is identified, and the vehicle parameter value of each vehicle parameter type and the road surface condition data of each road surface condition are used as test preparation information of the roadbed and road surface.

3. The method according to claim 2, characterized in that The step of identifying the test data of the roadbed and road surface based on the test preparation information and through a road surface test strategy includes: Based on the pavement condition data of each of the pavement conditions, collecting a pavement testing strategy for the roadbed and pavement; Based on the vehicle parameter values ​​of each of the vehicle parameter types and the road test strategy, identify the test process of the test vehicle and the test requirement information of the test vehicle, and generate the test control process of the roadbed and road surface based on the test process of the test vehicle and the test requirement information of the test vehicle; Through the test control process, the roadbed and pavement are tested and processed to obtain various test data of the roadbed and pavement.

4. The method according to claim 3, characterized in that Based on the pavement condition data of each of the pavement conditions, a pavement test strategy of the roadbed and pavement is collected, including: Based on the pavement condition data of each of the pavement conditions, identifying the pavement type of the roadbed pavement and the pavement state of the roadbed pavement; Based on the road surface type of the roadbed and road surface, querying each initial road surface test strategy corresponding to the roadbed and road surface in a test database; Identify the pavement condition data range of each pavement condition corresponding to each initial pavement test strategy, and based on the pavement state of the roadbed and pavement, and the pavement condition data range of each pavement condition corresponding to each initial pavement test strategy, select the pavement test strategy that is suitable for the roadbed and pavement in each of the initial pavement test strategies.

5. The method according to claim 1, characterized in that The step of identifying the target rebound deflection algorithm adapted for the roadbed and pavement based on the test preparation information includes: Obtaining the algorithm correction target of each rebound deflection algorithm, and querying the target condition information corresponding to each algorithm correction target in the algorithm database; Based on the target condition information and the pavement condition data of each of the pavement conditions, the target rebound deflection algorithm adapted for the roadbed and pavement is matched through an algorithm adaptation network.

6. The method according to claim 1, characterized in that The target rebound deflection information of the roadbed and pavement is calculated based on each of the test data by using the target rebound deflection algorithm, including: Based on each of the test data, identifying test data distribution information of each test type; Based on the test data distribution information of each test type, target measured data of each test type is identified, and based on the target measured data of each test type, each rebound deflection correlation value is calculated by the target rebound deflection algorithm; The rebound deflection associated values ​​are used as the target rebound deflection information of the roadbed and pavement.

7. A rebound deflection identification device for roadbed and pavement, characterized in that: The device comprises: An acquisition module, used to acquire vehicle detection data of a test vehicle and road surface associated information of a roadbed and road surface, and to identify test preparation information of the roadbed and road surface based on the vehicle detection data and the road surface associated information; An identification module, used to identify various test data of the roadbed and road surface based on the test preparation information and through a road surface test strategy, and to identify a target rebound deflection algorithm adapted for the roadbed and road surface based on the test preparation information; A calculation module is used to calculate the target rebound deflection information of the roadbed and pavement based on each of the test data through the target rebound deflection algorithm.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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