A road surface collapse degree detection method and system suitable for different roads

Abstract

This invention discloses a method and system for detecting road surface subsidence levels applicable to different types of roads, including a road information acquisition module, an image information acquisition module, an environmental information acquisition module, an earthquake information acquisition module, a data receiving module, a data processing module, a central control module, and an information sending module. The road information acquisition module collects road information, including road surface information and road construction time information. The image information acquisition module collects road image information, the environmental information acquisition module collects environmental information about the road, and the earthquake information acquisition module collects earthquake information at the road's location. The data receiving module receives the road information, road image information, environmental information about the road, and earthquake information at the road's location. This invention enables more accurate detection of road surface subsidence levels and has a wider range of applications.

Description

Technical Field

[0001] This invention relates to the field of detection systems, and more specifically to a method and system for detecting the degree of road surface subsidence applicable to different roads. Background Technology

[0002] Road surface subsidence is a phenomenon caused by vertical deformation of the roadbed and pavement, leading to road surface settlement. Road surface subsidence can be categorized into: uniform subsidence (due to the roadbed and pavement becoming more compacted and stable under natural factors and traffic, generally without causing road damage); uneven subsidence (caused by uneven compaction of the roadbed and pavement, resulting in deformation under water erosion and traffic); and localized subsidence (caused by areas of the roadbed that are not properly compacted, or the presence of graves, dry wells, tree pits, ditches, etc., leading to subsidence when exposed to water erosion).

[0003] When conducting road surface subsidence detection, it is necessary to use road surface subsidence detection methods and systems. By using these methods and systems, the extent of road surface subsidence can be determined, thereby enabling the development of road repair plans.

[0004] Existing methods and systems for detecting road subsidence have poor detection results in practical use and limited application scope, which has a certain impact on their use. Therefore, this paper proposes a method and system for detecting road subsidence that is suitable for different types of roads. Summary of the Invention

[0005] The technical problem to be solved by this invention is: how to address the poor detection effect and limited application range of existing road surface subsidence detection methods and systems in actual use, which has a certain impact on the use of road surface subsidence detection methods and systems. This invention provides a road surface subsidence detection method and system applicable to different roads.

[0006] The present invention solves the above-mentioned technical problems through the following technical solutions: the present invention includes a road information acquisition module, an image information acquisition module, an environmental information acquisition module, an earthquake information acquisition module, a data receiving module, a data processing module, a central control module, and an information sending module;

[0007] The road information collection module is used to collect road information, which includes road surface information and road construction time information.

[0008] The image information acquisition module is used to acquire road image information, the environmental information acquisition module is used to acquire environmental information of the road, and the earthquake information acquisition module is used to acquire earthquake information of the road location.

[0009] The data receiving module is used to receive road information, road image information, road environment information, and earthquake information at the road location. After recording the above information, it sends the information to the data processing module.

[0010] The data processing module is used to process the received road information, road image information, road environment information, and earthquake information at the road location to generate first detection information, second detection information, or third detection information.

[0011] Once any one of the first detection information, the second detection information, and the third detection information is generated, the central control module sends a control command to the collapse detection module, and the collapse detection module then runs to generate the collapse detection information.

[0012] After the collapse detection information is generated, the central control module controls the information sending module to send the collapse detection information to the preset receiving terminal for collapse detection and to obtain the collapse detection parameters.

[0013] The collapse detection parameters are then sent to the data processing module for data processing to generate collapse detection and evaluation information.

[0014] Furthermore, the specific processing procedures for the first detection information, the second detection information, and the third detection information are as follows:

[0015] Step 1: Extract the collected road information, extract road surface information and road construction time information from the road information, and process the road surface information and road construction time information to obtain the first evaluation parameters;

[0016] Step 2: Extract the image information, process the image information to obtain the number of passing vehicles and the number of warning vehicle types, and process the number of passing vehicles and the number of warning vehicle types to obtain the second evaluation parameters;

[0017] Step 3: Extract the collected environmental information of the road and process the environmental information to generate the third evaluation parameters;

[0018] Step 4: Extract the seismic information of the road location, process the seismic information to obtain the fourth assessment parameter information;

[0019] Step 5: Calculate and process the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter, and obtain their sum to obtain the total evaluation parameter;

[0020] Step Six: When the total evaluation parameter is greater than the preset value, the third detection information is generated; when the total evaluation parameter is greater than the preset value but within the preset value range, the second detection information is generated; when the total evaluation parameter is less than the preset value, the first detection information is generated.

[0021] Furthermore, the specific processing procedure for the first evaluation parameter is as follows: extract the collected road surface information and road construction time information, analyze the road surface information to obtain the road surface score K1. When the road surface is a cement concrete road surface, the road surface score K1 is a preset value a1. When the road surface is an asphalt road surface, the road surface score K1 is a preset value a2. When the road surface is a non-cement concrete road surface and an asphalt road surface, the road surface score K1 is a preset value a3, where a1 < a2 < a3.

[0022] The road construction time information is extracted and evaluated to obtain a time score K2. When the road construction time information is greater than the preset value, the time score K2 is the preset value b1. When the road construction time information is within the preset time, the time score K2 is the preset value b2. When the road construction time information is less than the preset value, the time score K2 is the preset value b3, where b3 > b2 > b1.

[0023] Then, the sum of the road surface score K1 and the duration score K2 is calculated, which yields the first evaluation parameter Kk.

[0024] Furthermore, the specific process of processing the image information to obtain the number of passing vehicles and the number of warning vehicle types is as follows: Vehicle model information is preset, including small vehicle models, medium vehicle models, and small vehicle models. The vehicle model information is added to the collected road image information, which is road vehicle traffic image information within a preset time period. The number of small vehicles, medium vehicles, and large vehicles is analyzed from the road image information. The sum of the number of small vehicles, medium vehicles, and large vehicles is calculated, which is the number of passing vehicles. The number of warning vehicle types is the same as the number of large vehicles.

[0025] The specific processing procedure for the second evaluation parameter is as follows: Extract the number of passing vehicles and the number of warning vehicle types. Collect the number of passing vehicles x times consecutively, where x ≥ 5. Then calculate the average number of passing vehicles x times to obtain the average number of passing vehicles information F1. Collect the number of warning vehicle types x times consecutively, and then calculate the average number of warning vehicle types x times to obtain the average number of warning vehicles information F2. Score F1; the larger F1 is, the higher the score. Score F2; the larger F2 is, the higher the score. Finally, calculate the sum of the scores of F1 and F2 to obtain the second evaluation parameter.

[0026] Furthermore, the specific processing procedure for the third evaluation parameter is as follows: extract the collected environmental information of the road, which is the monthly average rainfall information of the road location, score the monthly average rainfall information to obtain the third evaluation parameter, the larger the monthly average rainfall information is, the larger the third evaluation parameter is, and vice versa.

[0027] Furthermore, the specific processing procedure for the fourth evaluation parameter is as follows: extract the earthquake information at the location of the road. The earthquake information is the number of earthquakes at the location of the road within a preset time period. Process the earthquake number information to obtain the fourth evaluation parameter. The larger the earthquake number information, the larger the fourth evaluation parameter, and vice versa.

[0028] Furthermore, the collapse detection information generated when the first detection information is generated is: ground-penetrating radar detection is performed every preset time interval c1, and image data analysis is performed every preset time interval d1.

[0029] The collapse detection information generated during the second detection information generation is as follows: ground-penetrating radar detection is performed every preset time interval c2, and image data analysis is performed every preset time interval d2;

[0030] The collapse detection information generated during the third detection information generation is as follows: ground-penetrating radar detection is performed every preset time interval c3, and image data is collected every preset time interval d3.

[0031] The specific processing procedure for the collapse detection parameters is as follows: At least three ground-penetrating radar (GPR) detections are performed continuously within a preset time period, and the data are marked as Z1, Z2, and Z3. Then, the average value of Z1, Z2, and Z3 is calculated, which is the first detection parameter. After that, at least five more image data acquisitions are performed, and the average value of the changing parameters in the acquired image data is calculated, which is the second detection parameter. The first detection parameter and the second detection parameter together constitute the collapse detection parameters.

[0032] Furthermore, the collapse detection and evaluation information includes normal collapse and abnormal collapse. The collected collapse detection parameters are extracted, and a first detection parameter and a second detection parameter are obtained from the collapse detection parameters. When both the first detection parameter and the second detection parameter are less than a preset value, a normal collapse is generated. When both the first detection parameter and the second detection parameter are greater than the preset value, an abnormal collapse is generated.

[0033] Furthermore, the specific process of the image data analysis is as follows: measurement markers are set at preset locations on the road, and the positions of the measurement markers are collected in real time through image acquisition equipment. The height change images of the measurement markers are recorded, and then the height change of the measurement markers within the image duration is calculated to obtain the change parameters.

[0034] A method for detecting the degree of road surface subsidence applicable to different roads, the method comprising the following steps:

[0035] Step 1: Collect road information, including road surface information and road construction time information;

[0036] Step 2: Collect road image information through the image information acquisition module, collect environmental information of the road environment through the environmental information acquisition module, and collect earthquake information of the road location through the earthquake information acquisition module;

[0037] Step 3: The data processing module processes the received road information, road image information, road environment information, and seismic information at the road location to generate first detection information, second detection information, or third detection information;

[0038] Step 4: After any one of the first, second, and third detection information is generated, the central control module sends a control command to the collapse detection module, and the collapse detection module then runs to generate the collapse detection information.

[0039] Step 5: After the collapse detection information is generated, the central control module controls the information sending module to send the collapse detection information to the preset receiving terminal for collapse detection and to obtain the collapse detection parameters.

[0040] Step Six: The collapse detection parameters are then sent to the data processing module for data processing to generate collapse detection and evaluation information.

[0041] Compared with existing technologies, this invention has the following advantages: This method and system for detecting road surface subsidence is applicable to different roads. By processing received road information, road image information, road environment information, and seismic information at the road location, it generates any one of the following: first detection information, second detection information, or third detection information. The first, second, and third detection information represent different detection frequencies, thereby achieving optimal detection of road surface subsidence based on actual road conditions, road environment, and traffic information. This avoids frequent detections that could disrupt traffic. Furthermore, this system and method can be used to detect different types of road surfaces, meeting diverse user needs. More detailed analysis and processing of the detection data allows users to more intuitively understand the degree of road surface subsidence, enabling timely warnings and reducing accidents caused by road damage. This makes the system and method more worthy of widespread adoption. Attached Figure Description

[0042] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0043] The embodiments of the present invention are described in detail below. These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. However, the scope of protection of the present invention is not limited to the following embodiments.

[0044] like Figure 1 As shown, this embodiment provides a technical solution: a road surface collapse degree detection system suitable for different roads, including a road information acquisition module, an image information acquisition module, an environmental information acquisition module, an earthquake information acquisition module, a data receiving module, a data processing module, a central control module, and an information sending module;

[0045] The road information collection module is used to collect road information, which includes road surface information and road construction time information.

[0046] The image information acquisition module is used to acquire road image information, the environmental information acquisition module is used to acquire environmental information of the road, and the earthquake information acquisition module is used to acquire earthquake information of the road location.

[0047] The data receiving module is used to receive road information, road image information, road environment information, and earthquake information at the road location. After recording the above information, it sends the information to the data processing module.

[0048] The data processing module is used to process the received road information, road image information, road environment information, and earthquake information at the road location to generate first detection information, second detection information, or third detection information.

[0049] Once any one of the first detection information, the second detection information, and the third detection information is generated, the central control module sends a control command to the collapse detection module, and the collapse detection module then runs to generate the collapse detection information.

[0050] After the collapse detection information is generated, the central control module controls the information sending module to send the collapse detection information to the preset receiving terminal for collapse detection and to obtain the collapse detection parameters.

[0051] The collapse detection parameters are then sent to the data processing module for data processing to generate collapse detection and evaluation information.

[0052] This invention processes received road information, road image information, road environment information, and seismic information at the road location to generate any one of three detection information: a first detection information, a second detection information, or a third detection information. These three information represent different detection frequencies, allowing for optimal detection of road surface subsidence based on actual road conditions, road environment, and traffic information. This avoids frequent detections that could disrupt traffic flow. Furthermore, the system and method can be used to detect different types of road surfaces, meeting diverse user needs. More detailed analysis of the detection data provides users with a more intuitive understanding of the road surface subsidence level, enabling timely warnings and reducing accidents caused by road damage. Therefore, this system and method are worthy of widespread adoption.

[0053] The specific processing procedures for the first, second, and third detection information are as follows:

[0054] Step 1: Extract the collected road information, extract road surface information and road construction time information from the road information, and process the road surface information and road construction time information to obtain the first evaluation parameters;

[0055] Step 2: Extract the image information, process the image information to obtain the number of passing vehicles and the number of warning vehicle types, and process the number of passing vehicles and the number of warning vehicle types to obtain the second evaluation parameters;

[0056] Step 3: Extract the collected environmental information of the road and process the environmental information to generate the third evaluation parameters;

[0057] Step 4: Extract the seismic information of the road location, process the seismic information to obtain the fourth assessment parameter information;

[0058] Step 5: Calculate and process the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter, and obtain their sum to obtain the total evaluation parameter;

[0059] Step 6: When the total evaluation parameter is greater than the preset value, the third detection information is generated; when the total evaluation parameter is greater than the preset value but within the preset value range, the second detection information is generated; when the total evaluation parameter is less than the preset value, the first detection information is generated.

[0060] The above process ensures the accuracy of the first, second, and third detection information, avoiding road congestion caused by incorrect detection information generation.

[0061] The specific processing procedure for the first evaluation parameter is as follows: extract the collected road surface information and road construction time information, analyze the road surface information to obtain the road surface score K1. When the road surface is a cement concrete road surface, the road surface score K1 is a preset value a1. When the road surface is an asphalt road surface, the road surface score K1 is a preset value a2. When the road surface is a non-cement concrete road surface and an asphalt road surface, the road surface score K1 is a preset value a3, where a1 < a2 < a3.

[0062] The road construction time information is extracted and evaluated to obtain a time score K2. When the road construction time information is greater than the preset value, the time score K2 is the preset value b1. When the road construction time information is within the preset time, the time score K2 is the preset value b2. When the road construction time information is less than the preset value, the time score K2 is the preset value b3, where b3 > b2 > b1.

[0063] Then, the sum of the road surface score K1 and the duration score K2 is calculated, thus obtaining the first evaluation parameter Kk;

[0064] Through the above process, a more accurate first evaluation parameter Kk can be calculated. The larger the first evaluation parameter Kk is, the older the road is, the worse the road surface condition is, and the greater the possibility of road collapse or the greater the degree of road collapse.

[0065] The specific process of processing the image information to obtain the number of passing vehicles and the number of warning vehicle types is as follows: Vehicle model information is preset, including small vehicle model, medium vehicle model and small vehicle model. The vehicle model information is added to the collected road image information, which is road vehicle traffic image information within a preset time period. The number of small vehicles, medium vehicles and large vehicles is analyzed from the road image information. The sum of the number of small vehicles, medium vehicles and large vehicles is calculated, that is, the number of passing vehicles is obtained. The number of warning vehicle types is the same as the number of large vehicles.

[0066] The specific processing procedure for the second evaluation parameter is as follows: Extract the number of passing vehicles and the number of warning vehicle types, continuously collect the number of passing vehicles x times (x≥5), then calculate the average number of passing vehicles x times to obtain the average number of passing vehicles information F1, then continuously collect the number of warning vehicle types x times, then calculate the average number of warning vehicle types x times to obtain the average number of warning vehicles information F2, score F1 (the larger F1 is, the higher the score), score F2 (the larger F2 is, the higher the score), and then calculate the sum of the scores of F1 and F2 to obtain the second evaluation parameter;

[0067] The generated second evaluation parameters allow users to understand the traffic status of the road being inspected. Long periods of heavy and frequent traffic can easily lead to road collapse. Therefore, inspection plans should be developed based on the traffic conditions.

[0068] The specific processing procedure for the third evaluation parameter is as follows: extract the collected environmental information of the road, which is the monthly average rainfall information of the road location, score the monthly average rainfall information to obtain the third evaluation parameter. The larger the monthly average rainfall information, the larger the third evaluation parameter, and vice versa.

[0069] Through the above process, a more accurate third evaluation parameter can be generated. The larger the third evaluation parameter, the worse the detected road environment; the smaller the parameter, the better the detected road environment.

[0070] The specific processing procedure for the fourth evaluation parameter is as follows: extract the earthquake information of the road location. The earthquake information is the earthquake frequency information of the road location within a preset time period. Process the earthquake frequency information to obtain the fourth evaluation parameter. The larger the earthquake frequency information, the larger the fourth evaluation parameter, and vice versa.

[0071] Through the above process, the larger the fourth evaluation parameter, the more earthquakes the road has experienced, and the higher the degree of road collapse is likely to be.

[0072] The collapse detection information generated when the first detection information is generated is: ground-penetrating radar detection is performed every preset time interval c1, and image data analysis is performed every preset time interval d1;

[0073] The collapse detection information generated during the second detection information generation is as follows: ground-penetrating radar detection is performed every preset time interval c2, and image data analysis is performed every preset time interval d2;

[0074] The collapse detection information generated during the third detection information generation is as follows: ground-penetrating radar detection is performed every preset time interval c3, and image data is collected every preset time interval d3.

[0075] The specific processing procedure for the collapse detection parameters is as follows: At least three ground-penetrating radar detections are performed continuously within a preset time period, and the data are marked as Z1, Z2 and Z3. Then, the average value of Z1, Z2 and Z3 is calculated, which is the first detection parameter. Then, at least five image data acquisitions are performed, and the average value of the changing parameters in the acquired image data is calculated, which is the second detection parameter. The first detection parameter and the second detection parameter together constitute the collapse detection parameters.

[0076] Through the above process, more accurate collapse detection parameters can be obtained, thereby more accurately determining whether the road has collapsed.

[0077] The collapse detection and evaluation information includes normal collapse and abnormal collapse. The collected collapse detection parameters are extracted, and a first detection parameter and a second detection parameter are obtained from the collapse detection parameters. When both the first detection parameter and the second detection parameter are less than the preset value, a normal collapse is generated. When both the first detection parameter and the second detection parameter are greater than the preset value, an abnormal collapse is generated.

[0078] Through the above process, users can more intuitively understand whether the road has collapsed.

[0079] The specific process of the image data analysis is as follows: Measurement markers are set at preset locations on the road. The positions of the measurement markers are collected in real time by an image acquisition device, and the height change images of the measurement markers are recorded. Then, the height change of the measurement markers within the image duration is calculated to obtain the change parameters.

[0080] A method for detecting the degree of road surface subsidence applicable to different roads, the method comprising the following steps:

[0081] Step 1: Collect road information, including road surface information and road construction time information;

[0082] Step 2: Collect road image information through the image information acquisition module, collect environmental information of the road environment through the environmental information acquisition module, and collect earthquake information of the road location through the earthquake information acquisition module;

[0083] Step 3: The data processing module processes the received road information, road image information, road environment information, and seismic information at the road location to generate first detection information, second detection information, or third detection information;

[0084] Step 4: After any one of the first, second, and third detection information is generated, the central control module sends a control command to the collapse detection module, and the collapse detection module then runs to generate the collapse detection information.

[0085] Step 5: After the collapse detection information is generated, the central control module controls the information sending module to send the collapse detection information to the preset receiving terminal for collapse detection and to obtain the collapse detection parameters.

[0086] Step Six: The collapse detection parameters are then sent to the data processing module for data processing to generate collapse detection and evaluation information.

[0087] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0088] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0089] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A road surface subsidence detection system applicable to different roads, characterized in that, It includes a road information acquisition module, an image information acquisition module, an environmental information acquisition module, an earthquake information acquisition module, a data receiving module, a data processing module, a central control module, and an information sending module; The road information collection module is used to collect road information, which includes road surface information and road construction time information. The image information acquisition module is used to acquire road image information, the environmental information acquisition module is used to acquire environmental information of the road, and the earthquake information acquisition module is used to acquire earthquake information of the road location. The data receiving module is used to receive road information, road image information, road environment information, and earthquake information at the road location. After recording the above information, it sends the information to the data processing module. The data processing module is used to process the received road information, road image information, road environment information, and earthquake information at the road location to generate first detection information, second detection information, or third detection information. Once any one of the first detection information, the second detection information, and the third detection information is generated, the central control module sends a control command to the collapse detection module, and the collapse detection module then runs to generate the collapse detection information. After the collapse detection information is generated, the central control module controls the information sending module to send the collapse detection information to the preset receiving terminal for collapse detection and to obtain the collapse detection parameters. The collapse detection parameters are then sent to the data processing module for data processing to generate collapse detection and evaluation information. The specific processing procedure for the collapse detection parameters is as follows: At least three ground-penetrating radar detections are performed continuously within a preset time period, and the data are marked as Z1, Z2, and Z3. Then, the average value of Z1, Z2, and Z3 is calculated, which is the first detection parameter. Then, at least five image data acquisitions are performed, and the average value of the changing parameters in the acquired image data is calculated, which is the second detection parameter. The first detection parameter and the second detection parameter together constitute the collapse detection parameters. The specific processing procedures for the first, second, and third detection information are as follows: Step 1: Extract the collected road information, extract road surface information and road construction time information from the road information, and process the road surface information and road construction time information to obtain the first evaluation parameters; Step 2: Extract the image information, process the image information to obtain the number of passing vehicles and the number of warning vehicle types, and process the number of passing vehicles and the number of warning vehicle types to obtain the second evaluation parameters; Step 3: Extract the collected environmental information of the road and process the environmental information to generate the third evaluation parameters; Step 4: Extract the seismic information of the road location, process the seismic information to obtain the fourth assessment parameter information; Step 5: Calculate and process the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter, and obtain their sum to obtain the total evaluation parameter; Step 6: When the total evaluation parameter is greater than the preset value, the third detection information is generated; when the total evaluation parameter is within the preset value range, the second detection information is generated; when the total evaluation parameter is less than the preset value, the first detection information is generated.

2. The road surface subsidence detection system applicable to different roads according to claim 1, characterized in that: The specific processing procedure for the first evaluation parameter is as follows: extract the collected road surface information and road construction time information, analyze the road surface information to obtain the road surface score K1. When the road surface is a cement concrete road surface, the road surface score K1 is a preset value a1. When the road surface is an asphalt road surface, the road surface score K1 is a preset value a2. When the road surface is a non-cement concrete road surface and an asphalt road surface, the road surface score K1 is a preset value a3, where a1 < a2 < a3. The road construction time information is extracted and evaluated to obtain a time score K2. When the road construction time information is greater than the preset value, the time score K2 is the preset value b1. When the road construction time information is within the preset time, the time score K2 is the preset value b2. When the road construction time information is less than the preset value, the time score K2 is the preset value b3, where b3 > b2 > b1. Then, the sum of the road surface score K1 and the duration score K2 is calculated, which yields the first evaluation parameter Kk.

3. The road surface subsidence detection system applicable to different roads according to claim 2, characterized in that: The specific process of processing the image information to obtain the number of passing vehicles and the number of warning vehicle types is as follows: Vehicle model information is preset, including large vehicle models, medium vehicle models and small vehicle models. The road image information is the road vehicle traffic image information within a preset time period. The number of small vehicles, medium vehicles and large vehicles is analyzed from the road image information. The sum of the number of small vehicles, medium vehicles and large vehicles is calculated, that is, the number of passing vehicles is obtained. The number of warning vehicle types is the same as the number of large vehicles. The specific processing procedure for the second evaluation parameter is as follows: Extract the number of passing vehicles and the number of warning vehicle types. Collect the number of passing vehicles x times consecutively, where x ≥ 5. Then calculate the average number of passing vehicles x times to obtain the average number of passing vehicles information F1. Collect the number of warning vehicle types x times consecutively, and then calculate the average number of warning vehicle types x times to obtain the average number of warning vehicle types information F2. Score F1; the larger F1 is, the higher the score. Score F2; the larger F2 is, the higher the score. Finally, calculate the sum of the scores of F1 and F2 to obtain the second evaluation parameter.

4. The road surface subsidence detection system applicable to different roads according to claim 2, characterized in that: The specific processing procedure for the third evaluation parameter is as follows: extract the collected environmental information of the road, which is the monthly average rainfall information of the road location, score the monthly average rainfall information to obtain the third evaluation parameter. The larger the monthly average rainfall information, the larger the third evaluation parameter, and vice versa.

5. The road surface subsidence detection system applicable to different roads according to claim 1, characterized in that: The specific processing procedure for the fourth evaluation parameter is as follows: extract the earthquake information of the road location. The earthquake information is the earthquake frequency information of the road location within a preset time period. Process the earthquake frequency information to obtain the fourth evaluation parameter. The larger the earthquake frequency information, the larger the fourth evaluation parameter, and vice versa.

6. The road surface subsidence detection system applicable to different roads according to claim 1, characterized in that: The collapse detection information generated when the first detection information is generated is: ground-penetrating radar detection is performed every preset time interval c1, and image data analysis is performed every preset time interval d1; The collapse detection information generated during the second detection information generation is as follows: ground-penetrating radar detection is performed every preset time interval c2, and image data analysis is performed every preset time interval d2; The collapse detection information generated during the third detection information generation is as follows: ground-penetrating radar detection is performed every preset time interval c3, and image data analysis is performed every preset time interval d3.

7. A road surface subsidence detection system applicable to different roads according to claim 6, characterized in that: The collapse detection and evaluation information includes normal collapse and abnormal collapse. The collected collapse detection parameters are extracted, and a first detection parameter and a second detection parameter are obtained from the collapse detection parameters. When both the first detection parameter and the second detection parameter are less than the preset value, a normal collapse is generated. When both the first detection parameter and the second detection parameter are greater than the preset value, an abnormal collapse is generated.

8. A road surface subsidence detection system applicable to different roads according to claim 7, characterized in that: The specific process of the image data analysis is as follows: Measurement markers are set at preset locations on the road. The positions of the measurement markers are collected in real time by an image acquisition device, and the height change images of the measurement markers are recorded. Then, the height change of the measurement markers within the image duration is calculated to obtain the change parameters.

9. A method for detecting the degree of road surface subsidence applicable to different roads, wherein the method is applied in the detection system described in any one of claims 1-8, characterized in that: The method includes the following steps: Step 1: Collect road information, including road surface information and road construction time information; Step 2: Collect road image information through the image information acquisition module, collect environmental information of the road environment through the environmental information acquisition module, and collect earthquake information of the road location through the earthquake information acquisition module; Step 3: The data processing module processes the received road information, road image information, road environment information, and seismic information at the road location to generate first detection information, second detection information, or third detection information; Step 4: After any one of the first, second, and third detection information is generated, the central control module sends a control command to the collapse detection module, and the collapse detection module then runs to generate the collapse detection information. Step 5: After the collapse detection information is generated, the central control module controls the information sending module to send the collapse detection information to the preset receiving terminal for collapse detection and to obtain the collapse detection parameters. Step Six: The collapse detection parameters are then sent to the data processing module for data processing to generate collapse detection and evaluation information.

Images