Method and system for evaluating frost heave degree of airport concrete pavement

Abstract

The present invention relates to the technical field of pavement analysis. Disclosed are a method and system for evaluating the frost heave degree of an airport concrete pavement. The method comprises the following steps: step 1, dividing an airport concrete pavement into a plurality of monitoring areas, and periodically acquiring frost heave monitoring logs of each monitoring area; step 2, evaluating each monitoring area as a core frost heave area or an ordinary area on the basis of the frost heave monitoring logs; and step 3, analyzing potential associated areas of core frost heave areas, and then evaluating the frost heave degree of the airport concrete pavement. By means of the method, frost heave positions of the surface of an airport concrete pavement can be analyzed within a certain time, and potential frost heave positions of the airport concrete pavement can be accurately analyzed by means of association, thereby ensuring the accuracy of subsequent evaluation of the frost heave degree of the airport concrete pavement.

Description

A method and system for assessing the frost heave of airport concrete pavement Technical Field

[0001] This invention relates to the field of pavement analysis technology, and more specifically, to a method and system for assessing the degree of frost heave in airport concrete pavements. Background Technology

[0002] Frost heave is caused by the freezing of water in the soil and the growth of ice (especially lenticular ice), leading to soil expansion and uneven surface uplift. Assessing the frost heave of certain roads, such as airport concrete pavements, is particularly important. Currently, concrete pavement assessments are typically categorized into four types: no frost heave, weak frost heave, frost heave, and strong frost heave. However, when assessing the frost heave of airport concrete pavements, some sections are still in the potential frost heave stage during the assessment period, and their frost heave information is not yet apparent. Furthermore, due to the large area of ​​airport concrete pavements, existing assessment methods cannot accurately assess the overall frost heave extent of airport concrete pavements. Summary of the Invention

[0003] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a method and system for assessing the degree of frost heave of airport concrete pavement.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A method for assessing the frost heave of airport concrete pavement includes the following steps:

[0006] Step 1: Divide the airport concrete pavement into multiple monitoring areas and periodically obtain frost heave monitoring logs for each monitoring area;

[0007] Step 2: Based on the frost heave monitoring log, evaluate the monitored area as either a core frost heave area or a normal area;

[0008] Step 3: Analyze the potential related areas of the core frost heave zone, and then assess the degree of frost heave of the airport concrete pavement.

[0009] Furthermore, an airport concrete pavement frost heave assessment system includes a regional monitoring module, a regional evaluation module, and a frost heave assessment module.

[0010] The regional monitoring module divides the airport concrete pavement into multiple monitoring areas and periodically acquires frost heave monitoring logs for each monitoring area.

[0011] The regional evaluation module evaluates the monitored area as a core frost heave area or a normal area based on the frost heave monitoring log.

[0012] The frost heave assessment module analyzes the potential associated areas of the core frost heave region, thereby assessing the degree of frost heave of the airport concrete pavement.

[0013] Furthermore, the airport concrete pavement is divided into multiple monitoring areas. Based on a preset cycle, at each cycle node, the basic data of frost heave in the monitoring area is acquired, and a frost heave monitoring log for the monitoring area is generated. The frost heave monitoring log includes the frost heave evaluation value and the node time.

[0014] Furthermore, the frost heave evaluation value of the frost heave monitoring log is obtained in the following way: the basic frost heave data is used as the input data of the frost heave evaluation model to obtain the frost heave evaluation value.

[0015] Furthermore, a frost heave evaluation threshold is set. When the frost heave evaluation value in the frost heave monitoring log is less than the frost heave evaluation threshold, the number of frost heave markers is increased by one.

[0016] Furthermore, based on the frost heave monitoring log, the monitored area is evaluated as either a core frost heave area or a normal area, specifically as follows:

[0017] After continuously acquiring n frost heave monitoring logs for the monitoring area, the frost heave evaluation value of the monitoring log is marked as ZPi, where i is the sequential number of the frost heave monitoring log, i=1, 2, ..., n. The number of frost heave markings is summed to obtain the total number of frost heave markings, which is then marked as AHM. The formula is then used... The regional frost heave value TYB of the monitoring area is obtained, where a1 is the frost heave evaluation value coefficient and a2 is the coefficient of the total number of frost heave markings.

[0018] Set a regional frost heave threshold. When the regional frost heave value of the monitored area is greater than or equal to the regional frost heave threshold, the monitored area is marked as a core frost heave area.

[0019] When the regional frost heave value of the monitored area is less than the regional frost heave threshold, the monitored area is marked as a normal area.

[0020] Furthermore, the potential associated areas of the core frost heave region are analyzed. Specifically, a preset range is set with the core frost heave region as the center, and ordinary areas located within the preset range are marked as pre-selected areas.

[0021] Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the core frost heave region, and mark them as follows: Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the pre-selected area, and mark them as follows: The cosine similarity algorithm was used to calculate the potential correlation value between the core frost heave region and the pre-selected region.

[0022] Set a potential correlation threshold for frost heave. When the potential correlation value between the core frost heave region and the pre-selected region is greater than or equal to the potential correlation threshold, the pre-selected region is marked as a potential correlation region.

[0023] Furthermore, the total number of frost heave fluctuations is obtained as follows: All frost heave monitoring logs for the monitoring area are retrieved. The frost heave evaluation values ​​of all logs are sorted according to the chronological order of the nodes. The preceding and following frost heave evaluation values ​​are compared. If the preceding value is less than the following value, the difference between the two values ​​is calculated to obtain the frost heave change value. A frost heave change threshold is set; this threshold is a system-defined threshold that can be modified according to actual needs. When the frost heave change value is greater than or equal to the threshold, the number of frost heave fluctuations is incremented by one. When the frost heave change value is less than the threshold, no action is taken. The total number of frost heave fluctuations is then summed to obtain the total number of fluctuations.

[0024] Furthermore, the total number of evaluation changes is obtained as follows: All frost heave monitoring logs for the monitoring area are retrieved, and the frost heave evaluation values ​​for each log are obtained. High and low frost heave evaluation values ​​are set, both of which are system-preset thresholds that can be modified according to actual needs. When the frost heave evaluation value of a monitoring log is greater than the high value, the log is rated as a high-rated log. When the frost heave evaluation value is less than the high value, the log is rated as a low-rated log. When the frost heave evaluation value is between the high and low values, the log is rated as a medium-rated log. All frost heave monitoring logs are sorted according to their node time sequence. The evaluations of adjacent logs are compared. If the evaluations of adjacent logs are different, the number of evaluation changes is increased by one. If the evaluations of adjacent logs are the same, no action is taken. The total number of evaluation changes is then summed.

[0025] Furthermore, the degree of frost heave in the airport concrete pavement is assessed, specifically: the total number of core frost heave areas in the airport concrete pavement is obtained and labeled as SXP; the total number of potentially associated areas in the airport concrete pavement is obtained and labeled as BGC; the total number of monitored areas in the airport concrete pavement is obtained and labeled as AYG; and the formula is used to assess the frost heave. The degree assessment value Lj is obtained, where b1 is the total number coefficient of the core frost heave area and b2 is the total number coefficient of the potential associated area;

[0026] Each severity assessment value Lj is set to correspond to a frost heave assessment level. The severity assessment value Lj ranges from (0, L1], (L1, L2], ..., (Lj-1, Lj], and the frost heave assessment levels include frost heave assessment level 1, frost heave assessment level 2, ..., frost heave assessment level j-1, and frost heave assessment level j.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] 1. The method of the present invention can analyze the frost heave location of the airport concrete pavement surface within a certain period of time, and accurately analyze the potential frost heave location of the airport concrete pavement through correlation, so as to ensure the accuracy of subsequent assessment of the degree of frost heave of the airport concrete pavement.

[0029] 2. Set up regional monitoring and regional evaluation modules to divide the airport concrete pavement into multiple monitoring areas. Perform periodic analysis on each monitoring area to ensure accurate frost heave assessment for each monitoring area. Set up a frost heave evaluation module to analyze the potential related areas of the core frost heave area through correlation and three-dimensional analysis. Without needing to observe the frost heave information of the airport concrete pavement over a long period of time, it can accurately analyze the potential frost heave areas of the airport concrete pavement, ensuring the accuracy of subsequent assessment of the degree of frost heave of the airport concrete pavement. Attached Figure Description

[0030] Figure 1 is a flowchart of a method for assessing the frost heave of airport concrete pavement;

[0031] Figure 2 is a flowchart of the process for evaluating the monitoring area as a core frost heave area or a normal area.

[0032] Figure 3 is a flowchart for assessing the degree of frost heave of airport concrete pavement. Detailed Implementation Example

[0033] Referring to Figure 1, a method for assessing the frost heave of airport concrete pavement includes the following steps:

[0034] Step 1: Divide the airport concrete pavement into multiple monitoring areas and periodically obtain frost heave monitoring logs for each monitoring area;

[0035] Specifically, the airport concrete pavement is divided into multiple monitoring areas. Based on a preset cycle, at each cycle node, the basic data of frost heave in the monitoring area is obtained, and a frost heave monitoring log for the monitoring area is generated. The frost heave monitoring log includes the frost heave evaluation value and the node time (the time corresponding to the cycle node).

[0036] The frost heave evaluation value of the frost heave monitoring log is obtained in the following way: the basic frost heave data is used as the input data of the frost heave evaluation model to obtain the frost heave evaluation value.

[0037] Airport concrete pavement can be divided into multiple monitoring areas using a matrix partitioning method.

[0038] Basic data on frost heave include moisture content, soil particle size distribution, and soil temperature in the monitored area.

[0039] The frost heave evaluation model is obtained as follows: Multiple sets of basic frost heave data are acquired. This data can be real or virtual. This basic data is used as training data for the neural network model. The training data is labeled, and the labels are the frost heave evaluation values, ranging from 0 to 3. The training data is divided into a training set and a validation set according to a set ratio, which can be adjusted as needed. The neural network is iteratively trained using the training and validation sets. After training, the frost heave evaluation model is obtained. A frost heave evaluation value closer to 0 indicates a lower degree of frost heave in the monitored area, while a value closer to 3 indicates a higher degree of frost heave.

[0040] Set the frost heave evaluation threshold. The frost heave evaluation threshold is a system preset threshold and can be modified according to actual needs.

[0041] When the frost heave evaluation value in the frost heave monitoring log is greater than or equal to the frost heave evaluation threshold, no corresponding action is taken.

[0042] When the frost heave evaluation value in the frost heave monitoring log is less than the frost heave evaluation threshold, the number of frost heave markers will be increased by one.

[0043] Step Two: Evaluate the monitored area as a core frost heave area or a normal area based on the frost heave monitoring logs; specifically, after continuously acquiring n frost heave monitoring logs for the monitored area, mark the frost heave evaluation value of the frost heave monitoring log as ZPi, where i is the sequential number of the frost heave monitoring log, i=1, 2, ..., n. Sum the number of frost heave markings to obtain the total number of frost heave markings, and mark it as AHM. Use the formula... The regional frost heave value TYB of the monitoring area is obtained, where a1 is the frost heave evaluation value coefficient and a2 is the coefficient of the total number of frost heave markings. The value of a1 is 1.81 and the value of a2 is 1.13.

[0044] Set the regional frost heave threshold. The regional frost heave threshold is a system-set threshold that can be modified according to actual needs.

[0045] When the regional frost heave value of the monitored area is greater than or equal to the regional frost heave threshold, the monitored area is marked as the core frost heave area.

[0046] When the regional frost heave value of the monitored area is less than the regional frost heave threshold, the monitored area is marked as a normal area.

[0047] The system includes a regional monitoring module and a regional evaluation module. The airport concrete pavement is divided into multiple monitoring areas, and each monitoring area is periodically analyzed to ensure accurate frost heave assessment for each monitoring area.

[0048] Step 3: Analyze the potential related areas of the core frost heave zone to assess the degree of frost heave on the airport concrete pavement. Specifically, take the core frost heave zone as the center, set a preset range (the preset range is the area centered on the core frost heave zone, and the area can be modified according to actual needs), and mark the ordinary areas located within the preset range as pre-selected areas.

[0049] Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the core frost heave region, and mark them as follows: A1 represents the total number of frost heave fluctuations in the core frost heave region, and A2 represents the total number of evaluation changes in the core frost heave region. The total number of frost heave fluctuations and the total number of evaluation changes in the pre-selected region are obtained and marked as follows: B1 represents the total number of frost heave fluctuations in the pre-selected region, and B2 represents the total number of evaluation changes in the pre-selected region. The cosine similarity algorithm is used to calculate the potential correlation value between the core frost heave region and the pre-selected region.

[0050] Example: The total number of frost heave fluctuations in the core frost heave region is 8, and the total number of evaluation changes in the core frost heave region is 12. The total number of frost heave fluctuations in the pre-selected region is 7, and the total number of evaluation changes in the pre-selected region is 11. What is the potential correlation value between the frost heave of the core frost heave region and the pre-selected region? .

[0051] The total number of frost heave fluctuations is obtained as follows: All frost heave monitoring logs for the monitoring area are retrieved. The frost heave evaluation values ​​of all logs are sorted according to the chronological order of the nodes. The preceding and following frost heave evaluation values ​​are compared. If the preceding value is less than the following value, the difference between the two values ​​is calculated to obtain the frost heave change value. A frost heave change threshold is set; this threshold is a system-defined threshold that can be modified according to actual needs. When the frost heave change value is greater than or equal to the threshold, the frost heave fluctuation count is incremented by one. When the frost heave change value is less than the threshold, no action is taken. The total number of frost heave fluctuations is then summed to obtain the total number of fluctuations.

[0052] The total number of evaluation changes is obtained as follows: All frost heave monitoring logs for the monitoring area are retrieved, and the frost heave evaluation values ​​for each log are obtained. High and low frost heave evaluation values ​​are set, both of which are system-preset thresholds and can be modified according to actual needs. When the frost heave evaluation value of a log is greater than the high value, the log is rated as a high-rated log. When the frost heave evaluation value is less than the high value, the log is rated as a low-rated log. When the frost heave evaluation value is between the high and low values, the log is rated as a medium-rated log. All logs are sorted according to their node time sequence. The evaluations of adjacent logs are compared. If the evaluations of adjacent logs are different, the number of evaluation changes is increased by one. If the evaluations of adjacent logs are the same, no action is taken. The total number of evaluation changes is then summed.

[0053] Set a potential correlation threshold for frost heave. This threshold is a system-defined threshold and can be modified according to actual needs.

[0054] When the potential correlation value between the core frost heave region and the pre-selected region is greater than or equal to the potential correlation threshold, the pre-selected region is marked as a potential correlation region.

[0055] When the potential correlation value between the core frost heave region and the pre-selected region is less than the potential correlation threshold for frost heave, no corresponding action is taken.

[0056] Obtain the total number of core frost heave regions in the airport concrete pavement and label them as SXP; obtain the total number of potentially associated regions in the airport concrete pavement and label them as BGC (when a monitoring area is simultaneously labeled as a core frost heave region and a potentially associated region, the monitoring area is labeled as a core frost heave region); obtain the total number of monitoring areas in the airport concrete pavement and label them as AYG; and use the formula... The degree assessment value Lj is obtained, where b1 is the total number coefficient of the core frost heave area and b2 is the total number coefficient of the potential associated area. The value of b1 is 5 and the value of b2 is 2.

[0057] Each severity assessment value Lj is set to correspond to a frost heave assessment level. The range of severity assessment value Lj includes (0, L1], (L1, L2], ..., (Lj-1, Lj], and the frost heave assessment levels include frost heave assessment level 1, frost heave assessment level 2, ..., frost heave assessment level j-1, and frost heave assessment level j. When Lj∈(0, L1], the frost heave severity of the airport concrete pavement is assessed as frost heave assessment level 1. The higher the frost heave assessment level, the more severe the frost heave of the airport concrete pavement.

[0058] The above method can analyze the frost heave location of the airport concrete pavement surface within a certain period of time, and accurately analyze the potential frost heave location of the airport concrete pavement through correlation, ensuring the accuracy of subsequent assessment of the degree of frost heave of the airport concrete pavement.

[0059] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. Example

[0060] Referring to Figures 2-3, an airport concrete pavement frost heave assessment system includes a regional monitoring module, a regional evaluation module, and a frost heave assessment module.

[0061] The regional monitoring module divides the airport concrete pavement into multiple monitoring areas. Based on a preset cycle, it acquires the basic data on frost heave of the monitoring area at each cycle node and generates a frost heave monitoring log for the monitoring area. The frost heave monitoring log includes the frost heave evaluation value and the node time (the time corresponding to the cycle node).

[0062] The frost heave evaluation value of the frost heave monitoring log is obtained in the following way: the basic frost heave data is used as the input data of the frost heave evaluation model to obtain the frost heave evaluation value.

[0063] Airport concrete pavement can be divided into multiple monitoring areas using a matrix partitioning method.

[0064] Basic data on frost heave include moisture content, soil particle size distribution, and soil temperature in the monitored area.

[0065] The frost heave evaluation model is obtained as follows: Multiple sets of basic frost heave data are acquired. This data can be real or virtual. This basic data is used as training data for the neural network model. The training data is labeled, and the labels are the frost heave evaluation values, ranging from 0 to 3. The training data is divided into a training set and a validation set according to a set ratio, which can be adjusted as needed. The neural network is iteratively trained using the training and validation sets. After training, the frost heave evaluation model is obtained. A frost heave evaluation value closer to 0 indicates a lower degree of frost heave in the monitored area, while a value closer to 3 indicates a higher degree of frost heave.

[0066] Set the frost heave evaluation threshold. The frost heave evaluation threshold is a system preset threshold and can be modified according to actual needs.

[0067] When the frost heave evaluation value in the frost heave monitoring log is greater than or equal to the frost heave evaluation threshold, no corresponding action is taken.

[0068] When the frost heave evaluation value in the frost heave monitoring log is less than the frost heave evaluation threshold, the number of frost heave markers will be increased by one.

[0069] The regional evaluation module: After continuously acquiring n frost heave monitoring logs for the monitoring area, it marks the frost heave evaluation value of the frost heave monitoring log as ZPi, where i is the sequential number of the frost heave monitoring log, i=1, 2, ..., n. It then sums the number of frost heave markings to obtain the total number of frost heave markings, which is marked as AHM. The formula is then used... The regional frost heave value TYB of the monitoring area is obtained, where a1 is the frost heave evaluation value coefficient and a2 is the coefficient of the total number of frost heave markings. The value of a1 is 1.81 and the value of a2 is 1.13.

[0070] Set the regional frost heave threshold. The regional frost heave threshold is a system-set threshold that can be modified according to actual needs.

[0071] When the regional frost heave value of the monitored area is greater than or equal to the regional frost heave threshold, the monitored area is marked as the core frost heave area.

[0072] When the regional frost heave value of the monitored area is less than the regional frost heave threshold, the monitored area is marked as a normal area.

[0073] The system includes a regional monitoring module and a regional evaluation module. The airport concrete pavement is divided into multiple monitoring areas, and each monitoring area is periodically analyzed to ensure accurate frost heave assessment for each monitoring area.

[0074] The frost heave assessment module: takes the core frost heave area as the center, sets a preset range (the preset range is the range centered on the core frost heave area, and the area of ​​the range can be modified according to actual needs), and marks ordinary areas located within the preset range as pre-selected areas.

[0075] Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the core frost heave region, and mark them as follows: A1 represents the total number of frost heave fluctuations in the core frost heave region, and A2 represents the total number of evaluation changes in the core frost heave region. The total number of frost heave fluctuations and the total number of evaluation changes in the pre-selected region are obtained and marked as follows: B1 represents the total number of frost heave fluctuations in the pre-selected region, and B2 represents the total number of evaluation changes in the pre-selected region. The cosine similarity algorithm is used to calculate the potential correlation value between the core frost heave region and the pre-selected region.

[0076] Example: The total number of frost heave fluctuations in the core frost heave region is 8, and the total number of evaluation changes in the core frost heave region is 12. The total number of frost heave fluctuations in the pre-selected region is 7, and the total number of evaluation changes in the pre-selected region is 11. What is the potential correlation value between the frost heave of the core frost heave region and the pre-selected region? .

[0077] The total number of frost heave fluctuations is obtained as follows: All frost heave monitoring logs for the monitoring area are retrieved. The frost heave evaluation values ​​of all logs are sorted according to the chronological order of the nodes. The preceding and following frost heave evaluation values ​​are compared. If the preceding value is less than the following value, the difference between the two values ​​is calculated to obtain the frost heave change value. A frost heave change threshold is set; this threshold is a system-defined threshold that can be modified according to actual needs. When the frost heave change value is greater than or equal to the threshold, the frost heave fluctuation count is incremented by one. When the frost heave change value is less than the threshold, no action is taken. The total number of frost heave fluctuations is then summed to obtain the total number of fluctuations.

[0078] The total number of evaluation changes is obtained as follows: All frost heave monitoring logs for the monitoring area are retrieved, and the frost heave evaluation values ​​for each log are obtained. High and low frost heave evaluation values ​​are set, both of which are system-preset thresholds and can be modified according to actual needs. When the frost heave evaluation value of a log is greater than the high value, the log is rated as a high-rated log. When the frost heave evaluation value is less than the high value, the log is rated as a low-rated log. When the frost heave evaluation value is between the high and low values, the log is rated as a medium-rated log. All logs are sorted according to their node time sequence. The evaluations of adjacent logs are compared. If the evaluations of adjacent logs are different, the number of evaluation changes is increased by one. If the evaluations of adjacent logs are the same, no action is taken. The total number of evaluation changes is then summed.

[0079] Set a potential correlation threshold for frost heave. This threshold is a system-defined threshold and can be modified according to actual needs.

[0080] When the potential correlation value between the core frost heave region and the pre-selected region is greater than or equal to the potential correlation threshold, the pre-selected region is marked as a potential correlation region.

[0081] When the potential correlation value between the core frost heave region and the pre-selected region is less than the potential correlation threshold for frost heave, no corresponding action is taken.

[0082] Obtain the total number of core frost heave regions in the airport concrete pavement and label them as SXP; obtain the total number of potentially associated regions in the airport concrete pavement and label them as BGC (when a monitoring area is simultaneously labeled as a core frost heave region and a potentially associated region, the monitoring area is labeled as a core frost heave region); obtain the total number of monitoring areas in the airport concrete pavement and label them as AYG; and use the formula... The degree assessment value Lj is obtained, where b1 is the total number coefficient of the core frost heave area and b2 is the total number coefficient of the potential associated area. The value of b1 is 5 and the value of b2 is 2.

[0083] Each severity assessment value Lj is set to correspond to a frost heave assessment level. The range of severity assessment value Lj includes (0, L1], (L1, L2], ..., (Lj-1, Lj], and the frost heave assessment levels include frost heave assessment level 1, frost heave assessment level 2, ..., frost heave assessment level j-1, and frost heave assessment level j. When Lj∈(0, L1], the frost heave severity of the airport concrete pavement is assessed as frost heave assessment level 1. The higher the frost heave assessment level, the more severe the frost heave of the airport concrete pavement.

[0084] A frost heave assessment module is set up. Through correlational three-dimensional analysis of the potential related areas of the core frost heave area, it can accurately analyze the potential frost heave areas of the airport concrete pavement without having to observe the frost heave information of the airport concrete pavement over a long time period, thus ensuring the accuracy of subsequent assessment of the degree of frost heave of the airport concrete pavement.

[0085] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0086] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0087] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0088] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0089] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0090] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0091] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0092] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for assessing the frost heave of airport concrete pavement, characterized in that, Includes the following steps: Step 1: Divide the airport concrete pavement into multiple monitoring areas and periodically obtain frost heave monitoring logs for each monitoring area; Step 2: Based on the frost heave monitoring log, evaluate the monitored area as either a core frost heave area or a normal area; Step 3: Analyze the potential related areas of the core frost heave zone, and then assess the degree of frost heave of the airport concrete pavement.

2. A system for assessing the frost heave of airport concrete pavements, applied to the method for assessing the frost heave of airport concrete pavements as described in claim 1, characterized in that, Includes a regional monitoring module, a regional evaluation module, and a frost heave assessment module; The regional monitoring module divides the airport concrete pavement into multiple monitoring areas and periodically acquires frost heave monitoring logs for each monitoring area. The regional evaluation module evaluates the monitored area as a core frost heave area or a normal area based on the frost heave monitoring log. The frost heave assessment module analyzes the potential associated areas of the core frost heave region, thereby assessing the degree of frost heave of the airport concrete pavement.

3. The airport concrete pavement frost heave assessment system according to claim 2, characterized in that, The airport concrete pavement is divided into multiple monitoring areas. Based on a preset cycle, at each cycle node, the basic data of frost heave in the monitoring area is obtained, and a frost heave monitoring log for the monitoring area is generated. The frost heave monitoring log includes the frost heave evaluation value and the node time.

4. The airport concrete pavement frost heave assessment system according to claim 3, characterized in that, The frost heave evaluation value of the frost heave monitoring log is obtained in the following way: the basic frost heave data is used as the input data of the frost heave evaluation model to obtain the frost heave evaluation value.

5. The airport concrete pavement frost heave assessment system according to claim 4, characterized in that, Set a frost heave evaluation threshold. When the frost heave evaluation value in the frost heave monitoring log is less than the frost heave evaluation threshold, increase the number of frost heave markers by one.

6. The airport concrete pavement frost heave assessment system according to claim 5, characterized in that, Based on the frost heave monitoring log, the monitored area was evaluated as either a core frost heave area or a normal area, specifically: After continuously acquiring n frost heave monitoring logs for the monitoring area, the frost heave evaluation value of the monitoring log is marked as ZPi, where i is the sequential number of the frost heave monitoring log, i=1, 2, ..., n. The number of frost heave markings is summed to obtain the total number of frost heave markings, which is then marked as AHM. The formula is then used... The regional frost heave value TYB of the monitoring area is obtained, where a1 is the frost heave evaluation value coefficient and a2 is the coefficient of the total number of frost heave markings. Set a regional frost heave threshold. When the regional frost heave value of the monitored area is greater than or equal to the regional frost heave threshold, the monitored area is marked as a core frost heave area. When the regional frost heave value of the monitored area is less than the regional frost heave threshold, the monitored area is marked as a normal area.

7. The airport concrete pavement frost heave assessment system according to claim 6, characterized in that, The analysis of potential related areas of the core frost heave region is as follows: taking the core frost heave region as the center, a preset range is set, and ordinary areas located within the preset range are marked as pre-selected areas; Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the core frost heave region, and mark them as follows: Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the pre-selected area, and mark them as follows: The cosine similarity algorithm was used to calculate the potential correlation value between the core frost heave region and the pre-selected region. Set a potential correlation threshold for frost heave. When the potential correlation value between the core frost heave region and the pre-selected region is greater than or equal to the potential correlation threshold, the pre-selected region is marked as a potential correlation region.

8. The airport concrete pavement frost heave assessment system according to claim 7, characterized in that, The total number of frost heave fluctuations is obtained as follows: All frost heave monitoring logs for the monitoring area are retrieved. The frost heave evaluation values ​​of all logs are sorted according to the chronological order of the nodes. The preceding and following frost heave evaluation values ​​are compared. If the preceding value is less than the following value, the difference between the two values ​​is calculated to obtain the frost heave change value. A frost heave change threshold is set; this threshold is a system-defined threshold that can be modified according to actual needs. When the frost heave change value is greater than or equal to the threshold, the frost heave fluctuation count is incremented by one. When the frost heave change value is less than the threshold, no action is taken. The total number of frost heave fluctuations is then summed to obtain the total number of fluctuations.

9. The airport concrete pavement frost heave assessment system according to claim 8, characterized in that, The total number of evaluation changes is obtained as follows: All frost heave monitoring logs for the monitoring area are retrieved, and the frost heave evaluation values ​​for each log are obtained. High and low frost heave evaluation values ​​are set, both of which are system-preset thresholds and can be modified according to actual needs. When the frost heave evaluation value of a log is greater than the high value, the log is rated as a high-rated log. When the frost heave evaluation value is less than the high value, the log is rated as a low-rated log. When the frost heave evaluation value is between the high and low values, the log is rated as a medium-rated log. All logs are sorted according to their node time sequence. The evaluations of adjacent logs are compared. If the evaluations of adjacent logs are different, the number of evaluation changes is increased by one. If the evaluations of adjacent logs are the same, no action is taken. The total number of evaluation changes is then summed.

10. The airport concrete pavement frost heave assessment system according to claim 9, characterized in that, The assessment of frost heave in airport concrete pavement involves: obtaining the total number of core frost heave zones (SXP), the total number of potentially associated zones (BGC), and the total number of monitored zones (AYG). The assessment is then performed using the formula... The degree assessment value Lj is obtained, where b1 is the total number coefficient of the core frost heave area and b2 is the total number coefficient of the potential associated area; Each severity assessment value Lj is set to correspond to a frost heave assessment level. The severity assessment value Lj ranges from (0, L1] to (L1, L2], ..., (Lj-1, Lj], and the frost heave assessment levels include frost heave assessment level 1, frost heave assessment level 2, ..., frost heave assessment level j-1, and frost heave assessment level j.

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