An evaluation method and system for the frost heave degree of airport concrete pavements

Abstract

The present invention discloses a method and system for evaluating the frost heave degree of airport concrete pavements, which relates to the technical field of pavement analysis. The method discloses the following steps: Step 1: Divide the airport concrete pavement into multiple monitoring areas, and periodically obtain the frost heave monitoring logs of each monitoring area; Step 2: Evaluate the monitoring area as a core frost heave area or an ordinary area according to the frost heave monitoring logs; Step 3: Analyze the potential associated areas of the core frost heave area, and then evaluate the frost heave degree of the airport concrete pavement. This method can analyze the frost heave positions on the surface of the airport concrete pavement within a certain period of time, and accurately analyze the potential frost heave positions of the airport concrete pavement through association, ensuring the evaluation accuracy of the subsequent frost heave degree of the airport concrete pavement.

Description

Technical Field

[0001] The present invention relates to the technical field of pavement analysis, and more specifically, it relates to a method and system for evaluating the frost heave degree of airport concrete pavements. Background Art

[0002] Frost heave is the effect of soil expansion and uneven surface uplift caused by the freezing of water in the soil and the growth of ice bodies (especially lenticular ice bodies). The evaluation of the frost heave degree of some specific roads, such as airport concrete pavements, is particularly important. Currently, the evaluation of concrete pavements is usually divided into four categories, namely: no frost heave, weak frost heave, frost heave, and strong frost heave. At the same time, when evaluating the frost heave degree of airport concrete pavements, some pavements are still in the potential frost heave stage during the evaluation period, and the frost heave information at their locations has not yet emerged. At the same time, due to the large area of airport concrete pavements, the existing evaluation methods cannot accurately evaluate the frost heave degree of the entire airport concrete pavement. Summary of the Invention

[0003] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a method and system for evaluating the frost heave degree of airport concrete pavements.

[0004] To achieve the above purpose, the present invention provides the following technical solutions:

[0005] A method for evaluating the frost heave degree of airport concrete pavements includes the following steps:

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

[0007] Step 2: Evaluate the monitoring area as a core frost heave area or an ordinary area according to the frost heave monitoring log;

[0008] Step 3: Analyze the potential associated areas of the core frost heave area, and then evaluate the frost heave degree of the airport concrete pavement.

[0009] Furthermore, a system for evaluating the frost heave degree of airport concrete pavements includes a regional monitoring module, a regional evaluation module, and a frost heave evaluation module;

[0010] The regional monitoring module divides the airport concrete pavement into multiple monitoring areas and periodically obtains the frost heave monitoring logs of each monitoring area;

[0011] The regional evaluation module evaluates the monitoring area as a core frost heave area or an ordinary area according to the frost heave monitoring log;

[0012] The frost heave evaluation module analyzes the potential associated areas of the core frost heave area, and then evaluates the frost heave degree of the airport concrete pavement.

[0013] Furthermore, divide the airport concrete pavement into multiple monitoring areas. Based on a preset cycle, when each cycle node arrives, obtain the frost heaving basic data of the monitoring area and generate a frost heaving monitoring log for the monitoring area. The frost heaving monitoring log includes a frost heaving evaluation value and a node time.

[0014] Furthermore, the frost heaving evaluation value of the frost heaving monitoring log is obtained through the following method: Use the frost heaving basic data as the input data of the frost heaving evaluation model to obtain the frost heaving evaluation value.

[0015] Furthermore, set a frost heaving evaluation threshold. When the frost heaving evaluation value of the frost heaving monitoring log is less than the frost heaving evaluation threshold, increase the frost heaving mark count by one.

[0016] Furthermore, evaluate the monitoring area as a core frost heaving area or a general area according to the frost heaving monitoring log. Specifically:

[0017] After continuously obtaining n frost heaving monitoring logs of the monitoring area, mark the frost heaving evaluation value of the frost heaving monitoring log as ZPi, where i is the sequence number of the frost heaving monitoring log, i = 1, 2,..., n. Sum up the frost heaving mark counts to obtain the total frost heaving mark count, and mark it as AHM. Use the formula to obtain the regional frost heaving value TYB of the monitoring area, where a1 is the frost heaving evaluation value coefficient and a2 is the total frost heaving mark count coefficient;

[0018] Set a regional frost heaving threshold. When the regional frost heaving value of the monitoring area is greater than or equal to the regional frost heaving threshold, mark this monitoring area as a core frost heaving area;

[0019] When the regional frost heaving value of the monitoring area is less than the regional frost heaving threshold, mark this monitoring area as a general area.

[0020] Furthermore, analyze the potential associated areas of the core frost heaving area. Specifically: Take the core frost heaving area as the center, set a preset range, and mark the general areas within the preset range as preselected areas;

[0021] Obtain the total number of frost heaving fluctuations and the total number of evaluation changes of the core frost heaving area, and mark them as Obtain the total number of frost heaving fluctuations and the total number of evaluation changes of the preselected area, and mark them as Use the cosine similarity algorithm to calculate the frost heaving potential association value between the core frost heaving area and the preselected area;

[0022] Set a frost heaving potential association threshold. When the frost heaving potential association value between the core frost heaving area and the preselected area is greater than or equal to the frost heaving potential association threshold, mark this preselected area as a potential associated area.

[0023] Further, the total number of frost heave fluctuations is obtained in the following manner: Obtain all the frost heave monitoring logs of the monitoring area, sort the frost heave evaluation values of all the frost heave monitoring logs in the order of node time, compare the previous frost heave evaluation value with the next one after sorting, when the previous frost heave evaluation value is less than the next one, calculate the difference between the next frost heave evaluation value and the previous one to obtain the frost heave change value, set the frost heave change threshold, which is the system set threshold and can be modified according to actual requirements, when the frost heave change value is greater than or equal to the frost heave change threshold, increase the frost heave fluctuation count by one, when the frost heave change value is less than the frost heave change threshold, do not make corresponding processing, and sum up the frost heave fluctuation counts to obtain the total number of frost heave fluctuations.

[0024] Further, the total number of evaluation changes is obtained in the following manner: Obtain all the frost heave monitoring logs of the monitoring area, obtain the frost heave evaluation values of the frost heave monitoring logs, set the high frost heave evaluation value and the low frost heave evaluation value, both of which are system preset thresholds and can be modified according to actual requirements, when the frost heave evaluation value of the frost heave monitoring log is greater than the high frost heave evaluation value, evaluate the frost heave monitoring log as a high - evaluation monitoring log, when the frost heave evaluation value of the frost heave monitoring log is less than the low frost heave evaluation value, evaluate the frost heave monitoring log as a low - evaluation monitoring log, when the frost heave evaluation value of the frost heave monitoring log is between the high frost heave evaluation value and the low frost heave evaluation value, evaluate the frost heave monitoring log as a medium - evaluation monitoring log, sort all the frost heave monitoring logs in the order of node time, compare the evaluations of two adjacent frost heave monitoring logs after sorting, when the evaluations of two adjacent frost heave monitoring logs are different, increase the evaluation change count by one, when the evaluations of two adjacent frost heave monitoring logs are the same, do not make corresponding processing, and sum up the evaluation change counts to obtain the total number of evaluation changes.

[0025] Further, the frost heave degree of the airport concrete pavement is evaluated as follows: Obtain the total number of core frost heave areas in the airport concrete pavement and mark it as SXP, obtain the total number of potential associated areas in the airport concrete pavement and mark it as BGC, obtain the total number of monitoring areas in the airport concrete pavement and mark it as AYG, and use the formula to obtain the degree evaluation value Lj, where b1 is the coefficient of the total number of core frost heave areas and b2 is the coefficient of the total number of potential associated areas;

[0026] Set a frost heave evaluation grade corresponding to the range of each degree evaluation value Lj. Among them, the range of the degree evaluation value Lj includes (0, L1], (L1, L2], …, (Lj - 1, Lj], and the frost heave evaluation grades include frost heave evaluation grade 1, frost heave evaluation grade 2, …, frost heave evaluation grade j - 1, frost heave evaluation grade 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 positions on the surface of the airport concrete pavement within a certain period of time, and accurately analyze the potential frost heave positions of the airport concrete pavement through association, ensuring the evaluation accuracy of the subsequent frost heave degree of the airport concrete pavement;

[0029] 2. A regional monitoring module and a regional evaluation module are set up to divide the airport concrete pavement into multiple monitoring areas, and perform periodic analysis on each monitoring area to ensure accurate frost heave evaluation of each monitoring area. A frost heave evaluation module is set up to analyze the potential associated areas of the core frost heave area through associative three-dimensional analysis. On the basis of not needing to extend the time line to observe the frost heave information of the airport concrete pavement, accurately analyze the potential frost heave areas in the airport concrete pavement, and ensure the evaluation accuracy of the subsequent frost heave degree of the airport concrete pavement. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 is a flow chart of a method for evaluating the frost heave degree of an airport concrete pavement;

[0031] Figure 2 is a flow chart for evaluating a monitoring area as a core frost heave area or an ordinary area;

[0032] Figure 3 is a flow chart for evaluating the frost heave degree of an airport concrete pavement. DETAILED DESCRIPTION OF THE INVENTION

[0033] Example 1

[0034] Referring to Figure 1 , a method for evaluating the frost heave degree of an airport concrete pavement includes the following steps:

[0035] Step 1: Divide the airport concrete pavement into multiple monitoring areas, and periodically obtain the frost heave monitoring logs of each monitoring area;

[0036] Specifically: Divide the airport concrete pavement into multiple monitoring areas. Based on a preset period, when each period node arrives, obtain the basic frost heave data of the monitoring area and generate the frost heave monitoring log of the monitoring area. The frost heave monitoring log includes a frost heave evaluation value and a node time (the time corresponding to the period node).

[0037] The frost heave evaluation value of the frost heave monitoring log is obtained through the following method: Use the basic frost heave data as the input data of the frost heave evaluation model to obtain the frost heave evaluation value.

[0038] The airport concrete pavement can be divided into multiple monitoring areas by means of matrix division.

[0039] The frost heaving basic data includes the moisture content, soil particle size distribution, soil temperature, etc. of the monitoring area.

[0040] The frost heaving evaluation model is obtained in the following way: Obtain multiple groups of frost heaving basic data. The frost heaving basic data can be real data or virtual data. Use the frost heaving basic data as the training data of the neural network model, assign labels to the training data, and the label is the frost heaving evaluation value. The value range of the frost heaving evaluation value is (0 - 3). Divide the training data into a training set and a validation set according to a set ratio, and the set ratio can be adjusted according to requirements. Perform neural network iterative training through the training set and the validation set. After the training is completed, the frost heaving evaluation model is obtained. The closer the frost heaving evaluation value is to 0, the lower the frost heaving degree of the concrete in the monitoring area; the closer the frost heaving evaluation value is to 3, the higher the frost heaving degree of the concrete in the monitoring area.

[0041] Set the frost heaving evaluation threshold, and the frost heaving evaluation threshold is the system preset threshold, which can be modified according to actual requirements.

[0042] When the frost heaving evaluation value of the frost heaving monitoring log is greater than or equal to the frost heaving evaluation threshold, no corresponding processing is done.

[0043] When the frost heaving evaluation value of the frost heaving monitoring log is less than the frost heaving evaluation threshold, increase the frost heaving marking times by one.

[0044] Step 2: Evaluate the monitoring area as a core frost heaving area or a general area according to the frost heaving monitoring log; specifically: After continuously obtaining n frost heaving monitoring logs of the monitoring area, mark the frost heaving evaluation value of the frost heaving monitoring log as ZPi, where i is the sequence number of the frost heaving monitoring log, i = 1, 2,..., n. Sum up the frost heaving marking times to obtain the total frost heaving marking times, and mark it as AHM. Use the formula to obtain the regional frost heaving value TYB of the monitoring area, where a1 is the frost heaving evaluation value coefficient, a2 is the total frost heaving marking times coefficient, the value of a1 is 1.81, and the value of a2 is 1.13.

[0045] Set the regional frost heaving threshold, and the regional frost heaving threshold is the system set threshold, which can be modified according to actual requirements.

[0046] When the regional frost heaving value of the monitoring area is greater than or equal to the regional frost heaving threshold, mark the monitoring area as a core frost heaving area.

[0047] When the regional frost heaving value of the monitoring area is less than the regional frost heaving threshold, mark the monitoring area as a general area.

[0048] Set up a regional monitoring module and a regional evaluation module, divide the airport concrete pavement into multiple monitoring areas, and perform periodic analysis on each monitoring area to ensure accurate frost heaving evaluation of each monitoring area.

[0049] Step 3: Analyze the potential associated areas of the core frost heave area, and then evaluate the frost heave degree of the airport concrete pavement. Specifically: Taking the core frost heave area as the center, set a preset range (the preset range is a range centered on the core frost heave area, and the range area can be modified according to actual needs), and mark the ordinary areas within the preset range as preselected areas.

[0050] Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the core frost heave area, and mark them as , where A1 is the total number of frost heave fluctuations in the core frost heave area, A2 is the total number of evaluation changes in the core frost heave area, obtain the total number of frost heave fluctuations and the total number of evaluation changes in the preselected area, and mark them as , where B1 is the total number of frost heave fluctuations in the preselected area, B2 is the total number of evaluation changes in the preselected area, and use the cosine similarity algorithm to calculate the frost heave potential association value between the core frost heave area and the preselected area.

[0051] Example: If the total number of frost heave fluctuations in the core frost heave area is 8 times, the total number of evaluation changes in the core frost heave area is 12 times, the total number of frost heave fluctuations in the preselected area is 7 times, and the total number of evaluation changes in the preselected area is 11 times, then the frost heave potential association value between the core frost heave area and the preselected area .

[0052] The total number of frost heave fluctuations is obtained through the following method: Obtain all the frost heave monitoring logs in the monitoring area, sort the frost heave evaluation values of all the frost heave monitoring logs in the order of node time, compare the previous frost heave evaluation value with the next frost heave evaluation value after sorting. When the previous frost heave evaluation value is less than the next frost heave evaluation value, calculate the difference between the next frost heave evaluation value and the previous frost heave evaluation value to obtain the frost heave change value. Set the frost heave change threshold, which is the system set threshold and can be modified according to actual needs. When the frost heave change value is greater than or equal to the frost heave change threshold, increase the number of frost heave fluctuations by one. When the frost heave change value is less than the frost heave change threshold, no corresponding processing is done, and sum up the number of frost heave fluctuations to obtain the total number of frost heave fluctuations.

[0053] The total number of evaluation changes is obtained in the following way: all frost heave monitoring logs in the monitoring area are obtained, the frost heave evaluation values ​​of the frost heave monitoring logs are obtained, and the high frost heave evaluation value and the low frost heave evaluation value are set. The high frost heave evaluation value and the low frost heave evaluation value are both system preset thresholds and can be modified according to actual needs. When the frost heave evaluation value of the frost heave monitoring log is greater than the high frost heave evaluation value, the frost heave monitoring log is evaluated as a high-evaluation monitoring log. When the frost heave evaluation value of the frost heave monitoring log is less than the low frost heave evaluation value, the frost heave monitoring log is evaluated as a low-evaluation monitoring log. When the frost heave evaluation value of the frost heave monitoring log is between the high frost heave evaluation value and the low frost heave evaluation value, the frost heave monitoring log is evaluated as a medium-evaluation monitoring log. All frost heave monitoring logs are sorted in the order of node time, and the evaluations of two adjacent frost heave monitoring logs after sorting are compared. When the evaluations of two adjacent frost heave monitoring logs are different, the number of evaluation changes is increased by one. When the evaluations of two adjacent frost heave monitoring logs are the same, no corresponding processing is performed. The number of evaluation changes is summed to obtain the total number of evaluation changes.

[0054] Set the potential association threshold of frost heave. The potential association threshold of frost heave is a system-set threshold and can be modified according to actual needs.

[0055] When the potential correlation value of frost heave between the core frost heave area and the pre-selected area is greater than or equal to the potential correlation threshold of frost heave, the pre-selected area is marked as a potential correlation area.

[0056] When the potential correlation value of frost heave between the core frost heave area and the pre-selected area is less than the potential correlation threshold of frost heave, no corresponding processing is performed.

[0057] The total number of core frost heave areas in the airport concrete pavement is obtained and marked as SXP. The total number of potential associated areas in the airport concrete pavement is obtained and marked as BGC (when the monitoring area is marked as both the core frost heave area and the potential associated area, the monitoring area is marked as the core frost heave area). The total number of monitoring areas in the airport concrete pavement is obtained and marked as AYG. The formula is used to calculate the total number of core frost heave areas in the airport concrete pavement. The degree assessment value Lj is obtained, where b1 is the total number coefficient of the core frost heave area, b2 is the total number coefficient of the potential associated area, the value of b1 is 5, and the value of b2 is 2.

[0058] A range of each degree assessment value Lj is set to correspond to a frost heave assessment level, wherein the range of the degree 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 degree of the airport concrete pavement is assessed as frost heave assessment level 1. The higher the frost heave assessment level, the more serious the frost heave degree of the airport concrete pavement.

[0059] The above method can analyze the frost heave positions on the surface of the airport concrete pavement within a certain period of time, and accurately analyze the potential frost heave positions of the airport concrete pavement through correlation, ensuring the evaluation accuracy of the subsequent frost heave degree of the airport concrete pavement.

[0060] The above formulas are all dimensionless and take their numerical values for calculation. The formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formula are set by technicians in the field according to the actual situation.

[0061] Embodiment 2

[0062] Refer to Figures 2 - 3 , an airport concrete pavement frost heave degree evaluation system, including a regional monitoring module, a regional evaluation module, and a frost heave evaluation module.

[0063] The regional monitoring module: divides the airport concrete pavement into multiple monitoring areas. Based on a preset cycle, when each cycle node arrives, it acquires the frost heave basic data of the monitoring area and generates a frost heave monitoring log for the monitoring area. The frost heave monitoring log includes a frost heave evaluation value and a node time (the time corresponding to the cycle node).

[0064] The frost heave evaluation value of the frost heave monitoring log is obtained through the following method: taking the frost heave basic data as the input data of the frost heave evaluation model to obtain the frost heave evaluation value.

[0065] The airport concrete pavement can be divided into multiple monitoring areas by means of matrix division.

[0066] The frost heave basic data includes the moisture content, soil particle size distribution, soil temperature, etc. of the monitoring area.

[0067] The frost heave evaluation model is obtained through the following method: acquiring multiple groups of frost heave basic data. The frost heave basic data can be real data or virtual data. Taking the frost heave basic data as the training data of the neural network model, assigning labels to the training data, and the label is the frost heave evaluation value. The value range of the frost heave evaluation value is (0 - 3). Dividing the training data into a training set and a validation set according to a set ratio, and the set ratio can be adjusted according to requirements. Conducting neural network iterative training through the training set and the validation set, and obtaining the frost heave evaluation model after training is completed. The closer the frost heave evaluation value is to 0, the lower the frost heave degree of the concrete in the monitoring area; the closer the frost heave evaluation value is to 3, the higher the frost heave degree of the concrete in the monitoring area.

[0068] Set a frost heave evaluation threshold, and the frost heave evaluation threshold is a system preset threshold, which can be modified according to actual requirements.

[0069] When the frost heave evaluation value of the frost heave monitoring log is greater than or equal to the frost heave evaluation threshold, no corresponding processing is performed.

[0070] When the frost heave evaluation value in the frost heave monitoring log is less than the frost heave evaluation threshold, increase the frost heave marking count by one.

[0071] The said area evaluation module: After continuously obtaining n frost heave monitoring logs of the monitoring 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 up the frost heave marking counts to obtain the total frost heave marking count, and mark it as AHM. Use the formula to obtain the area frost heave value TYB of the monitoring area, where a1 is the frost heave evaluation value coefficient, a2 is the total frost heave marking count coefficient, the value of a1 is 1.81, and the value of a2 is 1.13.

[0072] Set the area frost heave threshold, and the area frost heave threshold is the system set threshold, which can be modified according to actual needs.

[0073] When the area frost heave value of the monitoring area is greater than or equal to the area frost heave threshold, mark this monitoring area as the core frost heave area.

[0074] When the area frost heave value of the monitoring area is less than the area frost heave threshold, mark this monitoring area as the ordinary area.

[0075] Set the area monitoring module and the area evaluation module, divide the airport concrete pavement into multiple monitoring areas, and conduct periodic analysis on each monitoring area to ensure accurate frost heave evaluation of each monitoring area.

[0076] The said frost heave evaluation module: Taking the core frost heave area as the center, set a preset range (the preset range is the range centered on the core frost heave area, and the range area can be modified according to actual needs), and mark the ordinary areas within the preset range as the preselected areas.

[0077] Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the core frost heave area, and mark them as , where A1 is the total number of frost heave fluctuations in the core frost heave area, A2 is the total number of evaluation changes in the core frost heave area, obtain the total number of frost heave fluctuations and the total number of evaluation changes in the preselected area, and mark them as, where B1 is the total number of frost heave fluctuations in the preselected area, B2 is the total number of evaluation changes in the preselected area, and use the cosine similarity algorithm to calculate the frost heave potential correlation value between the core frost heave area and the preselected area.

[0078] Example: The total number of frost heave fluctuations in the core frost heave area is 8 times, the total number of evaluation changes in the core frost heave area is 12 times, the total number of frost heave fluctuations in the preselected area is 7 times, and the total number of evaluation changes in the preselected area is 11 times. Then the frost heave potential correlation value between the core frost heave area and the preselected area .

[0079] The total number of frost heave fluctuations is obtained in the following way: all frost heave monitoring logs in the monitoring area are obtained, the frost heave evaluation values ​​of all frost heave monitoring logs are sorted in the order of node time, the previous frost heave evaluation value and the next frost heave evaluation value after sorting are compared, when the previous frost heave evaluation value is less than the next frost heave evaluation value, the difference between the next frost heave evaluation value and the previous frost heave evaluation value is calculated to obtain the frost heave change value, and the frost heave change threshold is set. The frost heave change threshold is a system-set threshold and can be modified according to actual needs. When the frost heave change value is greater than or equal to the frost heave change threshold, the number of frost heave fluctuations is increased by one, and when the frost heave change value is less than the frost heave change threshold, no corresponding processing is performed, and the number of frost heave fluctuations is summed to obtain the total number of frost heave fluctuations.

[0080] The total number of evaluation changes is obtained in the following way: all frost heave monitoring logs in the monitoring area are obtained, the frost heave evaluation values ​​of the frost heave monitoring logs are obtained, and the high frost heave evaluation value and the low frost heave evaluation value are set. The high frost heave evaluation value and the low frost heave evaluation value are both system preset thresholds and can be modified according to actual needs. When the frost heave evaluation value of the frost heave monitoring log is greater than the high frost heave evaluation value, the frost heave monitoring log is evaluated as a high-evaluation monitoring log. When the frost heave evaluation value of the frost heave monitoring log is less than the low frost heave evaluation value, the frost heave monitoring log is evaluated as a low-evaluation monitoring log. When the frost heave evaluation value of the frost heave monitoring log is between the high frost heave evaluation value and the low frost heave evaluation value, the frost heave monitoring log is evaluated as a medium-evaluation monitoring log. All frost heave monitoring logs are sorted in the order of node time, and the evaluations of two adjacent frost heave monitoring logs after sorting are compared. When the evaluations of two adjacent frost heave monitoring logs are different, the number of evaluation changes is increased by one. When the evaluations of two adjacent frost heave monitoring logs are the same, no corresponding processing is performed. The number of evaluation changes is summed to obtain the total number of evaluation changes.

[0081] Set the potential association threshold of frost heave. The potential association threshold of frost heave is a system-set threshold and can be modified according to actual needs.

[0082] When the potential correlation value of frost heave between the core frost heave area and the pre-selected area is greater than or equal to the potential correlation threshold of frost heave, the pre-selected area is marked as a potential correlation area.

[0083] When the potential correlation value of frost heave between the core frost heave area and the pre-selected area is less than the potential correlation threshold of frost heave, no corresponding processing is performed.

[0084] Obtain the total number of core frost heave regions in the airport concrete pavement and label it as SXP, obtain the total number of potential associated regions in the airport concrete pavement and label it as BGC (when a monitoring region is simultaneously labeled as a core frost heave region and a potential associated region, label this monitoring region as a core frost heave region), obtain the total number of monitoring regions in the airport concrete pavement, and label it as AYG, and use the formula to obtain the degree evaluation value Lj, where b1 is the total number coefficient of the core frost heave region, b2 is the total number coefficient of the potential associated region, the value of b1 is 5, and the value of b2 is 2.

[0085] Set a corresponding frost heave evaluation level for each range of the degree evaluation value Lj. Among them, the range of the degree evaluation value Lj includes (0, L1], (L1, L2], …, (Lj-1, Lj], and the frost heave evaluation levels include frost heave evaluation level 1, frost heave evaluation level 2, …, frost heave evaluation level j-1, frost heave evaluation level j. When Lj ∈ (0, L1], evaluate the frost heave degree of the airport concrete pavement as frost heave evaluation level 1. The higher the frost heave evaluation level, the more serious the frost heave degree of the airport concrete pavement.

[0086] Set up a frost heave evaluation module. By performing a three-dimensional analysis of the potential associated regions of the core frost heave regions, accurately analyze the potential frost heave regions in the airport concrete pavement on the basis of not needing to extend the time line to observe the frost heave information of the airport concrete pavement, and ensure the evaluation accuracy of the subsequent frost heave degree of the airport concrete pavement.

[0087] The above formulas are all dimensionless and take their numerical values for calculation. The formula is a formula obtained by collecting a large amount of data for software simulation to get the closest to the real situation. The preset parameters in the formula are set by technicians in this field according to the actual situation.

[0088] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of 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, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. 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 by wired or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, or a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0089] It should be understood that in various embodiments of the present application, the order numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0090] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0091] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be described herein again.

[0092] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in electrical, mechanical, or other forms.

[0093] If the above functions are implemented in the form of software function 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 the present application, in essence, or the part that contributes to the prior art, or a part of this 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 for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0094] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for evaluating the degree of frost heave of airport concrete pavement, characterized in that: The steps include: Step 1: Divide the airport concrete pavement into multiple monitoring areas and periodically obtain the frost heave monitoring log of each monitoring area; The airport concrete pavement is divided into multiple monitoring areas. Based on the preset cycle, at each cycle node, the basic frost heave data of the monitoring area is obtained, and a frost heave monitoring log of the monitoring area is generated. The frost heave monitoring log includes the frost heave evaluation value and the node time. Step 2: Evaluate the monitoring area as a core frost heave area or a common area based on the frost heave monitoring log; Set the frost heave evaluation threshold. When the frost heave evaluation value of the frost heave monitoring log is less than the frost heave evaluation threshold, the number of frost heave markings will be increased by one. According to the frost heave monitoring log, the monitoring area is evaluated as a core frost heave area or a general area, specifically: After continuously obtaining n frost heave monitoring logs in the monitoring area, the frost heave evaluation value of the frost heave monitoring log is marked as ZPi, i is the sequence number of the frost heave monitoring log, i=1, 2, ..., n, the number of frost heave marks is summed up to obtain the total number of frost heave marks, and marked as AHM, and the formula is used to calculate the frost heave evaluation value. 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 total number of frost heave marking coefficient; Set a regional frost heave threshold. When the regional frost heave value of the monitoring area is greater than or equal to the regional frost heave threshold, the monitoring area is marked as a core frost heave area. When the regional frost heave value of the monitoring area is less than the regional frost heave threshold, the monitoring area is marked as a normal area; Step 3: Analyze the potential associated areas of the core frost heave area, and then evaluate the frost heave degree of the airport concrete pavement; Analyze the potential associated areas of the core frost heave area, specifically: take the core frost heave area as the center, set a preset range, and mark the common areas within the preset range as pre-selected areas; Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the core frost heave area and mark them as , obtain the total number of frost heave fluctuations and the total number of evaluation changes in the pre-selected area, and mark them as , the cosine similarity algorithm is used to calculate the potential correlation value of frost heave between the core frost heave area and the pre-selected area; Set a potential correlation threshold for frost heave. When the potential correlation value between the core frost heave area and the pre-selected area is greater than or equal to the potential correlation threshold for frost heave, mark the pre-selected area as a potential correlation area. The total number of frost heave fluctuations is obtained in the following manner: all frost heave monitoring logs in the monitoring area are obtained, the frost heave evaluation values ​​of all frost heave monitoring logs are sorted in the order of node time, the previous frost heave evaluation value and the next frost heave evaluation value that are adjacent to each other after sorting are compared, when the previous frost heave evaluation value is less than the next frost heave evaluation value, the next frost heave evaluation value and the previous frost heave evaluation value are calculated for difference, and the frost heave change value is obtained, and the frost heave change threshold is set. The frost heave change threshold is a system-set threshold and can be modified according to actual needs. When the frost heave change value is greater than or equal to the frost heave change threshold, the number of frost heave fluctuations is increased once, and when the frost heave change value is less than the frost heave change threshold, no corresponding processing is performed, and the number of frost heave fluctuations is summed to obtain the total number of frost heave fluctuations; The total number of evaluation changes is obtained in the following manner: obtaining all frost heave monitoring logs in the monitoring area, obtaining the frost heave evaluation value of the frost heave monitoring log, setting a high frost heave evaluation value and a low frost heave evaluation value, both of which are system preset thresholds and can be modified according to actual needs, when the frost heave evaluation value of the frost heave monitoring log is greater than the high frost heave evaluation value, the frost heave monitoring log is evaluated as a high-evaluation monitoring log, when the frost heave evaluation value of the frost heave monitoring log is less than the low frost heave evaluation value, the frost heave monitoring log is evaluated as a low-evaluation monitoring log, when the frost heave evaluation value of the frost heave monitoring log is between the high frost heave evaluation value and the low frost heave evaluation value, the frost heave monitoring log is evaluated as a medium-evaluation monitoring log, all frost heave monitoring logs are sorted in the order of node time, the evaluations of two adjacent frost heave monitoring logs after sorting are compared, when the evaluations of two adjacent frost heave monitoring logs are different, the number of evaluation changes is increased by one, when the evaluations of two adjacent frost heave monitoring logs are the same, no corresponding processing is performed, the number of evaluation changes is summed up, and the total number of evaluation changes is obtained; The degree of frost heave of airport concrete pavement is evaluated by obtaining the total number of core frost heave areas in the airport concrete pavement and marking them as SXP, obtaining the total number of potential associated areas in the airport concrete pavement and marking them as BGC, obtaining the total number of monitoring areas in the airport concrete pavement and marking them as AYG, and 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; A range of each degree assessment value Lj is set to correspond to a frost heave assessment level, wherein the range of the degree 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.

2. A frost heave degree assessment system for airport concrete pavement, characterized in that: It includes regional monitoring module, regional evaluation module and frost heave assessment module; The regional monitoring module divides the airport concrete pavement into multiple monitoring areas and periodically obtains the frost heave monitoring log of each monitoring area; The regional evaluation module evaluates the monitoring area as a core frost heave area or a common area according to the frost heave monitoring log; The frost heave assessment module analyzes the potential associated areas of the core frost heave area, and then assesses the degree of frost heave of the airport concrete pavement; The airport concrete pavement is divided into multiple monitoring areas. Based on the preset cycle, at each cycle node, the basic frost heave data of the monitoring area is obtained, and a frost heave monitoring log of the monitoring area is generated. The frost heave monitoring log includes the frost heave evaluation value and the node time. Set the frost heave evaluation threshold. When the frost heave evaluation value of the frost heave monitoring log is less than the frost heave evaluation threshold, the number of frost heave markings will be increased by one. According to the frost heave monitoring log, the monitoring area is evaluated as a core frost heave area or a general area, specifically: After continuously obtaining n frost heave monitoring logs in the monitoring area, the frost heave evaluation value of the frost heave monitoring log is marked as ZPi, i is the sequence number of the frost heave monitoring log, i=1, 2, ..., n, the number of frost heave marks is summed up to obtain the total number of frost heave marks, and marked as AHM, and the formula is used to calculate the frost heave evaluation value. 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 total number of frost heave marking coefficient; Set a regional frost heave threshold. When the regional frost heave value of the monitoring area is greater than or equal to the regional frost heave threshold, the monitoring area is marked as a core frost heave area. When the regional frost heave value of the monitoring area is less than the regional frost heave threshold, the monitoring area is marked as a normal area; Analyze the potential associated areas of the core frost heave area, specifically: take the core frost heave area as the center, set a preset range, and mark the common areas within the preset range as pre-selected areas; Obtain the total number of frost heave fluctuations and the total number of evaluation changes in the core frost heave area and mark them as , obtain the total number of frost heave fluctuations and the total number of evaluation changes in the pre-selected area, and mark them as , the cosine similarity algorithm is used to calculate the potential correlation value of frost heave between the core frost heave area and the pre-selected area; Set a potential correlation threshold for frost heave. When the potential correlation value between the core frost heave area and the pre-selected area is greater than or equal to the potential correlation threshold for frost heave, mark the pre-selected area as a potential correlation area. The total number of frost heave fluctuations is obtained in the following manner: all frost heave monitoring logs in the monitoring area are obtained, the frost heave evaluation values ​​of all frost heave monitoring logs are sorted in the order of node time, the previous frost heave evaluation value and the next frost heave evaluation value that are adjacent to each other after sorting are compared, when the previous frost heave evaluation value is less than the next frost heave evaluation value, the next frost heave evaluation value and the previous frost heave evaluation value are calculated for difference, and the frost heave change value is obtained, and the frost heave change threshold is set. The frost heave change threshold is a system-set threshold and can be modified according to actual needs. When the frost heave change value is greater than or equal to the frost heave change threshold, the number of frost heave fluctuations is increased once, and when the frost heave change value is less than the frost heave change threshold, no corresponding processing is performed, and the number of frost heave fluctuations is summed to obtain the total number of frost heave fluctuations; The total number of evaluation changes is obtained in the following manner: obtaining all frost heave monitoring logs in the monitoring area, obtaining the frost heave evaluation value of the frost heave monitoring log, setting a high frost heave evaluation value and a low frost heave evaluation value, both of which are system preset thresholds and can be modified according to actual needs, when the frost heave evaluation value of the frost heave monitoring log is greater than the high frost heave evaluation value, the frost heave monitoring log is evaluated as a high-evaluation monitoring log, when the frost heave evaluation value of the frost heave monitoring log is less than the low frost heave evaluation value, the frost heave monitoring log is evaluated as a low-evaluation monitoring log, when the frost heave evaluation value of the frost heave monitoring log is between the high frost heave evaluation value and the low frost heave evaluation value, the frost heave monitoring log is evaluated as a medium-evaluation monitoring log, all frost heave monitoring logs are sorted in the order of node time, the evaluations of two adjacent frost heave monitoring logs after sorting are compared, when the evaluations of two adjacent frost heave monitoring logs are different, the number of evaluation changes is increased by one, when the evaluations of two adjacent frost heave monitoring logs are the same, no corresponding processing is performed, the number of evaluation changes is summed up, and the total number of evaluation changes is obtained; The degree of frost heave of airport concrete pavement is evaluated by obtaining the total number of core frost heave areas in the airport concrete pavement and marking them as SXP, obtaining the total number of potential associated areas in the airport concrete pavement and marking them as BGC, obtaining the total number of monitoring areas in the airport concrete pavement and marking them as AYG, and 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; A range of each degree assessment value Lj is set to correspond to a frost heave assessment level, wherein the range of the degree 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.

3. The airport concrete pavement frost heave degree assessment system according to claim 2, characterized in that: The frost heave evaluation value of the frost heave monitoring log is obtained in the following way: the frost heave basic data is used as the input data of the frost heave evaluation model to obtain the frost heave evaluation value.

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