Roadbed and pavement stability monitoring method based on desert road

Abstract

The invention discloses a roadbed and pavement stability monitoring method based on a desert highway, and particularly relates to the technical field of roadbed and pavement monitoring, which comprises the following steps: monitoring a roadbed and a pavement of the desert highway through a fixed-point monitoring method, collecting land subsidence information, soil strain information and stress change information, and ensuring the comprehensiveness and accuracy of monitoring data; the method comprises the following steps: quantifying the stability of roadbeds and pavements at different monitoring points, marking the monitoring points with poor stability as early warning monitoring points, carrying out clustering analysis on data of all the monitoring points, dividing a desert road into different road sections, carrying out threshold comparison on clustering centers of the different road sections, and identifying early warning road sections with potential risks in stability. According to a clustering result of monitoring points in the desert road, early warning information and risk information are extracted, stability risks of different road sections are quantified, the roadbed and pavement stability of the desert road can be effectively monitored and evaluated, and risk road sections can be identified and quantified.

Description

Technical Field

[0001] The invention relates to the technical field of roadbed and pavement monitoring, and more specifically to a roadbed and pavement stability monitoring method based on a desert highway. Background Art

[0002] At present, the maintenance and management of desert roads mainly rely on regular manual inspections and traditional monitoring methods. Due to the vastness and complex terrain of the desert area, traditional inspection and monitoring methods are difficult to achieve comprehensive coverage of the entire highway, and are prone to missing potential risk points. There is a lack of effective comprehensive analysis methods and it is impossible to accurately quantify the stability risks of different sections of the road, resulting in blind and inefficient maintenance decisions. In addition, due to the inability to accurately locate and warn of risky sections, maintenance work often needs to be carried out on a large scale, increasing maintenance costs and manpower investment.

[0003] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method for monitoring the stability of a roadbed and pavement of a desert highway to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for monitoring roadbed and pavement stability of a desert highway comprises the following steps:

[0007] S1: Monitor the roadbed and pavement of the desert highway through the fixed-point monitoring method, and collect ground settlement information, soil strain information and stress change information according to the monitoring equipment at the monitoring point;

[0008] S2: Comprehensively analyze the ground settlement information, soil strain information and stress change information, quantify the stability of the roadbed and pavement at different monitoring points, and mark the monitoring points with poor stability as early warning monitoring points;

[0009] S3: By clustering the monitoring points, the desert highway is divided into different sections, and the warning sections are determined by comparing the thresholds of the cluster centers of different sections;

[0010] S4: By clustering the monitoring points on the desert highway, we extract warning information and risk information, further comprehensively process the warning information and risk information, and quantify the stability risks of different road sections.

[0011] In a preferred embodiment, collecting ground settlement information, soil strain information and stress change information includes:

[0012] The ground settlement information, soil strain information and stress change information are determined through the data collected by the monitoring equipment at the monitoring point. The ground settlement information is represented by the settlement accumulation coefficient, the soil strain information is represented by the strain deviation coefficient, and the stress change information is represented by the stress fluctuation coefficient. The settlement accumulation coefficient, strain deviation coefficient and stress fluctuation coefficient are marked as: CJ jl , WY pc and QJ bd .

[0013] In a preferred embodiment, the logic for obtaining the strain deviation coefficient is:

[0014] Set the monitoring interval and collection interval, obtain the strain of the soil in the east-west direction within the monitoring interval at the monitoring point, and mark the strain of the soil in the east-west direction within the monitoring interval at the monitoring point as: DX n , where n = 1, 2, 3, ..., N, N is a positive integer, and n is the number of the collection interval within the monitoring interval;

[0015] Set the east-west strain range threshold and label the east-west strain range threshold as: D min ~D max , compare the east-west strain of the soil in the monitoring interval at the monitoring point with the east-west strain range threshold, obtain the strain that is not within the east-west strain range threshold, and re-mark the strain that is not within the east-west strain range threshold as: D0X i , where i = 1, 2, 3, ..., I, I is a positive integer, and i is the number of the strain that is not within the threshold of the east-west strain range;

[0016] Calculate the east-west strain deviation. The calculation formula for the east-west strain deviation is: Among them, PC dx To strain deviation for things;

[0017] The north-south strain deviation is calculated in the same way. The calculation formula of the north-south strain deviation is: Among them, PC bx is the north-south strain deviation, BX m is the strain that is not within the threshold of the north-south strain range, m = 1, 2, 3, ..., M, M is a positive integer, B min ~B max is the north-south strain range threshold;

[0018] Calculate the strain deviation coefficient. The calculation formula of the strain deviation coefficient is:

[0019] In a preferred embodiment, the logic for obtaining the sedimentation accumulation coefficient is:

[0020] Obtain the road settlement in the vertical direction at the monitoring point, determine the road settlement data in the vertical direction at the monitoring point and the corresponding collection interval, fit the road settlement data in the vertical direction at the monitoring point and the corresponding collection interval, obtain the functional relationship between the road settlement data and time in the monitoring interval, and mark the functional relationship between the road settlement data and time in the monitoring interval as: CJ(t);

[0021] Calculate the sedimentation accumulation coefficient. The calculation formula for the sedimentation accumulation coefficient is: Among them, t a ~t b It is the time period when the road surface settlement value exceeds the set road surface settlement threshold.

[0022] In a preferred embodiment, the logic for obtaining the stress fluctuation coefficient is:

[0023] Obtain the stress difference between the roadbed at the monitoring point and the initial roadbed, and mark the stress difference between the roadbed at the monitoring point and the initial roadbed as: JD r , where r = 1, 2, 3, ..., R, R is a positive integer, and r is the number of the stress difference between the roadbed at the monitoring point and the initial roadbed;

[0024] Calculate the average value and standard deviation of the stress difference between the roadbed at the monitoring point and the initial roadbed, and mark the average value and standard deviation of the stress difference between the roadbed at the monitoring point and the initial roadbed as: JD avg and J.D. bzc ,in,

[0025] Calculate the stress fluctuation coefficient. The calculation formula of the stress fluctuation coefficient is:

[0026] In a preferred embodiment, the stability of the roadbed and pavement at different monitoring points is quantified, and monitoring points with poor stability are marked as early warning monitoring points, including:

[0027] The settlement accumulation coefficient, strain deviation coefficient and stress fluctuation coefficient are weighted and calculated to generate a stability assessment coefficient;

[0028] Set the stability assessment coefficient threshold and mark the stability assessment coefficient threshold as: pg yz , obtain the stability assessment coefficients of all monitoring points in the desert highway, compare the stability assessment coefficients of all monitoring points in the desert highway with the stability assessment coefficient threshold, if the stability assessment coefficient is greater than the stability assessment coefficient threshold, then mark the monitoring point as a warning monitoring point, if the stability assessment coefficient is less than the stability assessment coefficient threshold, then do not mark it.

[0029] In a preferred embodiment, the warning section is determined by clustering the monitoring points, including:

[0030] The positions of all monitoring points in the desert highway are obtained, and the stability assessment coefficients of all monitoring points in the desert highway are obtained, the coordinate positions and stability assessment coefficients of the monitoring points are used as data points of the monitoring points, and the data points of all monitoring points in the desert highway are clustered using the K-means clustering algorithm to obtain different clusters, and the stability assessment coefficients of the cluster centers of different clusters are determined, and the stability assessment coefficients of the cluster centers are compared with the stability assessment coefficient threshold to obtain the clusters whose stability assessment coefficients of the cluster centers are greater than the stability assessment coefficient threshold, and the clusters whose stability assessment coefficients of the cluster centers are greater than the stability assessment coefficient threshold are marked as warning sections.

[0031] In a preferred embodiment, extracting warning information and risk information includes:

[0032] By clustering the monitoring points on the desert highway, we can obtain warning information and risk information. The warning information is expressed by the warning density coefficient, and the risk information is expressed by the risk superposition coefficient.

[0033] The logic for obtaining the warning density coefficient is: determine the number of monitoring points contained in the warning section, and mark the number of monitoring points contained in the warning section as: SL q , where q = 1, 2, 3, ..., Q, Q is a positive integer, q is the number of the warning section in the desert highway, that is, the number of monitoring points in the cluster, obtain the coordinates of the warning monitoring points in the warning section, calculate the distance between adjacent warning monitoring points, and mark the distance between adjacent warning monitoring points as: JL f , where f = 1, 2, 3, ..., F, F is a positive integer, and f is the number of the adjacent early warning monitoring point;

[0034] Calculate the early warning density coefficient. The calculation formula of the early warning density coefficient is: Among them, MD yj is the warning density coefficient;

[0035] The logic for obtaining the risk superposition coefficient is as follows: obtain the stability evaluation coefficient of the early warning monitoring point in the early warning section, and mark the stability evaluation coefficient of the early warning monitoring point in the early warning section as: pg w , where w = 1, 2, 3, ..., W, W is a positive integer, and w is the number of the warning monitoring point in the warning section;

[0036] Calculate the risk superposition coefficient using the following formula: Among them, FX is the risk superposition coefficient.

[0037] In a preferred embodiment, quantifying the stability risks of different road sections includes:

[0038] The warning information and risk information are comprehensively analyzed, and the road section evaluation coefficient is generated by weighted summation of the warning density coefficient and the risk superposition coefficient.

[0039] Set a section assessment coefficient threshold, and compare the section assessment coefficient of the warning section with the section assessment coefficient threshold. If the section assessment coefficient is greater than the section assessment coefficient threshold, a risk signal is generated, and the warning section is marked as a risk section. The staff will inspect the section. If the section assessment coefficient is less than the section assessment coefficient threshold, no risk signal is generated.

[0040] Technical effects and advantages of the present invention:

[0041] The present invention monitors the soil settlement, soil strain and subgrade stress of the roadbed and pavement of a desert highway by a fixed-point monitoring method, evaluates the stability of the roadbed and pavement at different monitoring points, and determines the sections where risks may occur by clustering different monitoring points, and quantifies the stability risks of the sections where risks may occur, which helps to effectively monitor and evaluate the stability of the roadbed and pavement of the desert highway, identify and quantify the risk sections, formulate targeted maintenance and management strategies, and improve the safety and durability of the highway. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0043] Figure 1 The present invention is a schematic flow chart of a method for monitoring roadbed and pavement stability based on a desert highway. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] Example 1

[0046] Figure 1 A schematic flow chart of a method for monitoring roadbed and pavement stability of a desert highway is provided, which specifically includes the following steps:

[0047] S1: Monitor the roadbed and pavement of the desert highway through the fixed-point monitoring method, and collect ground settlement information, soil strain information and stress change information according to the monitoring equipment at the monitoring point;

[0048] S2: Comprehensively analyze the ground settlement information, soil strain information and stress change information, quantify the stability of the roadbed and pavement at different monitoring points, and mark the monitoring points with poor stability as early warning monitoring points;

[0049] S3: By clustering the monitoring points, the desert highway is divided into different sections, and the warning sections are determined by comparing the thresholds of the cluster centers of different sections;

[0050] S4: By clustering the monitoring points on the desert highway, we extract warning information and risk information, further comprehensively process the warning information and risk information, and quantify the stability risks of different road sections.

[0051] Extreme high temperatures and large temperature differences between day and night in desert areas may cause thermal expansion and contraction of pavement materials, affecting the stability of the road surface. Wind and sand are common problems in desert areas. Wind and sand will erode the roadbed and road surface, causing road surface coverage, wear and damage. Lack of water and sparse vegetation will cause the roadbed to lack natural protection, increasing the risk of roadbed erosion. Therefore, it is particularly important to monitor the stability of the roadbed and road surface.

[0052] In the monitoring of roadbed and pavement stability of desert highways, fixed-point monitoring method and regional monitoring method are used. Among them, the fixed-point monitoring method is to set up monitoring points at specific locations, and judge the ground subsidence by regularly measuring the height changes of the monitoring points. Usually, the number of monitoring points should be as much as possible, and should cover the entire monitoring area as much as possible. The regional monitoring method is to set up a certain number of monitoring points in the entire monitoring area, and judge the ground subsidence by continuously measuring the height changes of the monitoring points.

[0053] For the roadbed and pavement stability monitoring method of desert highways, a fixed-point monitoring method is used to achieve comprehensive monitoring of the roadbed and pavement stability of desert highways. Fixed-point monitoring equipment is deployed at key locations to conduct high-precision displacement, inclination and settlement monitoring.

[0054] Monitoring means: Monitoring equipment is arranged at the monitoring points. The monitoring equipment includes single-point settlement gauge, horizontal soil strain gauge and earth pressure gauge. The specific implementation methods include:

[0055] According to the geological conditions and engineering characteristics of the desert highway, key locations prone to settlement and deformation are selected as monitoring points. Single-point settlement meters, horizontal soil strain gauges and earth pressure gauges are installed at each monitoring point to ensure that the equipment is firmly fixed to avoid displacement during installation. Initial calibration is carried out and the initial settlement values ​​are recorded as the basis for subsequent monitoring.

[0056] The ground settlement information, soil strain information and stress change information are determined through the data collected by the monitoring equipment at the monitoring point. The ground settlement information is represented by the settlement accumulation coefficient, the soil strain information is represented by the strain deviation coefficient, and the stress change information is represented by the stress fluctuation coefficient. The settlement accumulation coefficient, strain deviation coefficient and stress fluctuation coefficient are marked as: CJ jl , WY pc and QJ bd .

[0057] Set monitoring intervals and collection intervals. The monitoring interval is a specific length of time, and the collection interval is a shorter length of time. Usually, the monitoring interval consists of multiple collection intervals. The monitoring intervals and collection intervals are set by professional staff. According to the actual situation and safety requirements of the project, the frequency of data collection is determined, such as every minute, every hour or every day, and the periodicity of monitoring is planned to ensure that structural changes can be captured in time.

[0058] The logic for obtaining the strain deviation coefficient is as follows: observe through the horizontal soil strain gauge to obtain the strain of the soil in the east-west direction within the monitoring interval at the monitoring point, and mark the strain of the soil in the east-west direction within the monitoring interval at the monitoring point as: DX n , where n = 1, 2, 3, ..., N, N is a positive integer, and n is the number of the collection interval within the monitoring interval;

[0059] Set the east-west strain range threshold and label the east-west strain range threshold as: D min ~D max , compare the east-west strain of the soil in the monitoring interval at the monitoring point with the east-west strain range threshold, obtain the strain that is not within the east-west strain range threshold, and re-mark the strain that is not within the east-west strain range threshold as: D0X i , where i = 1, 2, 3, ..., I, I is a positive integer, and i is the number of the strain that is not within the threshold of the east-west strain range;

[0060] Calculate the east-west strain deviation. The calculation formula for the east-west strain deviation is: Among them, PC dx To strain deviation for things;

[0061] The north-south strain deviation is calculated in the same way. The calculation formula of the north-south strain deviation is: Among them, PC bx is the north-south strain deviation, BX m is the strain that is not within the threshold of the north-south strain range, m = 1, 2, 3, ..., M, M is a positive integer, B min ~B max is the north-south strain range threshold;

[0062] Calculate the strain deviation coefficient. The calculation formula of the strain deviation coefficient is:

[0063] It can be seen from the formula that the larger the strain deviation coefficient is, the greater the strain of the desert highway soil in the monitoring interval is, and there may be stability risks.

[0064] The logic of obtaining the settlement accumulation coefficient is as follows: observe through a single-point settlement meter to obtain the road settlement in the vertical direction at the monitoring point, determine the road settlement data in the vertical direction at the monitoring point and the corresponding collection interval, fit the road settlement data in the vertical direction at the monitoring point and the corresponding collection interval, obtain the functional relationship between the road settlement data and time in the monitoring interval, and mark the functional relationship between the road settlement data and time in the monitoring interval as: CJ(t);

[0065] It should be noted that the fitting process includes arranging the road settlement data in the vertical direction at the monitoring point and the corresponding collection time interval into a data set, and selecting a suitable fitting model according to the change trend of the actual settlement data, including linear fitting, quadratic curve fitting and exponential fitting;

[0066] Calculate the sedimentation accumulation coefficient. The calculation formula for the sedimentation accumulation coefficient is: Among them, t a ~t b It is the time period when the road surface settlement value exceeds the set road surface settlement threshold.

[0067] It can be seen from the formula that the larger the settlement accumulation coefficient, the greater the vertical settlement of the roadbed or pavement during the monitoring period, indicating that the soil or structure in the area has undergone significant subsidence, and the time period that may exceed the preset settlement threshold is longer, indicating that the problem not only exists but also lasts for a long time, which may have a greater impact on the stability of the roadbed and pavement, and the settlement rate may be higher, indicating that the settlement process may be more severe.

[0068] The logic of obtaining the stress fluctuation coefficient is: monitor at the monitoring point through the earth pressure gauge, obtain the stress difference between the roadbed at the monitoring point and the initial roadbed, and mark the stress difference between the roadbed at the monitoring point and the initial roadbed as: JD r , where r = 1, 2, 3, ..., R, R is a positive integer, and r is the number of the stress difference between the roadbed at the monitoring point and the initial roadbed;

[0069] Calculate the average value and standard deviation of the stress difference between the roadbed at the monitoring point and the initial roadbed, and mark the average value and standard deviation of the stress difference between the roadbed at the monitoring point and the initial roadbed as: JD avg and J.D. bzc ,in,

[0070] Calculate the stress fluctuation coefficient. The calculation formula of the stress fluctuation coefficient is:

[0071] It can be seen from the formula that the larger the stress fluctuation coefficient, the greater the change range of the roadbed stress and the more drastic the fluctuation, which may indicate that the road surface is greatly affected by the external environment and load, and there may be stability risks.

[0072] The settlement accumulation coefficient, strain deviation coefficient and stress fluctuation coefficient are weighted to generate the stability assessment coefficient. The calculation formula of the stability assessment coefficient is: Among them, pg is the stability assessment coefficient, α1, α2, and α3 are the proportional coefficients of the settlement accumulation coefficient, strain deviation coefficient, and stress fluctuation coefficient, and α1, α2, and α3 are greater than 0.

[0073] It can be seen from the formula that the larger the settlement accumulation coefficient, strain deviation coefficient and stress fluctuation coefficient, the larger the stability assessment coefficient, which means that the stability of the subgrade and pavement of the desert highway may be poor. Conversely, the smaller the settlement accumulation coefficient, strain deviation coefficient and stress fluctuation coefficient, the smaller the stability assessment coefficient, which means that the stability of the subgrade and pavement of the desert highway may be better.

[0074] Set the stability assessment coefficient threshold and mark the stability assessment coefficient threshold as: pg yz , obtain the stability assessment coefficients of all monitoring points in the desert highway, compare the stability assessment coefficients of all monitoring points in the desert highway with the stability assessment coefficient threshold, if the stability assessment coefficient is greater than the stability assessment coefficient threshold, then mark the monitoring point as a warning monitoring point, if the stability assessment coefficient is less than the stability assessment coefficient threshold, then do not mark it.

[0075] The positions of all monitoring points in the desert highway are obtained, and the stability assessment coefficients of all monitoring points in the desert highway are obtained, the coordinate positions and stability assessment coefficients of the monitoring points are used as data points of the monitoring points, and the data points of all monitoring points in the desert highway are clustered using the K-means clustering algorithm to obtain different clusters, and the stability assessment coefficients of the cluster centers of different clusters are determined, and the stability assessment coefficients of the cluster centers are compared with the stability assessment coefficient threshold to obtain the clusters whose stability assessment coefficients of the cluster centers are greater than the stability assessment coefficient threshold, and the clusters whose stability assessment coefficients of the cluster centers are greater than the stability assessment coefficient threshold are marked as warning sections.

[0076] Through the clustering results of monitoring points in the desert highway, the warning information and risk information are obtained, and the warning information is represented by the warning density coefficient, and the risk information is represented by the risk superposition coefficient. The logic for obtaining the warning density coefficient is: determine the number of monitoring points contained in the warning section, and mark the number of monitoring points contained in the warning section as: SL q, where q = 1, 2, 3, ..., Q, Q is a positive integer, q is the number of the warning section in the desert highway, that is, the number of monitoring points in the cluster, obtain the coordinates of the warning monitoring points in the warning section, calculate the distance between adjacent warning monitoring points, and mark the distance between adjacent warning monitoring points as: JL f , where f = 1, 2, 3, ..., F, F is a positive integer, and f is the number of the adjacent early warning monitoring point;

[0077] Calculate the early warning density coefficient. The calculation formula of the early warning density coefficient is: Among them, MD yj is the warning density coefficient.

[0078] It should be noted that the closer the early warning monitoring points are to each other, the higher the possibility that the road section is unstable. The farther the early warning monitoring points are from each other, the more likely the road section instability may occur accidentally.

[0079] The logic for obtaining the risk superposition coefficient is as follows: obtain the stability evaluation coefficient of the early warning monitoring point in the early warning section, and mark the stability evaluation coefficient of the early warning monitoring point in the early warning section as: pg w , where w = 1, 2, 3, ..., W, W is a positive integer, and w is the number of the warning monitoring point in the warning section;

[0080] Calculate the risk superposition coefficient using the following formula: Among them, FX is the risk superposition coefficient.

[0081] The warning information and risk information are comprehensively analyzed, and the road section evaluation coefficient is generated by weighted summation of the warning density coefficient and the risk superposition coefficient. The calculation formula of the road section evaluation coefficient is: pg L =β1MD yj +β2FX; where pg L is the road section assessment coefficient, β1 is the warning density coefficient, β2 is the proportional coefficient of the risk superposition coefficient, and both β1 and β2 are greater than 0.

[0082] Set a section assessment coefficient threshold, and compare the section assessment coefficient of the warning section with the section assessment coefficient threshold. If the section assessment coefficient is greater than the section assessment coefficient threshold, a risk signal is generated, and the warning section is marked as a risk section. The staff will inspect the section. If the section assessment coefficient is less than the section assessment coefficient threshold, no risk signal is generated.

[0083] The present invention monitors the soil settlement, soil strain and subgrade stress of the roadbed and pavement of a desert highway by a fixed-point monitoring method, evaluates the stability of the roadbed and pavement at different monitoring points, and determines the sections where risks may occur by clustering different monitoring points, and quantifies the stability risks of the sections where risks may occur, which helps to effectively monitor and evaluate the stability of the roadbed and pavement of the desert highway, identify and quantify the risk sections, formulate targeted maintenance and management strategies, and improve the safety and durability of the highway.

[0084] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0085] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. 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 process or function described in the embodiment of the present application is generated in whole or in part. 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 computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). 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 containing one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0086] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean 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 the present application.

[0087] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0088] In the 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0089] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0090] If the functions are implemented in the form of 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 the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0091] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for monitoring roadbed and pavement stability based on desert highways, characterized in that: The specific steps include: S1: Monitor the roadbed and pavement of the desert highway through the fixed-point monitoring method, and collect ground settlement information, soil strain information and stress change information according to the monitoring equipment at the monitoring point; S2: Comprehensively analyze the ground settlement information, soil strain information and stress change information, quantify the stability of the roadbed and pavement at different monitoring points, and mark the monitoring points with poor stability as early warning monitoring points; S3: By clustering the monitoring points, the desert highway is divided into different sections, and the warning sections are determined by comparing the thresholds of the cluster centers of different sections; S4: By clustering the monitoring points on the desert highway, we extract warning information and risk information, further comprehensively process the warning information and risk information, and quantify the stability risks of different road sections.

2. A method for monitoring roadbed and pavement stability based on desert highways according to claim 1, characterized in that: Collect ground settlement information, soil strain information and stress change information, including: The ground settlement information, soil strain information and stress change information are determined through the data collected by the monitoring equipment at the monitoring point. The ground settlement information is represented by the settlement accumulation coefficient, the soil strain information is represented by the strain deviation coefficient, and the stress change information is represented by the stress fluctuation coefficient. The settlement accumulation coefficient, strain deviation coefficient and stress fluctuation coefficient are marked as: CJ hl , WY pc and QJ bd .

3. The method for monitoring roadbed and pavement stability of desert highway according to claim 2 is characterized in that: The logic for obtaining the strain deviation coefficient is: Set the monitoring interval and collection interval, obtain the strain of the soil in the east-west direction within the monitoring interval at the monitoring point, and mark the strain of the soil in the east-west direction within the monitoring interval at the monitoring point as: DX n , where n = 1, 2, 3, ..., N, N is a positive integer, and n is the number of the collection interval within the monitoring interval; Set the east-west strain range threshold and label the east-west strain range threshold as: D min ~D max , compare the east-west strain of the soil in the monitoring interval at the monitoring point with the east-west strain range threshold, obtain the strain that is not within the east-west strain range threshold, and re-mark the strain that is not within the east-west strain range threshold as: D0X i , where i = 1, 2, 3, ..., I, I is a positive integer, and i is the number of the strain that is not within the threshold of the east-west strain range; Calculate the east-west strain deviation. The calculation formula for the east-west strain deviation is: Among them, PC dx For things strain deviation; The north-south strain deviation is calculated in the same way. The calculation formula of the north-south strain deviation is: Among them, PC bx is the north-south strain deviation, BX n is the strain that is not within the threshold of the north-south strain range, m = 1, 2, 3, ..., M, M is a positive integer, B min ~B max is the north-south strain range threshold; Calculate the strain deviation coefficient. The calculation formula of the strain deviation coefficient is:

4. The method for monitoring roadbed and pavement stability of a desert highway according to claim 1, characterized in that: The logic for obtaining the sedimentation accumulation coefficient is: Obtain the road settlement in the vertical direction at the monitoring point, determine the road settlement data in the vertical direction at the monitoring point and the corresponding collection interval, fit the road settlement data in the vertical direction at the monitoring point and the corresponding collection interval, obtain the functional relationship between the road settlement data and time in the monitoring interval, and mark the functional relationship between the road settlement data and time in the monitoring interval as: CJ(t); Calculate the sedimentation accumulation coefficient. The calculation formula for the sedimentation accumulation coefficient is: Among them, t a ~t b It is the time period when the road surface settlement value exceeds the set road surface settlement threshold.

5. The method for monitoring roadbed and pavement stability of desert highway according to claim 2, characterized in that: The logic for obtaining the stress fluctuation coefficient is: Obtain the stress difference between the roadbed at the monitoring point and the initial roadbed, and mark the stress difference between the roadbed at the monitoring point and the initial roadbed as: JD r , where r = 1, 2, 3, ..., R, R is a positive integer, and r is the number of the stress difference between the roadbed at the monitoring point and the initial roadbed; Calculate the average value and standard deviation of the stress difference between the roadbed at the monitoring point and the initial roadbed, and mark the average value and standard deviation of the stress difference between the roadbed at the monitoring point and the initial roadbed as: JD avg and J.D. bzc ,in, Calculate the stress fluctuation coefficient. The calculation formula of the stress fluctuation coefficient is:

6. The method for monitoring roadbed and pavement stability of a desert highway according to claim 1, characterized in that: Quantify the stability of the roadbed and pavement at different monitoring points, and mark the monitoring points with poor stability as early warning monitoring points, including: The settlement accumulation coefficient, strain deviation coefficient and stress fluctuation coefficient are weighted and calculated to generate a stability assessment coefficient; Set the stability assessment coefficient threshold and mark the stability assessment coefficient threshold as: pg yz , obtain the stability assessment coefficients of all monitoring points in the desert highway, compare the stability assessment coefficients of all monitoring points in the desert highway with the stability assessment coefficient threshold, if the stability assessment coefficient is greater than the stability assessment coefficient threshold, then mark the monitoring point as a warning monitoring point, if the stability assessment coefficient is less than the stability assessment coefficient threshold, then do not mark it.

7. A method for monitoring roadbed and pavement stability of desert highway according to claim 6, characterized in that: By clustering the monitoring points, the warning sections are determined, including: The positions of all monitoring points in the desert highway are obtained, and the stability assessment coefficients of all monitoring points in the desert highway are obtained, the coordinate positions and stability assessment coefficients of the monitoring points are used as data points of the monitoring points, and the data points of all monitoring points in the desert highway are clustered using the K-means clustering algorithm to obtain different clusters, and the stability assessment coefficients of the cluster centers of different clusters are determined, and the stability assessment coefficients of the cluster centers are compared with the stability assessment coefficient threshold to obtain the clusters whose stability assessment coefficients of the cluster centers are greater than the stability assessment coefficient threshold, and the clusters whose stability assessment coefficients of the cluster centers are greater than the stability assessment coefficient threshold are marked as warning sections.

8. The method for monitoring roadbed and pavement stability of desert highway according to claim 7, characterized in that: Extract early warning information and risk information, including: By clustering the monitoring points on the desert highway, we can obtain warning information and risk information. The warning information is expressed by the warning density coefficient, and the risk information is expressed by the risk superposition coefficient. The logic for obtaining the warning density coefficient is: determine the number of monitoring points contained in the warning section, and mark the number of monitoring points contained in the warning section as: SL q , where q = 1, 2, 3, ..., Q, Q is a positive integer, q is the number of the warning section in the desert highway, that is, the number of monitoring points in the cluster, obtain the coordinates of the warning monitoring points in the warning section, calculate the distance between adjacent warning monitoring points, and mark the distance between adjacent warning monitoring points as: JL f , where f = 1, 2, 3, ..., F, F is a positive integer, and f is the number of the adjacent early warning monitoring point; Calculate the early warning density coefficient. The calculation formula of the early warning density coefficient is: Among them, MD yj is the warning density coefficient; The logic for obtaining the risk superposition coefficient is as follows: obtain the stability evaluation coefficient of the early warning monitoring point in the early warning section, and mark the stability evaluation coefficient of the early warning monitoring point in the early warning section as: pg w , where w = 1, 2, 3, ..., W, W is a positive integer, and w is the number of the warning monitoring point in the warning section; Calculate the risk superposition coefficient using the following formula: Among them, FX is the risk superposition coefficient.

9. A method for monitoring roadbed and pavement stability of desert highways according to claim 8, characterized in that: Quantify the stability risk of different road sections, including: Comprehensively analyze the warning information and risk information, and generate the road section assessment coefficient by weighted summation of the warning density coefficient and the risk superposition coefficient; Set a section assessment coefficient threshold, and compare the section assessment coefficient of the warning section with the section assessment coefficient threshold. If the section assessment coefficient is greater than the section assessment coefficient threshold, a risk signal is generated, and the warning section is marked as a risk section. The staff will inspect the section. If the section assessment coefficient is less than the section assessment coefficient threshold, no risk signal is generated.

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