A high-speed tunnel maintenance detection method based on Beidou positioning

Abstract

The present invention relates to the technical field of tunnel maintenance, and in particular to a high-speed tunnel maintenance detection method based on Beidou positioning, comprising: installing a Beidou positioning system on a maintenance detection vehicle, uploading electronic design drawings of the high-speed tunnel, obtaining structural parameters of the high-speed tunnel in the electronic design drawings of the high-speed tunnel, and constructing a three-dimensional model of the high-speed tunnel according to the structural parameters of the high-speed tunnel; selecting a maintenance detection path in the three-dimensional model of the high-speed tunnel, feeding the maintenance detection path back to the maintenance detection vehicle, the maintenance detection vehicle uses the maintenance detection path as navigation, travels in the high-speed tunnel, and perceives the state parameters of the high-speed tunnel in real time; the present invention obtains tunnel pavement defects that need to be processed urgently, and assists tunnel pavement management personnel to obtain tunnel pavement defect information more quickly, thereby more conveniently and orderly repairing tunnel pavement defects and ensuring tunnel pavement safety.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel maintenance, and in particular to a high-speed tunnel maintenance detection method based on Beidou positioning. Background Art

[0002] Tunnel road maintenance is a key task to ensure the safe operation of tunnels. It covers structural inspections, such as lining condition assessment; facility maintenance, including the inspection and repair of lighting and ventilation systems; road maintenance, and the treatment of cracks, potholes and other defects. Through regular inspections, professional repairs and the application of advanced technologies, the service life of tunnels can be extended to ensure smooth vehicle travel and personnel safety.

[0003] The invention patent with application number CN202310424560.9 discloses a highway disease positioning method based on integrated inspection and maintenance, and the steps include: receiving inspection data provided by inspection personnel, obtaining highway disease information, recording inspection time, inspection method, disease type, disease degree, and disease image, and synchronously updating highway disease information to the disease library; receiving maintenance data provided by maintenance personnel, matching the maintenance data with the corresponding disease, and updating the maintenance information record of highway diseases in the disease library; comparing highway disease information, disease maintenance information and BIM three-dimensional model to synchronize disease information, and then tracking the evolution process of diseases with the same number according to the highway disease information and disease maintenance information recorded in the disease library, tracking the frequency of re-appearance of diseases after maintenance within the error range of the same positioning position, analyzing the derivative relationship between the same disease and other diseases, analyzing the correlation between diseases within the error range of the same positioning position, locating highway diseases and evaluating the implementation effect of maintenance methods, and judging repeated maintenance phenomena.

[0004] The system aims to solve the problem that "the existing disease database only records the location information of road diseases and the approximate disease types. It cannot compare the development of diseases before and after maintenance, cannot provide the system with disease prediction information, and cannot effectively track the maintenance effect of diseases."

[0005] In addition, during the long-term use of the tunnel, a large number of road cracks, deformations, potholes and other problems may occur. It will take too long and be difficult to repair all of these problems at once, so it is most appropriate to repair them in batches according to their urgency.

[0006] Therefore, a high-speed tunnel maintenance detection method based on Beidou positioning was proposed. Summary of the invention

[0007] In view of the above-mentioned shortcomings of the prior art, the present invention provides a high-speed tunnel maintenance detection method based on Beidou positioning, which solves the technical problems raised in the above-mentioned background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] A high-speed tunnel maintenance detection method based on Beidou positioning, comprising:

[0010] A BeiDou positioning system is installed on the maintenance detection vehicle, and an electronic design drawing of the high-speed tunnel is uploaded. The structural parameters of the high-speed tunnel are obtained from the electronic design drawings of the high-speed tunnel, and a three-dimensional model of the high-speed tunnel is constructed according to the structural parameters of the high-speed tunnel; a maintenance detection path is selected in the three-dimensional model of the high-speed tunnel, and the maintenance detection path is fed back to the maintenance detection vehicle. The maintenance detection vehicle uses the maintenance detection path as a navigation, travels in the high-speed tunnel, and perceives the state parameters of the high-speed tunnel in real time; the state parameters of the high-speed tunnel perceived by the maintenance detection vehicle are simultaneously obtained, and the state parameters of the high-speed tunnel are placed in the three-dimensional model of the high-speed tunnel for representation; the health status of the high-speed tunnel is evaluated according to the three-dimensional model of the high-speed tunnel with the state parameters of the high-speed tunnel placed, and the three-dimensional model of the high-speed tunnel with the state parameters of the high-speed tunnel is bound to and stored with the health status evaluation result of the high-speed tunnel; the stored health status evaluation result of the high-speed tunnel is obtained, and the health status evaluation result of the high-speed tunnel is applied to determine whether the high-speed tunnel is healthy. When the determination result is yes, the refresh step is executed, and when the determination result is no, the damaged position of the high-speed tunnel is captured; and the damaged position on the high-speed tunnel is output.

[0011] Furthermore, when the maintenance detection vehicle is driving on the road surface, it simultaneously senses road cracks, deformations, potholes, and humidity values ​​exceeding the safe humidity. The Beidou positioning system installed on the maintenance detection vehicle is used to sense the location information of the maintenance detection vehicle in real time. The structural parameters of the high-speed tunnel include: road surface width, road surface thickness, road surface length, tunnel portal interface size, and tunnel arm thickness;

[0012] Among them, after the three-dimensional model of the highway tunnel is completed, a point is selected in the three-dimensional model of the highway tunnel, the scale of the three-dimensional model of the highway tunnel and the actual highway tunnel is set, and the position information of the corresponding point of the selected point in the three-dimensional model of the highway tunnel and the actual highway tunnel is obtained. Based on the scale and the corresponding position information of the selected point as a reference, the position information of any point in the three-dimensional model of the highway tunnel in the actual highway tunnel is determined.

[0013] Furthermore, the maintenance detection vehicle is placed in the three-dimensional model of the high-speed tunnel as a three-dimensional model of a specified arbitrary shape for representation. When the maintenance detection vehicle moves based on the maintenance detection path, the corresponding three-dimensional model of the maintenance detection vehicle represented in the three-dimensional model of the high-speed tunnel obtains the corresponding moving distance based on the moving distance and scale of the maintenance detection vehicle, and moves in the three-dimensional model of the high-speed tunnel;

[0014] After selecting the maintenance detection path in the three-dimensional model of the high-speed tunnel, a group of position information with a spacing of 0.5m in the maintenance detection path is synchronously obtained, and the queue of position information obtained in sequence is used as the maintenance detection path of the maintenance detection vehicle;

[0015] Among them, when the maintenance detection vehicle travels in the high-speed tunnel, it senses the state parameters of the high-speed tunnel at a specified frequency.

[0016] Furthermore, the frequency of the maintenance detection vehicle sensing the state parameters of the high-speed tunnel is subject to:

[0017] ;

[0018] Where: The frequency of sensing high-speed tunnel status parameters for maintenance probe vehicles; The total number of bends in the maintenance detection path; is the slope of the i-th bending point on the road section where it is located; is the distance between the i-th bending point and the i+1-th bending point on the maintenance detection path; is the normalization factor;

[0019] Among them, the user-defined frequency threshold of the maintenance detection vehicle to perceive the state parameters of the high-speed tunnel, When within the frequency threshold, The application is to detect the frequency of high-speed tunnel status parameters perceived by the maintenance probe vehicle. When not within the frequency threshold, the frequency threshold is applied at the two extreme values. The extreme value with the smallest difference is used as the frequency of the maintenance detection vehicle sensing the state parameters of the high-speed tunnel.

[0020] Furthermore, the maintenance detection vehicle senses the highway tunnel status parameters, namely, road cracks, deformation, potholes, and humidity values ​​exceeding safe humidity. The highway tunnel status parameters are placed in the operation stage represented by the three-dimensional model of the highway tunnel, and four different three-dimensional models are simultaneously created to represent the status parameters of each type of highway tunnel. Based on the position where the maintenance detection vehicle senses the highway tunnel status parameters, the three-dimensional models corresponding to the sensed highway tunnel status parameters are placed at corresponding positions.

[0021] Furthermore, the evaluation logic of the health status of the high-speed tunnel is expressed as:

[0022] ;

[0023] Where: is the health performance value of the j-th curved road section in the maintenance detection path; is the total amount of three-dimensional models representing the state parameters of various types of high-speed tunnels on the j-th curved road section; is the straight-line distance between the vth three-dimensional model and the v+1th three-dimensional model; , , , The number of high-speed tunnel status parameters of type a, type b, type c, and type d respectively; , , , is the weight; The health status performance value of the high-speed tunnel corresponding to the maintenance detection path; The total number of curved road sections in the maintenance detection path;

[0024] Among them, the weight , , , It is customized by the system user, and , , , The sum is 1, and the weight , , , All are positive numbers.

[0025] Furthermore, the determination of the curved road section of the maintenance detection path is as follows:

[0026] Obtain all the bending points on the maintenance detection path, take the two sides of the bending point on the path as the curved road section identification target, mark a judgment point every 0.5m on the road sections on both sides of the bending point, and identify whether the angle formed by the road sections on both sides of the judgment point on the path is a straight angle in order from near to far according to the distance between the judgment point and the bending point. When the judgment point is identified as a straight angle, or has exceeded the next bending point adjacent to the bending point, the path between the judgment point and the bending point is the curved road section;

[0027] The curved road section is defined by two determination points and at least one bending point, and all the bending points on each curved road section are between the two determination points.

[0028] Furthermore, the logic for determining whether the high-speed tunnel is healthy is expressed as follows:

[0029] ;

[0030] Where: is the health status performance value of the high-speed tunnel corresponding to the latest maintenance detection path; is the health determination value of the high-speed tunnel; Compared to The health status performance value of the high-speed tunnel corresponding to the maintenance detection path obtained last time; Compared to The health status performance value of the high-speed tunnel corresponding to the maintenance detection path obtained last time;

[0031] Among them, based on the above formula, when formula (1) and formula (2) are established at the same time, the high-speed tunnel is judged to be healthy, otherwise, the high-speed tunnel is judged to be unhealthy.

[0032] Furthermore, the damaged position capture logic of the high-speed tunnel is the same as the judgment logic of whether the high-speed tunnel is healthy, and the damaged position capture target of the high-speed tunnel is each curved road section.

[0033] Furthermore, the damaged position of the expressway tunnel is represented by a curved road section. When the damaged position on the expressway tunnel is output, the three-dimensional model representing road surface cracking, deformation, potholes, and humidity values ​​exceeding the safe humidity placed on the curved road section corresponding to the damaged position on the three-dimensional model of the expressway tunnel is used as a retention target, and the three-dimensional model representing road surface cracking, deformation, potholes, and humidity values ​​exceeding the safe humidity in the remaining three-dimensional model of the expressway tunnel is used as a deletion target, and a deletion process is performed;

[0034] The three-dimensional models representing road cracks, deformations, potholes, and humidity values ​​exceeding safe humidity that have not been deleted, and the three-dimensional model of the high-speed tunnel in which they are located, are the contents output during the output phase of the damaged position on the high-speed tunnel.

[0035] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0036] The present invention provides a high-speed tunnel maintenance detection method based on Beidou positioning. During the execution of the method, the Beidou positioning technology is combined to provide a maintenance detection vehicle with an accurate tunnel pavement defect detection path, and the detected tunnel pavement defects are further evaluated in a distributed manner, so as to obtain tunnel pavement defects that are in urgent need of processing, and synchronously combine the construction of a high-speed tunnel three-dimensional model, a maintenance detection vehicle model and a pavement defect model to represent the real-time position of the maintenance detection vehicle in the tunnel and tunnel pavement defects that are in urgent need of repair. The method assists tunnel pavement management personnel to more quickly obtain tunnel pavement defect information, so as to more conveniently and orderly repair tunnel pavement defects and ensure tunnel pavement safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 The figure is a flow chart of a high-speed tunnel maintenance detection method based on Beidou positioning. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0040] The present invention will be further described below in conjunction with the embodiments.

[0041] Embodiment 1:

[0042] A high-speed tunnel maintenance detection method based on Beidou positioning in this embodiment, such as Figure 1 As shown, including:

[0043] Install the Beidou positioning system on the maintenance probe vehicle, upload the electronic design drawings of the high-speed tunnel, obtain the structural parameters of the high-speed tunnel from the electronic design drawings, and build a three-dimensional model of the high-speed tunnel based on the structural parameters of the high-speed tunnel;

[0044] The maintenance detection vehicle is placed in the three-dimensional model of the high-speed tunnel as a three-dimensional model of a specified arbitrary shape for representation. When the maintenance detection vehicle moves based on the maintenance detection path, the corresponding three-dimensional model of the maintenance detection vehicle represented in the three-dimensional model of the high-speed tunnel obtains the corresponding moving distance based on the moving distance and scale of the maintenance detection vehicle, and moves in the three-dimensional model of the high-speed tunnel;

[0045] After selecting the maintenance detection path in the three-dimensional model of the high-speed tunnel, a group of position information with a spacing of 0.5m in the maintenance detection path is synchronously obtained, and the queue of position information obtained in sequence is used as the maintenance detection path of the maintenance detection vehicle;

[0046] Among them, when the maintenance detection vehicle is driving in the high-speed tunnel, it senses the state parameters of the high-speed tunnel at a specified frequency;

[0047] The frequency of the maintenance detection vehicle sensing the state parameters of the high-speed tunnel obeys:

[0048] ;

[0049] Where: The frequency of sensing high-speed tunnel status parameters for maintenance probe vehicles; The total number of bends in the maintenance detection path; is the slope of the i-th bending point on the road section where it is located; is the distance between the i-th bending point and the i+1-th bending point on the maintenance detection path; is the normalization factor;

[0050] Among them, the user-defined frequency threshold of the maintenance detection vehicle to perceive the state parameters of the high-speed tunnel, When within the frequency threshold, The application is to detect the frequency of high-speed tunnel status parameters perceived by the maintenance probe vehicle. When not within the frequency threshold, the frequency threshold is applied at the two extreme values. The extreme value with the smallest difference is used as the frequency of the maintenance detection vehicle sensing the state parameters of the high-speed tunnel;

[0051] The above logic formula is used to limit the frequency with which the maintenance detection vehicle perceives the state parameters of the high-speed tunnel.

[0052] A maintenance detection path is selected in the three-dimensional model of the high-speed tunnel, and the maintenance detection path is fed back to the maintenance detection vehicle. The maintenance detection vehicle navigates in the high-speed tunnel using the maintenance detection path to sense the state parameters of the high-speed tunnel in real time.

[0053] Synchronously obtain the high-speed tunnel state parameters sensed by the maintenance detection vehicle, and place the high-speed tunnel state parameters into the high-speed tunnel three-dimensional model for representation;

[0054] The health status of the high-speed tunnel is evaluated according to the high-speed tunnel three-dimensional model with the high-speed tunnel status parameters placed thereon, and the high-speed tunnel three-dimensional model with the high-speed tunnel status parameters placed thereon and the health status evaluation result of the high-speed tunnel are mutually bound and stored;

[0055] The evaluation logic of the health status of high-speed tunnels is expressed as follows:

[0056] ;

[0057] Where: is the health performance value of the j-th curved road section in the maintenance detection path; is the total amount of three-dimensional models representing the state parameters of various types of high-speed tunnels on the j-th curved road section; is the straight-line distance between the vth three-dimensional model and the v+1th three-dimensional model; , , , The number of high-speed tunnel status parameters of type a, type b, type c, and type d respectively; , , , is the weight; The health status performance value of the high-speed tunnel corresponding to the maintenance detection path; The total number of curved road sections in the maintenance detection path;

[0058] Among them, the weight , , , It is customized by the system user, and , , , The sum is 1, and the weight , , , All are positive numbers;

[0059] Through the above logical formula, the health status of the high-speed tunnel corresponding to the maintenance detection path is represented in a digital form, providing data support for determining whether the high-speed tunnel is healthy.

[0060] The determination of the curved road section of the maintenance detection path is as follows:

[0061] Obtain all the bending points on the maintenance detection path, take the two sides of the bending point on the path as the curved road section identification target, mark a judgment point every 0.5m on the road sections on both sides of the bending point, and identify whether the angle formed by the road sections on both sides of the judgment point on the path is a straight angle in order from near to far according to the distance between the judgment point and the bending point. When the judgment point is identified as a straight angle, or has exceeded the next bending point adjacent to the bending point, the path between the judgment point and the bending point is the curved road section;

[0062] The curved road section is defined by two determination points and at least one bending point, and all the bending points on each curved road section are between the two determination points;

[0063] Obtaining the stored high-speed tunnel health status assessment result, applying the high-speed tunnel health status assessment result to determine whether the high-speed tunnel is healthy, and when the determination result is yes, executing the refresh step, and when the determination result is no, capturing the damaged position of the high-speed tunnel;

[0064] The logic for determining whether a high-speed tunnel is healthy is expressed as follows:

[0065] ;

[0066] Where: is the health status performance value of the high-speed tunnel corresponding to the latest maintenance detection path; is the health determination value of the high-speed tunnel; Compared to The health status performance value of the high-speed tunnel corresponding to the maintenance detection path obtained last time; Compared to The health status performance value of the high-speed tunnel corresponding to the maintenance detection path obtained last time;

[0067] Among them, based on the above formula, when formula (1) and formula (2) are both true, the high-speed tunnel is judged to be healthy, otherwise, the high-speed tunnel is judged to be unhealthy;

[0068] Through the above logical formula, an accurate judgment can be made on whether the high-speed tunnel is healthy.

[0069] The logic for capturing the damaged position of a high-speed tunnel is the same as the logic for determining whether the high-speed tunnel is healthy. The target for capturing the damaged position of a high-speed tunnel is each curved road section.

[0070] Output the damaged location on the high-speed tunnel.

[0071] In this embodiment, through the execution of the method in the above embodiment, Beidou positioning technology is used to provide a precise detection path for the maintenance detection vehicle, so as to comprehensively capture the defects of the tunnel pavement. Further combined with the construction of a three-dimensional model of the high-speed tunnel, a global health assessment of the tunnel pavement defects is performed, so as to capture the tunnel pavement defects based on the health assessment results, and assist tunnel pavement management personnel to modify the tunnel pavement defects more logically to ensure the functionality and safety of the tunnel pavement.

[0072] Embodiment 2:

[0073] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The high-speed tunnel maintenance detection method based on Beidou positioning in Example 1 is further specifically described as follows:

[0074] When the maintenance probe vehicle is driving on the road, it can simultaneously sense road cracks, deformation, potholes, and humidity values ​​that exceed safe humidity. The Beidou positioning system installed on the maintenance probe vehicle is used to sense the location information of the maintenance probe vehicle in real time. The structural parameters of the high-speed tunnel include: road width, road thickness, road length, tunnel portal interface size, and tunnel arm thickness;

[0075] Among them, after the three-dimensional model of the highway tunnel is completed, a point is selected in the three-dimensional model of the highway tunnel, and the scale of the three-dimensional model of the highway tunnel and the actual highway tunnel is further set, and the position information of the selected point in the three-dimensional model of the highway tunnel and the corresponding point in the actual highway tunnel is obtained. Based on the scale and the corresponding position information of the selected point as a reference, the position information of any point in the three-dimensional model of the highway tunnel in the actual highway tunnel is determined; the state parameters of the highway tunnel perceived by the maintenance detection vehicle are: road cracks, deformation, potholes, and humidity values ​​exceeding the safe humidity. The state parameters of the highway tunnel are placed in the operation stage represented in the three-dimensional model of the highway tunnel, and four different three-dimensional models are created simultaneously to represent the state parameters of each type of highway tunnel. Based on the position of the state parameters of the highway tunnel perceived by the maintenance detection vehicle, the corresponding three-dimensional models of the perceived state parameters of the highway tunnel are placed in the corresponding positions.

[0076] In this embodiment, through the above settings, data support is provided for further execution steps of the method in Example 1, ensuring that the method in Example 1 can stably and effectively detect road surface defects in high-speed tunnels.

[0077] like Figure 1 As shown, the damaged position of the high-speed tunnel is represented by a curved road section. When the damaged position on the high-speed tunnel is output, the three-dimensional model representing the road surface cracking, deformation, potholes, and humidity values ​​exceeding the safe humidity placed on the curved road section corresponding to the damaged position on the three-dimensional model of the high-speed tunnel is used as a retention target, and the three-dimensional model representing the road surface cracking, deformation, potholes, and humidity values ​​exceeding the safe humidity in the remaining three-dimensional model of the high-speed tunnel is used as a deletion target, and the deletion process is performed;

[0078] The three-dimensional models representing road cracks, deformations, potholes, and humidity values ​​exceeding safe humidity that have not been deleted, and the three-dimensional model of the high-speed tunnel in which they are located, are the contents output during the output phase of the damaged position on the high-speed tunnel.

[0079] Through the above settings, the output logic of the damaged location on the high-speed tunnel is further limited.

[0080] In summary, during the execution of the method in the above embodiment, the Beidou positioning technology is combined to provide the maintenance detection vehicle with an accurate tunnel pavement defect detection path, and further a distributed evaluation is performed on the detected tunnel pavement defects, so as to obtain the tunnel pavement defects that need to be dealt with urgently. The three-dimensional model of the high-speed tunnel, the maintenance detection vehicle model and the pavement defect model are simultaneously combined to represent the real-time position of the maintenance detection vehicle in the tunnel and the tunnel pavement defects that need to be repaired urgently. This assists tunnel pavement management personnel to obtain tunnel pavement defect information more quickly, thereby more conveniently repairing tunnel pavement defects in an orderly manner and ensuring tunnel pavement safety.

[0081] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A high-speed tunnel maintenance detection method based on Beidou positioning, characterized in that: include: Install the Beidou positioning system on the maintenance probe vehicle, upload the electronic design drawings of the high-speed tunnel, obtain the structural parameters of the high-speed tunnel from the electronic design drawings, and build a three-dimensional model of the high-speed tunnel based on the structural parameters of the high-speed tunnel; A maintenance detection path is selected in the three-dimensional model of the high-speed tunnel, and the maintenance detection path is fed back to the maintenance detection vehicle. The maintenance detection vehicle navigates in the high-speed tunnel using the maintenance detection path to sense the state parameters of the high-speed tunnel in real time. Synchronously obtain the high-speed tunnel state parameters sensed by the maintenance detection vehicle, and place the high-speed tunnel state parameters into the high-speed tunnel three-dimensional model for representation; The health status of the high-speed tunnel is evaluated according to the high-speed tunnel three-dimensional model with the high-speed tunnel status parameters placed thereon, and the high-speed tunnel three-dimensional model with the high-speed tunnel status parameters placed thereon and the health status evaluation result of the high-speed tunnel are mutually bound and stored; Obtaining the stored high-speed tunnel health status assessment result, applying the high-speed tunnel health status assessment result to determine whether the high-speed tunnel is healthy, and when the determination result is yes, executing the refresh step, and when the determination result is no, capturing the damaged position of the high-speed tunnel; Output the damaged location on the high-speed tunnel; The maintenance detection vehicle is placed in the three-dimensional model of the high-speed tunnel as a three-dimensional model of a specified arbitrary shape for representation. When the maintenance detection vehicle moves based on the maintenance detection path, the corresponding three-dimensional model of the maintenance detection vehicle represented in the three-dimensional model of the high-speed tunnel obtains the corresponding moving distance based on the moving distance and scale of the maintenance detection vehicle, and moves in the three-dimensional model of the high-speed tunnel; After selecting the maintenance detection path in the three-dimensional model of the high-speed tunnel, a group of position information with a spacing of 0.5m in the maintenance detection path is synchronously obtained, and the queue of position information obtained in sequence is used as the maintenance detection path of the maintenance detection vehicle; Among them, when the maintenance detection vehicle is driving in the high-speed tunnel, it senses the state parameters of the high-speed tunnel at a specified frequency; The frequency of the maintenance detection vehicle sensing the state parameters of the high-speed tunnel is subject to: Where: P is the frequency of the maintenance detection vehicle sensing the state parameters of the high-speed tunnel; M is the total number of bending points in the maintenance detection path; κ i is the slope of the i-th bending point on the road section where it is located; |d i -d i+1 | is the distance between the i-th bending point and the i+1-th bending point on the maintenance detection path; λ is the normalization factor; Among them, the user side customizes the frequency threshold of the maintenance detection vehicle to perceive the state parameters of the expressway tunnel. When P is within the frequency threshold, P is applied as the frequency of the maintenance detection vehicle to perceive the state parameters of the expressway tunnel. When P is not within the frequency threshold, the extreme value of the two extreme values ​​of the frequency threshold with the smallest difference with P is applied as the frequency of the maintenance detection vehicle to perceive the state parameters of the expressway tunnel.

2. A high-speed tunnel maintenance detection method based on Beidou positioning according to claim 1, characterized in that: When the maintenance detection vehicle is driving on the road, it simultaneously senses road cracks, deformation, potholes, and humidity values ​​exceeding safe humidity. The Beidou positioning system installed on the maintenance detection vehicle is used to sense the location information of the maintenance detection vehicle in real time. The structural parameters of the high-speed tunnel include: road width, road thickness, road length, tunnel portal interface size, and tunnel arm thickness; Among them, after the three-dimensional model of the highway tunnel is completed, a point is selected in the three-dimensional model of the highway tunnel, the scale of the three-dimensional model of the highway tunnel and the actual highway tunnel is set, and the position information of the corresponding point of the selected point in the three-dimensional model of the highway tunnel and the actual highway tunnel is obtained. Based on the scale and the corresponding position information of the selected point as a reference, the position information of any point in the three-dimensional model of the highway tunnel in the actual highway tunnel is determined.

3. The high-speed tunnel maintenance detection method based on Beidou positioning according to claim 1 is characterized in that: The maintenance detection vehicle senses the highway tunnel status parameters, namely, road cracks, deformations, potholes, and humidity values ​​exceeding safe humidity. The highway tunnel status parameters are placed in the operation phase represented by the three-dimensional model of the highway tunnel, and four three-dimensional models are simultaneously created to represent different types of highway tunnel status parameters. Based on the position where the maintenance detection vehicle senses the highway tunnel status parameters, the sensed highway tunnel status parameters are placed in the corresponding perception positions in the corresponding three-dimensional models.

4. The high-speed tunnel maintenance detection method based on Beidou positioning according to claim 3 is characterized in that: The evaluation logic of the health status of the high-speed tunnel is expressed as follows: Where: F j is the health performance value of the j-th curved road section in the maintenance detection path; u is the total amount of three-dimensional models representing the state parameters of various types of high-speed tunnels on the j-th curved road section; |d v -d v+1 | is the straight-line distance between the vth state parameter three-dimensional model and the v+1th state parameter three-dimensional model; m a 、m b 、m c 、m d is the number of high-speed tunnel state parameters of type a, type b, type c, and type d respectively; ω a ,ω b ,ω c ,ω d is the weight; F is the health status performance value of the high-speed tunnel corresponding to the maintenance detection path; n is the total number of curved road sections in the maintenance detection path; Among them, the weight ω a ,ω b ,ω c ,ω d It is customized by the system end user, and ω a ,ω b ,ω c ,ω d The sum is 1, and the weight ω a ,ω b ,ω c ,ω d All are positive numbers.

5. The high-speed tunnel maintenance detection method based on Beidou positioning according to claim 4 is characterized in that: The determination of the curved road section of the maintenance detection path is as follows: Obtain all the bending points on the maintenance detection path, take the two sides of the bending point on the path as the curved road section identification target, mark a judgment point every 0.5m on the road sections on both sides of the bending point, and identify whether the angle formed by the road sections on both sides of the judgment point on the path is a straight angle in order from near to far according to the distance between the judgment point and the bending point. When the judgment point is identified as a straight angle, or has exceeded the next bending point adjacent to the bending point, the path between the judgment point and the bending point is the curved road section; The curved road section is defined by two determination points and at least one bending point, and all the bending points on each curved road section are between the two determination points.

6. The high-speed tunnel maintenance detection method based on Beidou positioning according to claim 1 is characterized in that: The logic for determining whether the high-speed tunnel is healthy is expressed as follows: Where: F new is the health status performance value of the high-speed tunnel corresponding to the latest maintenance detection path; F0 is the health judgment value of the high-speed tunnel; F new-1 Compared to F new The health status performance value of the high-speed tunnel corresponding to the maintenance detection path obtained last time; F new-2 Compared to F new-1 The health status performance value of the high-speed tunnel corresponding to the maintenance detection path obtained last time; Among them, based on the above formula, when formula (1) and formula (2) are established at the same time, the high-speed tunnel is determined to be healthy, otherwise, the high-speed tunnel is determined to be unhealthy.

7. A high-speed tunnel maintenance detection method based on Beidou positioning according to claim 6, characterized in that: The logic for capturing the damaged position of the high-speed tunnel is the same as the logic for determining whether the high-speed tunnel is healthy, and the target for capturing the damaged position of the high-speed tunnel is each curved road section.

8. The high-speed tunnel maintenance detection method based on Beidou positioning according to claim 1 is characterized in that: The damaged position of the expressway tunnel is represented by a curved road section. When the damaged position on the expressway tunnel is output, the three-dimensional model representing road surface cracking, deformation, potholes, and humidity values ​​exceeding safe humidity placed on the curved road section corresponding to the damaged position on the three-dimensional model of the expressway tunnel is used as a retention target, and the three-dimensional model representing road surface cracking, deformation, potholes, and humidity values ​​exceeding safe humidity in the remaining three-dimensional model of the expressway tunnel is used as a deletion target, and a deletion process is performed; The three-dimensional models representing road cracks, deformations, potholes, and humidity values ​​exceeding safe humidity that have not been deleted, and the three-dimensional model of the high-speed tunnel in which they are located, are the contents output during the output phase of the damaged position on the high-speed tunnel.

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