Highway pavement high-efficiency rapid damage identification method

Abstract

The invention belongs to the technical field of road surface damage identification, and particularly discloses a highway road surface high-efficiency rapid damage identification method, which comprises the following steps: positioning a selected highway road surface apparent damage position, carrying out deep detection on an image structure of a corresponding position, detecting an internal base layer structure variation condition of the damage position, and calculating a highway road surface damage identification result; the roadbed damage degree is analyzed; by identifying the opening angle and the divergence angle of a main crack of a crack type damaged pavement, analyzing the axial damage gain of the main crack of a crack area, identifying the axial gain type of the main crack, analyzing the stack load damage gain of the crack area, and similarly, identifying the damage gain of a complex area, which is beneficial for finding potential pavement collapse and sudden crack risks in advance; by detecting roadbed curvature and load flow conditions of different damage positions of a road surface, differentiated targeted deep analysis is performed on crack type and deformation type damage positions, and damage gains between different damage points are explored.

Description

Technical Field

[0001] The invention belongs to the technical field of road surface damage identification and relates to a method for efficiently and quickly identifying damage to a highway road surface. Background Art

[0002] In the field of transportation infrastructure construction and maintenance today, highways are important lifelines, and their road conditions directly affect the safety and efficiency of transportation. With the vigorous development of my country's transportation industry, a series of large-scale highway construction projects such as the Yilai Project (Yila Expressway Construction Project) have emerged.

[0003] As a transportation link connecting important areas, Yilai Expressway has a large construction scale, a long route and a complex geographical environment. After completion, it will carry a large amount of traffic flow. In such a large-scale project, the highway pavement faces various potential damage factors. On the one hand, the complex topographic conditions (such as the mountainous areas where the Yilai project passes have large terrain undulations and steep slopes) exert different degrees of stress on the pavement, which easily leads to cracks, potholes, deformation and other damages on the pavement. On the other hand, high-frequency vehicle driving will accelerate the wear and fatigue damage of the pavement. Therefore, there is an urgent need for an efficient and fast pavement damage identification method that can meet the needs of the Yilai project and similar large-scale highway construction projects, detect pavement damage in a timely and accurate manner, ensure the safe operation of the highway, and reduce problems such as traffic interruption and increased maintenance costs caused by pavement damage.

[0004] There are also some solutions related to road damage identification in the prior art. For example, Chinese Patent Publication No. CN114202511A discloses a road marking damage detection method based on computer vision, which collects road images and establishes image sequences based on the road images; detects road markings in the road images and tracks the road markings; identifies damage to the road markings in the road images to obtain damage detection results; and further calculates the damage rate of the road markings based on the damage detection results. This method improves the detection accuracy.

[0005] However, traditional pavement damage identification methods have many limitations when facing large and complex highways such as the Yilai project. For example, when analyzing the road surface defect data, only the damage on the pavement surface can be observed, but there is a lack of in-depth analysis of the defect parameters in the defect area, which may not be able to fully cover the internal structure of the pavement, resulting in insufficient in-depth structural detection of the damaged location. At the same time, it is impossible to accurately identify the type and degree of damage, which is far from enough for the Yilai Expressway that requires long-term stable operation. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a method for efficiently and quickly identifying damage to highway pavement is proposed.

[0007] The objective of the present invention can be achieved through the following technical solutions: The present invention provides a method for efficiently and quickly identifying damage on a highway pavement, the method comprising the following steps: Step 1, obtaining a road body casting contour model of a selected highway, performing image scanning on the pavement of the selected highway by using an unmanned aerial vehicle or a scanning device carried by a vehicle, collecting various damage feature points of the pavement by using image recognition technology, such as various feature points of cracks and various feature points of deformations, and numbering each damage feature point as 1, 2, ...point..., d.

[0008] Step 2: Collect the internal image of each damage feature point through ray recognition technology, extract the internal base structure of each damage feature point, and construct a damage information image model of the selected highway.

[0009] Step 3: From the damage information image model of the selected highway, the crack areas and complex areas are delineated, the surface damage degree and internal base structure damage degree of each damage feature point of the selected highway pavement are detected, and the roadbed damage degree of each damage feature point of the selected highway pavement is analyzed. point And number each fracture area as 1, 2, ... f ..., d1, and each complex area as 1, 2, ... c ..., d2.

[0010] Step 4: Obtain geomorphic environment information of the selected highway, and analyze a type of damage gain array of the selected highway pavement damage feature points.

[0011] Step 5: Obtain the traffic load information of the selected highway and analyze the second-class damage gain array of the pavement damage feature points of the selected highway.

[0012] Step 6: Based on the first-class damage gain array and the second-class damage gain array of the selected highway pavement damage characteristic points, construct the damage iteration coefficients of the selected highway pavement damage characteristic points.

[0013] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention locates the apparent damage position of the road surface by performing image scanning on the road surface of the selected highway, and then performs in-depth detection of the image structure at the corresponding position. By detecting the abnormal changes in the internal base structure at the damaged position and analyzing the degree of roadbed damage at each damage feature point of the selected highway road surface, the problems existing in the roadbed, such as loose base material, changes in compaction, and formation of underground voids, can be more accurately understood.

[0014] (2) The present invention can accurately analyze the root causes of cracks by detecting the roadbed curvature and load flow conditions at different damaged locations on the road surface. Based on this, differentiated, targeted and in-depth analysis of crack and deformation damage locations is performed to explore the damage gain between different damage points. The formation mechanism of various damaged road surfaces (such as rutting, subsidence, and bumps) can be clearly revealed, thereby helping to formulate highly accurate repair plans.

[0015] (3) The present invention can quantitatively evaluate the current state of the crack by identifying the main crack opening angle and expansion angle of the crack-damaged pavement and analyzing the axial damage gain of the main crack in the crack zone. It can also help determine the expansion speed and degree of the crack in the axial direction by identifying its axial gain type and analyzing the superimposed damage gain in the crack zone, thereby predicting the possible future expansion path of the crack. Similarly, by identifying the damage gain of the complex zone, potential pavement collapse and sudden cracking risks can be discovered in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0017] Figure 1 The present invention is a schematic flow chart of the steps for implementing the method.

[0018] Figure 2 A schematic diagram of a damage information image model of a highway selected for the present invention.

[0019] Figure 3 Schematic diagram of the fracture zone of the present invention.

[0020] Figure 4 This is a schematic diagram of the curvature profile of the road body with reference to the crack area of ​​the present invention.

[0021] Figure numerals: 1. Internal base structure, 2. Apparent crack contour, 3. Branch crack, 4. Spatial boundary of horizontal plane, 5. Spatial boundary of vertical plane, 6. External tangent line, 7. Expansion line. DETAILED DESCRIPTION

[0022] 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.

[0023] See also Figure 1 As shown, the present invention provides a method for efficiently and quickly identifying damage to a highway pavement, the method comprising the following steps: Step 1, obtaining a road body casting contour model of a selected highway, performing image scanning on the pavement of the selected highway by using an unmanned aerial vehicle or a scanning device carried by a vehicle, collecting various damage feature points of the pavement by using image recognition technology, such as various feature points of cracks and various feature points of deformations, and numbering each damage feature point as 1, 2, ...point..., d.

[0024] The crack types include longitudinal cracks and transverse cracks, and the deformation types include rutting, subsidence, and swelling.

[0025] The longitudinal cracks extend along the driving direction and have a relatively regular shape, usually being straight or slightly curved; the transverse cracks are perpendicular to the driving direction and are mostly straight.

[0026] Step 2: Collect the internal image of each damage feature point through ray recognition technology, extract the internal base structure of each damage feature point, and construct a damage information image model of the selected highway.

[0027] In a preferred embodiment, the damage information image model of the selected highway is constructed by marking each damage feature point of the road surface in the road body casting contour model of the selected highway, and using computer vision technology to extract the internal base structure in the road body internal image of each damage feature point, and importing it into the road body casting contour model of the selected highway to obtain the damage information image model of the selected highway.

[0028] See also Figure 2 , 3 As shown in step 3, each crack area and each complex area are delineated from the damage information image model of the selected highway, the surface damage degree and internal base structure damage degree of each damage feature point of the selected highway pavement are detected, and the roadbed damage degree D of each damage feature point of the selected highway pavement is analyzed. point And number each fracture area as 1,2,...f...,d1, and each complex area as 1,2,...c...,d2.

[0029] In a preferred embodiment, the detection of the surface damage degree of each damage characteristic point on the pavement of a selected highway is specifically as follows: the crack length and crack width of each characteristic point of the crack type, the shape depth and aggregate displacement degree of each characteristic point of the deformation type are extracted from the damage position coordinate distribution map of the selected highway, and recorded as each apparent damage feature detection value of each damage feature point, which is then compared with the corresponding preset reference value of the corresponding apparent damage feature, and then the surface damage degree of each damage characteristic point on the pavement of the selected highway is obtained by summing them up.

[0030] The shape depth of each deformation characteristic point includes rutting depth, subsidence depth, and bump height. The aggregate displacement degree of the deformation characteristic point refers to the ratio between the volume of the displacement accumulation of the laying base material due to the deformation of the road surface and the preset reference accumulation volume.

[0031] In a further preferred embodiment, the analysis of the degree of roadbed damage at each damage feature point of the highway pavement includes: screening each feature point of the crack type from the damage information image model of the selected highway, and extracting the apparent crack contour of each feature point of the crack type, obtaining the deepest point position of each feature point of the crack type along the vertical and horizontal planes in the damage information image model, using them as the spatial boundaries of the horizontal and vertical planes, respectively, to delineate the spatial area, and thereby delineate the crack damage area of ​​each feature point of the crack type, which is recorded as each crack area.

[0032] The internal base structure of each crack zone is extracted from the internal base structure of each damage feature point, the apparent crack contour of each crack zone is taken as the main crack, and the intersection angle between each branch crack contour and the main crack is obtained from the internal base structure of each crack zone. And obtain the embedded crack volume V of each branch crack in each crack zone (f，b) , analyze the damage degree of the base structure in each crack area In the formula represents the preset cross angle compensation value, V0 represents the preset reference embedded crack volume, b represents the number of the corresponding branch cracks in the crack zone, b = 1, 2, ..., a.

[0033] Specifically, when the branch crack profile intersects the main crack at a small angle (acute angle), the stress concentration phenomenon will be more obvious near the intersection point, that is, the smaller the intersection angle, the more serious the damage to the base structure.

[0034] The embedded crack volume refers to the total volume of cracks that branch cracks open to the roadbed substratum.

[0035] The deformation feature points are screened out from the damage information image model of the selected highway, and the apparent deformation contours of the deformation feature points are extracted. The base layer to which the paving structure data of a certain base layer corresponding to the internal base structure of each deformation feature point exceeds the preset standard value of the corresponding base layer corresponding paving structure data and the paving structure data of each adjacent base layer do not exceed the preset standard value of the corresponding base layer corresponding paving structure data belongs is identified. The base layer is used as the deformation space boundary of the corresponding feature point of the deformation class, and the deformation damage area of ​​each deformation feature point is circled, recorded as each complex area, and the base structure damage degree D″ of each complex area is analyzed. c , including various paving structure data such as paving thickness and road crown slope.

[0036] The damage degree of the base structure of each crack area and the base structure of each complex area are summarized to obtain the damage degree D″ of the base structure of each damage characteristic point on the highway pavement. point , and then analyze and obtain the roadbed damage degree D of each damage characteristic point of the highway pavement point =D″ point *D′ point , D′ point Indicates the surface damage degree of the point-th damage feature point on the selected highway pavement.

[0037] In a further preferred embodiment, the analysis of the damage degree of the base structure of each complex area includes: extracting the internal base structure of each complex area from the internal base structure of each damage feature point to obtain the paving structure data of each base corresponding to the deformation damage area of ​​each complex area, subtracting the paving structure data of each base corresponding to the deformation damage area of ​​each complex area from the preset standard value of the paving structure data of the corresponding base of the corresponding road body area, and then comparing them with the preset reference difference value, and summing them to obtain the paving quality change coefficient P of each base corresponding to the deformation damage area of ​​each complex area (c,r) , r represents the number of the base layer, r = 1, 2, ..., g.

[0038] Detect the interlayer impurity content Su of each base layer and its adjacent base layer corresponding to each complex area (c,r) and interlaminar crack opening Ca (c,r) , analyze the damage degree of the base structure in each complex area Where Su′ and Ca′ represent the preset interlayer reference impurity content and interlayer reference crack opening, respectively.

[0039] The interlayer debris includes debris left over from construction (uncleaned loose materials, discarded construction material fragments), debris introduced from the environment (dust and soil, plant seeds and roots), and products of material aging or chemical reactions (asphalt aging products, chemical crystals).

[0040] The interlayer crack refers to a crack extending along the horizontal plane between the layers of adjacent base layers.

[0041] The present invention locates the apparent damage position of the road surface by performing image scanning on the road surface of the selected expressway, and then performs in-depth detection of the image structure at the corresponding position. By detecting the abnormal changes of the internal base structure at the damaged position and analyzing the degree of roadbed damage at each damage characteristic point of the selected expressway road surface, the problems existing in the roadbed, such as loose base material, changes in compaction, and formation of underground voids, can be more accurately understood.

[0042] Step 4: Obtain geomorphic environment information of the selected highway, and analyze a type of damage gain array of the selected highway pavement damage feature points.

[0043] The geomorphic environment information includes the road slope and road curvature of the road section.

[0044] See also Figure 4 As shown, in a preferred embodiment, the damage gain array of each damage feature point of the statistically selected highway pavement includes: obtaining the road slope and road curvature of the road section to which each damage feature point of the pavement belongs from the damage information image model of the selected highway.

[0045] Select any crack area as the reference crack area, obtain the road curvature of the reference crack area from the road curvature of the road section to which each damage characteristic point belongs, and obtain the road curvature profile of the reference crack area, locate the external tangent line, and compare it with the apparent crack profile of the reference crack area to obtain the main crack opening angle of the reference crack area

[0046] The external tangent line positioning method is: extracting the maximum arc point from the road body curvature profile, and making a tangent line of the road body curvature profile at this point.

[0047] The perpendicular line of the corresponding external tangent line of the road curvature contour of the reference crack area is used as the expansion line, and the intersection angle between the corresponding branch crack contours of the reference crack area and the expansion line in the horizontal direction is extracted. The embedded crack volume V of each branch crack in the reference crack zone is extracted from the embedded crack volume of each branch crack in each crack zone. b′ , identify the main crack expansion angle of the reference crack zone b′ represents the number of each branch crack corresponding to the transverse reference crack zone, b′=1, 2, ..., a′.

[0048] Analysis of the main crack axial damage gain in the reference crack zone in represents the preset reference opening angle of the main crack, γ represents the road slope of the reference crack area in the road slope of each damage characteristic point, represents the preset reference road slope, and the axial damage gain X of the corresponding main crack in each crack zone is obtained in this way. f , π represents 180°.

[0049] Match the corresponding deformation type of each complex area with the preset corresponding morphological complexity basic damage gain of each deformation type to obtain the corresponding morphological complexity basic damage gain β of each complex area c , analyze the corresponding morphological complexity damage gain of each complex area where γ c represents the road slope of the cth complex area in the road slope of the road section to which each damage feature point belongs, λ cIt represents the road curvature of the cth complex area in the road curvature of the road section to which each damage feature point belongs. Represent the preset reference road slope and reference road curvature respectively.

[0050] Exemplarily, the corresponding morphological complexity basic damage gain of each deformation type is set to β=0.3, the morphological complexity basic damage gain of the subsidence type is set to β=0.3, and the morphological complexity basic damage gain of the bulge type is set to β=0.4.

[0051] A type of damage gain array for statistically selecting highway pavement damage feature points Where X1 represents the axial damage gain of the main crack corresponding to the first crack zone, Y1 represents the first corresponding morphological complexity damage gain, f+c=d, d is the total number of damage characteristic points, f is the total number of crack zones, and c is the total number of complex zones.

[0052] Step 5: Obtain the traffic load information of the selected highway and analyze the second-class damage gain array of the pavement damage feature points of the selected highway.

[0053] The traffic load information is the daily flow rate of heavy vehicles on each axle of the road section.

[0054] In a preferred embodiment, the two-type damage gain array of each damage feature point of the highway pavement selected by statistics includes: monitoring the daily flow rate of heavy vehicles on each axle of the corresponding local section through cameras set up in each local section of the highway, matching the daily flow rate of heavy vehicles on each axle of each local section with the section to which each damage feature point of the pavement belongs, and obtaining the daily flow rate of heavy vehicles on each axle of the section to which each damage feature point of the pavement belongs Q( point,h ), analyze the load coefficient of the road section to which each damage characteristic point belongs Wherein κh represents the corresponding tire weight of each axle heavy-duty vehicle, Q0 represents the preset reference daily load flow, h represents the number of each axle heavy-duty vehicle, and h = 1, 2, ..., m.

[0055] The heavy-duty vehicles with different axles, such as large trucks, semi-trailers, etc., have different contact areas and contact pressures between their corresponding tires and the road surface.

[0056] Obtain each crack zone in each damage feature point of the pavement, identify the main crack axial gain type of each crack zone, and analyze the superimposed damage gain X′ of each crack zone based on the road slope and road curvature of the road section to which each damage feature point belongs. f .

[0057] Obtain the corresponding deformation type of each complex area in each damage feature point of the road surface, and obtain the basic damage gain according to the corresponding form of each complex area. Similarly, determine the load damage gain of the corresponding basic form of each complex area. Analysis of the superimposed load damage gain of each complex area Among them G c It represents the load coefficient of the section to which the cth complex area belongs among the load coefficients of the section to which each damage characteristic point of the road surface belongs.

[0058] Statistically select the second type of damage gain array of highway pavement damage feature points Where X′1 represents the overlay damage gain of the first crack zone, and Y′1 represents the overlay damage gain of the first complex zone.

[0059] In a further preferred embodiment, the method for identifying the main crack axial gain type of each crack zone is: determining the main crack axial gain type indicator of the reference crack zone When T0=0, it means that the axial gain type of the main crack in the reference crack zone is the transverse roadbed settlement gain, and when T0=1, it means that the axial gain type of the main crack in the reference crack zone is the longitudinal side body instability gain. In this way, the axial gain type of the main crack in each crack zone is obtained.

[0060] The axial types of the main cracks include transverse roadbed settlement gain and longitudinal side body instability gain, wherein the transverse roadbed settlement gain refers to the possibility of the roadbed being interrupted in a direction perpendicular to the driving direction, and the longitudinal side body instability gain refers to the possibility of the roadbed collapsing toward the edge of the road.

[0061] In a further preferred embodiment, the analysis of the overload damage gain of each crack zone is as follows: the main crack axial gain type of each crack zone is obtained. When the main crack axial gain type of a crack zone is the longitudinal side body instability gain, the boundary distance L0 between the center position of the corresponding main crack in the crack zone and the corresponding earth shoulder position of the roadbed is obtained, and the main crack length L′0 corresponding to the crack zone is extracted, and the longitudinal roadbed slope instability spatial weight of the crack zone is analyzed. in They represent the preset reference boundary distance and main crack reference length respectively, and e is a natural constant.

[0062] When the axial gain type of the main crack in the crack zone is the transverse roadbed settlement gain, the corresponding main crack width w0 and the road body slope γ0 of the crack zone are obtained to analyze the spatial weight of the transverse roadbed settlement in the crack zone. Wherein V0′ represents the preset main crack reference area.

[0063] Obtain the superimposed damage gain X′0=η0*G0 of the crack zone, where G0 represents the load coefficient of the section to which the crack zone belongs among the load coefficients of the sections to which each damage characteristic point of the road surface belongs. The superimposed damage gain of each crack zone is obtained by analysis in this way.

[0064] The present invention can quantitatively evaluate the current state of the crack by identifying the main crack opening angle and expansion angle of the crack-type damaged pavement and analyzing the axial damage gain of the main crack in the crack zone. It can also help determine the expansion speed and degree of the crack in the axial direction by identifying its axial gain type and analyzing the superimposed damage gain in the crack zone, thereby predicting the possible future expansion path of the crack. Similarly, by identifying the damage gain of the complex zone, potential pavement collapse and sudden cracking risks can be discovered in advance.

[0065] Step 6: Based on the first-class damage gain array and the second-class damage gain array of the selected highway pavement damage characteristic points, construct the damage iteration coefficients of the selected highway pavement damage characteristic points.

[0066] In a preferred embodiment, the damage iteration coefficient of the selected highway pavement damage feature point is constructed by performing a dot product of the first-class damage gain array and the second-class damage gain array of each damage feature point of the selected highway pavement to obtain the damage gain scalar U of the selected highway pavement damage feature point, and then constructing the damage iteration coefficient of the selected highway pavement damage feature point

[0067] Exemplarily, the dot product calculation method is:

[0068] By detecting the roadbed curvature and load flow conditions at different damaged locations on the road surface, the present invention can accurately analyze the root causes of cracks, and based on this, conduct differentiated, targeted and in-depth analysis of crack and deformation damage locations, explore the damage gain between different damage points, and clearly reveal the formation mechanism of various damaged road surfaces (such as rutting, subsidence, and bumps), thereby helping to formulate highly accurate repair plans.

[0069] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for efficiently and quickly identifying damage on a highway pavement, characterized in that: The method comprises the following steps: Step 1: Obtain a road body casting contour model of the selected highway, scan the road surface of the selected highway by using a scanning device carried by a drone or a vehicle, collect various damage feature points of the road surface by using image recognition technology, such as various feature points of cracks and various feature points of deformation, and number each damage feature point as 1, 2, ...point..., d; Step 2: Collect the internal image of each damage feature point through ray recognition technology, extract the internal base structure of each damage feature point, and construct a damage information image model of the selected highway; Step 3: From the damage information image model of the selected highway, the crack areas and complex areas are delineated, the surface damage degree and internal base structure damage degree of each damage feature point of the selected highway pavement are detected, and the roadbed damage degree of each damage feature point of the selected highway pavement is analyzed. point , and number each fracture area as 1, 2, ...f..., d1, and each complex area as 1, 2, ...c..., d2; Step 4: obtaining geomorphic environment information of the selected highway, and analyzing a type of damage gain array of the selected highway pavement damage feature points; Step 5: Obtain the traffic load information of the selected highway, and analyze the second type damage gain array of the pavement damage feature points of the selected highway; Step 6: Based on the first-class damage gain array and the second-class damage gain array of the selected highway pavement damage characteristic points, construct the damage iteration coefficients of the selected highway pavement damage characteristic points.

2. A method for efficiently and quickly identifying damage to a highway pavement according to claim 1, characterized in that: The damage information image model of the selected expressway is constructed in the following specific manner: marking each damage feature point of the road surface in the road body casting contour model of the selected expressway, and using computer vision technology to extract the internal base structure in the road body internal image of each damage feature point, and importing it into the road body casting contour model of the selected expressway to obtain the damage information image model of the selected expressway.

3. The method for efficiently and quickly identifying damage to a highway pavement according to claim 1 is characterized in that: The method of detecting the surface damage degree of each damage characteristic point of the selected highway pavement is specifically as follows: extracting the crack length and crack width of each characteristic point of the crack type, the shape depth and aggregate displacement degree of each characteristic point of the deformation type from the damage position coordinate distribution map of the selected highway, recording them as each apparent damage feature detection value of each damage characteristic point, comparing them with the corresponding preset reference value of the corresponding apparent damage feature, and then summing them to obtain the surface damage degree of each damage characteristic point of the selected highway pavement.

4. The method for efficiently and quickly identifying damage to a highway pavement according to claim 1 is characterized in that: The analysis of the roadbed damage degree of each damage characteristic point of the highway pavement includes: Screen out each characteristic point of the crack type from the damage information image model of the selected highway, extract the apparent crack contour of each characteristic point of the crack type, obtain the deepest point position of each characteristic point of the crack type along the vertical and horizontal planes in the damage information image model, use them as the spatial boundaries of the horizontal and vertical planes, respectively, and delineate the spatial region, thereby delineating the crack damage region of each characteristic point of the crack type, which is recorded as each crack region; The internal base structure of each crack zone is extracted, the apparent crack profile of each crack zone is taken as the main crack, and the intersection angle θ between each branch crack profile and the main crack is obtained from the internal base structure of each crack zone. (f，b) , and obtain the embedded crack volume V of each branch crack in each crack zone (f，b) , analyze the damage degree of the base structure in each crack area In the formula represents the preset cross angle compensation value, V0 represents the preset reference embedded crack volume, b represents the number of each branch crack corresponding to the crack zone, b = 1, 2, ..., a; The deformation feature points are screened from the damage information image model of the selected highway, and the apparent deformation contours of the deformation feature points are extracted. The deformation damage areas of the deformation feature points are circled and recorded as complex areas. The damage degree D″c of the base structure of each complex area is analyzed. The damage degree of the base structure of each crack area and the base structure of each complex area are summarized to obtain the damage degree D″ of the base structure of each damage characteristic point on the highway pavement. point , and then analyze and obtain the roadbed damage degree D of each damage characteristic point of the highway pavement point =D″ point *D′ point , D′ point Indicates the surface damage degree of the point-th damage feature point on the selected highway pavement.

5. A method for efficiently and quickly identifying damage to a highway pavement according to claim 4, characterized in that: The analysis of the damage degree of the base structure of each complex area includes: extracting the internal base structure of each complex area, obtaining the paving structure data of each base corresponding to the deformation damage area of ​​each complex area, and calculating the paving quality change coefficient of each base corresponding to the deformation damage area of ​​each complex area; The interlayer impurity content and interlayer crack opening of each base layer corresponding to each complex area and its adjacent base layer are detected, and the degree of damage to the base structure of each complex area is analyzed based on this.

6. The method for efficiently and quickly identifying damage to a highway pavement according to claim 1 is characterized in that: The damage gain array of each damage feature point of the highway pavement selected by statistics includes: Obtain the road slope and road curvature of the road section to which each damage feature point of the road surface belongs from the damage information image model of the selected highway; Select any crack area as the reference crack area, obtain the road curvature of the reference crack area, obtain the road curvature profile of the reference crack area, locate the external tangent line, and compare it with the apparent crack profile of the reference crack area to obtain the main crack opening angle θ′ of the reference crack area, 0°<θ′<90°; The perpendicular line of the corresponding external tangent line of the road curvature contour of the reference crack area is used as the expansion line, and the intersection angle θ between the corresponding branch crack contours of the reference crack area and the expansion line in the horizontal direction is extracted. b′ , and extract the embedded crack volume V of each branch crack corresponding to the reference crack area b′ , identify the main crack expansion angle of the reference crack zone b′ represents the number of each branch crack corresponding to the transverse reference crack zone, b′=1,2,...,a′; Analysis of the main crack axial damage gain in the reference crack zone in represents the preset reference opening angle of the main crack, γ represents the road slope of the reference crack area, represents the preset reference road slope, and the axial damage gain X of the corresponding main crack in each crack zone is obtained in this way. f , π represents 180°; Obtain the corresponding morphological complexity basic damage gain of each complex area, and analyze the corresponding morphological complexity damage gain Y of each complex area c ; A type of damage gain array for statistically selecting highway pavement damage feature points Where X1 represents the axial damage gain of the main crack corresponding to the first crack zone, Y1 represents the first corresponding morphological complexity damage gain, f+c=d, d is the total number of damage characteristic points, f is the total number of crack zones, and c is the total number of complex zones.

7. A method for efficiently and quickly identifying damage to a highway pavement according to claim 6, characterized in that: The two-type damage gain array of each damage feature point of the highway pavement selected by statistics includes: Monitor the daily flow of heavy vehicles on each axle of the corresponding local sections through the cameras set up in each local section of the expressway, match the daily flow of heavy vehicles on each axle of each local section with the section to which each road damage characteristic point belongs, obtain the daily flow of heavy vehicles on each axle of the section to which each road damage characteristic point belongs, and analyze the load coefficient Gpoint of the section to which each road damage characteristic point belongs; Obtain each crack zone in each damage feature point of the pavement, identify the main crack axial gain type of each crack zone, and analyze the superimposed damage gain X′ of each crack zone f ; Obtain the corresponding deformation type of each complex area in each damage feature point of the pavement, determine the corresponding basic form load damage gain of each complex area, and analyze the superimposed load damage gain Y′ of each complex area c ; Statistically select the second type of damage gain array of highway pavement damage feature points Where X′1 represents the overlay damage gain of the first crack zone, and Y′1 represents the overlay damage gain of the first complex zone.

8. The method for efficiently and quickly identifying damage to a highway pavement according to claim 7 is characterized in that: The corresponding method for identifying the main crack axial gain type of each crack zone is: determining the main crack axial gain type indicator of the reference crack zone When T0=0, it means that the axial gain type of the main crack in the reference crack zone is the transverse roadbed settlement gain, and when T0=1, it means that the axial gain type of the main crack in the reference crack zone is the longitudinal side body instability gain. In this way, the axial gain type of the main crack in each crack zone is obtained.

9. A method for efficiently and quickly identifying damage to a highway pavement according to claim 8, characterized in that: The analysis of the superimposed damage gain of each crack zone is as follows: Obtain the main crack axial gain type of each crack zone. When the main crack axial gain type of a crack zone is the longitudinal side body instability gain, obtain the boundary distance L0 between the center position of the corresponding main crack in the crack zone and the corresponding soil shoulder position of the roadbed, and extract the corresponding main crack length L′0 of the crack zone to analyze the spatial weight of the longitudinal roadbed slope instability in the crack zone. in They represent the preset reference boundary distance and main crack reference length respectively, and e is a natural constant; When the axial gain type of the main crack in the crack zone is the transverse roadbed settlement gain, the corresponding main crack width w0 and the road body slope γ0 of the crack zone are obtained to analyze the spatial weight of the transverse roadbed settlement in the crack zone. Where V0′ represents the preset main crack reference area; Obtain the superimposed damage gain X′0=η0*G0 of the crack zone, where G0 represents the load coefficient of the section to which the crack zone belongs among the load coefficients of the sections to which each damage characteristic point of the road surface belongs. The superimposed damage gain of each crack zone is obtained by analysis in this way.

10. The method for efficiently and quickly identifying damage to a highway pavement according to claim 1, characterized in that: The damage iteration coefficient of the selected highway pavement damage feature point is constructed by performing a dot product of the first-class damage gain array and the second-class damage gain array of each damage feature point of the selected highway pavement to obtain a damage gain scalar U of the selected highway pavement damage feature point, and then constructing the damage iteration coefficient of the selected highway pavement damage feature point

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