Method and device for quickly determining general road slope inspection route

Abstract

The invention belongs to the technical field of geotechnical engineering, and provides a method and a device for quickly determining a general road slope inspection route. The method comprises the steps of determining a basic point set and a feature point set of unmanned aerial vehicle inspection; determining a shortest inspection route according to the spatial distribution of the basic point set and the feature point set; and finally, determining the route direction by vectorizing the shortest inspection route. According to the invention, through systematic routing inspection point selection and scientific route planning, the routing inspection efficiency and accuracy of the road slope are effectively improved.

Description

Technical Field

[0001] The invention relates to the technical field of geotechnical engineering, and in particular to a general-purpose method and device for quickly determining a highway slope inspection route. Background Art

[0002] The current selection of inspection points in highway slope drone inspection routes lacks systematicity, resulting in incomplete inspection coverage or repeated inspections, waste of resources and other problems; the planning of inspection routes mostly relies on manual experience and lacks scientific algorithm support, making it difficult to achieve the optimal path, resulting in longer inspection distances, increased energy consumption and inspection costs; the existing inspection route planning does not adequately consider the importance of key parts such as drainage projects, slope protection and reinforcement projects, and the different states of key parts will have an important impact on slope stability and traffic safety.

[0003] In response to the above problems, a general method for quickly formulating inspection routes for highway slopes is proposed. By clarifying the classification of basic points and characteristic points, a unified selection standard is formulated to improve the consistency and accuracy of inspections; the shortest path algorithm is used to automatically determine all basic points and characteristic points, the shortest path connection method and the optimal route direction, so as to significantly reduce the flight distance and energy consumption while ensuring the inspection effect, realize the scientific planning of inspection routes and improve the inspection efficiency; through systematic inspection point selection and scientific route planning, the efficiency and accuracy of inspections are effectively improved. This method is also universal and can be applied to various types of slopes such as rock, soil and rock-soil mixed materials, and has great application and promotion value. Summary of the invention

[0004] In view of the defects in the prior art, the present invention provides a universal method and device for quickly determining a highway slope inspection route, so as to effectively improve the efficiency and accuracy of the inspection through systematic inspection point selection and scientific route planning.

[0005] A general method for quickly determining a highway slope inspection route comprises:

[0006] Determine the basic point set and feature point set for drone inspection;

[0007] Determine the shortest inspection route based on the spatial distribution of the basic point set and the feature point set;

[0008] By vectorizing the shortest inspection route, the route direction of the shortest inspection route is determined.

[0009] Furthermore, the basic point set for drone inspection includes:

[0010] Determine the slope profile curve equation;

[0011] Combined with the contour curve equation, the initial basic point target constraint function is constructed;

[0012] Determine the initial basic point set according to the initial basic point target constraint function;

[0013] Based on the initial basic point set, the basic point set is screened and determined.

[0014] Furthermore, according to the initial basic point objective constraint function, the initial basic point set is determined, including:

[0015] The method shown in the following formula is used to determine the initial basic point set according to the initial basic point target constraint function:

[0016]

[0017] in, represents the initial base point set, C represents the shortest distance from each point on the slope profile to the initial base point, λ represents the weight coefficient, represents the coordinates of the i1th initial base point, represents the coordinates of j1 initial base points, and are the coordinates of the adjacent initial base points, represents the average position of the initial base points, d min and d max Indicates the minimum and maximum distances between the coordinates of adjacent initial base points, x amin and x amax Indicates the minimum and maximum values ​​of the horizontal range of the slope profile, y amin and amax Indicates the minimum and maximum values ​​of the vertical range of the slope profile, and represents the horizontal and vertical coordinates of the i1th initial base point, δ is the convergence threshold.

[0018] Furthermore, the feature point set for drone inspection includes:

[0019] Determine the surface continuity function of the slope;

[0020] Calculate the slope surface curvature and slope surface gradient according to the slope surface continuous function;

[0021] Determine the initial feature point set according to the slope surface curvature and slope surface gradient;

[0022] According to the initial feature point set, the feature point set is screened and determined.

[0023] Furthermore, the slope surface curvature and slope surface gradient are calculated according to the surface continuous function of the slope, including:

[0024] The slope surface curvature is calculated using the following formula:

[0025]

[0026] Where K is the curvature of the slope surface; f versus x b ,y b The first partial derivative of , x b Represents the horizontal axis, y b represents the vertical coordinate; are the second-order partial derivatives respectively, and f is a continuous function of the slope;

[0027] The slope surface gradient is calculated using the following formula:

[0028]

[0029] in, represents the slope surface gradient; represents the continuous function f of the slope with respect to x b ,y b The partial derivative of .

[0030] Furthermore, according to the slope surface curvature and slope surface gradient, an initial feature point set is determined, including:

[0031] According to the slope surface curvature and slope surface gradient, determine the minimum point of the slope surface curvature modulus and the maximum point of the slope surface gradient modulus;

[0032] The method shown in the following formula is used to determine the minimum point of the slope surface curvature modulus and the maximum point of the slope surface gradient modulus according to the slope surface curvature and slope surface gradient:

[0033]

[0034] in, represents the minimum point of the curvature modulus of the slope surface, represents the maximum point of the slope surface gradient modulus, represents the Laplace operator, (x b ,y b ) represents the coordinates of the initial feature points;

[0035] The initial feature point set is determined according to the minimum point of the curvature modulus of the slope surface and the maximum point of the gradient modulus of the slope surface.

[0036] Furthermore, the shortest inspection route is determined according to the spatial distribution of the basic point set and the feature point set, including:

[0037] Construct a weighted graph model based on the basic point set and the feature point set;

[0038] Construct a traveling salesman mathematical model based on a weighted graph model;

[0039] According to the traveling salesman mathematical model, the shortest inspection route is output.

[0040] Furthermore, a traveling salesman mathematical model is constructed based on the weighted graph model, including:

[0041] Construct the traveling salesman mathematical model:

[0042]

[0043] Among them, n means that the weighted graph model has a total of n vertices, w ij represents the weight of the edge connecting vertex i and vertex j, x ij is a decision variable, indicating whether vertex i to vertex j is on the path; V represents the vertex set in the weighted graph model, S represents a proper subset of the vertex set V, and contains at least two vertices; x 1n =1, that is, starting from vertex v1 and returning to v1.

[0044] Furthermore, the shortest inspection route is vectorized to determine the route direction, including:

[0045] Vectorize the shortest inspection route and determine the angle between adjacent vectors;

[0046] Determine the constraints of the route direction based on the angle between adjacent vectors;

[0047] According to the constraints of the route direction, the route direction of the shortest inspection route is determined.

[0048] A general-purpose highway slope inspection route rapid determination device comprises a first determination unit, a second determination unit and a third determination unit, wherein:

[0049] The first determination unit is used to determine the basic point set and feature point set of the drone inspection;

[0050] A second determination unit is used to determine the shortest inspection route according to the spatial distribution of the basic point set and the feature point set;

[0051] The third determining unit is used to determine the route direction of the shortest inspection route by vectorizing the shortest inspection route.

[0052] Beneficial effects of the present invention:

[0053] (1) The present invention can improve the consistency and accuracy of inspection by clarifying basic points and characteristic points and formulating unified selection criteria; and the present invention uses the shortest path algorithm to automatically determine all basic points and characteristic points, the shortest inspection route and the optimal route direction, thereby significantly reducing the flight distance and energy consumption while ensuring the inspection effect, and realizing the scientific planning of the inspection route and improving the inspection efficiency;

[0054] (2) The present invention effectively improves the efficiency and accuracy of inspections through systematic inspection point selection and scientific route planning. The present invention is also universal and can be applied to various types of slopes such as rock, soil, and rock-soil mixed materials, and has great application and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the specific embodiments of the present invention, the following will briefly introduce the drawings required for the specific embodiments or the prior art description. In all the drawings, each element or part is not necessarily drawn according to the actual scale.

[0056] Figure 1 A flowchart of a general highway slope inspection route rapid determination method provided by one embodiment of the present invention;

[0057] Figure 2 A schematic diagram of the basic skeleton structure of an inspection route network provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The following embodiments of the technical solution of the present invention are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only used as examples, and cannot be used to limit the protection scope of the present invention.

[0059] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by those skilled in the art to which the invention belongs.

[0060] In one embodiment, a general highway slope inspection route rapid determination method is provided, comprising:

[0061] 1. Determine the basic point set and feature point set for drone inspection;

[0062] like Figure 2 As shown in the figure, the inspection points in the highway slope drone inspection route are divided into basic points and feature points, where the basic points are the basic skeleton of the inspection route network, ensuring that the drone can inspect and cover all corners of the slope. The basic points are usually located at key positions of the slope, such as the top, foot, turning point, etc., to form a comprehensive inspection network for the slope.

[0063] Feature points are set for specific structures or diseased areas on the slope, such as drainage ditches, retaining walls, cracks, landslides, etc. The purpose of setting feature points is to timely discover and evaluate the potential risks of the slope by observing key areas in detail.

[0064] The present invention mainly connects all basic points and feature points with the shortest path without duplication to form the shortest inspection route, and finally determines the route direction by vectorizing the shortest inspection route.

[0065] (1) Preferably, determining a basic point set for drone inspection includes:

[0066] 1) Determine the slope profile curve equation:

[0067] Optionally, let the slope profile curve equation be y a =f a (x a ), where x a is the horizontal distance, y a is the vertical height. The curve equation is used to quantify the slope contour and the coordinates of the base point, that is, if the horizontal coordinate of the base point is known, the vertical coordinate of the base point can be determined using the curve equation.

[0068] The purpose of setting the curve equation is to quantify the slope contour line, so as to facilitate the determination of the coordinates of any point on the slope contour line;

[0069] Specifically, a coordinate system parallel to the slope surface is established, with the position of the slope foot on the left side of the slope contour line as the origin. The horizontal distance and vertical height of each base point can be obtained through the height and width of the slope (that is, the coordinates of each base point are obtained, the horizontal distance refers to the horizontal coordinate of the base point, and the vertical height refers to the vertical coordinate of the base point).

[0070] 2) Combine the contour curve equation to construct the initial basic point target constraint function, including:

[0071] ① Combine the contour curve equation to construct the initial basic point constraint conditions;

[0072] Optionally, the initial base point constraint conditions include adjacent base point distance constraints, slope contour constraints, horizontal distance constraints, and vertical height constraints.

[0073] Specifically, the horizontal distance constraint is characterized by the following formula:

[0074]

[0075] x amin and x amax Indicates the minimum and maximum values ​​of the horizontal range of the slope profile, Represents the horizontal coordinate of the i1th initial base point.

[0076] The vertical height constraint is characterized by the following formula:

[0077]

[0078] y amin and amax Indicates the minimum and maximum values ​​of the vertical range of the slope profile, Represents the ordinate of the i1th initial base point.

[0079] The distance constraint between adjacent basic points is characterized by the following formula:

[0080]

[0081] in, and are adjacent initial base points, d min and d max Indicates the minimum and maximum distances between adjacent initial base point coordinates.

[0082] The slope contour constraint is characterized by the following formula:

[0083]

[0084] Among them, C is the function that constrains the initial base point to the slope contour line, x a represents the horizontal position of the initial base point on the slope contour; f(x a ) indicates that the horizontal position of the initial base point on the slope contour is x a The vertical height at x amax and x amin They respectively represent the maximum and minimum values ​​that the initial base point can take within the horizontal range of the slope profile; It means taking a point closest to the slope contour as the initial base point i1. Only when the initial base point is located on the slope contour line is it closest to the slope contour, that is, the initial base point and the slope contour line coincide; Represents the horizontal distance integral to the base point i1.

[0085] ② Construct the basic point objective function according to the initial basic point constraint conditions;

[0086] Preferably, the basic point objective function is characterized by the following formula:

[0087]

[0088] in, represents the initial base point set, C represents the shortest distance from each point on the slope profile to the initial base point, λ represents the weight coefficient, represents the coordinates of any initial base point i1, Represents the average position of the initial base points.

[0089] ③ Combine the initial basic point constraint conditions and the basic point objective function to construct the initial basic point objective constraint function.

[0090] 3) Determine the initial basic point set according to the initial basic point target constraint function;

[0091] Optionally, the initial basic point set is determined according to the following initial basic point objective constraint function:

[0092]

[0093] in, represents the initial base point set, C represents the shortest distance from each point on the slope profile to the initial base point, λ represents the weight coefficient, represents the coordinates of the i1th initial base point, represents the coordinates of j1 initial base points, and are adjacent initial base points, represents the average position of the initial base points, d min and d max Indicates the minimum and maximum distances between the coordinates of adjacent initial base points, x amin and x amax Indicates the minimum and maximum values ​​of the horizontal range of the slope profile, y amin and amax Indicates the minimum and maximum values ​​of the vertical range of the slope profile, and represents the horizontal and vertical coordinates of the i1th initial base point, δ is the convergence threshold.

[0094] 4) Based on the initial basic point set, screen and determine the basic point set.

[0095] Preferably, screening and determining the basic point set according to the initial basic point set includes:

[0096] ① Determine the number of foundation points based on the length of the slope contour and the average spacing of the preset foundation points;

[0097] Preferably, the number of foundation points is determined according to the contour length of the slope and the average spacing of the preset foundation points using the method shown in the following formula:

[0098]

[0099] Where n is the number of basic points, L is the length of the slope contour line, d avg The average spacing of preset base points.

[0100] ② Determine the coordinates of the basic points according to the number of basic points and the initial basic point set;

[0101] Here, it is necessary to filter out the basic point coordinates that meet the basic point quantity from the initial basic point set, and manual screening can be selected.

[0102] For example, suppose that the initial base point set includes 100 initial base points, but n is determined to be 50 according to the contour length of the slope and the average spacing of the preset base points. You can choose to manually screen the 100 initial base points according to the target number of 50 base points, so as to determine the coordinates of the 50 base points.

[0103] When some basic points fail or their selection has an impact on the route, the basic points can be optimized;

[0104] Preferably, the following formula is used to optimize the basic points:

[0105]

[0106] Among them, η is the learning rate and k is the number of iterations; and are the kth iteration and the k+1th iteration respectively. Point coordinates.

[0107] The set of all the basic points determined by screening is the basic point set.

[0108] (2) Determine the feature point set for drone inspection, including:

[0109] 1) Determine the surface continuity function of the slope;

[0110] Here we establish a coordinate system perpendicular to the slope surface. Each point on the coordinate system has a corresponding slope height. Specifically, let z = f(x b ,y b ), indicating that the slope surface height varies with the plane coordinate (x b ,y b ) changes, and f is a continuous function of the slope.

[0111] 2) Calculate the slope surface curvature and slope surface gradient according to the slope surface continuous function; including:

[0112] ① Preferably, the following formula is used to calculate the slope surface curvature:

[0113]

[0114] Where K is the curvature of the slope surface; f versus x b ,y b The first-order partial derivative of b is the horizontal axis, y b is the vertical coordinate; are the second-order partial derivatives respectively, and f is a continuous function of the slope;

[0115] ② Calculate the slope surface gradient using the following formula:

[0116]

[0117] in, represents the slope surface gradient; represents the continuous function f of the slope with respect to x b ,y b The partial derivative of .

[0118] 3) Determine the initial feature point set according to the slope surface curvature and slope surface gradient; including:

[0119] ① According to the slope surface curvature and slope surface gradient, determine the minimum point of the slope surface curvature modulus and the maximum point of the slope surface gradient modulus;

[0120] The following formula is used to calculate the minimum point of the curvature modulus of the slope surface and the maximum point of the gradient modulus of the slope surface:

[0121]

[0122] in, represents the minimum point of the curvature modulus of the slope surface, represents the maximum point of the slope surface gradient modulus, represents the Laplace operator, f(x b ,y b ) represents the continuous function of the slope surface, (x b ,y b ) represents the initial feature point;

[0123] ② Determine the initial feature points based on the minimum point of the curvature modulus of the slope surface and the maximum point of the gradient modulus of the slope surface.

[0124] The set of all the minimum points of the curvature modulus of the slope surface and the maximum points of the gradient modulus of the slope surface is the initial feature point set.

[0125] 4) Based on the initial feature point set, filter and determine the feature point set. Including:

[0126] ① Calculate the distance between any two points in the initial feature point set according to the geometric distance formula;

[0127] Preferably, the geometric distance between any two initial feature points is calculated using the following formula:

[0128]

[0129] in, Represents the geometric distance between the initial feature points and the initial feature points, and represents the horizontal coordinates of the i2th and j2th initial feature points, and Represents the ordinate of the i2th and j2th initial feature points.

[0130] ② Calculate the gradient similarity of any two points in the initial feature point set according to the gradient similarity formula;

[0131] Preferably, the gradient similarity of any two initial feature points is calculated using the following formula:

[0132]

[0133] in, and Represent the initial feature points and The slope gradient vector at ; express and The similarity of the slope gradients at two points is between 0 and 1. When the gradient vectors of the two initial feature points are exactly the same, the similarity is 1; when the gradient vectors of the two initial feature points are perpendicular, the similarity is 0.

[0134] ③ According to the distance between any two points in the initial feature point set and the gradient similarity between any two points in the initial feature point set, the feature point set is screened and determined.

[0135] All initial feature points in the initial feature point set are screened. Specifically, if the gradient similarity between any two initial feature points is higher than the set similarity threshold S t (Similarity threshold S t is set artificially), and the distance between any two initial feature points is less than the set distance threshold d t (distance threshold d t It is artificially set), indicating that the two feature points are actually different representations of the same physical feature (for example, a small displacement caused by noise or calculation error). We choose to keep one of the initial feature points as the feature point and delete the other one, so as to complete the screening of all the initial feature points and determine the feature point set.

[0136] When some feature points fail or their selection has an impact on the route, the feature points can be optimized;

[0137] Preferably, the following formula is used to optimize the feature points:

[0138]

[0139] In the formula, η is the learning rate, k is the number of iterations, and L is the loss function. and are the kth iteration and the k+1th iteration respectively. Point coordinates.

[0140] The set of all feature points determined by screening is the feature point set.

[0141] 2. Determine the shortest inspection route based on the spatial distribution of the basic point set and the feature point set;

[0142] Preferably, determining the shortest inspection route according to the spatial distribution of the basic point set and the feature point set includes:

[0143] (1) Construct a weighted graph model based on the basic point set and the feature point set;

[0144] The basic points and feature points are regarded as vertices in the weighted graph, and the direct connection between two vertices is regarded as the edge in the graph. The weight of the edge is defined as the vertex set V containing all the points that need to be connected;

[0145] Set the vertex set V = {v1, v2, ..., v n}, where vi represents the i-th vertex (vertices include basic points or feature points).

[0146] Edge set E = {(v i , v j , w ij )|v i , v j ∈V, i≠j} is used to describe the connection relationship between points, vi represents the i-th vertex in the weighted graph model, and v j Represents the jth vertex in the weighted graph model, where w ij Represents the weight of the edge connecting vertex i and vertex j; weight function w: E→R + ,satisfy Used to describe the cost of connection; adjacency matrix A = [a ij ], where a ij =w(v i , v j ), (v i , v j )∈E, if i=j, a ij =0, otherwise a ij =∞; degree matrix D = diag[d1, d2, ..., d n ],in The degree matrix is ​​a diagonal matrix, and the elements on the diagonal correspond to the degree of each vertex in the weighted graph model (that is, the number of edges directly connected to the vertex); the adjacency matrix A and the degree matrix D are important representations of the weighted graph model and are used in subsequent algorithm processing.

[0147] (2) Construct a traveling salesman mathematical model based on the weighted graph model;

[0148] Preferably, a traveling salesman mathematical model is constructed in combination with a weighted graph model:

[0149]

[0150] Among them, n means that the weighted graph model has a total of n vertices, w ij represents the weight of the edge connecting vertex i and vertex j, x ij is a decision variable, indicating whether vertex i to vertex j is on the path; V represents the vertex set in the weighted graph model, S represents a proper subset of the vertex set V, and contains at least two vertices; x 1n =1, that is, starting from vertex v1 and returning to v1.

[0151] Specifically, the objective function in the traveling salesman mathematical model is:

[0152]

[0153] x ij is a decision variable, indicating whether vertex i to vertex j is on the path, where x ij =1 means on the path, x ij =0 means not on the path.

[0154] The constraints are:

[0155] Indicates that each vertex is visited exactly once;

[0156] means that each vertex leaves exactly once;

[0157] ∑ i∈S ∑ j∈S,j≠i x ij ≤|S-1, 2≤|S|≤n-1, which indicates subcircuit elimination, which is used to prevent the formation of subloops, where S is a proper subset of the vertex set V and contains at least two vertices.

[0158] x 1n =1, indicating the same constraint of the starting point, starting from vertex v1 and returning to v1.

[0159] (3) Determine the shortest inspection route based on the traveling salesman mathematical model.

[0160] Specifically, the traveling salesman mathematical model is solved by combining linear programming relaxation with integer programming. That is, the problem is first relaxed by linear programming to obtain a fractional solution, and then the fractional solution is converted into an integer solution by combining integer programming.

[0161] Linear programming relaxation objective function: where c ij =w ij ;

[0162] The relaxed constraints are the same as those in the traveling salesman mathematical model.

[0163] The objective function and constraints of integer programming are the same as those of linear programming relaxation, but the decision variables x ij Must be an integer (0 or 1).

[0164] Assume that the solution space of integer programming is X, the initial solution set X0 = X, and the upper bound of the target value is Z u =+∞, lower bound Z l =-∞.

[0165] The branch and bound method is used to solve the problem by continuously narrowing the solution space and approaching the optimal solution. The process is as follows:

[0166] ① Select a fractional solution x* obtained by solving a linear programming problem and calculate the corresponding integer programming target value Z*;

[0167] ②If Z*>Z l , and Z*<Z u , then update Z l = Z*;

[0168] ③According to the fractional part of x*, select a variable x ij Branching is performed to generate two sub-problems;

[0169] ④ Repeat the above process until an integer solution is found or the stopping condition is met.

[0170] Through linear programming relaxation and integer programming solution, we can obtain the path corresponding to the objective function in the traveling salesman mathematical model, which passes through all inspection points (i.e., vertices) and has the smallest weight, that is, the path between two points that passes only once while satisfying all constraints. ij =1, and w of the entire route ij Minimum.

[0171] The output shortest inspection route includes the order of passing each point and the corresponding weight of each edge.

[0172] 3. Determine the route direction based on the shortest inspection route. Including:

[0173] (1) Vectorize the shortest inspection route and determine the angle between adjacent vectors;

[0174] use represents the vector between adjacent inspection points of the shortest inspection route determined above; then the angle between adjacent vectors in the route is

[0175]

[0176] Among them, θ k is the angle between adjacent vectors in the flight path, represents the vector between the kth group of adjacent inspection points, represents the vector between k-1 groups of adjacent inspection points, It represents the modulus of the corresponding vector, and arccos is the inverse cosine function.

[0177] (2) Determine the constraints on the route direction based on the angle between adjacent vectors;

[0178] Using the smoothing function θ s,k =Smooth(θ k ) angle θ k Smoothing process, θ s,k The angle after smooth adjustment;

[0179] Press θ g,k =argmin θ (θ-θ s,k ) 2 +γE(θ) for direction optimization, where γ is the weight coefficient, E(θ) is the energy consumption of the drone at the direction angle θ, and θ g,k is the optimized angle; argmin θ It means that the formula (θ-θ s,k ) 2 The value of the variable when it reaches its minimum value.

[0180] according to Make direction adjustments, where is the adjusted direction vector;

[0181] according to Update the route direction vector set, where P is the updated route direction vector set and N is the number of inspection points.

[0182] The determination of the route direction is subject to the following constraints:

[0183] Make sure the drone is within the permitted flight speed range:

[0184] Make sure the drone is within the allowed flight angle range: θ min ≤θ g，k ≤θ max

[0185] Among them, v min and v max Indicates the maximum and minimum flight speeds allowed for the drone in the corresponding area. Some areas are obtained according to regulations, and some are obtained according to drone performance; θ min and θ max It indicates the minimum and maximum steering angles that the drone can achieve when flying according to the route, obtained through flight testing.

[0186] (3) Determine the route direction of the shortest inspection route based on the constraints of the route direction.

[0187] Finally, the global optimal algorithm is used to solve the global optimal direction that satisfies the constraints, and we get: It represents the final route direction determined after optimization, that is, the inspection route containing N inspection points, which is connected by N-1 connecting lines. The calculation starts from the angle between the direction vectors of the initial connecting line and the subsequent connecting lines adjacent to it, ensuring that all adjacent direction vector angles and vectors between adjacent inspection points simultaneously satisfy "the drone is within the allowed flight speed range and the drone is within the allowed flight angle range". The corresponding direction is the route direction.

[0188] The present invention proposes a general method and device for quickly determining a highway slope inspection route. By clarifying basic points and characteristic points and formulating unified selection criteria, the consistency and accuracy of inspections can be improved; and the present invention uses the shortest path algorithm to automatically determine all basic points and characteristic points, the shortest inspection route and the optimal route direction, thereby significantly reducing the range and energy consumption while ensuring the inspection effect, and realizing the scientific planning of inspection routes and improving inspection efficiency; in summary, the present invention effectively improves the efficiency and accuracy of inspections through systematic inspection point selection and scientific route planning. The method and device are also universal and can be applied to various types of slopes such as rock, soil, and rock-soil mixtures, and are of great application and promotion value.

[0189] In one embodiment, a general highway slope inspection route rapid determination device is also provided, comprising a first determination unit, a second determination unit and a third determination unit, wherein:

[0190] The first determination unit is used to determine the basic point set and feature point set of the drone inspection;

[0191] A second determination unit is used to determine the shortest inspection route according to the spatial distribution of the basic point set and the feature point set;

[0192] The third determining unit is used to determine the route direction of the shortest inspection route by vectorizing the shortest inspection route.

[0193] In the description of the present invention, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0194] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0195] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A general method for quickly determining a highway slope inspection route, characterized in that: include: Determine the basic point set and feature point set for drone inspection; Determine the shortest inspection route according to the spatial distribution of the basic point set and the feature point set; By vectorizing the shortest inspection route, the route direction of the shortest inspection route is determined.

2. A general highway slope inspection route rapid determination method as claimed in claim 1, characterized in that: The basic point set for determining the drone inspection includes: Determine the slope profile curve equation; Combined with the contour curve equation, the initial basic point target constraint function is constructed; Determine the initial basic point set according to the initial basic point target constraint function; Based on the initial basic point set, the basic point set is screened and determined.

3. A general highway slope inspection route rapid determination method as claimed in claim 1, characterized in that: Determining the initial basic point set according to the initial basic point target constraint function includes: The method shown in the following formula is used to determine the initial basic point set according to the initial basic point target constraint function: in, represents the initial base point set, C represents the shortest distance from each point on the slope profile to the initial base point, λ represents the weight coefficient, represents the coordinates of the i1th initial base point, represents the coordinates of j1 initial base points, and are the coordinates of the adjacent initial base points, represents the average position of the initial base points, d min and d max Indicates the minimum and maximum distances between the coordinates of adjacent initial base points, x amin and x amax Indicates the minimum and maximum values ​​of the horizontal range of the slope profile, y amin and amax Indicates the minimum and maximum values ​​of the vertical range of the slope profile, and represents the horizontal and vertical coordinates of the i1th initial base point, δ is the convergence threshold.

4. A general highway slope inspection route rapid determination method as claimed in claim 1, characterized in that: The feature point set for determining the drone inspection includes: Determine the surface continuity function of the slope; Calculate the slope surface curvature and slope surface gradient according to the slope surface continuous function; Determine the initial feature point set according to the slope surface curvature and slope surface gradient; According to the initial feature point set, the feature point set is screened and determined.

5. A general highway slope inspection route rapid determination method as claimed in claim 4, characterized in that: The slope surface curvature and slope surface gradient are calculated based on the slope surface continuous function, including: The slope surface curvature is calculated using the following formula: Where K is the curvature of the slope surface; f versus x b ,y b The first partial derivative of , x b Represents the horizontal axis, y b represents the vertical coordinate; are the second-order partial derivatives respectively, and f is a continuous function of the slope; The slope surface gradient is calculated using the following formula: in, represents the slope surface gradient; represents the continuous function f of the slope with respect to x b ,y b The partial derivative of .

6. A general highway slope inspection route rapid determination method as claimed in claim 5, characterized in that: According to the slope surface curvature and slope surface gradient, the initial feature points are determined, including: According to the slope surface curvature and slope surface gradient, determine the minimum point of the slope surface curvature modulus and the maximum point of the slope surface gradient modulus; The method shown in the following formula is used to determine the minimum point of the slope surface curvature modulus and the maximum point of the slope surface gradient modulus according to the slope surface curvature and slope surface gradient: in, represents the minimum point of the curvature modulus of the slope surface, represents the maximum point of the slope surface gradient modulus, represents the Laplace operator, (x b ,y b ) represents the coordinates of the initial feature points; The initial feature points are determined according to the minimum point of the curvature modulus of the slope surface and the maximum point of the gradient modulus of the slope surface.

7. A general highway slope inspection route rapid determination method as claimed in claim 1, characterized in that: Determining the shortest inspection route according to the spatial distribution of the basic point set and the feature point set includes: Construct a weighted graph model based on the basic point set and the feature point set; Construct a traveling salesman mathematical model based on a weighted graph model; According to the traveling salesman mathematical model, the shortest inspection route is output.

8. A general highway slope inspection route rapid determination method as claimed in claim 7, characterized in that: The traveling salesman mathematical model is constructed according to the weighted graph model, comprising: Construct the traveling salesman mathematical model: Among them, n means that the weighted graph model has a total of n vertices, w ij represents the weight of the edge connecting vertex i and vertex j, x ij is a decision variable, indicating whether vertex i to vertex j is on the path; V represents the vertex set in the weighted graph model, S represents a proper subset of the vertex set V, and contains at least two vertices; x 1n =1, that is, starting from vertex v1 and returning to v1.

9. A general highway slope inspection route rapid determination method as claimed in claim 1, characterized in that: By vectorizing the shortest inspection route, the route direction is determined, including: Vectorize the shortest inspection route and determine the angle between adjacent vectors; Determine the constraints of the route direction based on the angle between adjacent vectors; According to the constraints of the route direction, the route direction of the shortest inspection route is determined.

10. A general-purpose highway slope inspection route rapid determination device, characterized in that: The method comprises a first determining unit, a second determining unit and a third determining unit, wherein: The first determination unit is used to determine a basic point set and a feature point set for drone inspection; The second determination unit is used to determine the shortest inspection route according to the spatial distribution of the basic point set and the feature point set; The third determining unit is used to determine the route direction of the shortest inspection route by vectorizing the shortest inspection route.

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