CN114357843A - Method for carrying out numerical collision experiment simulation aiming at wind power equipment transportation - Google Patents

Method for carrying out numerical collision experiment simulation aiming at wind power equipment transportation Download PDF

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CN114357843A
CN114357843A CN202210026964.8A CN202210026964A CN114357843A CN 114357843 A CN114357843 A CN 114357843A CN 202210026964 A CN202210026964 A CN 202210026964A CN 114357843 A CN114357843 A CN 114357843A
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matrix
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CN114357843B (en
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付俊峰
李玥康
魏博文
刘小林
华伟
李志伟
何中政
黄佩兵
黄子胜
罗育华
徐富刚
李怡静
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Power China Jiangxi Hydropower Engineering Bureau Co ltd
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Power China Jiangxi Hydropower Engineering Bureau Co ltd
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Abstract

The invention relates to the technical field of road transportation information, in particular to a method for carrying out numerical collision experiment simulation on wind power equipment transportation. The method provides a method for simulating the motion state of a fan component on a transportation road by using a numerical value, so that a numerical value collision test model is constructed. The problem of whether the large equipment can pass a bend without obstacles is solved when the fan equipment is transported, and a quick and effective tool is provided. The method also provides a point cloud boundary scanning method, a collision point is searched through a relative difference model, and finally the specific position and the formula quantity of the collision between the fan equipment and the obstacle are calculated by utilizing the three-dimensional application of the Riemann-Steyr integral. The method provides an effective reference basis for formulating and removing the obstacle scheme when the large piece is transported to encounter the obstacle.

Description

Method for carrying out numerical collision experiment simulation aiming at wind power equipment transportation
Technical Field
The invention relates to the technical field of road transportation information, in particular to a method for carrying out numerical collision experiment simulation on wind power equipment transportation.
Background
Wind power equipment transportation is a difficult point in wind power projects, and numerical collision simulation of the wind power equipment transportation is an important non-engineering measure for improving transportation efficiency in road transportation. At present, in the research of wind power equipment transportation, the transportation road process is optimized through a CAD technology, and although the method optimizes the swept track, the simulation depiction of the fan blade track is not fine. Road plane line parameter optimization is carried out on the wind power plant by using the AutoTURN, the AutoTURN can efficiently show the track of a fan component passing through a curve, but the condition that the fan blade collides with an obstacle outside a road cannot be shown.
Disclosure of Invention
The invention aims to provide a method for carrying out numerical collision experiment simulation on wind power equipment transportation. Therefore, transportation accidents in actual engineering can be avoided, so that the construction period is delayed and unnecessary economic loss is caused, and a new scheme is provided for improving the timeliness and the economy of wind power transportation.
The embodiment of the invention is realized by the following steps:
a method for carrying out numerical collision experiment simulation aiming at wind power equipment transportation provides a numerical simulation program by combining the actual driving posture of an engineering vehicle. Importing the fan component, the transport vehicle and the actual three-dimensional terrain parameters into a Java platform through semantic description, and performing collision test simulation with the three-dimensional terrain according to the actual vehicle running track and the blade tower drum rotation rule to obtain an accurate collision position and a collision volume, wherein the method mainly comprises the following steps:
step 1: the method comprises the steps of collecting terrain and road data through an unmanned aerial vehicle, and then extracting point cloud boundaries in point cloud data. For the output regular road surface point cloud data omega { P (X, y, z) } with the distance d, collecting X coordinates of all the point cloud data to generate a set X ═ X { (X)1,x2,…,xnD is used as precision discrete [ min X, max X }]Generating a set of rules
Figure BDA0003464431900000021
Step 2: for the
Figure BDA0003464431900000022
Can generate and
Figure BDA0003464431900000023
corresponding and ordered set of y coordinates
Figure BDA0003464431900000024
Then point is reached
Figure BDA0003464431900000025
I.e. corresponding to XRSet of boundary points TXThe point in { P (x, y, z) },
Figure BDA0003464431900000026
is prepared by reacting with
Figure BDA0003464431900000027
Corresponding to the coordinate of z. According to the same rule, a set of boundary points T corresponding to the y coordinate can be generatedY{ P (x, y, z) }. Set of boundary points TX、TYThere may be identical points, removing identical points and merging may generate a set of boundary points T, i.e. T ═ TX∪TY。
And step 3: and combining a finite element and vector analysis method to convert the fan transportation device into data.
And 4, step 4: method for constructing fan blade motion trail model R through given parameters1。
And 5: collecting site information from site, and constructing undetermined collision matrix R2The simulated collisions are coupled to determine a collision matrix V.
Step 6: integrating the field information of airborne LIDAR data, aerial images and observation information through a relative difference model, optimizing a parameter d, and constructing an attraction domain V of a matrix V1And repulsive domain V2. The coordinates of the obstacle points in the range of the attraction domain of the blade motion trail are summarized in a matrix H, the point coordinates in the matrix are compared with the coordinates of each corresponding blade track point, and if the track point Z is located1Value less than Z at a point in the matrix2And (4) extracting points in the matrix, and summarizing all the points extracted in the whole motion stage into a collision point matrix D.
And 7: and (4) solving collision point boundaries, namely solving a boundary matrix D' of collision points in the whole stage by using a formula for solving road boundary points and the principle thereof through the obtained collision point matrix D in the whole motion stage process of the blade.
And 8: the collision point area calculation adopts the three-dimensional application of Riemann-Steuerjess integration. A collision partition U 'of the boundary matrix D' refers to a finite number of collision surface bins, each called a sub-collision surface. D is defined as the discrete precision of these sub-impact areas. Sample segmentation, one sample segmentation of the boundary matrix D' means that after segmentation, at each sub-collisionA point h is taken out of the noodle. Obtaining U '═ U'h)，u′hThe non-normalized corresponding collision point area.
And step 9: normalizing the h-point sub-collision surface to obtain the final normalized corresponding collision total area U ═ U (U)h)。
Further, the set X in the step 1RSatisfy the requirement of
Figure BDA0003464431900000031
Further, the set y of coordinates y of the points on the road boundary in the step 2BThe following rules are met:
Figure BDA0003464431900000041
the collection
Figure BDA0003464431900000042
Satisfy the requirement of
Figure BDA0003464431900000043
Further, the fan transportation device in the step 3 comprises a tractor, a truck box with a steering function and a fan blade.
Further, in the step 3, the datamation of the fan transporting device is specifically realized by matrixing a motion track of the fan transporting device:
R＝{(xi1,yi1,zi1),(xi2,yi2,zi2)…(xim,yim,zim)}
in the formula, m is 1, 2, … i is 1, 2, …, R is a motion trajectory matrix, i is the number of stages, and m is a control point number.
Further, the relative difference model in step 6 is defined as: integrating on-site information of airborne LIDAR data, aerial images and observation information, optimizing parameter d, and constructing attraction domain V of matrix V1And repulsive domain V2Wherein d is1＝|xM-x|,d2＝|yMY |, setting fan blade motion track points M and barrier points such as a, b, etc., summarizing the point coordinates of the barriers in the attraction domain range of the blade motion track points into a matrix H, comparing the point coordinates in the matrix with the coordinates of each corresponding blade track point, and if the track point Z is the track point1Value less than Z at a point in the matrix2And (4) extracting points in the matrix, and summarizing all the points extracted in the whole motion stage into a collision point matrix D.
Further, u 'in the step 8'hSatisfies the formula:
Figure BDA0003464431900000051
further, the step 9 satisfies uhSatisfies the formula:
Figure BDA0003464431900000052
the technical scheme of the embodiment of the invention has the beneficial effects that:
the embodiment of the invention provides a method for carrying out numerical collision experiment simulation on wind power equipment transportation, and provides a method for simulating the motion form of a fan component on a transportation road by using a numerical value, so that a numerical collision experiment model is constructed. The problem of whether the large equipment can pass a bend without obstacles is solved when the fan equipment is transported, and a quick and effective tool is provided. And (3) providing a point cloud boundary scanning method, searching a collision point through a relative difference model, and finally calculating the specific position and the formula quantity of the collision between the fan equipment and the obstacle by utilizing the three-dimensional application of Riemann-Steyr integral. The method provides an effective reference basis for formulating and removing the obstacle scheme when the large piece is transported to encounter the obstacle.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of the operation of the present invention;
FIG. 2 is a schematic diagram of a road boundary provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram of road boundary extraction according to an embodiment of the present invention;
FIG. 4 is a diagram of a point cloud location provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram of a crash location provided by an embodiment of the present invention;
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a method for carrying out numerical collision experiment simulation on wind power equipment transportation. The collision feedback model comprises the steps of extracting a point cloud boundary, designing a basic component, calculating and feeding back a collision process, and specifically adopts the following technical scheme:
step 1: the point cloud data is processed, the original airborne radar point cloud data has more noise points, the original data needs to be preprocessed, three processes are mainly adopted,
the first process settles the original radar data, and then uses southsoild to remove noisy and isolated points in the solution data.
And step two, classifying the processed point cloud data into buildings, mountains, water areas, trees and roads.
And a third step of outputting the various extracted data into regular point clouds with equal intervals.
For the output regular road surface point cloud data omega { P (X, y, z) } with the distance d, collecting X coordinates of all the point cloud data to generate a set X ═ X { (X)1,x2,…,xnD is used as precision discrete [ minX, maxX }]Generating a set of rules
Figure BDA0003464431900000071
Wherein
Figure BDA0003464431900000072
For the
Figure BDA0003464431900000073
Can generate and
Figure BDA0003464431900000074
corresponding and ordered set of y coordinates
Figure BDA0003464431900000075
Wherein
Figure BDA0003464431900000076
The set y of coordinates y of points on the road boundaryBThe following rules should be followed:
Figure BDA0003464431900000077
then point is reached
Figure BDA0003464431900000078
I.e. corresponding to XRSet of boundary points TXThe point in { P (x, y, z) },
Figure BDA0003464431900000079
is prepared by reacting with
Figure BDA00034644319000000710
The corresponding z coordinate.
According to the same rule, a set of boundary points T corresponding to the y coordinate can be generatedY{ P (x, y, z) }. Set of boundary points TX、TYThe same points may exist, removing the same points and merging may generate a set of boundary points T, i.e.
T＝TX∪TY (2)
Step 2: the main components of the fan transportation are provided with a tractor, a carriage with a steering function and a fan blade, and the fan transportation device is digitalized by combining a finite element method and a vector analysis method.
1) Carrying vehicle
Simulated vehicle control points (X)i,Yi,Zi) The following conditions need to be satisfied for all control points:
Figure BDA0003464431900000081
Figure BDA0003464431900000082
Zi＝ZA (5)
in the formula: l is1、L2Vehicle length, width; m is1Counting the number of control points; l1Segment length is equally divided for control; alpha is a correction coefficient, and alpha is a correction coefficient,
Figure BDA0003464431900000083
theta is the deflection angle of the central axis to the y-axis,
Figure BDA0003464431900000084
2) blade
Simulated vehicle control points (X)j,Yj,Zj) The following conditions need to be satisfied for all control points:
Figure BDA0003464431900000085
Figure BDA0003464431900000086
Zj＝ZC+(j-1)l″2 (8)
in the formula: l is3、L4The length and the width of the fan blade; theta1The blade lift angle is adopted; theta2The turning angle of the base of the blade is,
Figure BDA0003464431900000091
m2counting the number of control points; l'2、l″2To control the projected length of the equal segment in XOY plane and Z axis, l'2＝l2cosθ1、l″2＝l2sinθ1，l2To control the equal segment length; beta is a correction coefficient, and beta is a correction coefficient,
Figure BDA0003464431900000092
φ(X,Y,Z)＝φ′(X,Y,Z),
Figure BDA0003464431900000093
and step 3: and screening collision points on the motion trail, wherein the screening process is based on LIDAR data, and the motion trail of the fan transport device is matriculated.
R＝{(xi1,yi1,zi1),(xi2,yi2,zi2)…(xim,yim,zim)} (9)
Wherein, m is 1, 2, … i is 1, 2, …, R is a motion track matrix, i is the number of stages, and m is a control point number. Given parameter construction fan blade motion trail model R1。
From scratchCollecting field information in a field, and constructing a pending collision matrix R2And simulating collision coupling to determine a collision matrix V, wherein the conventional collision model coupling has the problem of overlarge difference ambiguity, and a method for a relative difference model is provided. The relative difference model is defined as: integrating on-site information of airborne LIDAR data, aerial images and observation information, optimizing parameter d, and constructing attraction domain V of matrix V1And repulsive domain V2Wherein d is1＝|xM-x|,d2＝|yMY |, setting fan blade motion track points M and barrier points such as a, b, etc., summarizing the point coordinates of the barriers in the attraction domain range of the blade motion track points into a matrix H, comparing the point coordinates in the matrix with the coordinates of each corresponding blade track point, and if the track point Z is the track point1Value less than Z at a point in the matrix2Values, points within the matrix are extracted, and all points extracted throughout the motion phase are summarized in a collision point matrix D, as shown in fig. 2.
And 4, step 4: solving for collision point boundary and collision point area
1) Firstly, by means of the obtained collision point matrix D in the whole motion stage process of the blade, the boundary matrix D' of the collision point in the whole stage can be obtained by means of the formulas (1) and (2) for solving the road boundary points and the principle of the formulas.
2) The collision area is solved by three-dimensional application of Riemann-Steckes integral, which is similar to Riemann integral, and the definition of the Riemann-Steckes integral depends on the definition of interval segmentation: a collision partition U 'of the boundary matrix D' refers to a finite number of collision surface bins, each called a sub-collision surface. D is defined as the discrete precision of these sub-impact areas. The sampling division, one sampling division of the boundary matrix D', means that after division, a point h is taken out in each sub-collision surface. Wherein U ═ U'h)。
Figure BDA0003464431900000101
In formula (II) u'hThe area of the corresponding collision point is non-normalized; i is the number of groups of the current stage of the collision process, and two consecutive adjacent stages are a group of stages. x, y are points in the dangerous point boundary set D', and D is the discrete precision of the coordinate points of the obstacle.
Normalizing the h-point sub-collision surface to obtain the final normalized corresponding collision total area U ═ U (U)h) Wherein
Figure BDA0003464431900000102
Example one
Wind power projects in a certain city and a certain county of a certain province are used as research objects, and a numerical simulation model is applied to analyze the transportation state of the wind power roads. The algorithm is implemented in Java, and the running environment is Microsoft Windows 10 operating system, AMD Ryzen 73700X 8-Core Processor (3600MHz) Processor, 32G memory.
Before numerical simulation, parameters of each component need to be determined, and the parameters of the components are as follows:
1) three-dimensional topographic parameters
The method is characterized in that the road and terrain data are acquired by adopting an unmanned aerial vehicle aerial survey technology, the unmanned aerial vehicle uses Xinjiang matrix 300RTK, the working frequency is 2.40-2.48GHz and 5.72-5.85GHz, the flying height is 100m, and the speed is 23 m/s. The laser radar adopts a Possel Pandar40P, a single echo point frequency of 720000 points/second and a double echo point frequency of 1440000 points/second. Three-dimensional terrain data is acquired by adopting a simulated ground double-section flight mode. Resolving by using Usutio original data, denoising and classifying the point cloud data by using SouthLidar, and finally exporting an XYZ file.
Transport device
Due to the particularity of the blades, a special lifting vehicle with the bearing capacity of 120t is adopted, and the lifting vehicle has the functions of rotating the blades by 360 degrees, enabling the blades to rotate by 360 degrees to change the pitch, and avoiding obstacles in a forward or backward and 360-degree rotating mode. The vehicle size is 17.85m long, and wide 3.80m, and frock platform height 1.00 m. The tower wagon adopts a semi-trailer transport vehicle with the bearing capacity of 60t, the cargo platform is not higher than 1.30m, the effective loading length of the wagon plate is 17.00m, and the width of the wagon plate is 3.00 m.
Fan device
The single machine capacity is 4000kW, and the length, width and height of the blade are 81.00m multiplied by 5.56m multiplied by 3.27 m. The first tower barrel section has a length of 13.92m, a maximum outer diameter of 4.97m and a minimum outer diameter of 4.60 m. The length of the barrel section of the fifth tower barrel section is 25.00m, the maximum outer diameter is 4.11m, and the minimum outer diameter is 3.62 m.
The example shows that 4 typical scenes (curve 1 to curve 4) are selected as examples according to the conditions of roads and terrains and are respectively presented in the form of point clouds as shown in a, b, c and d in fig. 4.
4-a, the curve at the top of a tunnel has a turning radius of 64.17m, a high-voltage wire above the curve is 29.48m higher than the ground and 7.8m wider than the road, and the difficulty of the curve is that a step-shaped slope with a slope of 35 degrees and a slope height of 25m is arranged at the outer side of the curve. 4-b, the running direction of the vehicle enters a curve from a national road right-angle turn, and the difficulty of wind power transportation of the curve is mainly that the turning radius is too small and is 6.12 m. The national road is a bidirectional four-lane single-side width of 10.65m, the greening flower bed on the inner side of the curve is 1.2m high, the house is arranged on the outer side of the curve, the road middle greening belt is 10.15m high and the distance is 36 m. FIG. 4-c shows a Yangtoucun intersection with a road width of 5.59m, a curve radius of 10.13m, and a crossroad wire height of 6.43 m. The node difficulty lies in that the radius of a curve is small, residential areas are arranged on two sides of a road, and a large number of electric wires are arranged at intersections. Figure 4-d shows the ziggao mound with a side curve, curve radius 62.77m and road width 6.76 m. The joint difficulty is learned in temple piers on the outer side of a curve, the distance from the road is only 8.67m, and the joint difficulty is 6.56m in height when an electric wire crosses the road.
The four curves are simulated by using the constructed model, and the blades or the tower drum in the other curves except the curve 4 collide with the barrier, wherein the specific collision positions are listed in fig. 5.
As can be seen from FIG. 5-a, when the vehicle passes through the curve 1, the vehicle collides with the mountain outside the curve, and the collision shape is crescent, the maximum collision depth is 9m, and the collision area is 746.41m 2. When collision happens, the lifting angle of the blade is 20 degrees, and mainly the tail part of the fan blade is swept to a slope. As shown in fig. 5-b, the transport vehicle collides with the electric wire. The main reasons are the small turning radius and the large blade length, and the house outside the curve. The cost of dismantling the house is much higher than the cost of temporarily removing the wires, according to principles of reducing collision losses. Therefore, the fan transport vehicle lifts the blades by 20 degrees when the fan transport vehicle is bent over so as to ensure that the fan transport vehicle does not collide with a house, but the overall height of the fan transport vehicle is changed after the blades are lifted, so that the fan transport vehicle collides with an electric wire. As shown in fig. 5-c, the impact location occurs at the intersection wire. The main reason is that the blades are long, the vehicle can collide with a telegraph pole on the outer side of a bend when turning, and the blades are lifted by a certain angle. Measures are taken to temporarily remove the wires to ensure that the blade transport vehicle passes through smoothly. As can be seen in fig. 5-d, the tower truck collides with the outside pole. The main reason is that the turning radius of the intersection is only 10.13m, the total length of the tower car is 21m, and the tail of the tower car collides with the telegraph pole when the tower car turns. When the tower drum vehicle passes a bend, the telegraph pole at the outer side of the bend needs to be dismantled, and the tower drum transport vehicle can be ensured to pass through the intersection.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. A method for carrying out numerical collision experiment simulation aiming at wind power equipment transportation is characterized by comprising the following steps: a numerical simulation program is provided by combining the actual driving posture of the engineering vehicle. Importing the fan component, the transport vehicle and the actual three-dimensional terrain parameters into a Java platform through semantic description, and performing collision test simulation with the three-dimensional terrain according to the actual vehicle running track and the blade tower drum rotation rule to obtain an accurate collision position and a collision volume, wherein the method mainly comprises the following steps:
step 1: the method comprises the steps of collecting terrain and road data through an unmanned aerial vehicle, and then extracting point cloud boundaries in point cloud data. For the output regular road surface point cloud data omega { P (X, y, z) } with the distance d, collecting X coordinates of all the point cloud data to generate a set X ═ X { (X)1,x2,…,xnD is used as precision discrete [ min X, max X }]Generating a set of rules
Figure FDA0003464431890000011
Step 2: for the
Figure FDA0003464431890000012
Can generate and
Figure FDA0003464431890000013
corresponding and ordered set of y coordinates
Figure FDA0003464431890000014
Then point is reached
Figure FDA0003464431890000015
I.e. corresponding to XRSet of boundary points TXThe point in { P (x, y, z) },
Figure FDA0003464431890000016
is prepared by reacting with
Figure FDA0003464431890000017
Corresponding to the coordinate of z. According to the same rule, a correspondence can be generatedySet of boundary points T of coordinatesY{ P (x, y, z) }. Set of boundary points TX、TYThere may be identical points, removing identical points and merging may generate a set of boundary points T, i.e. T ═ TX∪TY。
And step 3: and combining a finite element and vector analysis method to convert the fan transportation device into data.
And 4, step 4: method for constructing fan blade motion trail model R through given parameters1。
And 5: collecting site information from site, and constructing undetermined collision matrix R2The simulated collisions are coupled to determine a collision matrix V.
Step 6: integration into airborne LIDAR via relative difference modelsSite information of data, aerial images and observation information, optimization of parameter d, construction of attraction domain V of matrix V1And repulsive domain V2. The coordinates of the obstacle points in the range of the attraction domain of the blade motion trail are summarized in a matrix H, the point coordinates in the matrix are compared with the coordinates of each corresponding blade track point, and if the track point Z is located1Value less than Z at a point in the matrix2And (4) extracting points in the matrix, and summarizing all the points extracted in the whole motion stage into a collision point matrix D.
And 7: and (4) solving collision point boundaries, namely solving a boundary matrix D' of collision points in the whole stage by using a formula for solving road boundary points and the principle thereof through the obtained collision point matrix D in the whole motion stage process of the blade.
And 8: the collision point area calculation adopts the three-dimensional application of Riemann-Steuerjess integration. A collision partition U 'of the boundary matrix D' refers to a finite number of collision surface bins, each called a sub-collision surface. D is defined as the discrete precision of these sub-impact areas. The sampling division, one sampling division of the boundary matrix D', means that after division, a point h is taken out in each sub-collision surface. Obtaining U '═ U'h)，u′hThe non-normalized corresponding collision point area.
And step 9: normalizing the h-point sub-collision surface to obtain the final normalized corresponding collision total area U ═ U (U)h)。
2. The method for numerical collision experimental simulation for wind power equipment transportation according to claim 1, characterized in that: set X in said step 1RSatisfy the requirement of
Figure FDA0003464431890000021
3. The method for numerical collision experimental simulation for wind power equipment transportation according to claim 2, characterized in that: coordinates of points on the road boundary in the step 2Set of yBThe following rules are met:
Figure FDA0003464431890000031
the collection
Figure FDA0003464431890000032
Satisfy the requirement of
Figure FDA0003464431890000033
4. The method for numerical collision experimental simulation for wind power equipment transportation according to claim 1, characterized in that: and the fan transportation device in the step 3 comprises a tractor, a wagon box with a steering function and a fan blade.
5. The method for numerical collision experimental simulation for wind power equipment transportation according to claim 1, characterized in that: in the step 3, the datamation of the fan transporting device is specifically realized by matrixing the motion track of the fan transporting device:
R＝{(xi1,yi1,zi1),(xi2,yi2,zi2)…(xim,yim,zim)}
in the formula, m is 1, 2, … i is 1, 2, …, R is a motion trajectory matrix, i is the number of stages, and m is a control point number.
6. The method for numerical collision experimental simulation for wind power equipment transportation according to claim 1, characterized in that: the relative difference model in step 6 is defined as: integrating on-site information of airborne LIDAR data, aerial images and observation information, optimizing parameter d, and constructing attraction domain V of matrix V1And repulsive domain V2Wherein d is1＝|xM-x|,d2＝|yM-y |, setting the motion track of the fan bladePoint M, obstacle points such as a, b, etc., summarizing the point coordinates of the obstacle in the attraction domain range of the motion track point of the blade in a matrix H, comparing the point coordinates in the matrix with the coordinates of the corresponding track point of the blade, and if the track point Z is in the attraction domain range of the motion track point of the blade, comparing the point coordinates in the matrix with the coordinates of the corresponding track point of the blade1Value less than Z at a point in the matrix2And (4) extracting points in the matrix, and summarizing all the points extracted in the whole motion stage into a collision point matrix D.
7. The method for numerical collision experimental simulation for wind power equipment transportation according to claim 1, characterized in that: u 'in the step 8'hSatisfies the formula:
Figure FDA0003464431890000041
8. the method for numerical collision experimental simulation for wind power equipment transportation according to claim 1, characterized in that: said step 9 satisfies uhSatisfies the formula:
Figure FDA0003464431890000042
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