CN112945198B - Automatic detection method for inclination of power transmission line iron tower based on laser LIDAR point cloud - Google Patents
Automatic detection method for inclination of power transmission line iron tower based on laser LIDAR point cloud Download PDFInfo
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Abstract
The invention discloses a power transmission line iron tower inclination automatic detection method based on laser LIDAR point clouds, which determines the center point of the minimum external rectangle of each layer of point clouds of an iron tower body as a central axis point by considering the structural characteristics that each layer of the iron tower body is projected on a level surface into a standard rectangle, and determines the inclination of the iron tower by performing space straight line fitting on the central axis of the iron tower through a plurality of layers of central axis points. The automatic extraction of the tower body is realized through the area and the proportion change of the minimum external rectangle, the applicability of the method under the conditions of noise and defects of the point cloud of the tower body is realized by utilizing the elevation inspection and the robust estimation of the rectangle internal tangent point, and the automation degree and the robustness of the inclination detection algorithm of the transmission line iron tower of the LiDAR point cloud are improved.
Description
Technical Field
The invention relates to the technical field of power equipment monitoring, in particular to a power transmission line iron tower inclination automatic detection method based on laser LIDAR point cloud.
Background
With the continuous deepening of the application of the airborne laser LiDAR technology in the operation and maintenance of the power grid, the power grid forms a periodic laser inspection working mode, and the point cloud data of the iron tower also becomes the stock data of the operation and maintenance of the power grid. Meanwhile, the airborne laser LiDAR technology has the characteristics of convenience and quickness in operation and high measurement precision, and becomes a new means for detecting the inclination of the power transmission line iron tower, which is safer, more convenient and more economical. The existing method for detecting the inclination of the iron tower by utilizing LiDAR point cloud data has two problems in general, namely 1) the tower body part with a symmetrical structure cannot be automatically extracted, and the influence of asymmetrical structures such as high and low legs, tower heads and the like on the inclination estimation of the iron tower is filtered; 2) The method for extracting the axis point in the tower body lacks necessary checking conditions, and has lower adaptability in the conditions of noise and defects of the point cloud of the tower body.
Disclosure of Invention
In view of the above, the present invention provides a method for detecting inclination of a LiDAR point cloud power transmission line iron tower based on a layered minimum circumscribed rectangle and robust estimation in consideration of structural features that each layer of an iron tower body is projected on a level surface to form a standard rectangle, wherein a central point of the minimum circumscribed rectangle of each layer of the point cloud of the iron tower body is determined as a central axis point, and spatial straight line fitting is performed through multiple layers of central axis points to determine inclination of the iron tower. The automatic extraction of the tower body is realized through the area and the proportional change of the minimum external rectangle, the applicability of the method under the conditions of noise and defects of the point cloud of the tower body is realized by utilizing the elevation inspection and the tolerance estimation of the rectangular vertex, and the automation degree and the robustness of the inclination detection algorithm of the iron tower of the LiDAR point cloud power transmission line are improved.
The purpose of the invention is realized by the following technical scheme:
the invention discloses a power transmission line iron tower inclination automatic detection method based on laser LIDAR point cloud, which comprises the following steps:
step S1: layering the point clouds of the iron towers: extracting lowest point elevation value h of iron tower point cloud min Dividing the iron tower point cloud into a plurality of layers along the elevation direction according to the step length k to obtain a layered point cloud set { phi [ ] 1 ,Φ 2 ,…,Φ n }；
Step S2: calculating a minimum bounding rectangle: cloud of layered points phi i Projecting the image to an xOy plane, and solving the minimum circumscribed rectangle R of the projected plane point set i With vertex (P) i 1 ,P i 2 ,P i 3 ,P i 4 ) The length and width areas are respectively L i ，W i ，S i ；
And step S3: extracting the tower body point cloud: filtering layered point clouds of high and low legs and a tower head by utilizing the characteristics that a tower body point cloud external rectangle is approximately in square distribution and the area is gradually reduced from bottom to top;
and step S4: detecting the inclination of the circumscribed rectangle: calculating inner contact points of each side of the minimum external rectangle in the layer and the layer point set, and filtering the inclination condition of the external rectangle caused by defects and noise points of the iron tower point cloud by utilizing the elevation test of the inner contact points, wherein the middle point of the rectangle possibly deviates from the center axis of the iron tower when the rectangle inclines;
step S5: and determining the shaft point in the tower. Taking the average elevation value of the inscribed points on the four sides as the central point of the circumscribed rectangle through the steps
Adding the central point into a shaft point set Pset of the tower;
step S6: fitting a robust estimation straight line: the robust estimation is applied to the fitting of the central axis of the iron tower, and the fitting weight of each central axis point is adaptively adjusted in a weight selection iteration mode, so that the purpose of reducing the influence degree of offset points in straight line fitting is achieved;
step S7: and calculating the inclination of the iron tower.
Further, in step S3, let i ← 1, perform layered point cloud Φ i Tower bodyChecking, and judging the formula as follows:
S last the area of the rectangle circumscribed by the upper layer of point cloud; if point cloud phi i According to the formula (1), phi i Adding to a tower layered point cloud set
In the middle, let S last ＝S i Otherwise, will phi i And 3) filtering the high and low leg and tower head point clouds, enabling i ← i +1, and repeating the step 3) until i is less than n.
5. Further, in the step S4, when the minimum inscribed point of the circumscribed rectangle is a noise point or is severely deviated due to a defect, the circumscribed rectangle is inclined, and at this time, the midpoint of the rectangle may be deviated from the central axis of the iron tower, so that before the central axis point of the iron tower is determined, the elevation of the inscribed point of the rectangle needs to be judged, and the inclination of the rectangle needs to be filtered. Let i ← 1 circumscribe four vertices of a rectangle with layering
Constructing a rectangular four-side plane linear equation and traversing a point set
And calculating the plane distances from each point in the point set to the four side lines of the rectangle, and selecting the point with the minimum distance from the plane distance of the side line as an inscribed point of the side line. And when the maximum distance difference between the points in the four sides is less than k/4, regarding the rectangle as being parallel to the xOy plane, performing step S5 to determine the shaft point in the tower, and otherwise, enabling i ← i +1, and repeating the step 4) until i is less than m.
Further, in step S6, regarding x and y as independent observed values, and constructing a linear equation with the independent variable z, respectively, so that the spatial linear equation of the central axis of the iron tower is as follows:
in the formula, a 1 、a 2 ，b 1 、b 2 Respectively are projection straight line parameters of the central axis of the iron tower on an xOz plane and a yOz plane; set the center axis point set of the iron tower as
Then the least squares coefficient matrix, weight matrix, and residual matrix are as follows:
in the formula (I), the compound is shown in the specification,
let the parameter array be X 4×1 ＝[a 1 a 2 b 1 b 2 ] T Then, the axis fitting parametric equation is:
v 2k×1 ＝B 2k×4 X 4×1 -L 2k×1 (4)
solution at V based on least square principle T The optimal solution under the condition of PV = min, however, when offset points exist in the axis point set Pset of the iron tower, the least square estimation result is influenced by the offset points to deviate from the true value, and the robust estimation calculates the residual value v after the least square estimation 2k×1 Performing error detection, and iteratively adjusting the weight of the outlier offset point until the adjustment result is converged; and (3) carrying out weight adjustment by using an IGG III function, wherein the weight formula is as follows:
in the formula, j is a residual value subscript, and the value range is (0, 2k); k 0 ,K 1 Is a constant;
is v i The corresponding normalized residual error is then calculated,
is v is i Corresponding medium error.
Further, the concrete flow of the fitting robust estimation of the central axis of the iron tower is as follows:
(a) Constructing a coefficient array B, a weight array P and a residual error array L according to a formula (3) based on the iron tower middle axis point set Pset;
(b) Let iteration number i ← 1, calculate parameter estimation matrix and residual matrix according to minimum quadratic fit as formula (6):
X(i)＝(B T PB) -1 B T PL,v(i)＝BX(i)-L (6)
(c) The error in calculating the unit weight and the residual error is as shown in formula (7), where r is the degree of freedom:
(c) Computing a weight matrix [ omega ] by IGG III function 1 ω 2 … ω 2k ]Adjusting the weight matrix P [ j, j]←P[j,j]ω j ；
(d) Step i ← i +1, repeat step b), recalculate matrices X (i), v (i);
(e) Repeating the steps (b) to (d) until an iteration conditional expression (8) is satisfied, ending the fitting process, wherein X (i) is a fitting result;
||X(i)-X(i-1)||＜ε (8)
ε is the threshold constant.
Further, the epsilon is taken to be 10 -4 。
Further, in the step S7, the tilt values of the iron tower in the xOz plane and the yOz plane are a respectively 1 ＝X(i)[1]、b 1 ＝X(i)[3]Actual value of tilt
Further, said S last Initial value 1000m 2 ；
Further, in step S1, the value of the step k is 1m.
The beneficial effects of the invention are:
1. the deviation phenomenon of the middle point of the rectangle and the actual center axis point of the iron tower is caused by the area and the proportion change of the minimum external rectangle of each layer of point cloud, the tower head and the high and low legs is filtered, the automatic extraction of the point cloud of the tower body is realized, the manual participation is reduced, and the automation degree of the algorithm is improved;
2. and (3) performing height difference inspection by using the minimum circumscribed rectangle inscribed point elevation value, and setting an inspection condition to filter most of rectangle inclination conditions caused by defects and noise points of point cloud, so that a large proportion of correct central axis points are provided for subsequent straight line fitting, and the rough tolerance resistance of the algorithm is enhanced.
3. And introducing robust estimation in spatial straight line fitting, and inhibiting the influence of the phenomenon that the midpoint of a layered rectangle deviates from the center axis point of the iron tower due to the defects and noise points of the tower body point cloud on the spatial straight line fitting by a way of reducing outlier weight through weight selection iteration, thereby improving the robustness of the whole algorithm.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the present invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of the method steps of the present invention.
Detailed Description
Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the preferred embodiments are illustrative of the invention only and are not limiting upon the scope of the invention.
As shown in the figure, the method for automatically detecting the inclination of the power transmission line iron tower based on the laser LIDAR point cloud comprises the following steps:
step S1: layering the point clouds of the iron towers: extracting lowest point elevation value h of iron tower point cloud min Dividing the iron tower point cloud into a plurality of layers along the elevation direction according to the step length k =1m to obtain a layered point cloud set { phi [ ] 1 ,Φ 2 ,…,Φ n }；
Step S2: calculating a minimum bounding rectangle: the layered point cloud phi i Projecting the image to an xOy plane, and solving the minimum circumscribed rectangle R of the projected plane point set i With vertex (P) i 1 ,P i 2 ,P i 3 ,P i 4 ) The length and width areas are respectively L i ，W i ，S i ；
And step S3: extracting the tower body point cloud: filtering layered point clouds of high and low legs and a tower head by utilizing the characteristics that a tower body point cloud external rectangle is approximately in square distribution and the area is gradually reduced from bottom to top; let i ← 1, carry out layered point cloud Φ i And (4) testing the tower body, wherein a judgment formula is as follows:
S last the area of the rectangle circumscribed by the previous layer of point cloud, in this embodiment, the S last Initial value of 1000m 2 (ii) a If point cloud phi i In accordance with the formula (1), phi i Adding to a tower layered point cloud set
In the middle, let S last ＝S i Otherwise, will phi i And (3) filtering the cloud of high and low legs and the tower head point, enabling i ← i +1, and repeating the step 3) until i is less than n.
And step S4: and detecting the inclination of the circumscribed rectangle. Because the tower body of the tower is a quadrangular frustum pyramid with a large lower part and a small upper part, when noise points and the influence of the defect conditions do not exist, the planes of the layered minimum external rectangle and the four internal tangent points of the layered point cloud are parallel to the xOz plane. When the inner tangent point of the minimum circumscribed rectangle is a noise point or is seriously deviated due to defects, the circumscribed rectangle is inclined, and the middle point of the rectangle possibly deviates from the central axis of the tower.
Therefore, before the axis point of the iron tower is determined, the elevation of the rectangular inscribed point needs to be judged, and the condition of the inclination of the rectangle needs to be filtered. Let i ← 1 circumscribe four vertices of a rectangle with layering
Constructing a rectangular four-side plane linear equation and traversing a point set
And calculating the plane distance from each point in the point set to the four rectangular sidelines, and selecting the point with the minimum distance from the sideline plane as the inscribed point of the sideline. And when the maximum distance difference between the points in the four sides is less than k/4, regarding the rectangle as being parallel to the xOz plane, performing step 5) to determine the shaft point in the tower, and otherwise, enabling i ← i +1, and repeating the step 4) until i is less than m.
Step S6: in the above steps, although the rectangular inclination caused by the defects and the noise points is filtered in the process of extracting the shaft point in the tower, the situation that the center of the minimum circumscribed rectangle deviates caused by all the noise points and the defects cannot be avoided. Therefore, the method applies the robust estimation to the fitting of the central axis of the tower, and adaptively adjusts the fitting weight of each central axis point in a weight selection iteration mode so as to achieve the purpose of reducing the influence degree of the offset point in the straight line fitting.
Specifically, x and y are regarded as mutually independent observed values, and a linear equation is respectively constructed with an independent variable z, so that the spatial linear equation of the central axis of the iron tower is as follows:
in the formula, a 1 、a 2 ，b 1 、b 2 Respectively are projection straight line parameters of the central axis of the iron tower on an xOz plane and a yOz plane; set the center axis point set of the iron tower as
Constructing a least square coefficient array, a weight array and a residual error array as follows:
in the formula (I), the compound is shown in the specification,
let the parameter array be X 4×1 ＝[a 1 a 2 b 1 b 2 ] T Then the axis fitting parametric equation is:
v 2k×1 ＝B 2k×4 X 4×1 -L 2k×1 (4)
the above process for fitting equation establishment is solved at V by the least square principle T The optimal solution under the condition of PV = min, however, when offset points exist in the axis point set Pset of the iron tower, the least square estimation result is influenced by the offset points to deviate from the true value, and the robust estimation calculates the residual value v after the least square estimation 2k×1 Error detection is carried out, iterative adjustment is carried out on the weight of the outlier deviation point, and the correctness of the tower inclination detection result can be ensured as far as possible under the condition that noise and defects exist in the point cloud.
The weight adjustment is performed by using iggiii function (i.e. robust iterative weight adjustment function), and the formula of the weight is as follows:
in the formula, j is a residual value subscript, and the value range is (0, 2k); k 0 ,K 1 Is constant and takes a value of 1.5,2.5;
is v is j The corresponding normalized residual error is then calculated,
is v is j Corresponding to a medium error.
The specific algorithm flow is as follows:
(a) Constructing a coefficient array B, a weight array P and a residual error array L according to a formula (3) based on the iron tower middle axis point set Pset;
(b) Let iteration number i ← 1, calculate parameter estimation matrix and residual matrix according to minimum quadratic fit as formula (6):
X(i)＝(B T PB) -1 B T PL,v(i)＝BX(i)-L (6)
(c) The error in calculating the unit weight and the residual error is shown as formula (7), where r is the degree of freedom:
(c) Computing a weight matrix [ omega ] by IGG III function 1 ω 2 … ω 2k ]Adjusting the weight matrix P [ j, j]←P[j,j]ω j ；
(d) Step i ← i +1, repeat step b), recalculate matrices X (i), v (i);
(e) Repeating the steps (b) to (d) until an iteration conditional expression (8) is satisfied, ending the fitting process, wherein X (i) is a fitting result;
||X(i)-X(i-1)||＜ε (8)
ε is the threshold constant, in this example, ε is taken to be 10 -4 。
Step S7: and calculating the inclination of the iron tower. The inclination values of the iron tower on the xOz plane and the yOz plane are respectively a 1 ＝X(i)[1]、b 1 ＝X(i)[3]Actual value of tilt
It should be recognized that embodiments of the present invention can be realized and implemented by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer-readable storage medium configured with the computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, according to the methods and figures described in the detailed description. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Further, the operations of processes described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) collectively executed on one or more processors, by hardware, or combinations thereof. The computer program includes a plurality of instructions executable by one or more processors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable connection, including but not limited to a personal computer, mini computer, mainframe, workstation, networked or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, or the like. Aspects of the invention may be embodied in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optically read and/or write storage medium, RAM, ROM, or the like, such that it may be read by a programmable computer, which when read by the storage medium or device, is operative to configure and operate the computer to perform the procedures described herein. Further, the machine-readable code, or portions thereof, may be transmitted over a wired or wireless network. The invention described herein includes these and other different types of non-transitory computer-readable storage media when such media include instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein.
A computer program can be applied to input data to perform the functions described herein to transform the input data to generate output data that is stored to non-volatile memory. The output information may also be applied to one or more output devices, such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including particular visual depictions of physical and tangible objects produced on a display.
Finally, the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all of them should be covered by the claims of the present invention.
Claims (8)
1. A power transmission line iron tower inclination automatic detection method based on laser LIDAR point cloud is characterized in that: the method comprises the following steps:
step S1: layering the point clouds of the iron towers: extracting lowest point elevation value h of iron tower point cloud min Dividing the iron tower point cloud into a plurality of layers along the elevation direction according to the step length k to obtain a layered point cloud set { phi [ ] 1 ,Φ 2 ,…,Φ n }；
Step S2: calculating the minimum circumscribed rectangle: the layered point cloud phi i Projecting the image to an xOy plane, and solving the minimum circumscribed rectangle R of the projected plane point set i With vertex (P) i 1 ,P i 2 ,P i 3 ,P i 4 ) The length and width areas are respectively L i ，W i ，S i ；
And step S3: extracting the tower body point cloud: filtering layered point clouds of high and low legs and a tower head by utilizing the characteristics that a tower body point cloud external rectangle is approximately in square distribution and the area is gradually reduced from bottom to top;
and step S4: detecting the inclination of the circumscribed rectangle: calculating inner contact points of each side of the minimum external rectangle in the layer and the layer point set, and filtering the inclination condition of the external rectangle caused by defects and noise points of the iron tower point cloud by utilizing the elevation test of the inner contact points, wherein the middle point of the rectangle possibly deviates from the center axis of the iron tower when the rectangle inclines; in the step S4, when the minimum inscribed point of the circumscribed rectangle is a noise point or is severely deviated due to a defect, the circumscribed rectangle is inclined, and at this time, the midpoint of the rectangle may deviate from the center axis of the iron tower, so that before the center axis point of the iron tower is determined, the elevation of the inscribed point of the rectangle needs to be judged, the inclination of the rectangle is filtered, and i ← 1 is performed by using four vertexes of the layered circumscribed rectangle
Constructing a rectangular four-side plane linear equation and traversing a point set
Calculating the plane distance from each point in the point set to the four rectangular edge lines, selecting a point with the minimum distance from the edge line plane as an inner tangent point of the edge line, when the maximum distance difference of the inner tangent points of the four edges is less than k/4, regarding the rectangle as being parallel to an xOy plane, performing step S5 to determine an axis point in the tower, and otherwise, enabling i ← i +1, and repeating the step S4 until i is less than m;
step S5: determining an axis point in the tower, and taking the average elevation value of the inscribed points on the four sides as the central point of the circumscribed rectangle
Adding the central point into a shaft point set Pset of the tower;
step S6: robust estimation line fitting: applying the robust estimation to the fitting of the central axis of the iron tower, and adaptively adjusting the fitting weight of each central axis point in a weight selection iteration mode to achieve the purpose of reducing the influence degree of the offset point in the straight line fitting;
step S7: and calculating the inclination of the iron tower.
2. The automatic detection method for the inclination of the power transmission line iron tower based on the laser LIDAR point cloud, according to claim 1, is characterized in that: in step S3, let i ← 1, perform layered point cloud Φ i The tower body is checked, and the judgment formula is as follows:
S last the area of the rectangle circumscribed by the upper layer of point cloud; if point cloud phi i According to the formula (1), phi i Adding to a tower layered point cloud set
In the middle, let S last ＝S i Otherwise, will phi i And (4) filtering the cloud of high and low legs and the tower head point, enabling i ← i +1, and repeating the step (S3) until i is less than n.
3. The method for automatically detecting the inclination of the power transmission line iron tower based on the laser LIDAR point cloud, according to claim 1, is characterized in that: in step S6, regarding x and y as independent observed values, and respectively constructing a linear equation with the independent variable z, where the linear equation of the space of the central axis of the iron tower is as follows:
in the formula, a 1 、a 2 ，b 1 、b 2 Respectively are projection straight line parameters of the central axis of the iron tower on an xOz plane and a yOz plane; set the center axis point set of the iron tower as
Then the least squares coefficient matrix, weight matrix, and residual matrix are as follows:
in the formula (I), the compound is shown in the specification,
let the parameter array be X 4×1 ＝[a 1 a 2 b 1 b 2 ] T Then, the axis fitting parametric equation is:
v 2k×1 ＝B 2k×4 X 4×1 -L 2k×1 (4)
solution at V based on least square principle T The optimal solution under the PV = min condition, however, when offset points exist in the iron tower axis point set Pset, the least square estimation result is influenced by the offset points to deviate from the true value, the robust estimation theory is introduced, and the residual value v after least square estimation is calculated 2k×1 Error detection is carried out, iterative adjustment is carried out on the weight of the outlier deviation point, and the correctness of the tower inclination detection result can be ensured as far as possible under the condition that noise and defects exist in the point cloud;
and (3) carrying out weight adjustment by using an IGG III function, wherein the weight factor formula is as follows:
in the formula, j is a residual value subscript, and the value range is (0, 2k); k 0 ,K 1 Is a constant;
is v is i The corresponding normalized residual error is then calculated,
is v i Corresponding medium error.
4. The automatic detection method for the inclination of the power transmission line iron tower based on the laser LIDAR point cloud, according to claim 3, characterized in that: the specific process of the fitting robust estimation of the central axis of the iron tower is as follows:
(a) Constructing a coefficient array B, a weight array P and a residual error array L according to a formula (3) based on the iron tower middle axis point set Pset;
(b) Let iteration number i ← 1, calculate parameter estimation matrix and residual matrix according to minimum quadratic fit as formula (6):
X(i)＝(B T PB) -1 B T PL,v(i)＝BX(i)-L (6)
(c) The error in calculating the unit weight and the residual error is shown as formula (7), where r is the degree of freedom:
(c) Computing a weight matrix [ omega ] by IGG III function 1 ω 2 …ω 2k ]Adjusting the weight matrix P [ j, j]←P[j,j]ω j ；
(d) Step (b) of repeating i ← i +1 to recalculate the matrices X (i), v (i);
(e) Repeating the steps (b) to (d) until an iteration conditional expression (8) is satisfied, ending the fitting process, wherein X (i) is a fitting result;
||X(i)-X(i-1)||＜ε (8)
ε is a threshold constant.
5. The automatic detection method for the inclination of the power transmission line iron tower based on the laser LIDAR point cloud, according to claim 4, is characterized in that: the epsilon is 10 -4 。
6. The method for automatically detecting the inclination of the power transmission line iron tower based on the laser LIDAR point cloud, according to claim 1, is characterized in that: in the step S7, the tilt values of the iron tower on the xOz plane and the yOz plane are a 1 ＝X(i)[1]、b 1 ＝X(i)[3]Actual value of tilt
7. The method for automatically detecting the inclination of the power transmission line iron tower based on the laser LIDAR point cloud, according to claim 2, is characterized in that: said S last Initial value of 1000m 2 。
8. The method for automatically detecting the inclination of the power transmission line iron tower based on the laser LIDAR point cloud, according to claim 1, is characterized in that: in step S1, the value of the step length k is 1m.
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