阅读说明：本技术 基于无人机激光雷达点云杆塔倾斜参数测量方法及系统 (Method and system for measuring point cloud tower inclination parameters based on unmanned aerial vehicle laser radar ) 是由 芦竹茂 龚浩 邓鹤鸣 杨虹 胡晓岑 杨罡 吴驰 阴崇智 胡庆武 李加元 连建华 于 2020-12-23 设计创作，主要内容包括：本发明公开了一种基于无人机激光雷达点云杆塔倾斜参数测量方法,包括如下步骤：杆塔三维点云滤波,杆塔分割与特征面提取,塔身三维重建及模型数据库建立,对待评估杆塔特征平面进行中心点计算,对待评估杆塔进行倾斜状态评估与倾斜角度计算。本发明实现对杆塔结构关键部位的自动识别及提取以及对线路杆塔的几何参数快速扫描与倾斜参数智能化评估。利用先进的无人机巡线技术,显著提升了线路巡检效率和准确度,降低了巡检费用以及工作人员的工作量和风险,实现具有工程实践意义上的杆塔倾斜地质监测预警和风险防控,提高线路运行可靠性,降低重大电网安全稳定运行风险。(The invention discloses a method for measuring a point cloud tower inclination parameter based on an unmanned aerial vehicle laser radar, which comprises the following steps: the method comprises the steps of pole tower three-dimensional point cloud filtering, pole tower segmentation and characteristic surface extraction, pole tower body three-dimensional reconstruction and model database establishment, center point calculation of a pole tower characteristic plane to be evaluated, and inclination state evaluation and inclination angle calculation of a pole tower to be evaluated. The invention realizes automatic identification and extraction of key parts of the tower structure, and quick scanning of geometric parameters and intelligent evaluation of tilt parameters of the tower. Utilize advance unmanned aerial vehicle to patrol the line technique, show and promoted circuit efficiency and the degree of accuracy of patrolling and examining, reduced the work load and the risk of patrolling and examining expense and staff, the realization has shaft tower slope geology monitoring early warning and risk prevention and control on the engineering practice meaning, improves circuit operational reliability, reduces great electric wire netting safety and stability operation risk.)

1. A point cloud tower inclination parameter measuring method based on an unmanned aerial vehicle laser radar is characterized by comprising the following steps:

step 1: selecting single tower pole point clouds in the three-dimensional laser point cloud of the transmission tower, and removing miscellaneous points and wire point clouds in the single tower pole point clouds to obtain filtered tower pole point clouds;

step 2: dividing the filtered tower point cloud into a tower foot point cloud, a tower body point cloud and a tower head point cloud so as to obtain a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model;

and step 3: combining a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model into a typical tower type three-dimensional point cloud model;

and 4, step 4: according to the typical tower type three-dimensional point cloud model, performing center point calculation on a tower characteristic plane to be evaluated to obtain the coordinates of the center point of each characteristic plane of the tower to be evaluated;

and 5: and calculating the inclination angle of the tower to be evaluated according to the coordinates of the central point of each characteristic plane of the tower to be evaluated.

2. The method for measuring the inclination parameters of the point cloud tower based on the unmanned aerial vehicle laser radar according to claim 1, wherein the method comprises the following steps: in the step 2, the tower foot elevation, the tower body elevation, the tower shoulder elevation and the tower head elevation are utilized to divide the filtered tower point cloud into a tower foot point cloud, a tower body point cloud and a tower head point cloud, so that a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model are obtained.

3. The method for measuring the inclination parameters of the point cloud tower based on the unmanned aerial vehicle laser radar according to claim 1, wherein the method comprises the following steps: in the step 2, an elevation histogram of the tower point cloud is generated, local extreme values in the histogram are extracted, extreme values of non-characteristic elevations are eliminated, characteristic elevations in the tower point cloud and characteristic planes corresponding to the characteristic elevations are obtained, tower shoulder elevations at the joint of the tower head and the tower body are extracted by judging the number of points included in the characteristic plane point cloud corresponding to each characteristic elevation, the tower head and the tower body are segmented, and the filtered tower point cloud is divided into tower foot point cloud, tower body point cloud and tower head point cloud by utilizing the segmentation mode of the tower head and the tower body.

4. The method for measuring the inclination parameters of the point cloud tower based on the unmanned aerial vehicle laser radar according to claim 1, wherein the method comprises the following steps: and in the step 3, inputting the typical tower-shaped three-dimensional point cloud model into a typical tower-shaped three-dimensional point cloud model database.

5. The method for measuring the inclination parameters of the point cloud tower based on the unmanned aerial vehicle laser radar according to claim 1, wherein the method comprises the following steps: in the step 4, according to the typical tower type three-dimensional point cloud model, the center point of the tower feature plane to be evaluated is calculated, and the specific method for obtaining the coordinates of the center point of each feature plane of the tower to be evaluated is as follows:

the method comprises the steps of calculating the center point of a tower feature plane to be evaluated, selecting a tower area to be subjected to inclination evaluation, matching a tower head three-dimensional vector model in a typical tower type three-dimensional point cloud model database with a tower to be evaluated so as to determine the tower type of the tower, performing ICP (inductively coupled plasma) matching on the tower to be evaluated by using the corresponding tower type feature plane, obtaining a rotation and translation matrix of each feature plane of the tower to be evaluated, and obtaining the coordinates of the center point of each feature plane of the tower to be evaluated through corresponding rotation and translation transformation of the center point of the tower type feature plane corresponding to the tower type in the typical tower type three-dimensional point cloud model database.

6. The method for measuring the inclination parameters of the point cloud tower based on the unmanned aerial vehicle laser radar according to claim 1, wherein the method comprises the following steps: in the step 2, reconstructing the tower head point cloud by combining an SVM classification method and a tower head model library to obtain a tower head three-dimensional vector model; and reconstructing the tower body point cloud in a plane fitting mode to obtain a tower head three-dimensional vector model, and reconstructing the tower foot point cloud in a manual interaction mode to obtain a tower foot three-dimensional vector model.

7. The method for measuring the inclination parameters of the point cloud tower based on the unmanned aerial vehicle laser radar according to claim 1, wherein the method comprises the following steps: in the step 5, the inclination parameters of the whole tower, the tower head and the tower body are calculated according to the following strategies, so that the inclination state of the tower is evaluated: connecting the central points of the characteristic planes of the tower to be evaluated in sequence to form a tower central line, calculating the included angle between each section of central line and the theoretical tower central line, if the included angle between part of central line segments and the theoretical central line is greater than a threshold value, judging that the tower is inclined, wherein the inclined position is between the two characteristic planes where the central line segments are located, and the inclined angle is the calculated included angle.

8. The method for measuring the inclination parameters of the point cloud tower based on the unmanned aerial vehicle laser radar according to claim 1, wherein the method comprises the following steps: in the step 1, the method for removing the miscellaneous points and the electric wire point clouds in the framed single tower pole point clouds comprises the following steps: the method comprises the steps of eliminating miscellaneous points at the bottom of a tower by setting an elevation threshold value, extracting the outline of the tower from the lowest characteristic plane when extracting the outline of the tower by using an Alpha Shapes algorithm for power line points in the tower elevation, obtaining the minimum outline in the extracted outlines, limiting the range of the point cloud of the next characteristic plane to be processed by using the extracted minimum outline, ensuring that the processing of the point cloud extraction outline of the next characteristic plane does not exceed the minimum outline, and eliminating the power line points by calculating the distance between the point cloud and the center of the tower.

9. The method for measuring the inclination parameters of the point cloud tower based on the unmanned aerial vehicle laser radar according to claim 8, wherein the method comprises the following steps: the concrete method for combining the tower foot three-dimensional vector model, the tower body three-dimensional vector model and the tower head three-dimensional vector model into the typical tower type three-dimensional point cloud model in the step 3 comprises the following steps:

determining the direction pointed by the tower tip of the tower by extracting the outer contour line of the characteristic plane of the tower body, and determining the position of the tower by calculating the circumscribed circle of the outer contour of the characteristic plane of the tower body;

classifying the outer contour of the tower body extracted by the Alpha Shapes algorithm according to the direction pointed by the tower shoulder of the tower to obtain point clouds on four circumferential side surfaces of the tower body, and performing quadrangular frustum fitting on the tower body by using the point clouds on the four circumferential side surfaces of the tower body to obtain a geometric model of the four circumferential side surfaces of the tower body;

solving intersection lines of geometric models of four circumferential sides of the tower body to obtain a frame of the tower body, extracting mode characteristics from the point cloud of the tower head, judging the type of the tower head through a mode identification method, then performing one-dimensional projection and seed point growth on the point cloud on the tower head characteristic elevation to obtain characteristic length, wherein the characteristic length comprises tower diaphragm span and tower diaphragm frame actual length, taking the characteristic length, the difference between the maximum value and the second maximum value in the tower diaphragm span and the difference between the maximum value and the second maximum value in the tower diaphragm frame actual length as the mode characteristics of the tower, and combining the tower head and the three-dimensional model of the corresponding tower body to obtain the tower type three-dimensional model.

10. A system for measuring the inclination parameters of a point cloud tower based on an unmanned aerial vehicle laser radar is characterized by comprising a point cloud filtering module (1), a three-dimensional vector model generating module (2), a three-dimensional point cloud model generating module (3), a center calculating module (4) of each characteristic plane of the tower to be evaluated and an inclination state evaluating module (5);

the point cloud filtering module (1) is used for selecting single tower pole point cloud in the three-dimensional laser point cloud of the transmission tower, eliminating miscellaneous points and wire point cloud in the single tower pole point cloud, and obtaining the filtered tower pole point cloud;

the three-dimensional vector model generation module (2) is used for dividing the filtered tower point cloud into a tower foot point cloud, a tower body point cloud and a tower head point cloud so as to obtain a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model;

the three-dimensional point cloud model generation module (3) is used for combining a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model into a typical tower-shaped three-dimensional point cloud model;

the center calculation module (4) of each characteristic plane of the tower to be evaluated is used for calculating the center point of the characteristic plane of the tower to be evaluated according to the typical tower type three-dimensional point cloud model to obtain the coordinates of the center point of each characteristic plane of the tower to be evaluated;

the inclination state evaluation module (5) is used for calculating the inclination angle of the tower to be evaluated according to the coordinates of the central point of each characteristic plane of the tower to be evaluated.

Technical Field

The invention relates to the technical field of laser point cloud monitoring and early warning and risk prevention and control, in particular to a method and a system for measuring a point cloud tower inclination parameter based on an unmanned aerial vehicle laser radar.

Background

The transmission line has wide coverage range and long transmission distance, passes through a plurality of regions with severe environmental conditions, complex geological topography and changeable climate along the way, such as provinces with complex geological conditions of Shanxi, Shaanxi, Sichuan, Xinjiang and the like, has more types of geological disasters and larger distribution area, and the running state of the transmission tower per se becomes the focus of attention of line operation and maintenance work. The traditional overhead transmission line disaster prevention faces several problems: the prevention and treatment workload is large, the prevention requirement is high, the prevention and treatment cost is high, and the like. By utilizing remote sensing monitoring based on SAR (Synthetic Aperture Radar) satellites, the advantages of wide monitoring range, large area and the like are achieved, but the requirements on the sampling period and the image resolution of a remote sensing image are high, the data acquisition cost is huge, the data processing is complex, and the comprehensive popularization is difficult. Due to the lack of efficient monitoring means, the risk state of the power transmission line pole tower inclined geological disaster is difficult to grasp in time, the risk and the pressure of operation and maintenance work are large, when the risk development is accumulated to a certain degree, the difficulty of large-scale treatment on scattered risk points is increased, and the cost investment is huge. Therefore, a practical technology capable of rapidly monitoring and early warning the inclination state of the tower in the geological unstable area in a large range is urgently needed.

Disclosure of Invention

The invention aims to provide a method and a system for measuring the point cloud tower inclination parameters based on an unmanned aerial vehicle laser radar.

In order to achieve the purpose, the invention discloses a method for measuring the inclination parameters of a point cloud tower based on an unmanned aerial vehicle laser radar, which comprises the following steps:

step 1: selecting single tower pole point clouds in the three-dimensional laser point cloud of the transmission tower, and removing miscellaneous points and wire point clouds in the single tower pole point clouds to obtain filtered tower pole point clouds;

step 2: dividing the filtered tower point cloud into a tower foot point cloud, a tower body point cloud and a tower head point cloud so as to obtain a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model;

and step 3: combining a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model into a typical tower type three-dimensional point cloud model;

and 4, step 4: according to the typical tower type three-dimensional point cloud model, performing center point calculation on a tower characteristic plane to be evaluated to obtain the coordinates of the center point of each characteristic plane of the tower to be evaluated;

and 5: and calculating the inclination angle of the tower to be evaluated according to the coordinates of the central point of each characteristic plane of the tower to be evaluated.

The invention has the beneficial effects that:

according to the invention, corridor division, filtering and classification are carried out on the collected three-dimensional laser radar data, tower extraction and identification are carried out according to structural characteristics, a tower accurate three-dimensional model is established, tower inclination state parameters are automatically calculated and evaluated and analyzed, and a tower inclination angle is automatically calculated, so that intelligent detection and early warning of the inclination state of the line tower are realized.

The invention realizes automatic identification and extraction of the key parts of the tower structure by using the scheme, and realizes the quick scanning of the geometric parameters of the line tower and the intelligent evaluation of the inclination parameters.

According to the invention, a three-dimensional laser radar remote sensing technology is adopted, and an unmanned aerial vehicle high-precision positioning and attitude determination technology, a remote sensing and remote measuring technology and a three-dimensional laser point cloud intelligent processing and analyzing technology are combined, so that the rapid and batch intelligent sensing level of the geometric state of the power transmission line tower is obviously improved, the tower inclination geological monitoring and early warning and risk prevention and control in the engineering practice sense are realized, the line operation reliability is improved, the major power grid safe and stable operation risk is reduced, and the operation reliability of the power transmission line is improved. The method has wide application prospect in the fields of line maintenance, public management, disaster prevention and early warning and the like.

Drawings

FIG. 1 is a schematic structural view of the present invention;

FIG. 2 is an elevation histogram of a tower point cloud in an embodiment of the present invention;

FIG. 3 is a schematic diagram illustrating elevation of features corresponding to local extrema extracted from a histogram in an exemplary embodiment of the invention;

FIG. 4 is a schematic diagram of a pyramid fitting of a tower body in an embodiment of the present invention;

FIG. 5 is a three-dimensional model of a tower mast of certain configurations in accordance with embodiments of the present invention;

FIG. 6 is a schematic view of a point cloud projection based on a three-view feature extraction algorithm in the present invention;

FIG. 7 is a one-dimensional projection line segment connection diagram based on a three-view feature extraction algorithm in the present invention;

FIG. 8 is a schematic diagram of a technique for removing fine line segments based on a three-view feature extraction algorithm in the present invention;

FIG. 9 is an elevation view of an original point cloud;

fig. 10 is a schematic diagram of a feature length extraction result.

The system comprises a point cloud filtering module 1, a three-dimensional vector model generating module 2, a three-dimensional point cloud model generating module 3, a center calculating module for each characteristic plane of the tower to be evaluated 4 and an inclination state evaluating module 5.

Detailed Description

The invention is described in further detail below with reference to the following figures and specific examples:

as shown in fig. 1, the method for measuring the inclination parameters of the point cloud tower based on the unmanned aerial vehicle laser radar is characterized by comprising the following steps:

step 1: acquiring three-dimensional laser point clouds of a transmission tower, selecting single tower pole point clouds in the three-dimensional laser point clouds of the transmission tower, removing miscellaneous points and wire point clouds in the selected single tower pole point clouds, and extracting tower pole point clouds after tower three-dimensional point cloud filtering;

step 2: dividing the filtered tower point cloud into a tower foot point cloud, a tower body point cloud and a tower head point cloud so as to obtain a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model;

and step 3: combining a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model into a typical tower type three-dimensional point cloud model, and inputting the typical tower type three-dimensional point cloud model into a typical tower type three-dimensional point cloud model database;

and 4, step 4: performing center Point calculation on a tower feature plane to be evaluated, selecting a tower area to be subjected to inclination evaluation, performing filtering operation to remove ground points and power lines, matching a tower head three-dimensional vector model in a typical tower type three-dimensional Point cloud model database with a tower to be evaluated so as to determine a tower type of the tower, performing ICP (Iterative Closest Point algorithm) matching on the tower to be evaluated by using a corresponding tower type feature plane respectively, acquiring rotation and translation matrixes of each feature plane of the tower to be evaluated, and acquiring center Point coordinates of each feature plane of the tower to be evaluated through corresponding rotation and translation transformation on a corresponding tower type feature plane center Point in the typical tower type three-dimensional Point cloud model database;

and 5: and calculating the inclination angle of the tower to be evaluated according to the coordinates of the central point of each characteristic plane of the tower to be evaluated.

In the step 2 of the technical characteristics, dividing the tower point cloud after the tower three-dimensional point cloud filtration into a tower foot point cloud, a tower body point cloud and a tower head point cloud by using the tower foot elevation, the tower body elevation, the tower shoulder elevation and the tower head elevation, and respectively modeling the tower foot point cloud, the tower body point cloud and the tower head point cloud to obtain a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model (dividing is performed based on a point cloud elevation distribution histogram according to the structural characteristics that a feature plane exists at every section of the tower body);

generating an elevation histogram of tower point clouds (such as figure 2, wherein the abscissa is the number of the point clouds and the ordinate is the elevation), extracting a local extreme value in the histogram, eliminating an extreme value of a non-characteristic elevation through a constraint condition that the interval between characteristic elevations is greater than a threshold value, obtaining a characteristic elevation in the tower point cloud, such as figure 3 and a corresponding characteristic plane, such as figure 4 (according to the structural characteristics of a tower body, a characteristic plane exists at every other section of elevation, namely a plane marked in figure 4), preliminarily extracting a tower shoulder elevation at the joint of a tower head and the tower body by judging the number of points contained in the characteristic plane point cloud corresponding to each characteristic elevation, realizing the segmentation of the tower head and the tower body, and dividing the filtered tower point cloud into tower foot point cloud, tower body point cloud and tower head point cloud by utilizing the segmentation mode of the tower head and the tower body;

in the step 1 of the technical scheme, the three-dimensional laser point cloud of the power transmission tower is obtained through an unmanned aerial vehicle LiDAR system, and the quality of the three-dimensional laser point cloud of the power transmission tower is improved in a double-laser-head fusion mode. The characteristic extraction of a typical tower type and the three-dimensional model building of various tower types need to manually frame and select a single tower point cloud. Finally, as a plurality of miscellaneous points exist in the tower point cloud selected manually, the distribution condition is complex, and the single method is difficult to remove, a scheme of progressive filtering is adopted, namely in the modeling process, the extracted information is utilized to filter the point cloud, a part of miscellaneous points are removed, then the electric power tower information is extracted, and then the point cloud is filtered until all the electric power tower information is extracted. The distribution of the heteropoints has the following characteristics:

1. both ground and vegetation points typically gather near the bottom of the tower.

2. The power line (jumper) point cloud near the tower body is generally far away from the center of the plane of the power tower.

3. The power line points on the tower head are complex in distribution and difficult to remove.

By setting an elevation threshold, the point cloud smaller than the elevation threshold is removed, so that the purpose of roughly removing the tower bottom miscellaneous points is achieved. And for the power line points near the tower body, filtering the point cloud by using the extracted information through a progressive filtering strategy, namely in the modeling process, eliminating a part of miscellaneous points by calculating the distance between the point cloud and the center of the tower, then extracting a part of power tower information, and then filtering the point cloud until the required power tower information is extracted.

In step 2 of the above technical scheme, a tower head three-dimensional Vector model is obtained by reconstructing a tower head point cloud by using a method of SVM (Support Vector Machines) classification in combination with a tower head model library; and reconstructing the tower body point cloud in a plane fitting mode to obtain a tower head three-dimensional vector model, and reconstructing the tower foot point cloud in a manual interaction mode to obtain a tower foot three-dimensional vector model.

In step 5 of the above technical scheme, the inclination parameters of the whole tower, the tower head and the tower body are calculated according to the following strategies, so as to evaluate the inclination state of the tower: connecting the central points of the characteristic planes of the tower to be evaluated in sequence to form a tower central line, calculating the included angle between each section of central line and a theoretical tower central line (the vertical line of the ground where the tower is located), if the included angle between a part of central line segment and the theoretical central line is larger than a threshold value, judging that the tower is inclined, wherein the inclined position is between the two characteristic planes where the central line segment is located, the inclined angle is the calculated included angle, and calculating the tower head deformation parameter by comparing the tower head geometric parameters, the inclined angle and the like at different moments with a tower head standard model.

In step 1 of the above technical scheme, the method for removing miscellaneous points and wire point clouds in a single tower pole point cloud selected by a frame comprises the following steps: the method comprises the steps of eliminating miscellaneous points at the bottom of a tower by setting an elevation threshold, extracting the outline of the tower from the lowest characteristic plane when the outline of the tower is extracted by using an Alpha Shapes algorithm for power line points in the tower elevation, obtaining the minimum outline in the extracted outlines, limiting the range of the point cloud of the next characteristic plane to be processed by using the extracted minimum outline, ensuring that the processing of the point cloud extraction outline of the next characteristic plane does not exceed the minimum outline, eliminating the miscellaneous points of the power line outside the outline, and eliminating the power line points by calculating the distance between the point cloud and the center of the tower to obtain the final Alpha Shapes outline.

In the above technical scheme, a specific method for combining the tower foot three-dimensional vector model, the tower body three-dimensional vector model and the tower head three-dimensional vector model into the typical tower type three-dimensional point cloud model in the step 3 is as follows:

the tower body characteristic plane corresponding to the tower body characteristic elevation is a group of regular rectangles, the longest side is searched by extracting the outer contour line of the tower body characteristic plane to obtain the main direction, the direction pointed by the tower tip of the tower is determined, and the position of the tower is determined by calculating the circumscribed circle of the outer contour of the tower body characteristic plane;

secondly, the tower body is of a regular quadrangular frustum pyramid structure, modeling is carried out in a fitting mode, point clouds on four circumferential side faces of the tower body are obtained by classifying the outer contour of the tower body extracted by an Alpha Shapes algorithm (scattered point contour algorithm) according to the direction pointed by the tower shoulder of the tower, and the quadrangular frustum pyramid fitting is carried out on the tower body by utilizing the point clouds on the four circumferential side faces of the tower body (the four side faces of the tower body are symmetrical relative to the central axis), so that a geometric model of the four circumferential side faces of the tower body is obtained;

solving intersecting lines of geometric models of four circumferential sides of a tower body to obtain a frame of the tower body, extracting a mode characteristic from a tower head point cloud as shown in figure 5, judging the type of the tower head by a mode identification method, rotating the tower head cloud according to a main direction to obtain a front view of the tower, performing one-dimensional projection and seed point growth on the point cloud on the tower characteristic elevation to obtain a characteristic length, wherein the characteristic length comprises a tower diaphragm span and the actual length of a tower diaphragm frame, the characteristic length, the difference between the maximum value and the second maximum value in the tower diaphragm span and the difference between the maximum value and the second maximum value in the actual length of the tower diaphragm frame are used as the mode characteristic of the tower, the mode characteristic of the tower is used for identifying the type of the tower, namely the type of the tower head, judging which type the tower head belongs to, and combining the tower head with the three-dimensional model of the corresponding tower body, the three-dimensional model of the tower-type tower is obtained (the surrounding ground points of the tower foot, the vegetation points and other miscellaneous points are numerous, the situation is complex, the automatic modeling difficulty is high, the tower foot of the tower is multi-corner, the type is simple, and the method of manual modeling is suitable to be adopted).

In the technical scheme, the mode characteristics of the tower are used for identifying the type of the tower, namely the type of the tower head, and judging which type of the tower head of the tower belongs to.

In the above technical scheme, the specific method for obtaining the characteristic length by performing one-dimensional projection and seed point growth on the point cloud on the tower characteristic elevation comprises the following steps:

a, performing one-dimensional projection on a point cloud P in a certain height range of delta H above and below a characteristic height H (namely Z belongs to [ H-delta H, H + delta H ]), wherein if points exist in a grid, the value of the grid is 1, otherwise, the value is 0, as shown in FIG. 6;

b, connecting the line segments in the one-dimensional projection, and combining the line segments with the adjacent distance (the distance between the end point of the left line segment and the start point of the right line segment in the two adjacent line segments) smaller than the threshold value into one line segment, as shown in FIG. 7;

step c, eliminating line segments with length less than threshold value after combination, and calculating range length L_sAnd a real length L_eWherein L is_sIs the distance between the leftmost line segment starting point and the rightmost line segment ending point, L_eFor the sum of all line segments, as shown in fig. 8, Le in Lei in fig. 8 represents the actual length, i here is the following 1 and 2 in dotted form, the longest actual length is Le1, and the next longest actual length is Le 2;

step d: a) c) are carried out on all the characteristic elevations, and the range length L of the longest and the next longest is found out_s1,L_s2And corresponding elevationLongest and next longest actual length L_e1,L_e2And corresponding elevation valueAnd calculating the elevation difference between the two_s,ΔH_e，[L_s1,L_s2,L_e1,L_e2,ΔH_s,ΔH_e]Namely, the characteristic value of the tower head of the power tower obtained by the method, the length extraction effect is shown in fig. 9 and 10.

A system for measuring the inclination parameters of a point cloud tower based on an unmanned aerial vehicle laser radar is shown in figure 1 and comprises a point cloud filtering module 1, a three-dimensional vector model generating module 2, a three-dimensional point cloud model generating module 3, a center calculating module 4 for each characteristic plane of the tower to be evaluated and an inclination state evaluating module 5;

the point cloud filtering module 1 is used for selecting a single tower pole point cloud in the three-dimensional laser point cloud of the transmission tower, eliminating miscellaneous points and wire point cloud in the single tower pole point cloud, and obtaining the filtered tower pole point cloud;

the three-dimensional vector model generation module 2 is used for dividing the filtered tower point cloud into a tower foot point cloud, a tower body point cloud and a tower head point cloud so as to obtain a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model;

the three-dimensional point cloud model generation module 3 is used for combining a tower foot three-dimensional vector model, a tower body three-dimensional vector model and a tower head three-dimensional vector model into a typical tower type three-dimensional point cloud model;

the center calculation module 4 of each characteristic plane of the tower to be evaluated is used for calculating the center point of the characteristic plane of the tower to be evaluated according to the typical tower type three-dimensional point cloud model to obtain the coordinates of the center point of each characteristic plane of the tower to be evaluated;

the inclination state evaluation module 5 is used for calculating the inclination angle of the tower to be evaluated according to the coordinates of the central point of each characteristic plane of the tower to be evaluated.

Unmanned aerial vehicle patrols and examines and has become the route of widelying popularize in the national grid system and patrol and examine the mode, is showing and is promoting efficiency and the degree of accuracy of patrolling and examining the route. On the basis, the invention fully excavates and expands the application function of the existing inspection unmanned aerial vehicle operation platform, realizes one-time flight and batch acquisition, quickly and efficiently carries out monitoring and early warning of the inclined three-dimensional space state of the tower, has technical feasibility, brings remarkable economic benefit and has important popularization value. Meanwhile, with the development of a three-dimensional measurement technology, the laser radar can quickly scan a measured object, establish a detailed and accurate three-dimensional point cloud model, provide accurate quantitative analysis and provide a motorized and flexible mode for measuring the inclination state of the power tower in the corridor of the power transmission line.

The invention provides a method and a technical process for measuring the inclination parameters of a point cloud tower based on an unmanned aerial vehicle laser radar for the first time, and realizes automatic identification and extraction of key parts of a tower structure, rapid scanning of geometric parameters of a line tower and intelligent evaluation of the inclination parameters. Utilize advance unmanned aerial vehicle to patrol the line technique, show and promoted circuit efficiency and the degree of accuracy of patrolling and examining, reduced the work load and the risk of patrolling and examining expense and staff, the realization has shaft tower slope geology monitoring early warning and risk prevention and control on the engineering practice meaning, improves circuit operational reliability, reduces great electric wire netting safety and stability operation risk.

Details not described in this specification are within the skill of the art that are well known to those skilled in the art.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.