CN112394743B - Method for detecting dangerous points of power tower inspection route - Google Patents
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Abstract
本发明提供了一种电力杆塔巡检航线危险点检测的方法，包括以下步骤：S1：将整体航线进行航点分段；S2：通过邻近点云数据影响因子计算出筛选阈值；S3：通过对每个航线段两端航点的高程值与筛选阈值进行结合原始点云数据集进行比对筛查，航线段中候选危险点云数据筛查出来；S4：对候选危险点云子集内的杆塔点云数据与航线段逐点进行空间安全距离碰撞检测；S5：对碰撞检测集合中的危险点集合进行复测；S6：将复测后的危险点存入危险点云子集中，对危险点云子集中的航线区分危险点和危险段。本发明所述的一种电力杆塔巡检航线危险点检测的方法解决了人工进行杆塔巡检的航线规划时间长，且规划完的航线质量无法全面检测的问题。
The present invention provides a method for detecting dangerous points in a power tower inspection route, which includes the following steps: S1: segment the entire route into waypoints; S2: calculate a screening threshold based on the influence factor of adjacent point cloud data; The elevation values of the waypoints at both ends of each route segment and the screening threshold are combined with the original point cloud data set for comparison and screening, and the candidate dangerous point cloud data in the route segment are screened; The point cloud data of the tower and the route segment are subjected to the point-by-point collision detection of the space safety distance; S5: re-test the dangerous point set in the collision detection set; S6: save the dangerous points after the re-test into the dangerous point cloud subset, and analyze the dangerous points. Routes in a subset of the point cloud distinguish between hazardous points and hazardous segments. The method for detecting dangerous points of a power pole and tower inspection route of the present invention solves the problem that the route planning time for manual pole and tower inspection is long and the quality of the planned route cannot be fully detected.
Description
Technical Field
The invention belongs to the field of unmanned aerial vehicle autonomous inspection flight path planning, and particularly relates to a method for detecting dangerous points of an inspection route of an electric power tower.
Background
In recent years, in the stage of rapid development of national power grid construction and development, security inspection of a power grid is more and more concerned. The increasing power grid construction and the traditional manual inspection mode have more prominent problems in aspects of poor inspection effect, high labor cost, low working efficiency and the like, and cannot meet the new requirements of power grid inspection. The traditional line inspection mode mainly relying on manpower cannot meet the strategic development requirements of pursuing management refinement, cost reduction and efficiency improvement in current and future power grid inspection. In the power transmission line inspection, particularly, the inspection requirement of a tower is increasingly outstanding. The mode that the pole tower was patrolled and examined is carried out to the manual work, needs the flight hand to plan the waypoint under the pole tower manually, carries out the pole tower and patrols and examines, can't carry out the visual of the dangerous point detection of airline, and manual airline planning time is longer, and the airline quality that has planned does not can not detect comprehensively yet, can not satisfy the demand that needs the pole tower to patrol and examine that increases gradually day by day.
Disclosure of Invention
In view of the above, the invention provides a method for detecting dangerous points of a power tower inspection route, so as to solve the problems that the planning time of a moving route for manually inspecting the tower is long, and the quality of the planned route cannot be comprehensively detected.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a method for detecting dangerous points of an electric power tower inspection route comprises the following steps:
s1: carrying out waypoint segmentation on the whole route;
s2: calculating a screening threshold value through the influence factors of the point cloud data adjacent to the waypoints in the route section;
s3: combining the elevation values of the waypoints at the two ends of each route section with a screening threshold, comparing and screening the combined data with the original point cloud data set, screening candidate dangerous point cloud data in the route section, and storing the candidate dangerous point cloud data in a candidate dangerous point cloud subset;
s4: carrying out space safe distance collision detection on the tower point cloud data and the route sections point by point in the candidate dangerous point cloud subset;
s5: retesting a dangerous point set in the collision detection set;
s6: and storing the dangerous points after re-measurement into a dangerous point cloud subset, and distinguishing dangerous points and dangerous sections of the route in the dangerous point cloud subset so as to revise the dangerous route again.
Further, the spatial safe distance collision detection used in step S4 includes performing collision detection on the point cloud data in the candidate subset point by point and the route segment, comparing the collision detection with an automatically adjusted route segment safety threshold to obtain a dangerous point in the current route segment, and storing the dangerous point in the dangerous point subset.
Further, the retesting utilized in step S5 is to perform random extraction retesting on the non-candidate point cloud subset, perform space safe distance collision detection on the randomly extracted points, and store the suspected dangerous points in the dangerous point subset for reducing the false negative rate.
Further, after the final dangerous point cloud subset is obtained in step S5, a navigation point in the dangerous point cloud subset is visually warned.
Further, when the visual warning is that the dangerous point detected by the flight segment is at a certain end point of the flight segment, only the part close to the flight segment is displayed by red warning, and the corresponding flight point is highlighted; and if the dangerous points are positioned between the navigation sections, performing red warning display on the whole navigation section, and highlighting the navigation points at the two ends.
Compared with the prior art, the invention has the following advantages:
(1) the method for detecting the dangerous points of the power tower inspection route can quickly and accurately distinguish the dangerous points and the dangerous sections, has clear guiding significance for final waypoint re-editing, outputs the positions of the dangerous points in the route more simply and clearly to a certain extent, and can quickly revise the dangerous route again.
(2) The method comprises the steps of segmenting waypoints of the whole route, screening an original point cloud data set according to the elevation values of the waypoints at two ends of the current route segment and a screening threshold value calculated by combining the influence factors of adjacent point cloud data for the segmented route segment, and storing the screened threshold value into a candidate point cloud subset, so that the reliability of dangerous point detection is improved, the calculation complexity is reduced, and the resource waste is reduced.
(3) And carrying out efficient space safe distance collision detection, namely distance detection from a space midpoint to a line segment on the point cloud data in the candidate point cloud data subset point by point and the route segment, and calculating a threshold value by combining the safe distance of the aircraft flight to obtain a dangerous point subset, wherein the calculation complexity is low and the operation efficiency is high.
(4) And the false report rate is reduced by retesting the non-candidate point cloud subset original data set.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of a method for detecting dangerous points of an electric power tower inspection route according to an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention. Furthermore, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art through specific situations.
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
As shown in fig. 1, a method for detecting dangerous points of a power tower inspection route includes the following steps:
s1: carrying out waypoint segmentation on the whole route;
s2: calculating a screening threshold value through the influence factors of the point cloud data adjacent to the waypoints in the route section;
s3: the elevation values of the waypoints at the two ends of each route section are combined with a screening threshold value, and then are compared with an original point cloud data set for screening, candidate dangerous point cloud data in the route section are screened out and stored in a candidate dangerous point cloud subset, so that the reliability of dangerous point detection is improved, the calculation complexity is reduced, and the resource waste is reduced;
s4: carrying out efficient space safe distance collision detection, namely distance detection from a space midpoint to a line segment on point-by-point cloud data in the candidate point cloud data subset and the line segment, and calculating a threshold value by combining the flying safe distance of the airplane to obtain a dangerous point subset, wherein the calculation complexity is low and the operation efficiency is high;
s5: retesting a dangerous point set in the collision detection set, retesting the screened dangerous point set, and verifying the dangerous points by randomly extracting 1/3 dangerous points and the original point cloud data set so as to reduce the false report rate;
s6: and storing the dangerous points after re-measurement into a dangerous point cloud subset, and distinguishing dangerous points and dangerous sections of the route in the dangerous point cloud subset so as to revise the dangerous route again.
The space safe distance collision detection used in the step S4 includes performing collision detection on point-by-point cloud data in the candidate subset and the route segment, comparing the collision detection with an automatically adjusted route segment safety threshold to obtain dangerous points in the current route segment, and storing the dangerous points in the dangerous point subset.
The retesting utilized in step S5 is to perform random extraction retesting on the non-candidate point cloud subset, perform space safety distance collision detection on the randomly extracted points, and store the suspected dangerous points in the dangerous point subset for reducing the false negative rate.
As shown in fig. 1, after the final dangerous point cloud subset is obtained in step S5, a navigation point in the dangerous point cloud subset is visually warned.
When the visual warning is that the dangerous point detected by the flight segment is at a certain end point of the flight segment, only the part close to the flight segment is displayed by red warning, and the corresponding flight point is highlighted; and if the dangerous points are positioned between the navigation sections, performing red warning display on the whole navigation section, and highlighting the navigation points at the two ends.
Based on high precision of point cloud data, a multi-level screening mechanism, route segmentation, space collision detection of candidate point cloud subsets in route segments one by one, a review mechanism of dangerous point subsets and non-candidate point cloud subsets, and a classification set of dangerous points in routes, the dangerous points of routes can be detected in an all-round and dead-angle-free manner. The method has the advantages that the method is full-automatic, multi-dimensional and multi-level route dangerous point detection, greatly improves the efficiency of route safety inspection, and outputs a one-key flight route with high availability and high safety. The method is characterized in that a multi-layer dangerous point screening mechanism and a space collision detection technology of candidate point cloud subsets in a route segment by route segment are the core of the method, and the method specifically comprises the following steps:
a multi-level dangerous point screening mechanism screens an original point cloud data set to obtain a candidate point cloud subset by carrying out route section refinement on a route, combining elevation values of route points at two ends of the route section and combining a screening threshold value calculated by adjacent point cloud data influence factors; carrying out efficient space safe distance collision detection on point cloud data in the candidate point cloud data subset point by point and the flight line segment, and calculating a threshold value by combining the safe distance of airplane flight to obtain a dangerous point subset; the method can retest the non-candidate point cloud subset original data set, reduce the false alarm rate to a certain extent, retest the screened dangerous point set, verify the dangerous points by randomly extracting 1/3 dangerous points and the original point cloud data set, and reduce the false alarm rate to a certain extent;
the space collision detection technology of the candidate point subset in the flight segment comprises the steps of carrying out collision detection on point-by-point cloud data in the candidate subset and the flight segment, comparing the collision detection with an automatically adjusted safety threshold of the flight segment to obtain dangerous points in the current flight segment, and storing the dangerous points in the dangerous point subset.
The method comprises the following specific steps:
1. loading a point cloud data set A of the current tower and an automatic planning route data set P of the current tower;
2. for every two adjacent waypoints P in the current route data set Pi,pi+1Dividing the inter route sections, and storing all generated route sections into a route section subset L;
3. combining the elevation values of the waypoints at the two ends of each route section with a screening threshold value, comparing and screening the elevation values with the original point cloud data set, screening candidate dangerous point cloud data in the route section, storing the candidate dangerous point cloud data into a candidate dangerous point cloud subset, and storing the screened point cloud data into the candidate dangerous point cloud subset
Performing the following steps;
4. performing collision detection on the point cloud data entering the candidate point cloud subset B and the target route segment one by one to obtain all collision detection results X, sequencing the collision detection results to obtain a detection minimum distance value XminComparing it with a threshold value calculated for the safe distance of flight of the aircraft if xminIf the value is smaller than the threshold value, storing the point cloud position information corresponding to the value and the attribute parameter table of the value in D, and storing the point cloud position information and the attribute parameter table of the value in a dangerous point detection set D (D belongs to D);
5. for non-candidate point cloud subsets
Random extraction and retesting are carried out, and suspected dangerous points are stored in a dangerous point subset D, mainly for reducing the rate of missing report;
6. classifying and attributing the dangerous point subset D, updating the position attribute of the dangerous point in a parameter table in the dangerous point D (D belongs to D), and mainly distinguishing whether the dangerous point belongs to the danger of a navigation point end or the danger of a navigation line segment;
and (3) sequentially reading the navigation line segments 1 belonging to the L one by one to complete the steps 3-6 of the dangerous point detection until the dangerous points of all the navigation line segments are detected completely.
7. Retesting the dangerous point subset D, adopting a random extraction mode to extract 1/3 dangerous points in the dangerous point subset D, storing the dangerous points in the set E to be retested, and naming the original dangerous point subset as the original dangerous point subset
And (3) carrying out collision detection on the dangerous points to be detected and the point cloud data set A one by one, and merging the detected dangerous points and the original dangerous point set D 'into a dangerous point set D', mainly aiming at reducing the false report rate.
And carrying out visual alarm on the waypoints in the dangerous point subset, distinguishing whether the dangers of the route segments are distributed on the waypoints or among the route segments, and finally reflecting the dangers on the waypoints.
And the collision detection of dangerous points in the flight segment mainly carries out space collision detection on the point cloud in the candidate subset and the flight segment point by point.
And calculating the spatial distance between each point cloud B (B belongs to B) in the candidate point cloud subset B and the route segment L (L belongs to L), and storing the calculated spatial distance in the collision detection set X. After point-by-point collision detection, sorting dangerous points in the detection set to obtain a minimum value xmin(xminE.g. X) comparing the minimum value with a flight safety distance calculation threshold value of the current model airplane, XminAnd if the current value is less than the threshold value, storing the corresponding point cloud position information and the parameter table into D and storing the point cloud position information and the parameter table into a dangerous point set D (D belongs to D). Classifying the suspected dangerous points, and classifying the dangerous points D (D belongs to D)The position attribute of the dangerous point in the parameter table is updated, the dangerous point is mainly distinguished from the danger of the navigation point end or the danger of the navigation line segment, and a basis is provided for subsequent visual display of the dangerous point.
The method mainly adopts the criteria that when the dangerous point detected by a airline section is at a certain end point of the airline section, only the part close to the airline section is displayed by red warning, and the corresponding airline point is highlighted; and if the dangerous points are positioned between the navigation sections, performing red warning display on the whole navigation section, and highlighting the navigation points at the two ends. And finally, outputting all dangerous point waypoints to prompt that waypoint adjustment is needed urgently, and executing dangerous point detection again until the dangerous points return to zero. From this, the safe, automated planning route can be used to perform flight operations.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
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