CN112184903A - Method, device, equipment and medium for detecting high-voltage line tree obstacle risk points - Google Patents
Method, device, equipment and medium for detecting high-voltage line tree obstacle risk points Download PDFInfo
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Abstract
The embodiment of the invention discloses a method, a device, equipment and a medium for detecting high-voltage line tree obstacle risk points. The method comprises the following steps: the method comprises the steps that an unmanned aerial vehicle carrying a multi-lens visible light camera is used for collecting line image data of a pole section to be detected in a high-voltage line, and a pole section inspection three-dimensional model is built according to the line image data; acquiring a pre-established tree barrier risk area three-dimensional model corresponding to the high-voltage line to-be-detected pole section, wherein the tree barrier risk area is marked in the tree barrier risk area three-dimensional model; and integrating the three-dimensional tree obstacle patrol model and the three-dimensional tree obstacle risk area model, and detecting point cloud data of the three-dimensional tree obstacle patrol model according to the tree obstacle risk area to determine tree obstacle risk points. According to the technical scheme, the cost investment is reduced, the model building speed and the detection efficiency and accuracy of the high-voltage line tree obstacle risk points are improved, the workload is reduced, and the working efficiency is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of image processing, in particular to a method, a device, equipment and a medium for detecting tree barrier risk points of high-voltage lines.
Background
When daily operation and maintenance are carried out on high-voltage line rows, particularly on the high-voltage line rows in mountainous areas, not only the defects of the high-voltage line row body need to be concerned, but also trees which are too high below the high-voltage line row need to be concerned.
At present, in the patrol inspection of a high-voltage line of a power system, because the influence and the limitation of the geography, the terrain and the climate which an unmanned aerial vehicle receives are relatively small, the unmanned aerial vehicle is generally utilized to judge the tree obstacle risk point. For example, after the suspected point of the tree obstacle risk is determined by using the unmanned aerial vehicle for patrol, the unmanned aerial vehicle is manually controlled to determine the distance between the suspected point and the lead, so that the patrol efficiency is undoubtedly reduced, and the distance is measured by naked eyes manually, so that a detection result has a large error. For another example, modeling is performed by using a laser radar device carried by an unmanned aerial vehicle, and data classification is performed to obtain tree obstacle risk points existing in a line environment, which undoubtedly results in slow data acquisition and processing speed, reduces modeling speed and detection efficiency, and causes high investment cost due to high instrument price of the laser radar device. Meanwhile, due to the fact that data of the existing tree obstacle risk point detection method cannot be reused, workload is increased, and working efficiency is reduced. Therefore, how to reduce the cost investment, improve the model building speed and the detection efficiency and accuracy of the high-voltage line tree obstacle risk points, reduce the workload, and improve the working efficiency is a problem to be solved urgently.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a medium for detecting high-voltage line tree barrier risk points, which are used for reducing cost investment, improving the model building speed and the detection efficiency and accuracy of the high-voltage line tree barrier risk points, reducing workload and improving working efficiency.
In a first aspect, an embodiment of the present invention provides a method for detecting a high-voltage line tree obstacle risk point, including:
the method comprises the steps that an unmanned aerial vehicle carrying a multi-lens visible light camera is used for collecting line image data of a pole section to be detected in a high-voltage line, and a pole section inspection three-dimensional model is built according to the line image data;
acquiring a pre-established tree barrier risk area three-dimensional model corresponding to the high-voltage line to-be-detected pole section, wherein the tree barrier risk area is marked in the tree barrier risk area three-dimensional model;
and integrating the three-dimensional tree obstacle patrol model and the three-dimensional tree obstacle risk area model, and detecting point cloud data of the three-dimensional tree obstacle patrol model according to the tree obstacle risk area to determine tree obstacle risk points.
In a second aspect, an embodiment of the present invention further provides a device for detecting a high-voltage line-row tree obstacle risk point, including:
the pole section inspection three-dimensional model building module is used for acquiring line image data of a pole section to be detected in a high-voltage line through an unmanned aerial vehicle carrying a multi-lens visible light camera and building a pole section inspection three-dimensional model according to the line image data;
the tree barrier risk area three-dimensional model acquisition module is set to acquire a pre-established tree barrier risk area three-dimensional model corresponding to the to-be-detected pole section of the high-voltage line, wherein the tree barrier risk area three-dimensional model is marked with a tree barrier risk area;
and the tree barrier risk point determining module is configured to integrate the three-dimensional tree section inspection model and the three-dimensional tree barrier risk area model, and detect point cloud data of the three-dimensional tree section inspection model according to the tree barrier risk area to determine tree barrier risk points.
In a third aspect, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor, when executing the program, implements the method for detecting a high-voltage line barrier risk point according to any embodiment of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for detecting a high-voltage line tree obstacle risk point according to any embodiment of the present invention.
According to the technical scheme provided by the embodiment of the invention, the line image data of the pole section to be detected in the high-voltage line is collected through the unmanned aerial vehicle carrying the multi-lens visible light camera, the pole section inspection three-dimensional model is constructed according to the collected line image data, the tree barrier risk area three-dimensional model which is pre-established and corresponds to the pole section to be detected in the high-voltage line and contains the tree barrier risk area identification is obtained, finally, the pole section inspection three-dimensional model and the tree barrier risk area three-dimensional model are integrated, the point cloud data of the pole section inspection three-dimensional model is detected according to the tree barrier risk area, and therefore, the tree barrier risk point can be determined. Above-mentioned technical scheme, gather the line image data of waiting to detect the pole section in high-pressure line through the unmanned aerial vehicle who carries on many camera lenses visible light camera, compare and use laser radar equipment, greatly reduced data acquisition equipment's cost input, the time of data acquisition and processing has been reduced, the quick construction of pole section inspection three-dimensional model has been realized, and it confirms tree barrier risk point to inspect three-dimensional model and the integration of tree barrier risk area three-dimensional model through the pole section, the position of tree barrier risk point has been realized fixing a position according to the demand of patrolling and examining fast, the detection efficiency and the degree of accuracy of high-pressure line tree barrier risk point have been improved, and can reuse tree barrier risk area three-dimensional model detection tree barrier risk point, the work load has been reduced, work efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of a method for detecting a high-voltage line barrier risk point according to a first embodiment of the present invention;
fig. 2 is a schematic flow chart of a method for detecting a high-voltage line barrier risk point according to a second embodiment of the present invention;
fig. 3a is a schematic flow chart of a method for detecting a high-voltage line barrier risk point according to a third embodiment of the present invention;
FIG. 3b is a schematic illustration of a three-dimensional model of a pole segment inspection in accordance with a third embodiment of the present invention;
FIG. 3c is a schematic diagram of a capital-constructed initial three-dimensional model corresponding to a pole segment to be detected in a high-voltage line in the third embodiment of the invention;
FIG. 3d is a schematic diagram of a three-dimensional model of a barrier risk area in a third embodiment of the present invention;
fig. 3e is a schematic diagram illustrating determination of a tree obstacle risk point according to a third embodiment of the present invention;
fig. 3f is a schematic top view of a high-voltage line corresponding to a pole segment to be detected in the high-voltage line according to the third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a device for detecting a high-voltage line-row tree barrier risk point according to a fourth embodiment of the present invention;
fig. 5 is a schematic hardware structure diagram of a computer device in the fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Example one
Fig. 1 is a flowchart of a method for detecting a high-voltage line tree barrier risk point according to an embodiment of the present invention, which is applicable to a situation where a high-voltage line tree barrier risk point is detected based on image data.
As shown in fig. 1, the method for detecting a high-voltage line obstacle risk point provided in this embodiment specifically includes:
s110, collecting line image data of the pole section to be detected in a high-voltage line through an unmanned aerial vehicle carrying a multi-lens visible light camera, and constructing a pole section inspection three-dimensional model according to the line image data.
Carry on many camera lenses visible light camera's unmanned aerial vehicle refers to the unmanned aerial vehicle that can carry on the visible light camera of at least one camera lens to unmanned aerial vehicle can carry big dipper positioning system in order to realize unmanned aerial vehicle's accurate location. To carrying on the unmanned aerial vehicle of single-lens visible light camera probably produce great error when gathering the image, consequently in this embodiment, optional, carry out image acquisition through the unmanned aerial vehicle of carrying on many lens visible light cameras to improve image acquisition's precision. Unmanned aerial vehicle carries on many camera lenses visible light camera, can adopt oblique photography's shooting mode to gather image data to the visible light image data who gathers satisfy certain photo overlap degree.
A high voltage line row refers to an environmental situation around an overhead high voltage transmission line arranged outdoors, for example, buildings, roads, vegetation, etc. around the high voltage transmission line. The pole section to be detected in the high-voltage line refers to the pole section range in which the tree obstacle risk point detection needs to be carried out in the high-voltage line.
A pole section inspection three-dimensional model refers to a three-dimensional model of a line tower, which can be used for carrying out three-dimensional modeling according to image data collected by a multi-lens visible light camera carried by an unmanned aerial vehicle and acquiring the three-dimensional model of the line tower needing to be used for detecting tree obstacle risk points. When the tree obstacle risk point of one section high tension line row needs to be detected, the high tension transmission line can be rapidly scanned through the multi-lens visible light camera carried by the unmanned aerial vehicle, and a pole section inspection three-dimensional model is established according to line image data acquired by the rapid channel inspection.
By means of the unmanned aerial vehicle carrying the multi-lens visible light camera, line image data of the pole section to be detected in the high-voltage line can be collected in an oblique photography shooting mode, three-dimensional modeling can be rapidly carried out according to the collected line image data, and a pole section inspection three-dimensional model can be constructed.
S120, obtaining a pre-established tree barrier risk area three-dimensional model corresponding to the to-be-detected pole section of the high-voltage line, wherein the tree barrier risk area is marked in the tree barrier risk area three-dimensional model.
The tree barrier risk area three-dimensional model refers to a three-dimensional model which can be used for identifying a tree barrier risk area and is used for determining whether a tree barrier risk point exists.
The tree obstacle risk area refers to a risk area in a high-voltage line row, and if an object (such as a treetop) falls into the risk area, the risk area can affect the high-voltage line, and is specifically used for detecting tree obstacle risk points in high-voltage line. The tree barrier risk area may be a space area with the high-voltage line as a center, for example, the tree barrier risk area is a space area with a cylindrical shape with the high-voltage line as a center; it may also be a spatial area near the high-voltage line, for example, a spatial area determined according to two specific elevation thresholds, assuming that the two elevation thresholds are H1And H2The corresponding tree obstacle risk area can be that the elevation satisfies H1＜H＜H2The spatial region of the condition(s).
S130, integrating the three-dimensional tree obstacle patrol model and the three-dimensional tree obstacle risk area model, and detecting point cloud data of the three-dimensional tree obstacle patrol model according to the tree obstacle risk area to determine tree obstacle risk points.
Integration means that at least two models can be placed in the same coordinate system, and the models can be partially or completely overlapped within the tolerance range.
The unmanned aerial vehicle which carries the multi-lens visible light camera and can be accurately positioned collects line image data of a pole section to be detected in a high-voltage line, when a pole section inspection three-dimensional model is constructed according to the collected line image data, the constructed pole section inspection three-dimensional model and the geographical position and height data of the tree barrier risk area three-dimensional model have no deviation or extremely small deviation, the two models are integrated, ground points of the two models can be overlapped in the same coordinate system and within the error allowable range, point cloud data of the pole section inspection three-dimensional model can be detected according to the tree barrier risk area identified in the tree barrier risk area three-dimensional model, and therefore the tree barrier risk point is determined.
Optionally, detecting point cloud data of the three-dimensional model by using the pole segment according to the tree obstacle risk area to determine a tree obstacle risk point, where the method includes:
and judging whether target point cloud data falling into the tree barrier risk area exists in the three-dimensional model of the pole section inspection, and if so, determining the tree barrier risk point according to the target point cloud data.
When the tree barrier risk point is determined, the tree barrier risk point can be judged according to whether point cloud data falling into a tree barrier risk area exist in the three-dimensional model of the pole section inspection, and if the point cloud data falling into the tree barrier risk area exist, the tree barrier risk point can be determined according to the point cloud data. By constructing a pole section inspection three-dimensional model, integrating the pole section inspection three-dimensional model with a tree barrier risk area three-dimensional model, judging whether point cloud data falling into a tree barrier risk area exist or not, rapidly determining tree barrier risk points according to actual pole section inspection requirements, and improving the detection efficiency and accuracy of the tree barrier risk points of a high-voltage line; and if the three-dimensional model of the pole section is not subjected to point cloud data falling into the tree barrier risk area, determining that no tree barrier risk point exists in the range of the pole section to be detected.
For example, if the tree barrier risk area is a cylindrical space area, the point falling in the cylindrical space area is determined to fall in the tree barrier risk area, and then the tree barrier risk point can be determined according to the target point cloud data, and if the point falling in the cylindrical space area does not exist, it is determined that no tree barrier risk point exists in the range of the to-be-detected pole section. For another example, if the area of the tree obstacle risk is an interval range formed by the elevation threshold value, the interval range is H1＜H＜H2When the elevation value H of some point cloud data falls in the interval range, the target object corresponding to the point cloud data is determined to fall in the tree barrier risk area, tree barrier risk points can be further determined according to the point cloud data, and if the elevation value of no point cloud data falls in the interval range, the tree barrier risk points are determined to be absent in the range of the to-be-detected pole section.
As an optional implementation manner, after determining the barrier risk point according to the target point cloud data, the method may further include:
respectively determining transverse distance data between each tree obstacle risk point and a preset tower;
and generating a tree barrier risk point detection report corresponding to the to-be-detected pole section of the high-voltage line according to each tree barrier risk point and the corresponding transverse distance data.
The preset tower refers to a preselected starting tower and serves as a reference position for determining the specific position information of the barrier risk point, and for example, the transverse distance between the barrier risk point and the tower can serve as the specific position information of the barrier risk point.
The transverse distance data refers to the horizontal distance between the tree obstacle risk point and a preset starting tower, and the specific position of the tree obstacle risk point can be accurately positioned by determining the horizontal distance value.
The tree barrier risk point detection report refers to a document which can contain specific position information of all tree barrier risk points in a detection pole section line and transverse distance data between the detection pole section line and a preset pole tower, the document can be a word document, and the generated tree barrier risk point detection report corresponding to the pole section to be detected in the high-voltage line can be uploaded to a ground server in real time to perform work such as tree barrier risk point analysis.
According to the technical scheme provided by the embodiment of the invention, the unmanned aerial vehicle carrying the multi-lens visible light camera is used for acquiring the line image data of the high-voltage line to-be-detected pole section and constructing the pole section inspection three-dimensional model, compared with a laser radar device, the cost investment of the data acquisition device is greatly reduced, the data acquisition and processing time is reduced, and the fast construction of the pole section inspection three-dimensional model is realized; the method comprises the steps of obtaining a pre-established tree barrier risk area three-dimensional model containing a tree barrier risk area identification corresponding to a pole section to be detected in a high-voltage line, integrating the pole section inspection three-dimensional model with the tree barrier risk area three-dimensional model, determining tree barrier risk points according to point cloud data of the tree barrier risk area detection pole section inspection three-dimensional model, achieving the purpose of rapidly positioning the tree barrier risk points according to inspection requirements, improving the detection efficiency and accuracy of the tree barrier risk points in the high-voltage line, repeatedly using the tree barrier risk area three-dimensional model to detect the tree barrier risk points, reducing the workload and improving the working efficiency.
Example two
Fig. 2 is a flowchart of a method for detecting a high-voltage line barrier risk point according to a second embodiment of the present invention. The embodiment is embodied on the basis of the above embodiment, wherein before acquiring the pre-established tree barrier risk area three-dimensional model corresponding to the pole segment to be detected in the high-voltage line, the method further includes: acquiring capital construction initial three-dimensional model data corresponding to the high-voltage line to-be-detected pole segment;
extracting tower point cloud data, wire point cloud data and ground point cloud data from the initial three-dimensional model data of the capital construction;
determining a tree barrier risk area corresponding to the high-voltage line to-be-detected pole section according to the wire point cloud data;
and establishing a three-dimensional model of the tree barrier risk area according to the tower point cloud data, the wire point cloud data, the ground point cloud data and the tree barrier risk area.
As shown in fig. 2, the method for detecting a high-voltage line obstacle risk point provided in this embodiment specifically includes:
s210, collecting line image data of the pole section to be detected in a high-voltage line through an unmanned aerial vehicle carrying a multi-lens visible light camera, and constructing a pole section inspection three-dimensional model according to the line image data.
S220, acquiring the initial three-dimensional model data of the capital construction corresponding to the high-voltage line to-be-detected pole segment.
And the initial three-dimensional model is constructed according to initial model data handed over by the construction project, and is a three-dimensional original model of the full-range high-voltage line. Initial model image data of line oblique photography that can gather through unmanned aerial vehicle, or the initial model data of gathering when the laser radar who carries on through unmanned aerial vehicle scans the line fast construct the initial three-dimensional model of capital construction, and this embodiment does not do specific limit to the collection mode of initial model data.
And acquiring the corresponding capital construction initial three-dimensional model data according to the to-be-detected pole segment of the high-voltage line. For example, if the pole segments to be detected in the high-voltage line are the pole segment a and the pole segment B, the data of the initial three-dimensional model of the capital construction between the pole segment a and the pole segment B are also selected from the initial three-dimensional model of the capital construction.
And S230, extracting tower point cloud data, wire point cloud data and ground point cloud data from the initial three-dimensional model data.
Point cloud data, which refers to data recorded in the form of points by the scan material, may exist in the data format of ". las". Each point cloud data not only contains corresponding three-dimensional coordinates, but also can comprise multi-echo information, intensity information, scanning angles, classification information, flight navigation band information, flight attitude information, project information, GPS information, data point color information and the like.
The initial three-dimensional model data of the capital construction at least comprises tower point cloud data, wire point cloud data, ground point cloud data and the like. And extracting tower point cloud data, wire point cloud data and ground point cloud data in the initial three-dimensional model data of the infrastructure, for example, segmenting the data by adopting a filtering mode, a resampling mode and the like to extract target point cloud data.
It should be noted that, in the data acquisition process, a situation that part of data is missing or damaged may occur, so that the missing data may be repaired before tower point cloud data, wire point cloud data, and ground point cloud data in the initial three-dimensional model data of the infrastructure are extracted, any data repair means in the prior art may be adopted to process the missing or damaged point cloud data, for example, data may be processed by data repair software, which is not specifically limited in this embodiment.
For example, extracting tower point cloud data and wire point cloud data from the initial three-dimensional model data may include:
and extracting tower point cloud data and wire point cloud data from the initial three-dimensional model data of the capital construction according to the marks corresponding to the tower and the wire respectively.
Marking means marking data in some form or means, such as manual marking, or marking by using an image processing technology, etc., so as to distinguish and classify different data, and specifically marking data in the form of a target object outline, etc.
When the tower point cloud data and the wire point cloud data are extracted from the initial three-dimensional model data of the capital construction, the corresponding tower point cloud data and the corresponding wire point cloud data can be extracted by adopting a frame selection or point selection mode according to the marks corresponding to the tower and the wire.
For example, extracting ground point cloud data in the initial three-dimensional model data may include:
determining a sphere area which takes one data point selected from the initial three-dimensional model data of the capital construction as a sphere center and takes a second preset distance as a radius;
taking the data point with the lowest height in the sphere area as a ground reference point;
and extracting data points of which the elevation distance from the ground datum point is less than a preset elevation threshold value from the initial three-dimensional model data of the capital construction to serve as ground points so as to obtain ground point cloud data.
In this embodiment, the second predetermined distance refers to a radius of a spherical space region, and a spherical space region can be defined according to the radius for determining qualified data points in the space region. The second predetermined distance may be selected according to an empirical value.
The ground reference point refers to a reference point corresponding to the ground, which is determined according to a certain selection rule in a region, and is used for screening ground points.
The preset elevation threshold value is a specific numerical value used for comparing the distance between the elevation value of the data point in the initial three-dimensional model data and the elevation value of the ground reference point, when the distance between the elevation value of the data point in the initial three-dimensional model data and the elevation value of the ground reference point is smaller than the preset elevation threshold value, the data point can be determined to be a ground point, and then corresponding ground point cloud data is extracted. The preset elevation threshold value can be set according to the density of the point cloud data and the geographic related characteristics.
Any data point in the initial three-dimensional model data of the capital construction is selected as a sphere center, a sphere with a second preset distance as a radius is created, points in a sphere range are searched, the data point with the lowest elevation in the sphere range can be selected as a ground reference point, then the data points in the initial three-dimensional model data of the capital construction are classified, the data point with the elevation distance from the ground reference point being smaller than a preset elevation threshold value is used as a ground point, and therefore ground point cloud data in the initial three-dimensional model data of the capital construction can be extracted.
For example, any data point with three-dimensional coordinates (x) is selected as the sphere center in the initial three-dimensional model data0,y0,z0) At a second predetermined distance r2For the radius, a sphere area is created, whose extent can be expressed as: (x-x)0)2+(y-y0)2+(z-z0)2≤r2 2Selecting a data point within the sphere having the lowest elevation, i.e., the smallest z value, will be associated with zminThe corresponding data points are used as ground reference points; then setting an elevation threshold value as f, and extracting data points with an elevation distance less than a preset elevation threshold value f from a ground datum point as ground points, namely, the data points satisfy | z-zminThe data points of the condition of | less than f can be determined as ground points, and ground point cloud data in the corresponding initial three-dimensional model data of the capital construction is extracted.
S240, determining a tree barrier risk area corresponding to the to-be-detected pole section of the high-voltage line according to the wire point cloud data.
And determining a tree barrier risk area corresponding to the high-voltage line to-be-detected pole section according to the extracted wire point cloud data in the constructed initial three-dimensional model data.
For example, a distance value interval range can be divided as a tree barrier risk area corresponding to the high-voltage line to-be-detected pole section according to the three-dimensional coordinates of the point cloud data of the conducting wire in the extracted initial three-dimensional model data of the capital construction combined with the values of the distances from the conducting wire in the vertical direction of the data points in the high-voltage line to-be-detected pole section.
For example, determining a tree barrier risk area corresponding to a to-be-detected pole section in a high-voltage line according to the wire point cloud data may include:
and taking the lead corresponding to the lead point cloud data as a central line, and taking a cylindrical area with a first preset distance as a radius as a tree barrier risk area corresponding to the high-voltage line to-be-detected pole section.
And the first preset distance refers to the minimum safe distance between the target object and the lead, and if the distance between the target object and the lead is less than the first preset distance, the target object can be determined to fall in the tree barrier risk area. Wherein, first preset distance can patrol and examine standard setting according to the electric power industry.
According to the wire point cloud data in the initial three-dimensional model of the capital construction, a cylinder area is constructed by taking a wire corresponding to the wire point cloud data as a central line and taking a first preset distance as a radius, the cylinder area can be taken as a tree barrier risk area, and then the tree barrier risk area corresponding to the to-be-detected pole section of the high-voltage line is determined.
For example, a conducting wire between any first base tower and any second base tower in the initial three-dimensional model of the capital construction can be selected as a central line, wherein the three-dimensional coordinate of the vertex corresponding to the first base tower is (a)1,b1,c1) The three-dimensional coordinate of the vertex corresponding to the second base tower is (a)2,b2,c2) At a first predetermined distance r1A cylinder area is created for the radius, and the equation of a straight line connected with the two base towers is the equation of the central line of the cylinder, namely
Wherein the y-axis coordinate and the z-axis coordinate may be expressed as:
and
the corresponding cylinder area can be expressed as:
the cylindrical area represented by the expression is a tree barrier risk area, the data points falling in the area are tree barrier risk points, and then the tree barrier risk area corresponding to the high-voltage line row to-be-detected pole section can be determined according to the high-voltage line row to-be-detected pole section.
And S250, establishing a three-dimensional model of the tree obstacle risk area according to the tower point cloud data, the wire point cloud data, the ground point cloud data and the tree obstacle risk area.
And establishing a tree barrier risk area three-dimensional model according to the tower point cloud data, the wire point cloud data and the ground point cloud data in the initial three-dimensional model of the capital construction and the constructed tree barrier risk area corresponding to the pole section to be detected in the high-voltage line, wherein the tree barrier risk area is marked in the tree barrier risk area three-dimensional model.
S260, integrating the three-dimensional tree obstacle patrol model and the three-dimensional tree obstacle risk area model, and detecting point cloud data of the three-dimensional tree obstacle patrol model according to the tree obstacle risk area to determine tree obstacle risk points.
As a preferred embodiment, when a cylindrical region is constructed as a tree barrier risk region, and tree barrier risk points are determined, three-dimensional coordinates of point cloud data in a three-dimensional model of a pole section inspection can be extracted, a vertex of a first base tower selected when the cylindrical region is constructed is used as a coordinate origin, relative coordinates of point cloud data in the three-dimensional model of the pole section inspection corresponding to the coordinate origin are determined, whether the relative coordinates of the point cloud data meet a cylindrical region expression is then judged, if yes, a point corresponding to the coordinate can be determined as a tree barrier risk point, a transverse distance value of the point relative to a vertex of the first base tower, namely an x-axis coordinate value, can be calculated, and transverse distance values of all the tree barrier risk points relative to the vertex of the first base tower can be obtained through traversal, so that specific positions of all the tree barrier risk points can be determined.
For those parts of this embodiment that are not explained in detail, reference is made to the aforementioned embodiments, which are not repeated herein.
According to the technical scheme, the tree barrier risk area corresponding to the pole section to be detected in the high-voltage line is determined by utilizing the capital construction initial three-dimensional model data, the tree barrier risk area three-dimensional model is established according to the extracted tower point cloud data, the extracted wire point cloud data, the extracted ground point cloud data and the tree barrier risk area, the tree barrier risk point detection can be carried out on the pole section to be inspected by repeatedly utilizing the tree barrier risk area three-dimensional model, the workload is reduced, and the working efficiency is improved; and the model is integrated with the pole section inspection three-dimensional model, and the tree barrier risk points are determined according to the point cloud data of the tree barrier risk area detection pole section inspection three-dimensional model, so that the detection efficiency and accuracy of the tree barrier risk points of the high-voltage line are improved.
EXAMPLE III
Fig. 3a is a flowchart of a method for detecting a high-voltage line tree barrier risk point according to a third embodiment of the present invention, fig. 3b is a schematic diagram of a three-dimensional model for inspecting a pole section according to the third embodiment of the present invention, fig. 3c is a schematic diagram of an initial three-dimensional model for capital construction according to the third embodiment of the present invention, fig. 3d is a schematic diagram of a three-dimensional model for a tree barrier risk area according to the third embodiment of the present invention, fig. 3e is a schematic diagram of a determined tree barrier risk point corresponding to a pole section to be detected according to the third embodiment of the present invention, and fig. 3f is a schematic diagram of a top view of a high-voltage line corresponding to a pole section to be detected according to the third embodiment of the present invention. The embodiment is embodied on the basis of the above embodiment, wherein a top view of the high-voltage line corresponding to the pole segment to be detected in the high-voltage line can be obtained, and the transverse distance data between each barrier risk point and the preset pole tower is determined.
As shown in fig. 3a, the method for detecting a high-voltage line tree obstacle risk point provided in this embodiment specifically includes:
s310, collecting line image data of the pole section to be detected in the high-voltage line through an unmanned aerial vehicle carrying a multi-lens visible light camera, and constructing a pole section inspection three-dimensional model according to the line image data.
For example, as shown in the pole patrol three-dimensional model in fig. 3b, an unmanned aerial vehicle carrying a multi-lens visible light camera can perform fast scanning above the high-voltage transmission line, and the pole patrol three-dimensional model is established by patrolling acquired line image data through a fast channel. The precision of the acquired line image data can be related to the number of lenses of the visible light cameras carried by the unmanned aerial vehicle, the precision of the line image data acquired by the single-lens visible light camera is low, and the precision of the line image data acquired by the multi-lens visible light camera is high.
S320, acquiring the initial three-dimensional model data of the capital construction corresponding to the high-voltage line to-be-detected pole segment, and extracting the point cloud data of the pole tower, the point cloud data of the conducting wire and the point cloud data of the ground.
For example, as shown in the schematic diagram of the initial three-dimensional model of the capital construction corresponding to the pole segment to be detected in the high-voltage line row provided in fig. 3c, the initial three-dimensional model data of the capital construction can be obtained, and the point cloud data of the pole tower, the point cloud data of the wire and the point cloud data of the ground can be extracted.
S330, determining a tree barrier risk area corresponding to the pole section to be detected in the high-voltage line according to the wire point cloud data, and establishing a three-dimensional model of the tree barrier risk area according to the pole and tower point cloud data, the wire point cloud data, the ground point cloud data and the tree barrier risk area.
For example, a tree obstacle risk area corresponding to a pole section to be detected in a high-voltage line is determined according to the wire point cloud data, as shown in a cylinder area in fig. 3d, wherein the circle center of the circular area is the top point of the pole tower, the radius of the cylinder area is the minimum safe distance between the target object and the wire, and the formed cylinder area is the tree obstacle risk area. A tree barrier risk area three-dimensional model can be established according to the tower point cloud data, the wire point cloud data, the ground point cloud data and the tree barrier risk area, as shown in the tree barrier risk area three-dimensional model in fig. 3 d.
S340, integrating the three-dimensional model of the rod section patrol and the three-dimensional model of the tree obstacle risk area, and detecting point cloud data of the three-dimensional model of the rod section patrol according to the tree obstacle risk area to determine tree obstacle risk points.
For example, after the three-dimensional model of the pole section patrol is integrated with the three-dimensional model of the tree barrier risk area, the point cloud data of the three-dimensional model of the pole section patrol can be detected according to the tree barrier risk area, so as to determine the tree barrier risk points, as shown in fig. 3e, where a box in fig. 3e contains the determined tree barrier risk points.
And S350, acquiring a top view of the high-voltage line corresponding to the pole section to be detected in the high-voltage line, and determining the transverse distance data between each tree obstacle risk point and a preset pole tower.
The top view of the high-voltage line refers to a scanned image obtained by scanning the high-voltage line over the high-voltage line, wherein the scanned image can be automatically generated in computer software through point cloud data.
For example, as shown in fig. 3f, the transverse distance between the barrier risk point and a preset tower may be determined according to a top view of a high-voltage line, so that the barrier risk point may be located to determine specific position information of the barrier risk point.
For those parts of this embodiment that are not explained in detail, reference is made to the aforementioned embodiments, which are not repeated herein.
According to the technical scheme, the tree barrier risk points are determined by integrating the three-dimensional tree barrier patrol model and the three-dimensional tree barrier risk area model and detecting point cloud data of the three-dimensional tree barrier patrol model according to the tree barrier risk area, so that the detection efficiency and accuracy of the tree barrier risk points in the high-voltage line are improved; and a high-voltage line top view corresponding to the high-voltage line to-be-detected pole section can be acquired, the transverse distance data between each tree barrier risk point and the preset pole tower is determined, the specific position of the tree barrier risk point is further determined, and the positioning of the tree barrier risk point is realized.
Example four
Fig. 4 is a schematic structural diagram of a device for detecting a high-voltage line tree barrier risk point according to a fourth embodiment of the present invention, which is applicable to a case where the high-voltage line tree barrier risk point is detected based on image data, and the device can be implemented in a software and/or hardware manner, and can be generally integrated in a computer device.
As shown in fig. 4, the device for detecting the high-voltage line tree obstacle risk point specifically includes: the tree obstacle navigation system comprises a pole section inspection three-dimensional model building module 410, a tree obstacle risk area three-dimensional model obtaining module 420 and a tree obstacle risk point determining module 430. Wherein the content of the first and second substances,
the pole section inspection three-dimensional model building module 410 is arranged for acquiring line image data of a pole section to be detected in a high-voltage line through an unmanned aerial vehicle carrying a multi-lens visible light camera and building a pole section inspection three-dimensional model according to the line image data;
the tree barrier risk area three-dimensional model acquisition module 420 is configured to acquire a pre-established tree barrier risk area three-dimensional model corresponding to the to-be-detected pole section of the high-voltage line, wherein a tree barrier risk area is marked in the tree barrier risk area three-dimensional model;
and the tree barrier risk point determining module 430 is configured to integrate the three-dimensional tree barrier inspection model and the three-dimensional tree barrier risk area model, and detect point cloud data of the three-dimensional tree barrier inspection model according to the tree barrier risk area to determine tree barrier risk points.
According to the technical scheme provided by the embodiment of the invention, the unmanned aerial vehicle carrying the multi-lens visible light camera is used for acquiring the line image data of the high-voltage line to-be-detected pole section and constructing the pole section inspection three-dimensional model, compared with a laser radar device, the cost investment of the data acquisition device is greatly reduced, the data acquisition and processing time is reduced, and the fast construction of the pole section inspection three-dimensional model is realized; the method comprises the steps of obtaining a pre-established tree barrier risk area three-dimensional model containing a tree barrier risk area identification corresponding to a pole section to be detected in a high-voltage line, integrating the pole section inspection three-dimensional model with the tree barrier risk area three-dimensional model, determining tree barrier risk points according to point cloud data of the tree barrier risk area detection pole section inspection three-dimensional model, achieving the purpose of rapidly positioning the tree barrier risk points according to inspection requirements, improving the detection efficiency and accuracy of the tree barrier risk points in the high-voltage line, repeatedly using the tree barrier risk area three-dimensional model to detect the tree barrier risk points, reducing the workload and improving the working efficiency.
Further, the tree obstacle risk point determining module 430 is specifically configured to:
and judging whether target point cloud data falling into the tree barrier risk area exists in the three-dimensional model of the pole section inspection, if so, determining tree barrier risk points according to the target point cloud data.
As an optional implementation, the apparatus further includes: a capital construction initial three-dimensional model data acquisition module, a point cloud data extraction module, a tree barrier risk area determination module and a tree barrier risk area three-dimensional model establishment module, wherein,
the capital construction initial three-dimensional model data acquisition module is set to acquire capital construction initial three-dimensional model data corresponding to the high-voltage line row pole section to be detected before acquiring a pre-established tree barrier risk region three-dimensional model corresponding to the high-voltage line row pole section to be detected;
the point cloud data extraction module is used for extracting tower point cloud data, wire point cloud data and ground point cloud data from the initial three-dimensional model data of the capital construction;
the tree barrier risk area determining module is used for determining a tree barrier risk area corresponding to the to-be-detected pole section of the high-voltage line according to the wire point cloud data;
and the tree barrier risk area three-dimensional model establishing module is used for establishing the tree barrier risk area three-dimensional model according to the tower point cloud data, the wire point cloud data and the ground point cloud data and the tree barrier risk area.
Further, a tree obstacle risk area determination module is specifically configured to:
and taking the lead corresponding to the lead point cloud data as a central line, and taking a cylindrical area with a first preset distance as a radius as a tree barrier risk area corresponding to the high-voltage line to-be-detected pole section.
Further, the point cloud data extraction module is specifically configured to:
determining a sphere area which takes one data point selected from the initial three-dimensional model data of the capital construction as a sphere center and takes a second preset distance as a radius;
taking the data point with the lowest height in the sphere area as a ground reference point;
and extracting data points of which the elevation distance from the ground datum points is smaller than a preset elevation threshold value from the initial three-dimensional model data of the capital construction to serve as ground points so as to obtain ground point cloud data.
Further, the point cloud data extraction module is specifically configured to:
and extracting tower point cloud data and wire point cloud data from the initial three-dimensional model data of the capital construction according to marks corresponding to the tower and the wire respectively.
As an optional implementation, the apparatus further includes: the detection report generation module is used for respectively determining transverse distance data between each tree barrier risk point and a preset tower after determining the tree barrier risk points according to the target point cloud data; and generating a tree barrier risk point detection report corresponding to the to-be-detected pole section of the high-voltage line according to each tree barrier risk point and the corresponding transverse distance data.
The detection device for the high-voltage line tree obstacle risk points can execute the detection method for the high-voltage line tree obstacle risk points provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method for the high-voltage line tree obstacle risk points.
EXAMPLE five
Fig. 5 is a schematic diagram of a hardware structure of a computer device according to a fifth embodiment of the present invention. FIG. 5 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention. The computer device 12 shown in FIG. 5 is only an example and should not bring any limitations to the functionality or scope of use of embodiments of the present invention.
As shown in FIG. 5, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing a method for detecting a high-voltage line fault risk point provided by the embodiment of the present invention. That is, the processing unit implements, when executing the program:
the method comprises the steps that an unmanned aerial vehicle carrying a multi-lens visible light camera is used for collecting line image data of a pole section to be detected in a high-voltage line, and a pole section inspection three-dimensional model is built according to the line image data; acquiring a pre-established tree barrier risk area three-dimensional model corresponding to the high-voltage line to-be-detected pole section, wherein the tree barrier risk area is marked in the tree barrier risk area three-dimensional model; and integrating the three-dimensional tree obstacle patrol model and the three-dimensional tree obstacle risk area model, and detecting point cloud data of the three-dimensional tree obstacle patrol model according to the tree obstacle risk area to determine tree obstacle risk points.
EXAMPLE six
The sixth embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a method for detecting a high-voltage line tree obstacle risk point, as provided in all embodiments of the present invention: that is, the program when executed by the processor implements:
the method comprises the steps that an unmanned aerial vehicle carrying a multi-lens visible light camera is used for collecting line image data of a pole section to be detected in a high-voltage line, and a pole section inspection three-dimensional model is built according to the line image data; acquiring a pre-established tree barrier risk area three-dimensional model corresponding to the high-voltage line to-be-detected pole section, wherein the tree barrier risk area is marked in the tree barrier risk area three-dimensional model; and integrating the three-dimensional tree obstacle patrol model and the three-dimensional tree obstacle risk area model, and detecting point cloud data of the three-dimensional tree obstacle patrol model according to the tree obstacle risk area to determine tree obstacle risk points.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for detecting tree obstacle risk points of a high-voltage line is characterized by comprising the following steps:
the method comprises the steps that an unmanned aerial vehicle carrying a multi-lens visible light camera is used for collecting line image data of a pole section to be detected in a high-voltage line, and a pole section inspection three-dimensional model is built according to the line image data;
acquiring a pre-established tree barrier risk area three-dimensional model corresponding to the high-voltage line to-be-detected pole section, wherein the tree barrier risk area is marked in the tree barrier risk area three-dimensional model;
and integrating the three-dimensional tree obstacle patrol model and the three-dimensional tree obstacle risk area model, and detecting point cloud data of the three-dimensional tree obstacle patrol model according to the tree obstacle risk area to determine tree obstacle risk points.
2. The method of claim 1, wherein detecting point cloud data of the three-dimensional model of the pole segment tour from the barrier risk area to determine barrier risk points comprises:
and judging whether target point cloud data falling into the tree barrier risk area exists in the three-dimensional model of the pole section inspection, if so, determining tree barrier risk points according to the target point cloud data.
3. The method as claimed in claim 1, before obtaining the pre-established tree barrier risk area three-dimensional model corresponding to the pole segment to be detected in the high-voltage line, further comprising:
acquiring capital construction initial three-dimensional model data corresponding to the high-voltage line row rod section to be detected;
extracting tower point cloud data, wire point cloud data and ground point cloud data from the initial three-dimensional model data of the capital construction;
determining a tree barrier risk area corresponding to the high-voltage line to-be-detected pole section according to the wire point cloud data;
and establishing a three-dimensional model of the tree barrier risk area according to the tower point cloud data, the wire point cloud data, the ground point cloud data and the tree barrier risk area.
4. The method of claim 3, wherein determining a tree barrier risk area corresponding to the high-voltage line to-be-detected pole section according to the wire point cloud data comprises:
and taking the lead corresponding to the lead point cloud data as a central line, and taking a cylindrical area with a first preset distance as a radius as a tree barrier risk area corresponding to the high-voltage line to-be-detected pole section.
5. The method of claim 3, wherein extracting ground point cloud data in the baseline initial three-dimensional model data comprises:
determining a sphere area which takes one data point selected from the initial three-dimensional model data of the capital construction as a sphere center and takes a second preset distance as a radius;
taking the data point with the lowest height in the sphere area as a ground reference point; and extracting data points of which the elevation distance from the ground datum points is smaller than a preset elevation threshold value from the initial three-dimensional model data of the capital construction to serve as ground points so as to obtain ground point cloud data.
6. The method of claim 3, wherein extracting tower point cloud data and wire point cloud data from the baseline initial three-dimensional model data comprises:
and extracting tower point cloud data and wire point cloud data from the initial three-dimensional model data of the capital construction according to marks corresponding to the tower and the wire respectively.
7. The method of claim 2, after determining a tree barrier risk point from the target point cloud data, further comprising:
respectively determining transverse distance data between each tree obstacle risk point and a preset tower;
and generating a tree barrier risk point detection report corresponding to the to-be-detected pole section of the high-voltage line according to each tree barrier risk point and the corresponding transverse distance data.
8. The utility model provides a detection apparatus for high-voltage line goes tree obstacle risk point which characterized in that includes:
the pole section inspection three-dimensional model building module is used for acquiring line image data of a pole section to be detected in a high-voltage line through an unmanned aerial vehicle carrying a multi-lens visible light camera and building a pole section inspection three-dimensional model according to the line image data;
the tree barrier risk area three-dimensional model acquisition module is set to acquire a pre-established tree barrier risk area three-dimensional model corresponding to the to-be-detected pole section of the high-voltage line, wherein the tree barrier risk area three-dimensional model is marked with a tree barrier risk area;
and the tree barrier risk point determining module is configured to integrate the three-dimensional tree section inspection model and the three-dimensional tree barrier risk area model, and detect point cloud data of the three-dimensional tree section inspection model according to the tree barrier risk area to determine tree barrier risk points.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-7 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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| CN114119606A (en) * | 2022-01-20 | 2022-03-01 | 国网江西省电力有限公司电力科学研究院 | Intelligent tree obstacle hidden danger analysis method based on visible light photo power line coloring |
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