Pole tower main material deflection calculation method and device based on point cloud, equipment and medium

Abstract

The invention provides a point cloud-based tower main material deflection calculation method and device, equipment and a medium, a laser point cloud technology is used, only a laser radar, a processor and the like are needed, redundant hardware is not needed, and the system is simpler and more convenient; meanwhile, the deflection of the tower main material can be calculated in a non-contact mode based on laser point cloud data, the detection precision and the processing efficiency are effectively improved in combination with a used calculation scheme, the influence of point cloud noisy points is considered, noisy point filtering is carried out on the main material point cloud, and the robustness of a detection result is better. In addition, the scheme disclosed by the invention does not need to manually climb a tower to arrange a heavy hammer and erect a total station, so that the workload is greatly reduced, and the labor cost is saved.

Description

Technical Field

[0001] The present invention relates to the field of electric power, and in particular to a method, device, equipment, and medium for calculating the deflection of a main material of a tower based on point cloud. Background Art

[0002] At present, with the rapid development of my country's industrial technology, the demand and supply of electricity are also increasing, and the capacity requirements for power transmission are also increasing. Therefore, the voltage level of power transmission is constantly increasing. With the increase of voltage level, the height and weight of the tower are constantly increasing, which easily causes problems such as "deformation" of the main material of the tower.

[0003] The tower deflection is the maximum distance that the main material structure of the tower deflects from its connecting line after being subjected to high load for a long time. However, the existing technology has problems in calculating the tower deflection, such as numerous hardware equipment, high labor costs, and low accuracy and efficiency. Summary of the invention

[0004] The present disclosure at least provides a method, device, equipment, and medium for calculating the deflection of the main material of a tower based on point cloud to solve at least one of the above-mentioned technical problems.

[0005] According to one aspect of the present disclosure, a method for calculating the deflection of a main material of a tower based on a point cloud is provided, comprising:

[0006] Acquire laser point cloud data in the target area, and perform segmentation processing on the laser point cloud data based on the center point of each marked tower top to obtain multiple groups of segmentation point cloud data; and perform point cloud classification processing on each group of segmentation point cloud data respectively;

[0007] For each pole tower, the center point corresponding to the pole tower is connected with the center point corresponding to the previous pole tower and the center point corresponding to the next pole tower, and the bisector of the formed angle is used as the horizontal line direction of the pole tower, and the line direction perpendicular to the horizontal line direction is used as the longitudinal line direction of the pole tower;

[0008] For each pole tower, extract the pole tower point cloud data corresponding to the pole tower from at least one set of cut-off point cloud data corresponding to the pole tower according to the center point corresponding to the pole tower, the preset point cloud extraction range and the result of the point cloud classification processing, and divide the extracted pole tower point cloud data into four quadrants based on the along-line direction and the transverse line direction of the pole tower;

[0009] For each pole tower, the pole tower point cloud data in each quadrant of the pole tower is layered according to the first preset layering height; for each layer of point cloud data in each quadrant, the projection value of each point in the layer of point cloud data in the quadrant, in the along-line direction and the transverse line direction, is calculated, and the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value is calculated, and the point corresponding to the minimum horizontal distance is used as the main material point of the layer of point cloud data in the quadrant;

[0010] For each pole tower, the main material points of the pole tower in each quadrant are layered in the vertical direction according to the second preset layering height; for each quadrant, based on the horizontal distance between each layer of the main material points in the quadrant and the center point corresponding to the pole tower, the height of the pole tower cross arm position corresponding to the quadrant is determined, and the main material points in the quadrant that are located above the height of the pole tower cross arm position are removed, and the noise points of the main material points in the quadrant are filtered out;

[0011] For each pole tower, the deflection straight line of the pole tower in each quadrant is determined according to the highest main material point and the lowest main material point of the pole tower in each quadrant; for each quadrant, the main material point in the quadrant that is farthest from the deflection straight line is determined, and the distance between the farthest main material point and the deflection straight line is used as the target deflection value of the main material of the pole tower in the quadrant.

[0012] In a possible implementation, the laser point cloud data is subjected to a file-slicing process based on the center point of each marked top of the tower to obtain multiple sets of file-slicing point cloud data, including:

[0013] For every two adjacent pole towers, based on the center points corresponding to the two adjacent pole towers, determine a pole tower connection line of the two adjacent pole towers;

[0014] Determine the position of the cut-off rectangle according to the pole tower line of the two adjacent pole towers, the extension distance on both sides of the pole tower line, and the width of the pole tower channel;

[0015] The point cloud data located within the cutting rectangle is taken as a group of cutting point cloud data.

[0016] In a possible implementation, the extracting tower point cloud data is divided into four quadrants based on the along-line direction and the transverse-line direction of the tower, including:

[0017] Taking the center point corresponding to the pole tower as the reference point, calculate the projection value of each point in the pole tower point cloud data corresponding to the pole tower in the along-line direction and the transverse-line direction;

[0018] According to the positive and negative values ​​of the projection value, the tower point cloud data corresponding to the tower is divided into four quadrants.

[0019] In a possible implementation, calculating the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value includes:

[0020] For each point in the layer of point cloud data, the projection value of the point in the quadrant, in the along-line direction and in the transverse-line direction are calculated respectively, and based on the determined projection value, the horizontal distance from the point to the point corresponding to the maximum projection value is calculated.

[0021] In a possible implementation manner, determining the height of the cross arm position of the tower corresponding to the quadrant based on the horizontal distance from the main material point of each layer in the quadrant to the center point corresponding to the tower includes:

[0022] For each layer of main material points, calculate the horizontal distance from each point in the main material points of the layer to the center point corresponding to the tower, and take the average of the horizontal distances corresponding to each main material point as the horizontal distance from the main material point of the layer to the center point corresponding to the tower;

[0023] In the vertical order from low to high, when the difference in the horizontal distances corresponding to the main material points of two adjacent layers is greater than the preset value, the height of the main material points of the next layer between the two adjacent layers is used as the height of the cross arm position of the tower corresponding to the quadrant.

[0024] In a possible implementation manner, filtering out noise points of the main material points in the quadrant includes:

[0025] The main material points in the quadrant are layered according to the third preset layer height;

[0026] For each layer of main material points, a straight line is fitted using the random sampling consensus method, and the main material points whose distance from the fitted straight line is greater than a preset distance are treated as noise points and filtered out.

[0027] In a possible implementation, the above-mentioned method for calculating the deflection of the main material of the tower based on point cloud further includes:

[0028] For each pole tower in each quadrant, the ratio of the target deflection value of the main material of the pole tower in the quadrant to the length of the line segment corresponding to the highest main material point and the lowest main material point of the pole tower in the quadrant is used as the deformation rate of the main material of the pole tower in the quadrant.

[0029] According to another aspect of the present disclosure, a point cloud-based tower main material deflection calculation device is provided, comprising:

[0030] The point cloud acquisition and classification module is used to obtain the laser point cloud data in the target area, and based on the center point of each marked tower top, the laser point cloud data is cut to obtain multiple groups of cut point cloud data; and each group of cut point cloud data is respectively subjected to point cloud classification processing;

[0031] A direction determination module is used to connect, for each pole tower, the center point corresponding to the pole tower with the center point corresponding to the previous pole tower and the center point corresponding to the next pole tower, respectively, and use the bisector of the formed angle as the horizontal line direction of the pole tower, and use the line direction perpendicular to the horizontal line direction as the along-line direction of the pole tower;

[0032] A quadrant segmentation module is used to extract the tower point cloud data corresponding to each tower from at least one set of cut-off point cloud data corresponding to the tower according to the center point corresponding to the tower, the preset point cloud extraction range and the result of the point cloud classification processing, and to segment the extracted tower point cloud data into four quadrants based on the along-line direction and the transverse line direction of the tower;

[0033] The main material point determination module is used to, for each tower, perform layered processing on the tower point cloud data in each quadrant of the tower according to a first preset layering height; for each layer of point cloud data in each quadrant, respectively calculate the projection value of each point in the layer of point cloud data in the quadrant, in the along-line direction and the transverse line direction, and calculate the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value, and use the point corresponding to the minimum horizontal distance as the main material point of the layer of point cloud data in the quadrant;

[0034] The main material point filtering module is used to, for each pole tower, perform layering processing on the main material points in each quadrant of the pole tower in the vertical direction according to the second preset layering height; for each quadrant, based on the horizontal distance between each layer of the main material points in the quadrant and the center point corresponding to the pole tower, determine the height of the pole tower cross arm position corresponding to the quadrant, and remove the main material points in the quadrant that are located above the height of the pole tower cross arm position, and filter out the noise points of the main material points in the quadrant;

[0035] The deflection determination module is used to determine the deflection straight line of each pole tower in each quadrant according to the highest main material point and the lowest main material point of the pole tower in each quadrant; for each quadrant, determine the main material point in the quadrant that is farthest from the deflection straight line, and use the distance between the farthest main material point and the deflection straight line as the target deflection value of the main material of the pole tower in the quadrant.

[0036] According to another aspect of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor implements any of the above methods when executing the computer program.

[0037] According to another aspect of the present disclosure, a computer-readable storage medium is provided, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, any of the above-mentioned methods is implemented.

[0038] The point cloud-based deflection calculation method of the pole tower main material disclosed in the present invention first uses a laser radar to collect laser point cloud data in a target area, that is, uses a laser radar to collect point cloud data of a power channel, then marks the center point of the top of each pole tower, and uses the marked center point to cut and classify the laser point cloud data to separate the pole tower point cloud data; then uses the marked center point to calculate the horizontal line direction and the line direction of each pole tower; then divides the pole tower point cloud data of each pole tower into In four quadrants; then for each pole tower, the pole tower point cloud data in each quadrant is layered, the maximum projection value of each layer of pole tower point cloud data in each quadrant in the horizontal line direction and the line direction is calculated, and the point closest to the maximum projection value in the horizontal direction is calculated, and this point is used as the main material point; then for each pole tower, the main material points in each quadrant are sorted according to the vertical coordinates, and the main material points above the height of the tower cross arm position are removed according to the sudden "increase" characteristic of the distance between the cross arm point cloud and the center point; then the main material points in each quadrant are filtered for noise. Finally, according to the highest main material point and the lowest main material point in each quadrant, the deflection line of the corresponding pole tower in each quadrant is determined, and the main material point farthest from the deflection line is determined in each quadrant, and the distance between the main material point and the deflection line is used as the target deflection value of the main material of the corresponding pole tower in the corresponding quadrant.

[0039] The above-mentioned scheme disclosed in the present invention uses laser point cloud technology, which only requires laser radar, processor, etc., without redundant hardware, and the system is simpler and more convenient; at the same time, based on laser point cloud data, the present invention can calculate the deflection of the main material of the pole tower in a non-contact manner, and the calculation scheme used in combination is effectively improved. In addition, the present invention takes into account the influence of point cloud noise points, and filters out the noise points of the main material point cloud, so that the robustness of the detection result is better. In addition, the scheme disclosed in the present invention does not require manual climbing of the tower to arrange the weight hammer and set up the total station, which greatly reduces the workload and saves labor costs.

[0040] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0042] Figure 1 is a flow chart of a method for calculating the deflection of a main material of a tower based on point cloud according to the present disclosure;

[0043] Figure 2Ais a schematic diagram of determining a horizontal line direction and a longitudinal line direction according to an embodiment of the present disclosure;

[0044] Figure 2B is a schematic diagram of the cut-file point cloud data according to an embodiment of the present disclosure;

[0045] Figure 2C is a schematic diagram of removing main material points above the height of the tower cross arm position according to an embodiment of the present disclosure;

[0046] Figure 2D is a schematic diagram of performing noise filtering on main material points according to an embodiment of the present disclosure;

[0047] Figure 3 It is a structural schematic diagram of a tower main material deflection calculation device based on point cloud according to the present disclosure;

[0048] Figure 4 is a schematic structural diagram of an electronic device according to the present disclosure. DETAILED DESCRIPTION

[0049] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0050] The present invention is based on the problem that the prior art has many hardware devices, high labor costs, and low accuracy and efficiency when calculating the deflection of the pole tower. A method, device, equipment, and medium for calculating the deflection of the main material of the pole tower based on point cloud is provided. The present invention uses laser point cloud technology, which only requires laser radar, processor, etc., without redundant hardware, and the system is simpler and more convenient; at the same time, the present invention can calculate the deflection of the main material of the pole tower in a non-contact manner based on laser point cloud data, and the detection accuracy and processing efficiency are effectively improved by combining the calculation scheme used, and the present invention takes into account the influence of point cloud noise, and filters the noise of the main material point cloud, so that the robustness of the detection result is better. In addition, the scheme of the present invention does not require manual climbing of the tower to arrange the weight and set up the total station, which greatly reduces the workload and saves labor costs.

[0051] The technical solution of the present disclosure is described below through specific embodiments.

[0052] like Figure 1 As shown, it is a flow chart of the method for calculating the deflection of the main material of the tower based on the point cloud of this embodiment. The execution subject of this embodiment is a computing device or component with data processing capability. The specific method of this embodiment may include the following steps:

[0053] S110, acquiring laser point cloud data in the target area, and performing segmentation processing on the laser point cloud data based on the center point of each marked tower top to obtain multiple groups of segmentation point cloud data; and performing point cloud classification processing on each group of segmentation point cloud data respectively.

[0054] Specifically, airborne laser radar can be used to collect laser point cloud data, where the laser point cloud data includes point cloud data corresponding to wires, poles, towers, and ground objects.

[0055] After the laser point cloud data is obtained, the center point of the top of each tower can be manually marked on the laser point cloud data.

[0056] The point cloud classification processing methods include deep learning automatic classification and manual classification. Deep learning automatic classification is used first, and then manual classification is used to correct the classification results. The classification categories of point cloud classification processing include wires, poles, vegetation, and ground points.

[0057] S120. For each pole tower, connect the center point corresponding to the pole tower with the center point corresponding to the previous pole tower and the center point corresponding to the next pole tower respectively, use the bisector of the formed angle as the lateral line direction of the pole tower, and use the line direction perpendicular to the lateral line direction as the longitudinal line direction of the pole tower.

[0058] Calculating the horizontal and longitudinal directions of the pole is to prepare for calculating the deflection of the four main materials of the tower in the quadrants. Based on the force balance principle of the tower, the horizontal direction of the tower (i.e. the direction of the tower cross arm) must be located at the bisector of the angle between the line connecting the previous tower and the line connecting the next tower. Figure 2A As shown, taking the horizontal and longitudinal direction of the No. 7 pole tower as an example, the black ball point is the center point of the marked pole tower, the direction of the line connecting the previous pole tower is A, and the direction of the line connecting the next pole tower is C, then the horizontal line direction of the No. 7 pole tower is D, and from the principle of force balance, it can be known that: D = (A + C) / 2, the longitudinal direction is perpendicular to the transverse direction, so the longitudinal direction of the No. 7 pole tower can be obtained. This method can be used to obtain the horizontal and longitudinal direction of each pole tower. The above-mentioned D direction is the angle between the A and C directions.

[0059] S130. For each pole tower, extract the pole tower point cloud data corresponding to the pole tower from at least one group of cut-off point cloud data corresponding to the pole tower according to the center point corresponding to the pole tower, the preset point cloud extraction range and the result of the point cloud classification processing, and divide the extracted pole tower point cloud data into four quadrants based on the along-line direction and the transverse line direction of the pole tower.

[0060] Here, the center point corresponding to the pole tower can be used as the reference point to calculate the projection value of each point in the pole tower point cloud data corresponding to the pole tower in the along-line direction and the transverse line direction; here each point obtains a projection value in the along-line direction and the transverse line direction respectively; then, according to the positive and negative values ​​of the projection value, the pole tower point cloud data corresponding to the pole tower is divided into four quadrants.

[0061] The tower point cloud data is divided into four quadrants to facilitate the subsequent independent calculation of the deflection values ​​of the main materials in the four quadrants.

[0062] S140. For each pole tower, the pole tower point cloud data in each quadrant is layered according to a first preset layering height; for each layer of point cloud data in each quadrant, the projection value of each point in the layer of point cloud data within the quadrant, in the along-line direction and the transverse-line direction is calculated, and the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value is calculated, and the point corresponding to the minimum horizontal distance is used as the main material point of the layer of point cloud data in the quadrant.

[0063] The above-mentioned maximum projection value includes the maximum projection value in the along-line direction and the maximum projection value in the transverse line direction; the point corresponding to the maximum projection value is the point determined by using these two maximum projection values.

[0064] The above calculation of the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value can be implemented using the following steps:

[0065] For each point in the layer of point cloud data, the projection value of the point in the quadrant, in the along-line direction and in the transverse-line direction are calculated respectively, and based on the determined projection value, the horizontal distance from the point to the point corresponding to the maximum projection value is calculated.

[0066] In this step, the pole tower point cloud data is layered, and the maximum projection distance in two directions (i.e., the above-mentioned maximum projection value) is calculated for each quadrant. Then, the point closest to the point corresponding to the maximum projection distance is calculated to obtain the main material points of each layer of the pole tower point cloud data in each quadrant; finally, all the layered main material points are sorted out, and the main material points of the main materials in the four quadrants can be obtained by dividing the quadrants.

[0067] S150. For each pole tower, the main material points of the pole tower in each quadrant are layered in the vertical direction according to the second preset layering height; for each quadrant, based on the horizontal distance from each layer of the main material points in the quadrant to the center point corresponding to the pole tower, the height of the pole tower cross arm position corresponding to the quadrant is determined, and the main material points in the quadrant that are located above the height of the pole tower cross arm position are removed, and the noise points of the main material points in the quadrant are filtered out.

[0068] The second preset layer height can be set to 0.3 meters, and of course it can also be flexibly set according to the actual scenario.

[0069] Here, the height of the tower cross arm position is determined based on the characteristic that the horizontal distance from the point cloud to the center point of the tower suddenly "increases" at the location where the tower cross arm position is located. This can be achieved using the following steps:

[0070] Step 1: For each layer of main material points, calculate the horizontal distance from each point in the layer of main material points to the center point corresponding to the tower, and use the average of the horizontal distances corresponding to each main material point as the horizontal distance from the main material point of the layer to the center point corresponding to the tower.

[0071] Step 2: In the vertical order from low to high, when the difference in the horizontal distances between two adjacent layers of main material points is greater than the preset value, the height of the next layer of main material points between the two adjacent layers is used as the height of the tower cross arm position corresponding to the quadrant. The preset value here can be set to 1.5 meters, and of course it can be flexibly set according to the actual scenario.

[0072] This step can remove the point cloud above the cross arm and retain the main material points below the cross arm. Figure 2C As shown, the left side is the tower point cloud, the middle is the extracted main material points of the tower, and the right side is the main material points remaining after filtering out the main material points above the cross arm.

[0073] S160. For each pole tower, determine the deflection straight line of the pole tower in each quadrant according to the highest main material point and the lowest main material point of the pole tower in each quadrant; for each quadrant, determine the main material point in the quadrant that is farthest from the deflection straight line, and use the distance between the farthest main material point and the deflection straight line as the target deflection value of the main material of the pole tower in the quadrant.

[0074] After obtaining the target deflection value, the deformation rate of the main material can also be calculated using the target deflection value, which can be achieved using the following steps:

[0075] For each tower in each quadrant, the ratio of the target deflection value of the main material of the tower in the quadrant to the length of the line segment corresponding to the highest and lowest main material points of the tower in the quadrant is used as the deformation rate of the main material of the tower in the quadrant. The calculation formula is as follows: Rate = d / ||AC||, where d represents the target deflection value, and ||AC|| represents the length of the line segment corresponding to the highest and lowest main material points.

[0076] In some embodiments, the laser point cloud data is subjected to file-slicing processing based on the center point of each marked top of the tower to obtain multiple sets of file-slicing point cloud data, which can be specifically implemented by the following steps:

[0077] Step 1: for every two adjacent pole towers, based on the center points corresponding to the two adjacent pole towers, determine the pole tower connection line of the two adjacent pole towers.

[0078] The center point is calibrated. By connecting two center points, we can get the tower connection line of two adjacent towers, such as Figure 2B In the figure, connect the center points of tower 2 and tower 3 to obtain the tower connection line of the two towers.

[0079] Step 2: Determine the position of the cut-off rectangle according to the pole-tower line of the two adjacent pole-towers, the extension distance on both sides of the pole-tower line, and the width of the pole-tower channel.

[0080] like Figure 2B As shown, the channel distance direction of pole tower 2 and pole tower 3 is the pole tower channel width direction. The pole tower channel width is pre-set, which refers to the distance extended to both sides by the vertical line of the pole tower connection line. Figure 2B The extension distance in is the extension distance on both sides of the above-mentioned tower connection line, that is, the distance that the tower connection line extends to both sides of the tower.

[0081] The four points of a rectangle can be determined according to the pole tower connection line, the extension distance on both sides of the pole tower connection line and the width of the pole tower channel, that is, the position of the above-mentioned cutting rectangle is determined.

[0082] Step 3: taking the point cloud data within the cutting rectangle as a group of cutting point cloud data.

[0083] In some embodiments, the above-mentioned filtering out of the noise points of the main material points in the quadrant can be specifically implemented by the following steps:

[0084] Step 1: The main material points in the quadrant are layered according to the third preset layer height. The third preset layer height here can be set to 3 meters, and of course it can also be flexibly set according to the actual scene.

[0085] Step 2: For each layer of main material points, use the random sampling consensus method to fit a straight line, and treat the main material points whose distance from the fitted straight line is greater than a preset distance as noise points and filter them out.

[0086] Since extreme noise points may exist when the laser radar collects or extracts the main material points, filtering out the noise points with large deviation values ​​has a significant impact on the calculation results of the deflection value. Since the main material of the tower presents a "straight line" shape within a certain height range, the main material point cloud of each quadrant can be layered with a 3-meter height threshold, and each layer uses the random sampling consensus method to fit a straight line, and removes the noise points far from the straight line according to the straight line. The above straight line can be displayed in the form of a straight line equation; Figure 2D , the left side is the main material points of the extracted tower, and the right side is the main material points after filtering out noise points.

[0087] Based on the same inventive concept, the present disclosure provides a point cloud-based tower main material deflection calculation device, the steps performed by the components of the device are the same or similar to the above method, so similar parts are not repeated, such as Figure 3 As shown, the point cloud-based tower main material deflection calculation device of this embodiment includes:

[0088] The point cloud acquisition and classification module 310 is used to obtain the laser point cloud data in the target area, and based on the center point of each marked tower top, the laser point cloud data is cut to obtain multiple groups of cut point cloud data; and each group of cut point cloud data is subjected to point cloud classification processing.

[0089] The direction determination module 320 is used to connect the center point corresponding to each tower with the center point corresponding to the previous tower and the center point corresponding to the next tower, respectively, for each tower, and use the bisector of the formed angle as the horizontal line direction of the tower, and use the line direction perpendicular to the horizontal line direction as the longitudinal line direction of the tower.

[0090] The quadrant segmentation module 330 is used to extract the tower point cloud data corresponding to each tower from at least one group of cutting point cloud data corresponding to the tower according to the center point corresponding to the tower, the preset point cloud extraction range and the result of the point cloud classification processing, and divide the extracted tower point cloud data into four quadrants based on the along-line direction and the transverse line direction of the tower.

[0091] The main material point determination module 340 is used to, for each tower, perform layered processing on the tower point cloud data in each quadrant of the tower according to a first preset layering height; for each layer of point cloud data in each quadrant, calculate the projection value of each point in the layer of point cloud data within the quadrant, in the along-line direction and the transverse-line direction, and calculate the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value, and take the point corresponding to the minimum horizontal distance as the main material point of the layer of point cloud data in the quadrant.

[0092] The main material point filtering module 350 is used to layer the main material points in each quadrant of each tower in the vertical direction according to a second preset layering height; for each quadrant, based on the horizontal distance from each layer of the main material points in the quadrant to the center point corresponding to the tower, determine the height of the tower crossarm position corresponding to the quadrant, and remove the main material points in the quadrant that are located above the height of the tower crossarm position, and filter out the noise points of the main material points in the quadrant.

[0093] The deflection determination module 360 ​​is used to determine, for each pole tower, the deflection straight line of the pole tower in each quadrant according to the highest main material point and the lowest main material point of the pole tower in each quadrant; for each quadrant, determine the main material point in the quadrant that is farthest from the deflection straight line, and use the distance between the farthest main material point and the deflection straight line as the target deflection value of the main material of the pole tower in the quadrant.

[0094] In some embodiments, the point cloud acquisition and classification module 310 performs file-slicing processing on the laser point cloud data based on the center point of each marked tower top to obtain multiple sets of file-slicing point cloud data, and is used to:

[0095] For every two adjacent pole towers, based on the center points corresponding to the two adjacent pole towers, determine a pole tower connection line of the two adjacent pole towers;

[0096] Determine the position of the cut-off rectangle according to the pole tower line of the two adjacent pole towers, the extension distance on both sides of the pole tower line, and the width of the pole tower channel;

[0097] The point cloud data located within the cutting rectangle is taken as a group of cutting point cloud data.

[0098] In some embodiments, when the quadrant segmentation module 330 segments the extracted tower point cloud data into four quadrants based on the along-line direction and the transverse line direction of the tower, it is used to:

[0099] Taking the center point corresponding to the pole tower as the reference point, calculate the projection value of each point in the pole tower point cloud data corresponding to the pole tower in the along-line direction and the transverse-line direction;

[0100] According to the positive and negative values ​​of the projection value, the tower point cloud data corresponding to the tower is divided into four quadrants.

[0101] In some embodiments, when calculating the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value, the main material point determination module 340 is used to:

[0102] For each point in the layer of point cloud data, the projection value of the point in the quadrant, in the along-line direction and in the transverse-line direction are calculated respectively, and based on the determined projection value, the horizontal distance from the point to the point corresponding to the maximum projection value is calculated.

[0103] In some embodiments, when determining the height of the cross arm position of the tower corresponding to the quadrant based on the horizontal distance from each layer of the main material point in the quadrant to the center point corresponding to the tower, the main material point filtering module 350 is used to:

[0104] For each layer of main material points, calculate the horizontal distance from each point in the main material points of the layer to the center point corresponding to the tower, and take the average of the horizontal distances corresponding to each main material point as the horizontal distance from the main material point of the layer to the center point corresponding to the tower;

[0105] In the vertical order from low to high, when the difference in the horizontal distances corresponding to the main material points of two adjacent layers is greater than the preset value, the height of the main material points of the next layer between the two adjacent layers is used as the height of the cross arm position of the tower corresponding to the quadrant.

[0106] In some embodiments, when filtering out noise points of the main material points in the quadrant, the main material point filtering module 350 is used to:

[0107] The main material points in the quadrant are layered according to the third preset layer height;

[0108] For each layer of main material points, a straight line is fitted using the random sampling consensus method, and the main material points whose distance from the fitted straight line is greater than a preset distance are treated as noise points and filtered out.

[0109] In some embodiments, the deflection determination module 360 ​​is further configured to:

[0110] For each pole tower in each quadrant, the ratio of the target deflection value of the main material of the pole tower in the quadrant to the length of the line segment corresponding to the highest main material point and the lowest main material point of the pole tower in the quadrant is used as the deformation rate of the main material of the pole tower in the quadrant.

[0111] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a computer-readable storage medium.

[0112] Figure 4 A schematic block diagram of an example electronic device 400 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0113] like Figure 4As shown, the device 400 includes a computing unit 410, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 420 or a computer program loaded from a storage unit 480 into a random access memory (RAM) 430. In the RAM 430, various programs and data required for the operation of the device 400 can also be stored. The computing unit 410, the ROM 420, and the RAM 430 are connected to each other via a bus 440. An input / output (I / O) interface 450 is also connected to the bus 440.

[0114] A number of components in the device 400 are connected to the I / O interface 450, including: an input unit 460, such as a keyboard, a mouse, etc.; an output unit 470, such as various types of displays, speakers, etc.; a storage unit 480, such as a disk, an optical disk, etc.; and a communication unit 490, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 490 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0115] The computing unit 410 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 410 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 410 performs the various methods and processes described above. For example, in some embodiments, any of the above methods may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 480. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 400 via ROM 420 and / or a communication unit 490. When the computer program is loaded into RAM 430 and executed by the computing unit 410, one or more steps of any of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 410 may be configured to perform any of the methods described above in any other appropriate manner (e.g., by means of firmware).

[0116] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0117] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0118] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0119] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0120] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0121] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0122] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0123] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for calculating the deflection of a tower main material based on point cloud, characterized in that: include: Acquire laser point cloud data in the target area, and perform segmentation processing on the laser point cloud data based on the center point of each marked tower top to obtain multiple groups of segmentation point cloud data; and perform point cloud classification processing on each group of segmentation point cloud data respectively; For each pole tower, the center point corresponding to the pole tower is connected with the center point corresponding to the previous pole tower and the center point corresponding to the next pole tower, and the bisector of the formed angle is used as the horizontal line direction of the pole tower, and the line direction perpendicular to the horizontal line direction is used as the longitudinal line direction of the pole tower; For each pole tower, extract the pole tower point cloud data corresponding to the pole tower from at least one set of cut-off point cloud data corresponding to the pole tower according to the center point corresponding to the pole tower, the preset point cloud extraction range and the result of the point cloud classification processing, and divide the extracted pole tower point cloud data into four quadrants based on the along-line direction and the transverse line direction of the pole tower; For each pole tower, the pole tower point cloud data in each quadrant of the pole tower is respectively layered according to a first preset layer height; For each layer of point cloud data in each quadrant, the projection values ​​of each point in the layer of point cloud data in the quadrant, in the along-line direction and the transverse-line direction are calculated respectively, and the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value is calculated, and the point corresponding to the minimum horizontal distance is taken as the main material point of the layer of point cloud data in the quadrant; For each pole tower, the main material points of the pole tower in each quadrant are respectively layered in the vertical direction according to the second preset layering height; For each quadrant, based on the horizontal distance from each layer of the main material point in the quadrant to the center point corresponding to the tower, determine the height of the tower cross arm position corresponding to the quadrant, and remove the main material points in the quadrant that are located above the height of the tower cross arm position, and filter out the noise points of the main material points in the quadrant; For each pole tower, the deflection straight line of the pole tower in each quadrant is determined according to the highest main material point and the lowest main material point of the pole tower in each quadrant; for each quadrant, the main material point in the quadrant that is farthest from the deflection straight line is determined, and the distance between the farthest main material point and the deflection straight line is used as the target deflection value of the main material of the pole tower in the quadrant.

2. The method according to claim 1, characterized in that Based on the center point of each marked tower top, the laser point cloud data is subjected to file-slicing processing to obtain multiple sets of file-slicing point cloud data, including: For every two adjacent pole towers, based on the center points corresponding to the two adjacent pole towers, determine a pole tower connection line of the two adjacent pole towers; Determine the position of the cut-off rectangle according to the pole tower line of the two adjacent pole towers, the extension distance on both sides of the pole tower line, and the width of the pole tower channel; The point cloud data located within the cutting rectangle is taken as a group of cutting point cloud data.

3. The method according to claim 1, characterized in that The extracted tower point cloud data is divided into four quadrants based on the along-line direction and the transverse line direction of the tower, including: Taking the center point corresponding to the pole tower as the reference point, calculate the projection value of each point in the pole tower point cloud data corresponding to the pole tower in the along-line direction and the transverse-line direction; According to the positive and negative values ​​of the projection value, the tower point cloud data corresponding to the tower is divided into four quadrants.

4. The method according to claim 1, characterized in that: The step of calculating the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value includes: For each point in the layer of point cloud data, the projection value of the point in the quadrant, in the along-line direction and in the transverse-line direction are calculated respectively, and based on the determined projection value, the horizontal distance from the point to the point corresponding to the maximum projection value is calculated.

5. The method according to claim 1, characterized in that The determining of the height of the cross arm position of the tower corresponding to the quadrant based on the horizontal distance from the main material point of each layer in the quadrant to the center point corresponding to the tower comprises: For each layer of main material points, calculate the horizontal distance from each point in the main material points of the layer to the center point corresponding to the tower, and take the average of the horizontal distances corresponding to each main material point as the horizontal distance from the main material point of the layer to the center point corresponding to the tower; In the vertical order from low to high, when the difference in the horizontal distances corresponding to the main material points of two adjacent layers is greater than the preset value, the height of the main material points of the next layer between the two adjacent layers is used as the height of the cross arm position of the tower corresponding to the quadrant.

6. The method according to claim 1, characterized in that The filtering out the noise points of the main material points in the quadrant includes: The main material points in the quadrant are layered according to the third preset layer height; For each layer of main material points, a straight line is fitted using the random sampling consensus method, and the main material points whose distance from the fitted straight line is greater than a preset distance are treated as noise points and filtered out.

7. The method according to claim 1, characterized in that Also includes: For each pole tower in each quadrant, the ratio of the target deflection value of the main material of the pole tower in the quadrant to the length of the line segment corresponding to the highest main material point and the lowest main material point of the pole tower in the quadrant is used as the deformation rate of the main material of the pole tower in the quadrant.

8. A point cloud-based tower main material deflection calculation device, characterized in that: include: The point cloud acquisition and classification module is used to obtain the laser point cloud data in the target area, and based on the center point of each marked tower top, the laser point cloud data is cut to obtain multiple groups of cut point cloud data; and each group of cut point cloud data is respectively subjected to point cloud classification processing; A direction determination module is used to connect, for each pole tower, the center point corresponding to the pole tower with the center point corresponding to the previous pole tower and the center point corresponding to the next pole tower, respectively, and use the bisector of the formed angle as the horizontal line direction of the pole tower, and use the line direction perpendicular to the horizontal line direction as the along-line direction of the pole tower; A quadrant segmentation module is used to extract the tower point cloud data corresponding to each tower from at least one set of cut-off point cloud data corresponding to the tower according to the center point corresponding to the tower, the preset point cloud extraction range and the result of the point cloud classification processing, and to segment the extracted tower point cloud data into four quadrants based on the along-line direction and the transverse line direction of the tower; A main material point determination module is used to perform layered processing on the tower point cloud data of each tower in each quadrant according to a first preset layering height for each tower; For each layer of point cloud data in each quadrant, the projection values ​​of each point in the layer of point cloud data in the quadrant, in the along-line direction and the transverse-line direction are calculated respectively, and the horizontal distance from each point in the layer of point cloud data to the point corresponding to the maximum projection value is calculated, and the point corresponding to the minimum horizontal distance is taken as the main material point of the layer of point cloud data in the quadrant; A main material point filtering module is used to perform layering processing on the main material points of each tower in each quadrant in the vertical direction according to a second preset layering height for each tower; For each quadrant, based on the horizontal distance from each layer of the main material point in the quadrant to the center point corresponding to the tower, determine the height of the tower cross arm position corresponding to the quadrant, and remove the main material points in the quadrant that are located above the height of the tower cross arm position, and filter out the noise points of the main material points in the quadrant; The deflection determination module is used to determine the deflection straight line of each pole tower in each quadrant according to the highest main material point and the lowest main material point of the pole tower in each quadrant; for each quadrant, determine the main material point in the quadrant that is farthest from the deflection straight line, and use the distance between the farthest main material point and the deflection straight line as the target deflection value of the main material of the pole tower in the quadrant.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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