A method and system for measuring jumper sag distance

Abstract

The invention relates to the technical field of power transmission line measurement, and discloses a method and system for measuring the sag distance of a jumper. The method uses a laser radar mounted on an unmanned aerial vehicle to perform radar scanning on a target object, obtain a three-dimensional image of the target object, thereby obtaining point cloud coordinate data of the target object, and determining the point cloud coordinate distance between tower bodies of two adjacent tension towers according to the routing direction of the power transmission line. The point cloud coordinate data are separated by the point cloud coordinate distance, thereby separating a plurality of point cloud coordinate sets, and the point cloud coordinate set is used as a measurement unit, and a random sampling consistency algorithm is used to fit a jumper fitting model, and the point cloud coordinate data of the nearest tension tower body and the jumper, as well as the point cloud coordinate data of the farthest cross arm and the jumper are obtained, and the nearest distance between the tension tower body and the jumper and the farthest distance between the cross arm and the jumper are respectively calculated, thereby improving the measurement efficiency of the sag distance of the jumper and reducing the work intensity.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission line measurement, and in particular to a method and system for measuring the sag distance of a jumper. Background Art

[0002] At present, cross arms are set in tension towers to fix jumpers. However, during operation, if the sag of the conductor jumper is too small from the tower body of the tension tower or the sag is too deep, it is very easy to cause line fault tripping due to insufficient wind deviation distance or insufficient lightning resistance distance during lightning strike. The commonly used distance measurement methods for the sag of the jumper of the tension tower are manual measurement or measurement on the ground using theodolite and rangefinder. When using instruments for measurement on the ground, the position of the erected instrument, the measurement visual difference and other reasons will produce certain errors, affecting the measurement results. Moreover, this method has high work intensity and low efficiency. If this method is used for acceptance of each base, a lot of time will be wasted. Summary of the invention

[0003] The invention provides a jumper sag distance measurement method and system, which solve the technical problems of low jumper sag distance measurement efficiency and high work intensity.

[0004] In view of this, a first aspect of the present invention provides a method for measuring a jumper sag distance, comprising the following steps:

[0005] The drone is used to reach a target position above the transmission line along a preset route trajectory, and a laser radar carried by the drone is used to perform a radar scan on the target object, thereby obtaining a three-dimensional image of the target object, wherein the target object includes a tension tower body and a cross arm and a jumper connected thereto;

[0006] Converting the three-dimensional image into a point cloud image based on a point cloud coordinate system, thereby obtaining point cloud coordinate data of the target object;

[0007] Acquire the routing direction of the transmission line, determine the point cloud coordinate distance between two adjacent tension towers according to the routing direction, separate the point cloud coordinate data by the point cloud coordinate distance, thereby separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between two adjacent tension towers;

[0008] Extracting the point cloud coordinates of the jumper from the point cloud coordinate set using a random sampling consensus algorithm;

[0009] Performing parabola fitting on the point cloud coordinates of the jumper based on the routing direction of the transmission line, thereby fitting a jumper fitting model;

[0010] Projecting the jumper fitting model, the point cloud coordinate data of the cross arm, and the point cloud coordinate data of the tension tower body into the same three-dimensional point cloud coordinate system, obtaining the point cloud coordinate data of the tension tower body and the jumper that are closest, and the point cloud coordinate data of the cross arm and the jumper that are farthest away;

[0011] The shortest distance between the tower body of the tension tower and the jumper is calculated based on the point cloud coordinate data of the closest tower body and the jumper, and the farthest distance between the crossarm and the jumper is calculated based on the point cloud coordinate data of the farthest crossarm and the jumper.

[0012] Preferably, the step of obtaining the routing direction of the transmission line and the spacing distance between two adjacent tension tower bodies, separating the point cloud coordinate data, and thus separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between two adjacent tension tower bodies, comprises:

[0013] The point cloud coordinate data is subjected to point cloud filtering processing, thereby performing point cloud denoising on the point cloud coordinate data.

[0014] Preferably, the step of obtaining the routing direction of the transmission line, determining the point cloud coordinate distance between two adjacent tension tower bodies according to the routing direction, and separating the point cloud coordinate data by the point cloud coordinate distance, thereby separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between two adjacent tension tower bodies, specifically comprises:

[0015] Sorting all discrete point cloud coordinates in the point cloud coordinate data in ascending order to obtain a minimum discrete point cloud coordinate and a maximum discrete point cloud coordinate, projecting the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate onto a two-dimensional plane, connecting the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate to determine a line segment, wherein the line segment is the routing direction of the transmission line;

[0016] Projecting all discrete point cloud coordinates in the point cloud coordinate data onto the two-dimensional plane, obtaining discrete point cloud coordinates falling on the line segment, and calculating the point cloud coordinate distance between two adjacent tower bodies of the tension tower according to two adjacent discrete point cloud coordinates falling on the line segment;

[0017] The point cloud coordinate distance between the tower bodies of the two adjacent tension towers is used as a segmentation threshold to segment the point cloud coordinate data, thereby separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between the tower bodies of the two adjacent tension towers.

[0018] Preferably, the method further comprises:

[0019] Determine whether the shortest distance between the tower body of the tension tower and the jumper is less than a preset first threshold value, and if the above judgment is less than, generate an early warning signal and send it to the main station for early warning;

[0020] It is determined whether the maximum distance between the cross arm and the jumper is greater than a preset second threshold. If the above determination is greater than, an early warning signal is generated and sent to the main station for early warning.

[0021] In a second aspect, the present invention further provides a jumper sag distance measurement system, comprising:

[0022] A scanning module is used to use a drone to reach a target position above the transmission line along a preset route trajectory, and to perform radar scanning on the target object through a laser radar carried by the drone, so as to obtain a three-dimensional image of the target object, wherein the target object includes a tension tower body and a cross arm and a jumper connected thereto;

[0023] A point cloud conversion module, used to convert the three-dimensional image into a point cloud image based on a point cloud coordinate system, so as to obtain point cloud coordinate data of the target object;

[0024] A point cloud separation module is used to obtain the routing direction of the transmission line, determine the point cloud coordinate distance between the tower bodies of two adjacent tension towers according to the routing direction, separate the point cloud coordinate data according to the point cloud coordinate distance, and thus separate a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between the tower bodies of two adjacent tension towers;

[0025] A point cloud extraction module, used for extracting the point cloud coordinates of the jumper from the point cloud coordinate set by using a random sampling consistency algorithm;

[0026] A point cloud fitting module, used for performing parabola fitting on the point cloud coordinates of the jumper based on the routing direction of the transmission line, so as to obtain a jumper fitting model;

[0027] A projection module is used to project the jumper fitting model, the point cloud coordinate data of the cross arm, and the point cloud coordinate data of the tension tower body into the same three-dimensional point cloud coordinate system, and obtain the point cloud coordinate data of the tension tower body and the jumper that are closest, and the point cloud coordinate data of the cross arm and the jumper that are farthest away;

[0028] The sag calculation module is used to calculate the shortest distance between the tower body of the tension tower and the jumper based on the point cloud coordinate data of the closest tower body and the jumper, and also calculate the farthest distance between the crossarm and the jumper based on the point cloud coordinate data of the farthest crossarm and the jumper.

[0029] Preferably, the system further comprises:

[0030] The denoising module is used to perform point cloud filtering processing on the point cloud coordinate data, thereby performing point cloud denoising on the point cloud coordinate data.

[0031] Preferably, the point cloud segmentation module specifically includes:

[0032] A routing module, used for sorting all discrete point cloud coordinates in the point cloud coordinate data in ascending order to obtain a minimum discrete point cloud coordinate and a maximum discrete point cloud coordinate, projecting the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate onto a two-dimensional plane, connecting the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate to determine a line segment, wherein the line segment is the routing direction of the transmission line;

[0033] A distance calculation module is used to project all discrete point cloud coordinates in the point cloud coordinate data onto the two-dimensional plane, obtain the discrete point cloud coordinates falling on the line segment, and calculate the point cloud coordinate distance between two adjacent tower bodies of the tension tower according to two adjacent discrete point cloud coordinates falling on the line segment;

[0034] The threshold segmentation module is used to separate the point cloud coordinate data by using the point cloud coordinate distance between the tower bodies of the two adjacent tension towers as the segmentation threshold, thereby separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between the tower bodies of the two adjacent tension towers.

[0035] Preferably, the system further comprises:

[0036] A first warning module is used to determine whether the shortest distance between the tower body of the tension tower and the jumper is less than a preset first threshold value, and if the above determination is less than, a warning signal is generated and sent to the main station for warning;

[0037] The second warning module is used to determine whether the maximum distance between the cross arm and the jumper is greater than a preset second threshold. If the above determination is greater than, a warning signal is generated and sent to the main station for warning.

[0038] It can be seen from the above technical solutions that the present invention has the following advantages:

[0039] The invention uses a laser radar equipped with an unmanned aerial vehicle to perform radar scanning on a target object to obtain a three-dimensional image of the target object, converts the three-dimensional image into a point cloud image, thereby obtaining point cloud coordinate data of the target object, determines the point cloud coordinate distance between two adjacent tension tower bodies according to the routing direction of the transmission line, separates the point cloud coordinate data according to the point cloud coordinate distance, thereby separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between two adjacent tension tower bodies, and uses the point cloud coordinate set as a measurement unit, and uses a random sampling consistency algorithm to extract the point cloud coordinates of a jumper in the point cloud coordinate set, thereby fitting a jumper fitting model, and projecting the jumper fitting model, the point cloud coordinate data of a cross arm, and the point cloud coordinate data of a tension tower body into the same three-dimensional point cloud coordinate system, obtaining the point cloud coordinate data of the nearest tension tower body and the jumper, and the point cloud coordinate data of the farthest cross arm and the jumper, respectively calculating the closest distance between the tension tower body and the jumper and the farthest distance between the cross arm and the jumper, thereby improving the jumper sag distance measurement efficiency and reducing the work intensity. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flow chart of a method for measuring the sag distance of a jumper provided by an embodiment of the present invention;

[0041] Figure 2 A schematic structural diagram of a jumper sag distance measurement system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] For easier understanding, see Figure 1 The present invention provides a method for measuring the sag distance of a jumper wire, comprising the following steps:

[0044] S1. The drone arrives at the target position above the transmission line along a preset route trajectory, and the laser radar carried by the drone performs radar scanning on the target object to obtain a three-dimensional image of the target object, which includes the tower body of the tension tower and the crossarms and jumpers connected thereto.

[0045] In this embodiment, the route trajectory planning of the UAV can be set in advance. The UAV arrives at the target position above the transmission line according to the route trajectory planning. The target object is scanned by the laser radar carried by the UAV to obtain a three-dimensional image of the target object. The target object includes the tower body of the tension tower and the crossarms and jumpers connected thereto, wherein the jumpers are suspended between the side insulators on both sides of the crossarms of the tension tower.

[0046] The drone is equipped with real-time kinematic (RTK) technology. RTK technology uses a base station with precise ground coordinates to calculate the difference between the base station's precise coordinates and the real-time coordinates to obtain a comprehensive error for coordinate correction, achieving millimeter-level error accuracy, further ensuring the accuracy of the measurement.

[0047] The laser radar includes a high-precision camera, a laser transmitter, a receiver, and the system integrates a comprehensive application laser rangefinder system, a global positioning system (GPS), an inertial navigation system (INS), and related control storage units. In the laser rangefinder system, after the laser pulse is emitted by the laser transmitter, the laser reaches the surface of the object and an emission effect occurs. The emitted laser pulse signal is received by the laser receiver in the system. By measuring the number of laser pulses and combining the speed of light of 3×108, the distance A of the measured object can be obtained through the formula. Due to the influence of the atmosphere, interference from buildings, and many other factors, there is a certain error in GPS positioning. Therefore, the dynamic differential GPS system, the ground reference station and the airborne positioning work together to calculate and verify the error between the measured coordinates and the known reference station coordinates. By calibrating the error, high-precision three-dimensional coordinates can be obtained. The inertial navigation system measures the acceleration of the drone body, combines the three attitude information of the laser radar's main optical axis pitch, roll and yaw, and calculates through mathematical models to obtain its actual flight speed and flight position, so as to achieve the goal of accurately positioning the airborne drone and provide a reliable digital basis for subsequent data processing.

[0048] S2. Convert the three-dimensional image into a point cloud image based on the point cloud coordinate system, thereby obtaining point cloud coordinate data of the target object.

[0049] The point cloud coordinate system can be pre-set, and the three-dimensional image is projected into the point cloud coordinate system, so that the point cloud coordinate data of the target object can be obtained.

[0050] S3. Obtain the alignment direction of the transmission line, determine the point cloud coordinate distance between the tower bodies of two adjacent tension towers according to the alignment direction, separate the point cloud coordinate data by the point cloud coordinate distance, and thus separate a number of point cloud coordinate sets, which are the point cloud coordinate data between the tower bodies of two adjacent tension towers.

[0051] The point cloud coordinate data between the tower bodies of two adjacent tension towers include the point cloud coordinates of the tower bodies of the tension towers and the point cloud coordinates of the jumper wires.

[0052] S4. Use the random sampling consistency algorithm to extract the point cloud coordinates of the jumper in the point cloud coordinate set.

[0053] It should be noted that the jumper is distributed in the air, and the jumper point cloud data may contain other ground objects. Therefore, based on the projection distribution characteristics of the jumper points, the random sample consensus algorithm (RANSAC) can be used to achieve accurate extraction of the jumper points.

[0054] It adopts the random sampling consistency algorithm in the existing technology. Based on the characteristic that the projection of the jumper on the horizontal plane is linearly distributed, the random sampling consistency algorithm is used to eliminate the noise points that are not on the same line as the power line; then, based on the characteristic that the projection of the power line on the vertical plane is parabolic distribution, the random sampling consistency algorithm is used to fit and eliminate the noise points on the same vertical plane as the high-voltage line; finally, after eliminating all noise points, the power line point cloud is accurately extracted, which can meet the requirements of conductor sag inspection.

[0055] S5. Perform parabola fitting on the point cloud coordinates of the jumper based on the routing direction of the transmission line, thereby obtaining a jumper fitting model.

[0056] S6. Project the jumper fitting model, the point cloud coordinate data of the cross arm, and the point cloud coordinate data of the tension tower body into the same three-dimensional point cloud coordinate system, and obtain the point cloud coordinate data of the tension tower body and the jumper that are closest, as well as the point cloud coordinate data of the cross arm and the jumper that are farthest away.

[0057] It is understandable that in actual applications, the jumper is not necessarily a regular arc. Therefore, the jumper fitting model, the point cloud coordinate data of the cross arm, and the point cloud coordinate data of the tension tower body are projected into the same three-dimensional point cloud coordinate system, so that the tension tower body and the cross arm and jumper connected thereto are projected into the three-dimensional point cloud coordinate system for easy observation. At the same time, based on the point cloud coordinate data of the target object, the point cloud coordinate data of the nearest tension tower body and jumper, as well as the point cloud coordinate data of the farthest cross arm and jumper can be determined.

[0058] S7. Calculate the shortest distance between the tension tower body and the jumper based on the point cloud coordinate data of the closest tension tower body and the jumper, and calculate the farthest distance between the cross arm and the jumper based on the point cloud coordinate data of the farthest cross arm and the jumper.

[0059] It can be understood that after determining the point cloud coordinate data of the nearest tension tower body and jumper, as well as the point cloud coordinate data of the farthest crossarm and jumper, the closest distance between the corresponding tension tower body and jumper, as well as the farthest distance between the crossarm and jumper can be obtained through mathematical calculations.

[0060] In a specific embodiment, before step S3, the process includes:

[0061] The point cloud coordinate data is subjected to point cloud filtering processing, thereby performing point cloud denoising on the point cloud coordinate data.

[0062] It should be noted that in the actual use of LiDAR, high-voltage transmission lines and other ground objects, such as tall trees, ground buildings, etc., will be collected. Eliminating irrelevant interfering objects is crucial to measuring high-voltage transmission lines. To this end, it is necessary to perform point cloud filtering on the point cloud coordinate data to distinguish the transmission line body and other irrelevant interfering objects, and extract the required valid point cloud data. At the same time, the point cloud data may contain errors or erroneous coordinates, so it is necessary to screen and split the error noise to accurately calibrate the high-voltage transmission line body data.

[0063] In a specific embodiment, step S3 specifically includes:

[0064] S301. Sort all discrete point cloud coordinates in the point cloud coordinate data in ascending order to obtain the minimum discrete point cloud coordinates and the maximum discrete point cloud coordinates, project the minimum discrete point cloud coordinates and the maximum discrete point cloud coordinates onto a two-dimensional plane, connect the minimum discrete point cloud coordinates and the maximum discrete point cloud coordinates to determine a line segment, and the line segment is the routing direction of the transmission line.

[0065] It should be noted that the point cloud coordinates in the point cloud coordinate data are discrete. By sorting all discrete point cloud coordinates in ascending order, the minimum discrete point cloud coordinates and the maximum discrete point cloud coordinates can be obtained. The minimum discrete point cloud coordinates and the maximum discrete point cloud coordinates are projected onto a two-dimensional plane, and the connected line segments are the alignment direction of the transmission line.

[0066] S302, projecting all discrete point cloud coordinates in the point cloud coordinate data onto a two-dimensional plane, obtaining discrete point cloud coordinates falling on the line segment, and calculating the point cloud coordinate distance between two adjacent discrete point cloud coordinates falling on the line segment.

[0067] It should be noted that all discrete point cloud coordinates in the point cloud coordinate data are projected onto a two-dimensional plane. Since the point cloud coordinate data includes the point cloud coordinates of the tension tower body and the point cloud coordinates of the jumper, and the line segment is composed of the minimum discrete point cloud coordinates and the maximum discrete point cloud coordinates of the tension tower body, and since the altitudes of the tension tower bodies are basically the same, the point cloud coordinates of the tension tower bodies will fall on the same line segment, while the point cloud coordinates of the jumper will not fall on the line segment. Therefore, the point cloud coordinate distance between two adjacent tension tower bodies can be calculated through two adjacent discrete point cloud coordinates falling on the line segment, and the point cloud coordinate distance is the interval unit distance of the tension tower body of the transmission line.

[0068] S303, using the point cloud coordinate distance between two adjacent tension tower bodies as a segmentation threshold, segmenting the point cloud coordinate data, thereby separating a plurality of point cloud coordinate sets, where the point cloud coordinate sets are the point cloud coordinate data between two adjacent tension tower bodies.

[0069] It should be noted that, by using the point cloud coordinate distance between the tower bodies of two adjacent tension towers as the segmentation threshold, the point cloud coordinate data can be separated, thereby separating out several point cloud coordinate sets, and the length of each point cloud coordinate set is the point cloud coordinate distance.

[0070] In a specific embodiment, the method further comprises:

[0071] Determine whether the shortest distance between the tower body of the tension tower and the jumper is less than a preset first threshold value, and if the above judgment is less than, generate an early warning signal and send it to the main station for early warning;

[0072] It is determined whether the maximum distance between the cross arm and the jumper is greater than a preset second threshold. If the above determination is greater than, an early warning signal is generated and sent to the main station for early warning.

[0073] It can be understood that if the closest distance between the tower body of the tension tower and the jumper is less than the preset first threshold, or the farthest distance between the crossarm and the jumper is greater than the preset second threshold, it indicates that there is a certain risk and an early warning is required, where the preset first threshold and second threshold can be set based on historical experience.

[0074] The present embodiment provides a method for measuring the arc sag distance of a jumper. A laser radar is mounted on a drone to perform a radar scan on a target object to obtain a three-dimensional image of the target object, and the three-dimensional image is converted into a point cloud image, thereby obtaining point cloud coordinate data of the target object. The point cloud coordinate distance between two adjacent tension towers is determined according to the routing direction of the transmission line, and the point cloud coordinate data is separated by the point cloud coordinate distance, thereby separating a plurality of point cloud coordinate sets, which are point cloud coordinate data between two adjacent tension towers, and the point cloud coordinate set is used as the measurement. Unit, a random sampling consistency algorithm is used to extract the point cloud coordinates of the jumper in the point cloud coordinate set, so as to fit the jumper fitting model, and the jumper fitting model, the point cloud coordinate data of the crossarm, and the point cloud coordinate data of the tension tower body are projected into the same three-dimensional point cloud coordinate system, and the point cloud coordinate data of the nearest tension tower body and the jumper, as well as the point cloud coordinate data of the farthest crossarm and the jumper are obtained, and the nearest distance between the tension tower body and the jumper and the farthest distance between the crossarm and the jumper are calculated respectively, thereby improving the efficiency of the jumper sag distance measurement and reducing the workload.

[0075] The above is a detailed description of an embodiment of a jumper sag distance measurement method provided by the present invention. The following is a detailed description of an embodiment of a jumper sag distance measurement system provided by the present invention.

[0076] For easier understanding, see Figure 2 The present invention provides a jumper sag distance measurement system, comprising:

[0077] The scanning module 100 is used to use a drone to reach a target position above the transmission line along a preset route trajectory, and to perform radar scanning on the target object through a laser radar carried by the drone, so as to obtain a three-dimensional image of the target object, wherein the target object includes a tension tower body and a cross arm and a jumper connected thereto;

[0078] The point cloud conversion module 200 is used to convert the three-dimensional image into a point cloud image based on the point cloud coordinate system, so as to obtain the point cloud coordinate data of the target object;

[0079] The point cloud separation module 300 is used to obtain the routing direction of the transmission line, determine the point cloud coordinate distance between the tower bodies of two adjacent tension towers according to the routing direction, and separate the point cloud coordinate data by the point cloud coordinate distance, thereby separating a plurality of point cloud coordinate sets, where the point cloud coordinate sets are the point cloud coordinate data between the tower bodies of two adjacent tension towers;

[0080] A point cloud extraction module 400 is used to extract the point cloud coordinates of the jumper from the point cloud coordinate set using a random sampling consistency algorithm;

[0081] The point cloud fitting module 500 is used to perform parabola fitting on the point cloud coordinates of the jumper based on the routing direction of the transmission line, so as to obtain a jumper fitting model;

[0082] The projection module 600 is used to project the jumper fitting model, the point cloud coordinate data of the cross arm, and the point cloud coordinate data of the tension tower body into the same three-dimensional point cloud coordinate system, and obtain the point cloud coordinate data of the tension tower body and the jumper that are closest, and the point cloud coordinate data of the cross arm and the jumper that are farthest away;

[0083] The sag calculation module 700 is used to calculate the shortest distance between the tension tower body and the jumper according to the point cloud coordinate data of the closest tension tower body and the jumper, and also calculate the farthest distance between the crossarm and the jumper according to the point cloud coordinate data of the farthest crossarm and the jumper.

[0084] In a specific embodiment, the system further includes:

[0085] The denoising module is used to perform point cloud filtering processing on the point cloud coordinate data, thereby performing point cloud denoising on the point cloud coordinate data.

[0086] In a specific embodiment, the point cloud segmentation module specifically includes:

[0087] A routing module is used to sort all discrete point cloud coordinates in the point cloud coordinate data in ascending order to obtain the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate, project the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate onto a two-dimensional plane, connect the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate to determine a line segment, and the line segment is the routing direction of the transmission line;

[0088] A distance calculation module is used to project all discrete point cloud coordinates in the point cloud coordinate data onto a two-dimensional plane, obtain the discrete point cloud coordinates falling on the line segment, and calculate the point cloud coordinate distance between two adjacent tension tower bodies according to two adjacent discrete point cloud coordinates falling on the line segment;

[0089] The threshold segmentation module is used to separate the point cloud coordinate data by taking the point cloud coordinate distance between the tower bodies of two adjacent tension towers as the segmentation threshold, thereby separating a number of point cloud coordinate sets, which are the point cloud coordinate data between the tower bodies of two adjacent tension towers.

[0090] In a specific embodiment, the system further includes:

[0091] The first early warning module is used to determine whether the shortest distance between the tower body of the tension tower and the jumper is less than a preset first threshold value. If the above determination is less than, a warning signal is generated and sent to the main station for early warning;

[0092] The second warning module is used to determine whether the maximum distance between the cross arm and the jumper is greater than a preset second threshold. If the above judgment is greater than, a warning signal is generated and sent to the main station for warning.

[0093] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0094] The present embodiment provides a jumper sag distance measurement system, which uses a laser radar mounted on an unmanned aerial vehicle to perform radar scanning on a target object to obtain a three-dimensional image of the target object, converts the three-dimensional image into a point cloud image, thereby obtaining point cloud coordinate data of the target object, determines the point cloud coordinate distance between two adjacent tension towers according to the routing direction of the transmission line, separates the point cloud coordinate data by the point cloud coordinate distance, thereby separating a plurality of point cloud coordinate sets, the point cloud coordinate sets are the point cloud coordinate data between two adjacent tension towers, and uses the point cloud coordinate sets as the measurement Unit, a random sampling consistency algorithm is used to extract the point cloud coordinates of the jumper in the point cloud coordinate set, so as to fit the jumper fitting model, and the jumper fitting model, the point cloud coordinate data of the crossarm, and the point cloud coordinate data of the tension tower body are projected into the same three-dimensional point cloud coordinate system, and the point cloud coordinate data of the nearest tension tower body and the jumper, as well as the point cloud coordinate data of the farthest crossarm and the jumper are obtained, and the nearest distance between the tension tower body and the jumper and the farthest distance between the crossarm and the jumper are calculated respectively, thereby improving the efficiency of the jumper sag distance measurement and reducing the workload.

[0095] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0096] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0097] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0098] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for measuring the sag distance of a jumper wire, characterized in that: The following steps are involved: The drone is used to reach a target position above the transmission line along a preset route trajectory, and a laser radar carried by the drone is used to perform a radar scan on the target object, thereby obtaining a three-dimensional image of the target object, wherein the target object includes a tension tower body and a cross arm and a jumper connected thereto; Converting the three-dimensional image into a point cloud image based on a point cloud coordinate system, thereby obtaining point cloud coordinate data of the target object; Acquire the routing direction of the transmission line, determine the point cloud coordinate distance between two adjacent tension towers according to the routing direction, separate the point cloud coordinate data by the point cloud coordinate distance, thereby separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between two adjacent tension towers; Extracting the point cloud coordinates of the jumper from the point cloud coordinate set using a random sampling consensus algorithm; Performing parabola fitting on the point cloud coordinates of the jumper based on the routing direction of the transmission line, thereby fitting a jumper fitting model; Projecting the jumper fitting model, the point cloud coordinate data of the cross arm, and the point cloud coordinate data of the tension tower body into the same three-dimensional point cloud coordinate system, obtaining the point cloud coordinate data of the tension tower body and the jumper that are closest, and the point cloud coordinate data of the cross arm and the jumper that are farthest away; The shortest distance between the tower body of the tension tower and the jumper is calculated based on the point cloud coordinate data of the closest tower body and the jumper, and the farthest distance between the crossarm and the jumper is calculated based on the point cloud coordinate data of the farthest crossarm and the jumper.

2. The method for measuring the jumper sag distance according to claim 1, characterized in that: The step of obtaining the alignment direction of the transmission line and the spacing distance between two adjacent tension tower bodies, separating the point cloud coordinate data, and thus separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between two adjacent tension tower bodies, comprises: The point cloud coordinate data is subjected to point cloud filtering processing, thereby performing point cloud denoising on the point cloud coordinate data.

3. The method for measuring the jumper sag distance according to claim 1, characterized in that: The step of obtaining the routing direction of the transmission line, determining the point cloud coordinate distance between two adjacent tension tower bodies according to the routing direction, and separating the point cloud coordinate data by the point cloud coordinate distance to separate a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between two adjacent tension tower bodies, specifically comprises: Sorting all discrete point cloud coordinates in the point cloud coordinate data in ascending order to obtain a minimum discrete point cloud coordinate and a maximum discrete point cloud coordinate, projecting the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate onto a two-dimensional plane, connecting the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate to determine a line segment, wherein the line segment is the routing direction of the transmission line; Projecting all discrete point cloud coordinates in the point cloud coordinate data onto the two-dimensional plane, obtaining discrete point cloud coordinates falling on the line segment, and calculating the point cloud coordinate distance between two adjacent tower bodies of the tension tower according to two adjacent discrete point cloud coordinates falling on the line segment; The point cloud coordinate distance between the tower bodies of the two adjacent tension towers is used as a segmentation threshold to segment the point cloud coordinate data, thereby separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between the tower bodies of the two adjacent tension towers.

4. The method for measuring the jumper sag distance according to claim 1, characterized in that: Also includes: Determine whether the shortest distance between the tower body of the tension tower and the jumper is less than a preset first threshold value, and if the above judgment is less than, generate an early warning signal and send it to the main station for early warning; It is determined whether the maximum distance between the cross arm and the jumper is greater than a preset second threshold. If the above determination is greater than, an early warning signal is generated and sent to the main station for early warning.

5. A jumper sag distance measurement system, characterized in that: include: A scanning module is used to use a drone to reach a target position above the transmission line along a preset route trajectory, and to perform radar scanning on the target object through a laser radar carried by the drone, so as to obtain a three-dimensional image of the target object, wherein the target object includes a tension tower body and a cross arm and a jumper connected thereto; A point cloud conversion module, used to convert the three-dimensional image into a point cloud image based on a point cloud coordinate system, so as to obtain point cloud coordinate data of the target object; A point cloud separation module is used to obtain the routing direction of the transmission line, determine the point cloud coordinate distance between the tower bodies of two adjacent tension towers according to the routing direction, separate the point cloud coordinate data according to the point cloud coordinate distance, and thus separate a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between the tower bodies of two adjacent tension towers; A point cloud extraction module, used for extracting the point cloud coordinates of the jumper from the point cloud coordinate set by using a random sampling consistency algorithm; A point cloud fitting module, used for performing parabola fitting on the point cloud coordinates of the jumper based on the routing direction of the transmission line, so as to obtain a jumper fitting model; A projection module is used to project the jumper fitting model, the point cloud coordinate data of the cross arm, and the point cloud coordinate data of the tension tower body into the same three-dimensional point cloud coordinate system, and obtain the point cloud coordinate data of the tension tower body and the jumper that are closest, and the point cloud coordinate data of the cross arm and the jumper that are farthest away; The sag calculation module is used to calculate the shortest distance between the tower body of the tension tower and the jumper based on the point cloud coordinate data of the closest tower body and the jumper, and also calculate the farthest distance between the crossarm and the jumper based on the point cloud coordinate data of the farthest crossarm and the jumper.

6. The jumper sag distance measurement system according to claim 5, characterized in that: Also includes: The denoising module is used to perform point cloud filtering processing on the point cloud coordinate data, thereby performing point cloud denoising on the point cloud coordinate data.

7. The jumper sag distance measurement system according to claim 5, characterized in that: The point cloud segmentation module specifically includes: A routing module, used for sorting all discrete point cloud coordinates in the point cloud coordinate data in ascending order to obtain a minimum discrete point cloud coordinate and a maximum discrete point cloud coordinate, projecting the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate onto a two-dimensional plane, connecting the minimum discrete point cloud coordinate and the maximum discrete point cloud coordinate to determine a line segment, wherein the line segment is the routing direction of the transmission line; A distance calculation module is used to project all discrete point cloud coordinates in the point cloud coordinate data onto the two-dimensional plane, obtain the discrete point cloud coordinates falling on the line segment, and calculate the point cloud coordinate distance between two adjacent tower bodies of the tension tower according to two adjacent discrete point cloud coordinates falling on the line segment; The threshold segmentation module is used to separate the point cloud coordinate data by using the point cloud coordinate distance between the tower bodies of the two adjacent tension towers as the segmentation threshold, thereby separating a plurality of point cloud coordinate sets, wherein the point cloud coordinate sets are the point cloud coordinate data between the tower bodies of the two adjacent tension towers.

8. The jumper sag distance measurement system according to claim 5, characterized in that: Also includes: A first warning module is used to determine whether the shortest distance between the tower body of the tension tower and the jumper is less than a preset first threshold value, and if the above determination is less than, a warning signal is generated and sent to the main station for warning; The second warning module is used to determine whether the maximum distance between the cross arm and the jumper is greater than a preset second threshold. If the above determination is greater than, a warning signal is generated and sent to the main station for warning.

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