CN113449688B - A power transmission tree barrier identification system based on image and laser point cloud data fusion - Google Patents

Abstract

The invention provides a power transmission tree obstacle recognition system based on image and laser point cloud data fusion, which comprises a detection device, an acquisition device, a sampling device, an analysis device and a processor, wherein the detection device is used for detecting a power transmission line; the acquisition device is used for acquiring data of the path or the obstacle on the power transmission line; the sampling device is used for sampling data of the tree obstacle and the power transmission line; and the analysis device positions the power transmission line and performs auxiliary fusion with the data of the sampling device. According to the invention, the abnormal region position of the image data is extracted through the processing operation of the processor, and the abnormal point of the region is identified, so that the abnormal point position can be accurately positioned, and the detection efficiency of the abnormal point is further improved.

Description

A power transmission tree barrier identification system based on image and laser point cloud data fusion

technical field

The invention relates to the technical field of power transmission or power supply, in particular to a power transmission tree barrier identification system based on image and laser point cloud data fusion.

Background technique

At present, the inspection and maintenance of power transmission equipment mainly relies on on-site inspection, and the human eye can identify whether there is an abnormal situation. In recent years, due to the development of drone technology, drones can be used to take pictures, and then these photos can be screened by personnel. , which saves some manpower, but still cannot meet the needs of intelligence, and the efficiency of testing and maintaining power transmission equipment is still not high.

For example, the prior art of CN111929698A discloses a method for identifying hidden dangers of tree barriers in the corridor area of transmission lines. The current detection methods for tree barriers mainly rely on manual visual judgment. The distance of the line, however, due to the measurement angle and position relationship between the person and the tree barrier point, the detection result is likely to have a large error. Another way is to use oblique photographic modeling to measure the safety distance, but these inspection methods are easy to regard the hardware and insulators near the transmission line hanging point and other components that are close to the transmission line corridor area as trees. The hidden dangers of tree obstacles are not accurately judged.

After a large number of searches, it is found that there are existing technologies such as KR101654364B1, EP2482996B1 and US08721396B1. In recent years, with the development of my country's forestry, the implementation of the policy of returning farmland to forests and the increasing requirements for environmental protection, the existence of trees under the transmission line has caused damage to the transmission line. The threat of hidden dangers has become more and more serious; in recent years, the tripping and power outage accidents caused by tree barriers in various provinces have occurred more than 100 times a year, which seriously affected the daily life of residents and caused a lot of economic losses. At present, the common tree barrier maintenance strategy for transmission lines is to rely on grid line patrol staff to conduct regular line patrols. However, the manual line patrol relies on visual inspection to judge whether there is a threat, and the visual inspection is inaccurate, and there is an error in the judgment of whether the transmission line is a threat. In addition, line hunters only judge whether the current number is a threat through visual inspection, while ignoring the growth margin of fast-growing trees before the next line patrol, resulting in transmission line tree obstruction accidents caused by untimely line patrols.

In order to solve the common problems in the field of low detection accuracy, inaccurate prediction growth margin, high detection intensity and inaccurate data analysis, the present invention is made.

SUMMARY OF THE INVENTION

The purpose of the present invention is to propose a power transmission tree-barrier recognition system based on the fusion of image and laser point cloud data, aiming at the shortcomings of the current tree-barrier intelligent recognition.

In order to overcome the deficiencies of the prior art, the present invention adopts the following technical solutions:

A power transmission tree barrier identification system based on image and laser point cloud data fusion, which includes a detection device, a collection device, a sampling device, an analysis device and a processor, the detection device is used to detect transmission lines; the acquisition device It is used to collect data on the paths or obstacles on the transmission line; the sampling device is used to sample the data of the tree barrier and the transmission line; the analysis device locates the transmission line and communicates with all the data. auxiliary fusion of the data of the sampling device; the sampling device includes a sampling mechanism and a data acquisition module, the sampling mechanism is used for sampling the position data of the tree barrier and the transmission line; the data acquisition module The data of the sampling mechanism is summarized and stored in the memory; the sampling mechanism includes a sampling probe and a steering mechanism, the sampling probe is used for identifying the tree barrier; the steering mechanism is used for the sampling Adjust the detection angle of the mechanism;

collecting multiple sets of image data of the sampling probe, and detecting the positions of abnormal points on the multiple sets of data, and if there are abnormal points, locating the abnormal points;

Collect the basic data of the image, and calculate the amplitude and angle of the image in the adjacent area of the circle with the abnormal point as the center and ω(r)*ρ as the radius within the range of the detection scale ρ; there are:

Wherein, G(x, y) is the magnitude of the image gradient; x is the abscissa in the image pixel coordinate system, and y is the ordinate in the image pixel coordinate system;

Among them, θ(x, y) is the argument of the image gradient; L represents the scale of the abnormal point;

Among them, r is the step size of detection; r _max is the maximum allowable step size, and the value range is 1-4.5 times of r.

Optionally, the detection device includes a moving mechanism and a stabilization mechanism, the moving mechanism is used to adjust the collection device; the stabilization mechanism is used to stabilize the detection process of the moving mechanism; the moving mechanism A mobile platform is included, and the acquisition device is arranged on the mobile platform and collects data on the moving path following the movement of the mobile platform.

Optionally, the analysis device includes a positioning mechanism and an auxiliary mechanism, the positioning mechanism is used for positioning the position of the power transmission line; the auxiliary mechanism is used for auxiliary positioning of the positioning mechanism; the positioning mechanism includes a positioning mechanism An identification member and a binding member, the positioning identification member is arranged on the binding member, and performs data transmission with the acquisition device; the binding member is used for binding the power transmission frame of the power transmission line.

Optionally, the auxiliary mechanism is used in pairs with the positioning mechanism, the auxiliary mechanism includes a plurality of auxiliary positioning pieces and a support pole, each of the auxiliary positioning pieces is arranged on the support pole, and is used for the support pole. The range of the power transmission frame is calibrated; one end of each of the supporting vertical rods is provided with a limiting member, and the limiting member is in contact with the ground and maintains a vertically upward state.

Optionally, the stabilization mechanism includes a buffer member and an anti-shake module, the buffer member is used for buffering the vibration generated during the movement of the moving mechanism; position protection; the buffer member includes a movable cavity, a movable part, an elastic module and an inflatable module, the movable part and the elastic module are nested to form a movable part, and the movable part is arranged in the movable cavity; the The inflatable module communicates with the movable cavity through a pipeline.

Optionally, the collection device includes a collection mechanism and an adjustment mechanism, the adjustment mechanism is used to adjust the position of the collection mechanism; the collection mechanism is used to collect the position or image data of the transmission line; The collection mechanism includes a collection probe and a marking module, the collection probe collects point cloud data on the transmission line; the marking module is used to mark the depth position or abnormal detection position in the point cloud data.

The present invention provides a computer-readable storage medium for a power transmission tree barrier identification system suitable for image and laser point cloud data fusion, the computer-readable storage medium includes the power transmission tree barrier suitable for image and laser point cloud data fusion A control method and a data processing program for an identification system, the control method and data processing program for a power transmission tree barrier identification system suitable for image and laser point cloud data fusion are executed by a processor to realize a power transmission tree for image and laser point cloud data fusion The control method and data processing steps of the fault identification system.

The beneficial effects obtained by the present invention are:

1. Extract the location of the abnormal area of the image data through the processing operation of the processor, and identify the abnormal point in the area, so that the location of the abnormal point can be accurately located, and the detection efficiency of the abnormal point can be further improved;

2. By using the sampling mechanism to cooperate with the data acquisition module, the data collected by the sampling mechanism can be transmitted through the data acquisition module and the communication mechanism;

3. By using the detection device to cooperate with the acquisition device, the point cloud data of the transmission line can be collected;

4. By using the guiding mechanism to limit the movement range or the recognition range of the UAV, the efficiency and accuracy of the recognition can be improved;

5. By adopting the orientation offset of the abnormal shadow position in the image, and dividing the step size into multiple equal parts based on the distance between the position of the current step size and the shadow position, the step size is in the process of detection. The abnormal position can be accurately positioned, and the error caused by the inaccurate detection of the edge position can also be prevented by dividing r and the abnormal shadow position;

6. By using the stabilization mechanism to limit connection with the collection probe, the sampling probe can be buffered during the movement or flight of the drone, ensuring that the sampling probe can be detected during the detection process. Stable, so that the collected image data can be more accurate and clear.

Description of drawings

The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Like reference numerals designate corresponding parts throughout the different views.

FIG. 1 is a schematic diagram of a control flow of the present invention.

FIG. 2 is a schematic structural diagram of the mobile platform.

FIG. 3 is a schematic structural diagram of the mobile platform and the sampling device.

FIG. 4 is a schematic structural diagram of the control handle.

FIG. 5 is a schematic structural diagram of the analysis device.

FIG. 6 is a partial structural schematic diagram of the steering mechanism.

FIG. 7 is a schematic structural diagram of the steering mechanism.

FIG. 8 is a schematic cross-sectional view of the buffer member.

FIG. 9 is a schematic diagram of an application scenario of the present invention.

Description of reference numerals: 1-UAV; 2-Acquisition probe; 3-Tree barrier; 4-Transmission frame; 5-Sampling device; 6-Display screen; 7-Buffer member; 8-Sampling probe; 9-Support frame ; 10- drive part; 11- operating handle; 12- support pole; 13- auxiliary positioning part; 14- limit ring; 15- positioning identification part; 16- analysis device; 17- marking module; ; 19- movable parts; 20- movable cavity; 21- inflatable modules; 22- elastic modules.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with its embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention, not to limit the present invention. invention. Other systems, methods and/or features of the present embodiments will become apparent to those skilled in the art upon review of the following detailed description. It is intended that all such additional systems, methods, features and advantages be included within this description, be within the scope of the present invention, and be protected by the accompanying claims. Additional features of the disclosed embodiments are described in the following detailed description and will be apparent from the following detailed description.

The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar components; in the description of the present invention, it should be understood that if the terms “upper”, “lower”, “left” and “right” are used The orientation or positional relationship indicated by etc. is based on the orientation or positional relationship shown in the accompanying drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or component must have a specific orientation. Orientation structure and operation, so the terms describing the positional relationship in the accompanying drawings are only used for exemplary illustration, and should not be construed as a limitation on the present patent. Those of ordinary skill in the art can understand the specific meanings of the above terms according to specific situations.

Embodiment 1: With reference to Figures 1-9, this embodiment provides a power transmission tree barrier identification system based on image and laser point cloud data fusion, which includes a detection device, a collection device, a sampling device, an analysis device, and a processor. The detection device is used to detect the transmission line; the collection device is used to collect data on the path or obstacle on the transmission line; the sampling device is used to sample the data of the tree barrier and the transmission line ; The analysis device locates the transmission line and fuses with the data of the sampling device; the sampling device includes a sampling mechanism and a data acquisition module, and the sampling mechanism is used to detect the tree barrier and the The position data of the transmission line is sampled; the data acquisition module summarizes the data of the sampling mechanism and stores it in the memory; the sampling mechanism includes a sampling probe and a steering mechanism, and the sampling probe is used to The tree barrier is identified; the steering mechanism is used to adjust the detection angle of the sampling mechanism;

collecting multiple sets of image data of the sampling probe, and detecting the positions of abnormal points on the multiple sets of data, and if there are abnormal points, locating the abnormal points;

Collect the basic data of the image, and calculate the amplitude and angle of the image in the adjacent area of the circle with the abnormal point as the center and ω(r)*ρ as the radius within the range of the detection scale ρ; there are:

Wherein, G(x, y) is the magnitude of the image gradient; x is the abscissa in the image pixel coordinate system, and y is the ordinate in the image pixel coordinate system;

Among them, θ(x, y) is the argument of the image gradient; L represents the scale of the abnormal point;

Among them, r is the step size of detection; r _max is the maximum allowable step size, and the value range is 1-4.5 times of r;

Further, the detection device includes a moving mechanism and a stabilization mechanism, the moving mechanism is used to adjust the collection device; the stabilization mechanism is used to stabilize the detection process of the moving mechanism; the moving mechanism includes a mobile platform, the collection device is arranged on the mobile platform, and follows the movement of the mobile platform to collect data on the moving path;

Further, the analysis device includes a positioning mechanism and an auxiliary mechanism, the positioning mechanism is used for positioning the position of the power transmission line; the auxiliary mechanism is used for auxiliary positioning of the positioning mechanism; the positioning mechanism includes a positioning identification and a binding member, the positioning identification member is arranged on the binding member, and performs data transmission with the acquisition device; the binding member is used for binding the power transmission frame of the transmission line;

Further, the auxiliary mechanism is paired with the positioning mechanism, and the auxiliary mechanism includes a plurality of auxiliary positioning members and a support pole, each of the auxiliary positioning members is arranged on the support pole, and is used for the power transmission. The range of the frame is calibrated; one end of each of the support poles is provided with a limiting member, and the limiting member is in contact with the ground and maintains a vertical upward state;

Further, the stabilization mechanism includes a buffer member and an anti-shake module, the buffer member is used for buffering the vibration generated during the movement of the moving mechanism; the anti-shake module is used for the position of the acquisition device for protection; the buffer member includes a movable cavity, a movable part, an elastic module and an inflatable module, the movable part and the elastic module are nested to form a movable part, and the movable part is arranged in the movable cavity; the inflation The module communicates with the movable cavity through a pipeline;

Further, the collection device includes a collection mechanism and an adjustment mechanism, the adjustment mechanism is used to adjust the position of the collection mechanism; the collection mechanism is used to collect the position or image data of the transmission line; The collection mechanism includes a collection probe and a marking module, the collection probe collects point cloud data on the transmission line; the marking module is used to mark the depth position or abnormal detection position in the point cloud data;

The present invention provides a computer-readable storage medium for a power transmission tree barrier identification system suitable for image and laser point cloud data fusion, the computer-readable storage medium includes the power transmission tree barrier suitable for image and laser point cloud data fusion A control method and a data processing program for an identification system, the control method and data processing program for a power transmission tree barrier identification system suitable for image and laser point cloud data fusion are executed by a processor to realize a power transmission tree for image and laser point cloud data fusion The control method and data processing steps of the fault identification system.

Embodiment 2: This embodiment should be understood to include at least all the features of any one of the foregoing embodiments, and further improve on the basis thereof. In conjunction with Figures 1-9, this embodiment provides a method based on images and laser point clouds. A data fusion power transmission tree barrier identification system, which includes a detection device, a collection device, a sampling device, an analysis device and a processor, the detection device is used to detect the transmission line; the acquisition device is used to detect the transmission line on the transmission line. The sampling device is used to sample the data of the tree barrier and the transmission line; the analysis device locates the transmission line and performs auxiliary fusion with the data of the sampling device ; The processor is respectively connected to the detection device, the collection device, the sampling device, and the analysis device, and based on the processor, performs centralized control of each device, so that the tree barrier can be In addition, the detection device cooperates with the acquisition device, so that the point cloud data of the transmission line can be collected; at the same time, the sampling device cooperates with the analysis device, so that all The image data of the transmission line or the tree barrier can be collected and analyzed;

The identification system further includes a guiding device, which is used for back-transmitting and storing the data of the collecting device or the sampling device; at the same time, it can also monitor the range of the power transmission line or intrude into the range of the power transmission line. The tree barrier is used to collect image data; in addition, the guiding device also limits the moving path or moving range of the mobile platform to ensure that the mobile platform can perform identification operations within the set range; the The guiding device includes a guiding platform and a communication mechanism, the guiding platform is used for supporting the position of the mobile platform; the communication mechanism is used for supporting the position of the guiding platform and the mobile platform of the mobile device Make a communication connection, and guide the mobile platform of the detection device to move or fly according to a predetermined route; in this embodiment, the mobile platform includes but is not limited to the following: unmanned aerial vehicle, remote control aircraft and fixed-wing aircraft, etc.; in this embodiment, an unmanned aerial vehicle is preferably used; in addition, the unmanned aerial vehicle needs to establish a communication transmission link with the guidance platform before use, so that the collection of the unmanned aerial vehicle The data can be transmitted with the ground, and at the same time, it can also guide the moving range or moving path of the UAV, so as to improve the accurate detection of the UAV in the set range. The detection of the tree barrier ensures the safety of the transmission line; the guiding device further includes a guiding mechanism, and the guiding mechanism is used to limit the movement range or the recognition range of the UAV, so that the recognized Efficiency and accuracy can be improved;

The sampling device includes a sampling mechanism and a data acquisition module, the sampling mechanism is used to sample the position data of the tree barrier and the transmission line; the data acquisition module summarizes and stores the data of the sampling mechanism In the memory; the sampling mechanism includes a sampling probe and a steering mechanism, the sampling probe is used to identify the tree barrier; the steering mechanism is used to adjust the detection angle of the sampling mechanism; the The sampling mechanism cooperates with the data acquisition module, so that the data collected by the sampling mechanism can be transmitted through the data acquisition module and the communication mechanism; in addition, the sampling device is also arranged on the mobile platform, And the data collection of the transmission line is carried out under the driving of the mobile platform; the sampling probe and the steering mechanism cooperate with each other, so that the sampling angle of the sampling probe can be accurately controlled, and at the same time, it can also The detection angle of the sampling probe is adjusted through a remote control handle; the collection device is arranged on the drone and follows the movement of the drone to collect data on the transmission line; in addition, the sampling probe Cooperate with the steering mechanism, so that the angle of the sampling probe can be adjusted; the control of the drone through the control handle is a technical means well known to those skilled in the art, and those skilled in the art can inquire about relevant This technology is known in the technical manual, so it is not repeated in this embodiment; in addition, the control handle is also used in conjunction with the display screen to detect the moving position of the mobile platform; the display The screen is also connected in communication with the mobile platform, the sampling device and the acquisition device, and displays the image data collected by the mobile platform in real time;

In addition, the steering mechanism includes a support frame, a set of rotating parts, a rotation driving mechanism and an angle detection member, and the support frame is used to support the sampling probe; a set of the rotating parts is arranged on the support frame. the two sides of the supporting frame are adjusted; the rotating driving mechanism is respectively drivingly connected with a group of the rotating parts to form a driving part, and the driving part drives the supporting frame synchronously; the angle detecting member Detecting the rotation angle of the driving part; in addition, the processor is controlled and connected to the driving part, and controls the driving part to drive the support frame, so that the detection probe provided on the support frame detects The angle can be adjusted; in addition, the UAV is provided with a cavity for accommodating the steering mechanism and the sampling probe; in addition, the cavity is provided with an opening toward the lower bottom of the UAV , used to place the lens of the sampling probe, so that the acquisition probe can collect data during the movement of the drone; in addition, the opening is provided with a transparent sealing plate for placing the sampling probe and the steering mechanism for protection;

Collect multiple sets of image data of the sampling probe, and perform abnormal point position detection on the multiple sets of data. If there is an abnormal point, locate the abnormal point; in this embodiment, the abnormal point position includes but does not It is limited to the following: interference of tree barriers on the transmission line, abnormal shadows on the transmission line, etc.; The processing operations include, but are not limited to, the following: operations such as graying the image, cropping the position of the abnormal area of the image data, etc.; in the process of identifying the abnormal point, the processing operation of the processor can be used. Extract the position of the abnormal area of the image data, and identify the abnormal point in the area, so that the position of the abnormal point can be accurately located, and the detection efficiency of the abnormal point can be further improved;

Collect the basic data of the image, and calculate the amplitude and angle of the image in the adjacent area of the circle with the abnormal point as the center and ω(r)*ρ as the radius within the range of the detection scale ρ; there are:

Among them, G(x, y) is the magnitude of the image gradient; L is the scale of the abnormal point; x is the abscissa in the image pixel coordinate system, and y is the ordinate in the image pixel coordinate system.

Among them, θ(x, y) is the argument of the image gradient; L represents the scale of the abnormal point;

Among them, r is the step size of detection; r _max is the maximum allowable step size, and the value range is 1-4.5 times of r; The orientation of the position is offset, and the step size is divided into multiple equal parts based on the distance between the current step size and the shadow position, so that the step size can accurately locate the abnormal position during the detection process. , by dividing r and the abnormal shadow position, the error caused by the inaccurate detection of the edge position is also prevented; when a certain area is detected, the processor detects the next adjacent abnormal area of the image data. ;

The detection device includes a moving mechanism and a stabilization mechanism, the moving mechanism is used to adjust the collection device; the stabilization mechanism is used to stabilize the detection process of the moving mechanism; the moving mechanism includes a moving platform, The collection device is arranged on the mobile platform, and follows the movement of the mobile platform to collect data on the moving path; the moving mechanism is used to support the collection device, so that the collection device can collecting image data of the tree barrier or the power transmission line; the stabilization mechanism and the moving mechanism cooperate with each other, so that the collecting device arranged on the moving mechanism can perform stable collection; the moving mechanism Platforms include but are not limited to the following: unmanned aerial vehicles, remote-controlled aircraft, and fixed-wing aircraft; The sampling probe can be buffered during the movement or flight of the UAV, to ensure that the sampling probe can be stable during the detection process, so that the collected image data can be more accurate and clear;

The stabilization mechanism includes a buffer member and an anti-shake module, the buffer member is used for buffering the vibration generated during the movement of the moving mechanism; the anti-shake module is used to protect the position of the collection device; The buffer member includes a movable cavity, a movable part, an elastic module and an inflatable module, the movable part is nested with the elastic module to form a movable part, and the movable part is arranged in the movable cavity; the inflatable module passes through a pipeline communicating with the movable cavity; the stabilization mechanism is arranged in the cavity of the unmanned aerial vehicle, and is connected with the steering member through one end of the movable piece, so that the steering member and the sampling probe are moving The best detection effect is obtained during the sampling of image data; one end of the movable part is connected to the support, the other end is connected to the bottom of the cavity, and the drone is in the process of moving The vibration of the drone can be reduced, so that the sampling probe can collect the best image data;

The anti-shake module includes a detection sensor and a microcontroller, the microcontroller is configured to control the buffering amount of the buffering member to increase or decrease by providing one or more commands to at least one buffering member; the detection The sensor is used to detect the vibration of the sampling device, and if the amplitude of the vibration exceeds a set threshold, the micro-controller will perform an operation of reducing the vibration or limiting the amplitude of the buffer member; the anti-shake module also Controlled connection with the processor, and based on the control of the processor to perform a vibration reduction operation on the acquisition device; the anti-shake module further includes an inertial measurement unit, the inertial measurement unit is used for The inertia of the flight of the human-machine is detected; at least one detection sensor is located on the drone and is configured to provide sensor information to the microcontroller; the sensor information includes acceleration information representing a lateral acceleration value; in addition, the microcontroller the sensor is configured to determine a turn event by determining that the drone is turning based on comparing the lateral acceleration value to a first threshold; the sensor information further includes yaw rate information indicative of a yaw rate; in other embodiments, The microcontroller is further configured to determine a turn event by determining that the drone is turning based on comparing the yaw rate to a second threshold; a steering sensor; the sensor information further includes an indication of a steering position or a steering rate corresponding to the steering wheel the steering information; the microcontroller is configured to determine a turn event by determining that the drone is turning based on comparing the steering position to a third threshold; wherein the detection sensor information includes a yaw indicating a yaw rate rate information and steering information indicative of a steering position or a steering rate, and wherein the microcontroller is further configured to prioritize the yaw rate information over the steering information such that the microcontroller is configured to be based on the yaw indicative of turning in the first direction rate determining that the drone is performing a turn in a first direction, and even if the steering position or rate of steering indicates a turn in the second direction or does not indicate a turn; wherein the detection sensor information includes steering information and an indication of the position of the steering or the rate of the turn acceleration information of a lateral acceleration value, and wherein the microcontroller is further configured to prioritize the acceleration information over the steering information, such that the microcontroller is configured to determine that the vehicle is moving in a direction based on the lateral acceleration value indicative of turning in the first direction Performing a turn in the first direction and even if the steering position or steering rate indicates a turn in the second direction or does not indicate a turn;

The analysis device includes a positioning mechanism and an auxiliary mechanism, the positioning mechanism is used for positioning the position of the power transmission line; the auxiliary mechanism is used for auxiliary positioning of the positioning mechanism; the positioning mechanism includes a positioning identification member, so The positioning identification piece is arranged on the auxiliary mechanism, and performs data transmission with the acquisition device; the positioning device cooperates with the detection device, so that the drone can be based on the positioning data of the positioning device. The image data within the set range is collected; in this embodiment, the positioning mechanism and the auxiliary mechanism cooperate with each other to ensure that the flight range of the UAV can be limited, and improve the transmission lines or transmission lines in the limited area. tree barrier for collection;

In addition, the auxiliary mechanism is used for auxiliary support for the position of the positioning mechanism, so that the signal sent by the positioning mechanism can be captured by the UAV, and the UAV is positioned based on the positioning mechanism At the same time, the auxiliary mechanism is paired with the positioning mechanism, and the auxiliary mechanism includes a number of auxiliary positioning pieces and a support pole, and each of the auxiliary positioning pieces is arranged on the support pole, The range of the transmission frame is calibrated; a limiting member is provided at one end of each of the supporting vertical rods, and the limiting member is in contact with the ground and maintains a vertical upward state; The peripheral side of one end of the supporting vertical rod is arranged on the peripheral side and is hinged with the limit ring, so that the supporting vertical rod can always be set vertically upward; in addition, the positioning mechanism is arranged on the other end of the supporting vertical rod, and all the The positioning mechanism is communicated with the unmanned aerial vehicle; in addition, the positioning mechanism arranged on each support pole is a positioning node, and each node is matched with each other to form a positioning network, and the positioning network is also connected with the unmanned aerial vehicle. Carry out the functions of navigation, positioning or guiding, so that the UAV and the sampling mechanism can collect the transmission line or the tree barrier; in this embodiment, the support pole is provided with a A support ring for connecting each of the auxiliary positioning pieces, the support ring is used to be able to slide on the support pole during the process of supporting and limiting the support pole, so that the support pole can be Be stably supported and always maintain a vertical upward posture;

The collection device includes a collection mechanism and an adjustment mechanism, the adjustment mechanism is used to adjust the position of the collection mechanism; the collection mechanism is used to collect the position or image data of the transmission line; the collection mechanism It includes a collection probe and a marking module, the collection probe collects point cloud data on the transmission line; the marking module is used to mark the longitudinal depth position or abnormal detection position in the point cloud data; the collection device Cooperate with the mobile device, so that the mobile platform can ensure that the position or image data of the transmission line can be collected during the moving process; the collection device also detects based on the area of the transmission line, so that The state on the power transmission line can be detected; in addition, the marking module is arranged on the power transmission rack, and the position of the marking module is identified with the acquisition probe to ensure that the drone is in the Marking between different marking modules effectively enhances the detection of different positions or the longitudinal direction of the transmission line by the UAV; the image data of the transmission line in the longitudinal direction is collected by the acquisition device , so that the image data of the violation of the tree barrier on the transmission line can be accurately collected; each marking module arranged on the transmission frame cooperates with the UAV, and communicates with the UAV, so that the UAV Detection can be carried out along the safe distance set by each of the marking modules, improving the collection of accurate data at the position, and detecting that the vertical distance between the tree barrier and the transmission line can be detected;

The present invention provides a computer-readable storage medium for a power transmission tree barrier identification system suitable for image and laser point cloud data fusion, the computer-readable storage medium includes the power transmission tree barrier suitable for image and laser point cloud data fusion A control method and a data processing program for an identification system, the control method and data processing program for a power transmission tree barrier identification system suitable for image and laser point cloud data fusion are executed by a processor to realize a power transmission tree for image and laser point cloud data fusion The control method and data processing steps of the fault identification system; the computer storage medium is used to store the detection program, so that the data collected by the sampling device or the acquisition device is analyzed or regulated, so that the power transmission The data of the tree barriers on the line can be collected, and precise adjustments can be made based on the collected data.

Embodiment 3: This embodiment should be understood to include at least all the features of any one of the foregoing embodiments, and to further improve on the basis thereof. With reference to Figures 1-9, this embodiment provides an image and laser point cloud based method. A data fusion power transmission tree barrier identification system, which includes a detection device, a collection device, a sampling device, an analysis device and a processor, the detection device is used to detect the transmission line; the acquisition device is used to detect the transmission line on the transmission line. The sampling device is used to sample the data of the tree barrier and the transmission line; the analysis device locates the transmission line and performs auxiliary fusion with the data of the sampling device ; The processor is respectively connected to the detection device, the collection device, the sampling device, and the analysis device, and based on the processor, performs centralized control of each device, so that the tree barrier can be In addition, the detection device cooperates with the acquisition device, so that the point cloud data of the transmission line can be collected; at the same time, the sampling device cooperates with the analysis device, so that all image data of the transmission line or the tree barrier can be collected;

The identification system further includes a guiding device, which is used for back-transmitting and storing the data of the collecting device or the sampling device; at the same time, it can also monitor the range of the power transmission line or intrude into the range of the power transmission line. The tree barrier is used to collect image data; in addition, the guiding device also limits the moving path or moving range of the mobile platform to ensure that the mobile platform can perform identification operations within the set range; the The guiding device includes a guiding platform and a communication mechanism, the guiding platform is used for supporting the position of the mobile platform; the communication mechanism is used for supporting the position of the guiding platform and the mobile platform of the mobile device Make a communication connection, and guide the mobile platform of the detection device to move or fly according to a predetermined route; in this embodiment, the mobile platform includes but is not limited to the following: unmanned aerial vehicle, remote control aircraft and fixed-wing aircraft, etc.; in this embodiment, an unmanned aerial vehicle is preferably used; in addition, the unmanned aerial vehicle needs to establish a communication transmission link with the guidance platform before use, so that the collection of the unmanned aerial vehicle The data can be transmitted with the ground, and at the same time, it can also guide the moving range or moving path of the UAV, so as to improve the accurate detection of the UAV in the set range. The detection of the tree barrier ensures the safety of the transmission line; the guiding device further includes a guiding mechanism, and the guiding mechanism is used to limit the movement range or the recognition range of the UAV, so that the recognized Efficiency and accuracy can be improved;

The collection device includes a collection mechanism and an adjustment mechanism, the adjustment mechanism is used to adjust the position of the collection mechanism; the collection mechanism is used to collect the position or image data of the transmission line; the collection mechanism It includes a collection probe and a marking module, the collection probe collects point cloud data on the transmission line; the marking module is used to mark the depth position or abnormal detection position in the point cloud data; the collection device is connected to The mobile devices cooperate with each other, so that the mobile platform can ensure that the position or image data of the transmission line can be collected during the moving process; The state on the power transmission line can be detected; in addition, the marking module is arranged on the power transmission frame, and the position of the marking module is identified with the acquisition probe to ensure that the UAV is in different Marking between the marking modules effectively enhances the UAV to detect different positions or the longitudinal direction of the transmission line; the image data of the transmission line in the longitudinal direction is collected by the collection device, The image data of the intrusion of the tree barrier on the transmission line can be accurately collected; each marking module arranged on the transmission frame cooperates with the unmanned aerial vehicle and is connected in communication, so that the unmanned aerial vehicle can be Detecting is carried out along the safe distance set by each of the marking modules, improving the collection of accurate data at the position, and detecting that the vertical distance between the tree barrier and the transmission line can be detected; the collecting Probes include but are not limited to the following: cameras, detection sensors, cameras with imaging functions and other instruments;

The position of the marking module is collected by the acquisition probe, and the difference between the K-th frame image and the K-1-th frame image is calculated to obtain the image D _K after vehicle classification, and then the image D _K after vehicle classification is segmented Make the image D _K be binarized; through this setting, when a certain pixel D _K of the differential image D _K is greater than the set threshold, the pixel point is considered to be the detected target, and vice versa. background pixels; after the difference image DK is _binarized , it can also be filtered by mathematical morphology, and then the final image is obtained; finally, the regional analysis is performed on the _DK image, when the area of a connected area is If it is greater than a certain set threshold, it becomes the detection target, and the area is set as the detection area range, and the smallest circumscribed rectangle is determined;

D _K (x, y)=|f _k (x, y)-f _k-1 (x, y)|

Among them, f _k (x, y), f _k-1 (x, y) are two consecutive frames of images; D _K (x, y) is a frame difference image;

Among them, T is the threshold value that is known and set, and its value can be considered to be set;

In addition, in this embodiment, the detection or positioning of the marking module also filters the noise of transmission lines or other tree barriers; the filtering method includes the following steps:

S1: Preprocess the sequence image to remove the random noise of the image;

S2: Select the background image B _k (x, y) from the sequence image sequence, so that the background image only contains a fixed background image;

S3: Select two consecutive frames of images in the image sequence of the video, wherein the previous frame image is G _k-1 (x, y), and the current frame image is G _k (x, y);

S4: Calculate the difference FD(x, y) between the current frame and the background frame, and extract the complete target from the image;

S5: Calculate the difference FG(x, y) of the current frame to obtain the change amount of the target;

S6: obtain a rough moving area image of the moving target from the intersection of the frame difference FD(x, y) and FG(x, y);

S6: remove the noise in the background through a noise reduction algorithm;

in,

In the formula, T is the threshold value. For a given video sequence image, assuming that there is no motion at the pixel point K, the frame difference d _k obeys a normal distribution N(0, δ ² ) with a mean value of 0 and a variance of δ ² :

Among them, H ₀ represents the assumption of no motion, δ ² is the statistical variance of the frame difference, and its value is twice the noise variance of the sampling probe;

In the foregoing embodiments, the description of each embodiment has its own emphasis. For parts that are not described or described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

While the invention has been described above with reference to various embodiments, it should be understood that many changes and modifications can be made without departing from the scope of the invention. That said, the methods, systems and apparatus discussed above are examples. Various configurations may omit, substitute or add various procedures or components as appropriate. For example, in alternative configurations, the methods may be performed in an order different from that described, and/or various components may be added, omitted, and/or combined. Furthermore, features described with respect to certain configurations may be combined in various other configurations, eg, different aspects and elements of the configurations may be combined in a similar manner. Furthermore, elements therein may be updated as technology develops, ie, many of the elements are examples and do not limit the scope of the disclosure or the claims.

Specific details are given in the description to provide a thorough understanding of example configurations, including implementations. However, configurations may be practiced without these specific details. For example, well-known circuits, procedures, algorithms, structures and techniques have been shown without unnecessary detail in order to avoid obscuring the configurations. This description provides example configurations only, and does not limit the scope, applicability, or configuration of the claims. Rather, the foregoing descriptions of configurations will provide those skilled in the art with an enabling description for implementing the described techniques. Various changes may be made in the function and arrangement of elements without departing from the spirit or scope of the disclosure.

In conclusion, it is intended that the above detailed description is to be considered as illustrative rather than restrictive, and it should be understood that these embodiments above should be understood to be merely illustrative of the present invention and not intended to limit the scope of protection of the present invention. After reading the contents of the description of the present invention, the skilled person can make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims (5)

1. a power transmission tree barrier identification system based on image and laser point cloud data fusion, is characterized in that, comprises detection device, acquisition device, sampling device, analysis device and processor, and described detection device is used to detect the transmission line ; the collection device is used to collect data on the paths or obstacles on the transmission line; the sampling device is used to sample the data of the tree barrier and the transmission line; the analysis device is used for the transmission line. performing positioning and auxiliary fusion with the data of the sampling device; the sampling device includes a sampling mechanism and a data acquisition module, and the sampling mechanism is used to sample the position data of the tree barrier and the transmission line; the The data acquisition module summarizes the data of the sampling mechanism and stores it in the memory; the sampling mechanism includes a sampling probe and a steering mechanism, the sampling probe is used to identify the tree barrier; the steering mechanism is used to identify the tree barrier. The detection angle of the sampling mechanism is adjusted; collecting multiple sets of image data of the sampling probe, and detecting the positions of abnormal points on the multiple sets of data, and if there are abnormal points, locating the abnormal points; Collect the basic data of the image, and calculate the amplitude and angle of the image in the adjacent area of the circle with the abnormal point as the center and ω(r)*ρ as the radius within the range of the detection scale ρ; there are:

Among them, G(x, y) is the magnitude of the image gradient;

Among them, θ(x, y) is the argument of the image gradient; L represents the scale of the abnormal point;

Among them, r is the detection step size; r _max is the maximum allowable step size, and the value range is 1-4.5 times of r; the detection device includes a moving mechanism and a stabilizing mechanism, and the moving mechanism is used for the collection The stabilizing mechanism is used to stabilize the detection process of the moving mechanism; the moving mechanism includes a moving platform, and the collecting device is arranged on the moving platform and follows the movement of the moving platform to The data on the moving path is collected; the stabilization mechanism includes a buffer member and an anti-shake module, the buffer member is used for buffering the vibration generated during the movement of the moving mechanism; the anti-shake module is used for anti-shake module. The position of the collection device is protected; the buffer member includes a movable cavity, a movable part, an elastic module and an inflatable module, the movable part is nested with the elastic module to form a movable part, and the movable part is arranged on the movable part. In the cavity; the inflatable module communicates with the movable cavity through a pipeline. 2 . The transmission tree barrier identification system based on image and laser point cloud data fusion according to claim 1 , wherein the analysis device comprises a positioning mechanism and an auxiliary mechanism, and the positioning mechanism is used to detect the power transmission line. 3 . The auxiliary mechanism is used for auxiliary positioning of the positioning mechanism; the positioning mechanism includes a positioning identification piece and a binding member, and the positioning identification piece is provided on the binding member and is connected with the The collection device performs data transmission; the binding member is used for binding the power transmission frame of the power transmission line. 3 . A power transmission tree barrier identification system based on image and laser point cloud data fusion according to claim 2 , wherein the auxiliary mechanism is paired with the positioning mechanism, and the auxiliary mechanism comprises several auxiliary mechanisms. 4 . A positioning piece and a support pole, each of the auxiliary positioning pieces is arranged on the support pole, and the range of the power transmission frame is calibrated; one end of each of the support poles is provided with a limit member, and the limit The component is in contact with the ground and remains vertically upward. 4 . A power transmission tree barrier identification system based on image and laser point cloud data fusion according to claim 1 , wherein the collection device comprises a collection mechanism and an adjustment mechanism, and the adjustment mechanism is used to The position of the collection mechanism is adjusted; the collection mechanism is used to collect the position or image data of the transmission line; the collection mechanism includes a collection probe and a marking module, and the collection probe is used for the point cloud on the transmission line. The data is collected; the marking module is used to mark the depth position or abnormal detection position in the point cloud data. 5. A computer-readable storage medium suitable for the transmission tree barrier identification system based on the fusion of image and laser point cloud data according to one of claims 1-4, wherein the computer-readable storage medium comprises: The control method and data processing program of the power transmission tree barrier identification system based on image and laser point cloud data fusion, the control method and data processing program of the power transmission tree barrier identification system based on image and laser point cloud data fusion are executed by a processor At the time, the control method and data processing steps of the power transmission tree barrier identification system based on image and laser point cloud data fusion are realized.

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