CN113449688B - Power transmission tree obstacle recognition system based on image and laser point cloud data fusion - Google Patents
Power transmission tree obstacle recognition system based on image and laser point cloud data fusion Download PDFInfo
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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
Technical Field
The invention relates to the technical field of power transmission or power supply, in particular to a power transmission tree obstacle recognition system based on image and laser point cloud data fusion.
Background
At present, the inspection and maintenance of power transmission equipment mainly depend on-site investigation, and whether people's eyes go to discern the unusual condition, in recent years because the development of unmanned aerial vehicle technique, can utilize unmanned aerial vehicle to go to shoot, screens these photos through personnel again, and then saves some manpowers, nevertheless still can't satisfy intelligent demand, and the efficiency of detecting and maintaining power transmission equipment is still not high.
For example, the CN111929698A prior art discloses a method for identifying hidden danger of tree obstacle in corridor area of power transmission line, the current detection means of tree obstacle mainly depends on manual and visual judgment, and the patrol personnel determines the distance between tree and power transmission line by holding laser ranging on the ground, however, because of the relation between the measurement angle and position of the person and the tree obstacle point, the detection result is very large and may have large error. In another mode, oblique photography modeling is used for measuring the safety distance, but in the seed detection methods, hardware fittings near a hanging point of the power transmission line and parts, such as insulators, close to a power transmission line corridor area are easily regarded as potential tree obstacle hazards when detection is carried out, so that the potential tree obstacle hazards are not judged accurately.
A large number of searches find existing prior art such as KR101654364B1, EP2482996B1 and US08721396B1, in recent years, with the development of forestry in China, the implementation of the policy of returning to farming and forest and the annual improvement of the requirement for environmental protection, the hidden danger threat caused by the existence of trees below the power transmission line to the power transmission line is more serious; in recent years, the tripping and power-off accidents caused by tree barriers in each province are more than one hundred times per year, the daily life of residents is seriously influenced, and a large amount of economic loss is caused. At present, a common power transmission line tree obstacle maintenance strategy depends on a power grid line patrol worker to regularly patrol the line, however, the visual inspection method for manually patrolling the line judges whether the threat exists or not, the visual inspection is inaccurate, and the judgment whether the threat exists or not on the power transmission line has an error. In addition, the hunting personnel only judge whether the current number has a threat through visual inspection, but neglect the growth margin of the fast-growing trees before next line patrol, and cause the tree fault accident of the power transmission line generated when the line patrol is not in time.
The invention aims to solve the problems of low detection precision, inaccurate growth prediction margin, high detection strength, inaccurate data analysis and the like in the field.
Disclosure of Invention
The invention aims to provide a power transmission tree obstacle recognition system based on image and laser point cloud data fusion, aiming at the defects existing in the current intelligent recognition of the tree obstacle.
In order to overcome the defects of the prior art, the invention adopts the following technical scheme:
a power transmission tree obstacle recognition system based on image and laser point cloud data fusion 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 barrier and the power transmission line; the analysis device positions the power transmission line and performs auxiliary fusion with the data of the sampling device; the sampling device comprises a sampling mechanism and a data acquisition module, wherein the sampling mechanism is used for sampling the position data of the tree obstacle and the power transmission line; the data acquisition module collects the data of the sampling mechanism and stores the data in the memory; the sampling mechanism comprises a sampling probe and a steering mechanism, and the sampling probe is used for identifying the tree barrier; the steering mechanism is used for adjusting the detection angle of the sampling mechanism;
collecting a plurality of groups of image data of the sampling probe, detecting the positions of abnormal points of the plurality of groups of data, and if the abnormal points exist, positioning the abnormal points;
acquiring basic data of the image, and calculating the amplitude and the argument of the image in the adjacent areas of a circle taking an abnormal point as the center of a circle and omega (r) × ρ as the radius in the range with 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;
wherein θ (x, y) is the argument of the image gradient; l represents the scale of the abnormal point;
wherein r is the step length of detection; r ismaxThe maximum allowable step length is r which is 1 to 4.5 times.
Optionally, the detection device includes a moving mechanism and a stabilizing mechanism, and the moving mechanism is used to adjust the acquisition device; the stabilizing mechanism is used for stabilizing the detection process of the moving mechanism; the mobile mechanism comprises a mobile platform, and the acquisition device is arranged on the mobile platform and acquires data on a mobile path along with the movement of the mobile platform.
Optionally, the analysis device includes a positioning mechanism and an auxiliary mechanism, and the positioning mechanism is used for positioning the position of the power transmission line; the auxiliary mechanism is used for performing auxiliary positioning on the positioning mechanism; the positioning mechanism comprises a positioning identification piece and a binding component, and the positioning identification piece is arranged on the binding component and carries out data transmission with the acquisition device; the binding component is used for binding the power transmission frame of the power transmission line.
Optionally, the auxiliary mechanism is used in pair with the positioning mechanism, the auxiliary mechanism includes a plurality of auxiliary positioning pieces and a supporting upright rod, and each auxiliary positioning piece is arranged on the supporting upright rod and calibrates the range of the power transmission rack; and one end of each supporting vertical rod is provided with a limiting member which is in contact with the ground and keeps a vertically upward state.
Optionally, the stabilizing mechanism includes a buffer member and an anti-shake module, and the buffer member is used for buffering vibration generated during the movement of the moving mechanism; the anti-shake module is used for protecting the position of the acquisition device; the buffer component comprises a movable cavity, a movable part, an elastic module and an inflation module, wherein 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 module is communicated with the movable cavity through a pipeline.
Optionally, the collecting device includes a collecting mechanism and an adjusting mechanism, and the adjusting mechanism is used for adjusting the position of the collecting mechanism; the acquisition mechanism is used for acquiring the position of the power transmission line or image data; the acquisition mechanism comprises an acquisition probe and a marking module, and the acquisition probe acquires point cloud data on the power transmission line; the marking module is used for marking a depth position or an abnormal detection position in the point cloud data.
The invention provides a computer readable storage medium of a power transmission tree barrier recognition system suitable for image and laser point cloud data fusion, wherein the computer readable storage medium comprises a control method and a data processing program of the power transmission tree barrier recognition system suitable for image and laser point cloud data fusion, and when the control method and the data processing program of the power transmission tree barrier recognition system suitable for image and laser point cloud data fusion are executed by a processor, the control method and the data processing step of the power transmission tree barrier recognition system suitable for image and laser point cloud data fusion are realized.
The beneficial effects obtained by the invention are as follows:
1. the abnormal area position of the image data is extracted through the processing operation of the processor, and the abnormal point of the area is identified, so that the abnormal point position can be accurately positioned, and the detection efficiency of the abnormal point is further improved;
2. the sampling mechanism is matched with the data acquisition module, so that the data acquired by the sampling mechanism can be transmitted with the communication mechanism through the data acquisition module;
3. the detection device is matched with the acquisition device, so that point cloud data of the power transmission line can be acquired;
4. the guide mechanism is used for limiting the movement range or the identification range of the unmanned aerial vehicle, so that the identification efficiency and accuracy can be improved;
5. the direction deviation of the abnormal shadow position in the image is adopted, and the division of the step length which is divided into multiple equal parts is carried out on the distance between the position based on the current step length and the shadow position, so that the step length can accurately position the abnormal position in the detection process, and the error caused by the inaccurate detection of the edge position is also prevented by dividing r and the abnormal shadow position;
6. through adopting stabilizing mean with the spacing connection of acquisition probe makes the sampling probe is in unmanned aerial vehicle removes or the in-process of flying can cushion, guarantees the in-process that the sampling probe can be stable at the detection for the image data of gathering can be more accurate and clear.
Drawings
The invention will 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 control flow diagram 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 view of the control handle.
Fig. 5 is a schematic structural view of the analysis device.
Fig. 6 is a partial structural schematic view of the steering mechanism.
Fig. 7 is a schematic structural view of the steering mechanism.
Fig. 8 is a schematic cross-sectional view of the cushioning member.
Fig. 9 is a schematic view of an application scenario of the present invention.
The reference numbers illustrate: 1-unmanned aerial vehicle; 2-collecting the probe; 3-tree obstacle; 4-a power transmission rack; 5-a sampling device; 6, a display screen; 7-a cushioning member; 8-sampling probe; 9-a support frame; 10-a drive section; 11-an operating handle; 12-supporting vertical rods; 13-an auxiliary positioning element; 14-a stop collar; 15-positioning the identification element; 16-an analysis device; 17-a labeling module; 18-a stop member; 19-a movable member; 20-a movable cavity; 21-an inflation module; 22-elastic modules.
Detailed Description
In order to make the objects and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the embodiments thereof; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the 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 invention, and be protected by the accompanying claims. Additional features of the disclosed embodiments are described in, and will be apparent from, the detailed description below.
The same or similar reference numerals 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 there is an orientation or positional relationship indicated by the term "upper" - "lower" - "left" - "right", etc., based on the orientation or positional relationship shown in the drawings, it is only for convenience of description and simplification of the description, but not to indicate or imply that the device or component referred to must have a specific orientation.
The first embodiment is as follows: with reference to fig. 1 to 9, the present embodiment provides a power transmission tree obstacle recognition system based on image and laser point cloud data fusion, which includes a detection device, an acquisition device, a sampling device, an analysis device, and a processor, where the detection device is used to detect 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 barrier and the power transmission line; the analysis device positions the power transmission line and performs auxiliary fusion with the data of the sampling device; the sampling device comprises a sampling mechanism and a data acquisition module, wherein the sampling mechanism is used for sampling the position data of the tree obstacle and the power transmission line; the data acquisition module collects the data of the sampling mechanism and stores the data in the memory; the sampling mechanism comprises a sampling probe and a steering mechanism, and the sampling probe is used for identifying the tree barrier; the steering mechanism is used for adjusting the detection angle of the sampling mechanism;
collecting a plurality of groups of image data of the sampling probe, detecting the positions of abnormal points of the plurality of groups of data, and if the abnormal points exist, positioning the abnormal points;
acquiring basic data of an image, and calculating the amplitude and the argument of the image in the adjacent areas of a circle with an abnormal point as the center of a circle and omega (r) rho as the radius in the range with the detection scale rho; 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;
wherein θ (x, y) is the argument of the image gradient; l represents the scale of the abnormal point;
wherein r is the step length of detection; r is a radical of hydrogenmaxThe maximum allowable step length is r, and the value range is 1 to 4.5 times;
further, the detection device comprises a moving mechanism and a stabilizing mechanism, and the moving mechanism is used for adjusting the acquisition device; the stabilizing mechanism is used for stabilizing the detection process of the moving mechanism; the mobile mechanism comprises a mobile platform, and the acquisition device is arranged on the mobile platform and acquires data on a mobile path along with the movement of the mobile platform;
further, the analysis device comprises a positioning mechanism and an auxiliary mechanism, wherein the positioning mechanism is used for positioning the position of the power transmission line; the auxiliary mechanism is used for performing auxiliary positioning on the positioning mechanism; the positioning mechanism comprises a positioning identification piece and a binding component, and the positioning identification piece is arranged on the binding component and carries out data transmission with the acquisition device; the binding component is used for binding a power transmission frame of the power transmission line;
furthermore, the auxiliary mechanism is matched with the positioning mechanism for use, the auxiliary mechanism comprises a plurality of auxiliary positioning pieces and a supporting upright rod, and each auxiliary positioning piece is arranged on the supporting upright rod and used for calibrating the range of the power transmission rack; one end of each supporting vertical rod is provided with a limiting member, and the limiting member is in contact with the ground and keeps a vertically upward state;
further, the stabilizing mechanism comprises a buffer component and an anti-shake module, wherein the buffer component is used for buffering vibration generated in the moving process of the moving mechanism; the anti-shake module is used for protecting the position of the acquisition device; the buffer component comprises a movable cavity, a movable piece, an elastic module and an inflation module, wherein the movable piece and the elastic module are nested to form a movable part, and the movable part is arranged in the movable cavity; the inflation module is communicated with the movable cavity through a pipeline;
furthermore, the acquisition device comprises an acquisition mechanism and an adjusting mechanism, wherein the adjusting mechanism is used for adjusting the position of the acquisition mechanism; the acquisition mechanism is used for acquiring the position or image data of the power transmission line; the acquisition mechanism comprises an acquisition probe and a marking module, and the acquisition probe acquires point cloud data on the power transmission line; the marking module is used for marking a depth position or an abnormal detection position in the point cloud data;
the invention provides a computer readable storage medium of a power transmission tree barrier recognition system suitable for image and laser point cloud data fusion, wherein the computer readable storage medium comprises a control method and a data processing program of the power transmission tree barrier recognition system suitable for image and laser point cloud data fusion, and when the control method and the data processing program of the power transmission tree barrier recognition system suitable for image and laser point cloud data fusion are executed by a processor, the control method and the data processing step of the power transmission tree barrier recognition system suitable for image and laser point cloud data fusion are realized.
The second embodiment: the present embodiment should be understood to at least include all the features of any one of the foregoing embodiments, and further improvements are made on the basis of the foregoing embodiments, and with reference to fig. 1 to 9, the present embodiment provides a power transmission tree obstacle identification system based on fusion of image and laser point cloud data, which includes a detection device, an acquisition device, a sampling device, an analysis device, and a processor, where the detection device is used to detect 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 barrier and the power transmission line; the analysis device positions the power transmission line and performs auxiliary fusion with the data of the sampling device; the processor is respectively in control connection with the detection device, the acquisition device, the sampling device and the analysis device, and performs centralized control on all the devices based on the processor, so that the tree barrier can be accurately identified; in addition, the detection device is matched with the acquisition device, so that point cloud data of the power transmission line can be acquired; meanwhile, the sampling device is matched with the analysis device, so that the image data of the power transmission line or the tree obstacle can be collected and analyzed;
the identification system further comprises a guiding device, wherein the guiding device is used for returning and storing the data of the acquisition device or the sampling device; meanwhile, the image data can be acquired within the range of the power transmission line or the tree obstacles invading into the range of the power transmission line; in addition, the guide device also limits the moving path or the moving range of the moving platform, and ensures that the moving platform performs identification operation in a set range; the guiding device comprises a guiding platform and a communication mechanism, wherein the guiding platform is used for supporting the position of the mobile platform; the communication mechanism is used for performing communication connection on the positions of the guide platform and the mobile platform of the mobile device and guiding the mobile platform of the detection device to move or fly according to a set route; in this embodiment, the mobile platform includes, but is not limited to, the following: unmanned planes, remote control planes, fixed wing planes, and the like; in this embodiment, an unmanned aerial vehicle is preferably used; in addition, before the unmanned aerial vehicle is used, a communication transmission link needs to be established with the guide platform, so that the data acquired by the unmanned aerial vehicle can be transmitted with the ground, and meanwhile, the moving range or moving path of the unmanned aerial vehicle can be guided, so that the unmanned aerial vehicle is promoted to carry out accurate detection in a set range, the detection of tree obstacles is promoted, and the safety of the power transmission line is ensured; the guiding device further comprises a guiding mechanism, and the guiding mechanism is used for limiting the movement range or the identification range of the unmanned aerial vehicle, so that the identification efficiency and accuracy can be improved;
the sampling device comprises a sampling mechanism and a data acquisition module, wherein the sampling mechanism is used for sampling the position data of the tree obstacle and the power transmission line; the data acquisition module collects the data of the sampling mechanism and stores the data in the memory; the sampling mechanism comprises a sampling probe and a steering mechanism, and the sampling probe is used for identifying the tree barrier; the steering mechanism is used for adjusting the detection angle of the sampling mechanism; the sampling mechanism is matched with the data acquisition module, so that the data acquired by the sampling mechanism can be transmitted to the communication mechanism through the data acquisition module; in addition, the sampling device is also arranged on the mobile platform and is driven by the mobile platform to acquire data of the power transmission line; the sampling probe is matched with the steering mechanism, so that the sampling angle of the sampling probe can be accurately controlled, and meanwhile, the detection angle of the sampling probe can be adjusted through the remote control handle; the acquisition device is arranged on the unmanned aerial vehicle and acquires data of the power transmission line along with the movement of the unmanned aerial vehicle; in addition, the sampling probe is matched with the steering mechanism, so that the angle of the sampling probe can be adjusted; the control of the unmanned aerial vehicle through the control handle is a technical means well known by those skilled in the art, and those skilled in the art can query a relevant technical manual to obtain the technology, so that details are not repeated in this embodiment; in addition, the control handle is matched with a display screen for use and is used for detecting the moving position of the moving platform; the display screen is also in communication connection with the mobile platform, the sampling device and the acquisition device and displays image data acquired by the mobile platform in real time;
in addition, the steering mechanism comprises a support frame, a group of rotating parts, a rotation driving mechanism and an angle detection part, and the support frame is used for supporting the sampling probe; the group of rotating pieces are arranged on two sides of the supporting frame and used for adjusting the supporting frame; the rotation driving mechanism is respectively in driving connection with the group of rotation pieces to form a driving part, and the driving part drives the supporting frame synchronously; the angle detection piece detects the rotation angle of the driving part; in addition, the processor is in control connection with the driving part and controls the driving part to drive the supporting frame, so that the detection angle of the acquisition probe arranged on the supporting frame can be adjusted; in addition, a cavity for accommodating the steering mechanism and the sampling probe is formed in the unmanned aerial vehicle; in addition, the cavity is provided with an opening facing the lower bottom of the unmanned aerial vehicle and used for placing a lens of the sampling probe, so that the sampling probe can collect data in the moving process of the unmanned aerial vehicle; in addition, the opening is provided with a transparent sealing plate for protecting the sampling probe and the steering mechanism;
collecting a plurality of groups of image data of the sampling probe, detecting the positions of abnormal points of the plurality of groups of data, and if the abnormal points exist, positioning the abnormal points; in the present embodiment, the abnormal point position includes, but is not limited to, the following listed several: interference of the tree obstacles on the power transmission line, abnormal shadow on the power transmission line and the like; additionally, the processor also performs processing operations on sets of image data of the acquisition probe, including, but not limited to, the following listed ones: carrying out operations such as graying the image, cutting the abnormal area position of the image data and the like; in the process of identifying the abnormal points, the abnormal area position of the image data can be extracted through the processing operation of the processor, and the abnormal points of the area are identified, so that the abnormal point position can be accurately positioned, and the detection efficiency of the abnormal points is further improved;
acquiring basic data of an image, and calculating the amplitude and the argument of the image in the adjacent areas of a circle with an abnormal point as the center of a circle and omega (r) rho as the radius in the range with the detection scale rho; there are:
wherein G (x, y) is the magnitude of the image gradient; l represents 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
Wherein θ (x, y) is the argument of the image gradient; l represents the scale of the abnormal point;
wherein r is the step length of detection; r is a radical of hydrogenmaxThe maximum allowable step length is 1-4.5 times of r; in addition, in the process of selecting the image data, the direction of the abnormal shadow position in the image is deviated, and the step length is divided into multiple equal parts based on the distance between the position of the current step length and the shadow position, so that the abnormal position can be accurately positioned in the detection process of the step length, and the error caused by inaccurate detection of the edge position is also prevented by dividing r and the abnormal shadow position; after a certain area is detected, detecting a next adjacent abnormal area of the image data through the processor;
the detection device comprises a moving mechanism and a stabilizing mechanism, and the moving mechanism is used for adjusting the acquisition device; the stabilizing mechanism is used for stabilizing the detection process of the moving mechanism; the mobile mechanism comprises a mobile platform, and the acquisition device is arranged on the mobile platform and acquires data on a mobile path along with the movement of the mobile platform; the moving mechanism is used for supporting the acquisition device, so that the acquisition device can acquire image data of the tree barrier or the power transmission line; the stabilizing mechanism is matched with the moving mechanism, so that the acquisition device arranged on the moving mechanism can perform stable acquisition; the mobile platform includes, but is not limited to, the following listed ones: unmanned planes, remote control planes, fixed wing planes, and the like; in this embodiment, an unmanned aerial vehicle is preferably used; the stabilizing mechanism is in limit connection with the acquisition probe, so that the sampling probe can buffer in the process of moving or flying of the unmanned aerial vehicle, the sampling probe can be ensured to be stable in the detection process, and the acquired image data can be more accurate and clear;
the stabilizing mechanism comprises a buffer component and an anti-shake module, and the buffer component is used for buffering vibration generated in the moving process of the moving mechanism; the anti-shake module is used for protecting the position of the acquisition device; the buffer component comprises a movable cavity, a movable part, an elastic module and an inflation module, wherein 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 module is communicated with the movable cavity through a pipeline; the stabilizing mechanism is arranged in a cavity of the unmanned aerial vehicle and is connected with the steering component through one end of the movable piece, so that the steering component and the sampling probe obtain the best detection effect in the process of sampling image data; one end of the movable piece is connected with the supporting piece, the other end of the movable piece is connected with the bottom of the cavity, and the unmanned aerial vehicle can reduce the vibration of the unmanned aerial vehicle in the action process, so that the sampling probe can acquire the optimal image data;
the anti-shake module includes a detection sensor and a microcontroller configured to control an increase or decrease in a cushioning amount of at least one cushioning member by providing one or more commands to the cushioning member; the detection sensor is used for detecting the vibration of the sampling device, and if the amplitude of the vibration exceeds a set threshold value, the microcontroller is used for carrying out vibration reduction or amplitude limitation operation on the buffer component; the anti-shake module is also in control connection with the processor and is used for carrying out vibration reduction operation on the acquisition device under the control of the processor; the anti-shake module further comprises an inertia measurement unit, and the inertia measurement unit is used for detecting the inertia of the flight of the unmanned aerial vehicle; at least one detection sensor is located on the drone and configured to provide sensor information to a microcontroller; the sensor information includes acceleration information representing a lateral acceleration value; additionally, the microcontroller is configured to determine a turning 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 turning 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 steering information indicating a steering position or a steering rate corresponding to the steering wheel; the microcontroller is configured to determine a turning event by determining that the drone is turning based on comparing the steering position to a third threshold; wherein the detection sensor information comprises yaw rate information indicative of a yaw rate and steering information indicative of a steering position or 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 determine that the drone is performing a turn in a first direction based on the yaw rate indicating turning in the first direction, and to steer the drone in a second direction or no steering even if the steering position or rate indicates steering; wherein the detection sensor information comprises steering information indicative of a steering position or steering rate and acceleration information indicative 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 performing a turn in a first direction based on the lateral acceleration value indicative of a turn in the first direction and to steer a second direction or no turn is indicated even if the steering position or steering rate indicates a turn;
the analysis device comprises a positioning mechanism and an auxiliary mechanism, wherein the positioning mechanism is used for positioning the position of the power transmission line; the auxiliary mechanism is used for performing auxiliary positioning on the positioning mechanism; the positioning mechanism comprises a positioning identification piece, and the positioning identification piece is arranged on the auxiliary mechanism and performs data transmission with the acquisition device; the positioning device is matched with the detection device, so that the unmanned aerial vehicle can acquire image data within a set range based on the positioning data of the positioning device; in this embodiment, the positioning mechanism and the auxiliary mechanism are matched with each other, so that the flight range of the unmanned aerial vehicle can be limited, and the collection of the power transmission lines or the tree barriers in a limited area is promoted;
in addition, the auxiliary mechanism is used for carrying out auxiliary support on the position of the positioning mechanism, so that a signal sent by the positioning mechanism can be captured by the unmanned aerial vehicle, and the unmanned aerial vehicle carries out reciprocating detection based on positioning data of the positioning mechanism; meanwhile, the auxiliary mechanism is matched with the positioning mechanism for use, the auxiliary mechanism comprises a plurality of auxiliary positioning pieces and a supporting upright rod, and each auxiliary positioning piece is arranged on the supporting upright rod and used for calibrating the range of the power transmission rack; one end of each supporting upright rod is provided with a limiting member which is in contact with the ground and keeps a vertically upward state; each auxiliary positioning piece is arranged along the peripheral side of one end of the supporting vertical rod and is hinged with the limiting ring, so that the supporting vertical rod can be vertically and upwards arranged all the time; in addition, the positioning mechanism is arranged at the other end of the supporting upright rod and is in communication connection with the unmanned aerial vehicle; in addition, the positioning mechanism arranged on each supporting upright rod is a positioning node, the nodes are matched with each other to form a positioning network, and the positioning network also has the functions of navigation, positioning or guidance with the unmanned aerial vehicle, so that the unmanned aerial vehicle and the sampling mechanism arranged on the unmanned aerial vehicle can collect the power transmission line or the tree obstacle; in this embodiment, the supporting upright is provided with a supporting ring for connecting the auxiliary positioning members, and the supporting ring is used for sliding on the supporting upright in the process of supporting and limiting the supporting upright, so that the supporting upright can be stably supported and always kept in a vertically upward posture;
the acquisition device comprises an acquisition mechanism and an adjusting mechanism, wherein the adjusting mechanism is used for adjusting the position of the acquisition mechanism; the acquisition mechanism is used for acquiring the position of the power transmission line or image data; the acquisition mechanism comprises an acquisition probe and a marking module, and the acquisition probe acquires point cloud data on the power transmission line; the marking module is used for marking a longitudinal depth position or an abnormal detection position in the point cloud data; the acquisition device is matched with the mobile device, so that the position of the power transmission line or image data can be acquired in the moving process of the mobile platform; the acquisition device also detects based on the area range of the power transmission line, so that the state on the power transmission line can be detected; in addition, the marking modules are arranged on the power transmission frame, and the positions of the marking modules are identified through the acquisition probes, so that the unmanned aerial vehicle is ensured to mark among different marking modules, and the unmanned aerial vehicle is effectively promoted to detect different positions or the longitudinal direction of the power transmission line; the acquisition device is used for acquiring the image data of the power transmission line in the longitudinal direction, so that the image data of the power transmission line infringed by the tree obstacle can be accurately acquired; each marking module arranged on the power transmission frame is matched with the unmanned aerial vehicle and is in communication connection with the unmanned aerial vehicle, so that the unmanned aerial vehicle can detect along the safety distance set by each marking module, the accurate data acquisition of the position is promoted, and the longitudinal distance of the tree barrier to the power transmission line can be detected;
the invention provides a computer readable storage medium of a power transmission tree obstacle recognition system suitable for image and laser point cloud data fusion, wherein the computer readable storage medium comprises a control method and a data processing program of the power transmission tree obstacle recognition system suitable for image and laser point cloud data fusion, and when the control method and the data processing program of the power transmission tree obstacle recognition system suitable for image and laser point cloud data fusion are executed by a processor, the control method and the data processing step of the power transmission tree obstacle recognition system suitable for image and laser point cloud data fusion are realized; the computer storage medium is used for storing a detection program, so that the data collected by the sampling device or the collecting device is analyzed or regulated, the data of the tree obstacles on the power transmission line can be collected, and accurate adjustment is performed based on the collected data.
Example three: the present embodiment should be understood to include at least all the features of any one of the foregoing embodiments, and further improved on the basis of the features of any one of the foregoing embodiments, and with reference to fig. 1 to 9, the present embodiment provides a power transmission tree obstacle recognition system based on fusion of image and laser point cloud data, which includes a detection device, an acquisition device, a sampling device, an analysis device, and a processor, where the detection device is used to detect 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; the analysis device positions the power transmission line and performs auxiliary fusion with the data of the sampling device; the processor is respectively in control connection with the detection device, the acquisition device, the sampling device and the analysis device, and is used for carrying out centralized control on all the devices based on the processor, so that the tree barriers can be accurately identified; in addition, the detection device is matched with the acquisition device, so that point cloud data of the power transmission line can be acquired; meanwhile, the sampling device is matched with the analysis device, so that the image data of the power transmission line or the tree obstacle can be acquired;
the identification system further comprises a guiding device, wherein the guiding device is used for returning and storing the data of the acquisition device or the sampling device; meanwhile, the image data can be acquired within the range of the power transmission line or the tree barriers invading the range of the power transmission line; in addition, the guide device also limits the moving path or the moving range of the moving platform, and ensures that the moving platform performs identification operation in a set range; the guiding device comprises a guiding table and a communication mechanism, wherein the guiding table is used for supporting the position of the mobile platform; the communication mechanism is used for performing communication connection on the positions of the guide platform and the mobile platform of the mobile device and guiding the mobile platform of the detection device to move or fly according to a set route; in this embodiment, the mobile platform includes, but is not limited to, the following listed types: unmanned planes, remote control planes, fixed wing planes, and the like; in this embodiment, an unmanned aerial vehicle is preferably used; in addition, a communication transmission link needs to be established between the unmanned aerial vehicle and the guide platform before the unmanned aerial vehicle is used, so that the data acquired by the unmanned aerial vehicle can be transmitted with the ground, and meanwhile, the moving range or the moving path of the unmanned aerial vehicle can be guided, so that the unmanned aerial vehicle is promoted to carry out accurate detection in a set range, the detection of the tree obstacles is promoted, and the safety of the power transmission line is ensured; the guiding device further comprises a guiding mechanism, and the guiding mechanism is used for limiting the movement range or the identification range of the unmanned aerial vehicle, so that the identification efficiency and accuracy can be improved;
the acquisition device comprises an acquisition mechanism and an adjusting mechanism, and the adjusting mechanism is used for adjusting the position of the acquisition mechanism; the acquisition mechanism is used for acquiring the position of the power transmission line or image data; the acquisition mechanism comprises an acquisition probe and a marking module, and the acquisition probe acquires point cloud data on the power transmission line; the marking module is used for marking a depth position or an abnormal detection position in the point cloud data; the acquisition device is matched with the mobile device, so that the position of the power transmission line or image data can be acquired in the moving process of the mobile platform; the acquisition device also detects based on the area range of the power 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 frame, and the positions of the marking module are identified through the acquisition probe, so that the unmanned aerial vehicle is ensured to mark among different marking modules, and the unmanned aerial vehicle is effectively promoted to detect different positions or the longitudinal direction of the power transmission line; the acquisition device is used for acquiring the image data of the power transmission line in the longitudinal direction, so that the image data of the power transmission line infringed by the tree obstacle can be accurately acquired; each marking module arranged on the power transmission frame is matched with the unmanned aerial vehicle and is in communication connection with the unmanned aerial vehicle, so that the unmanned aerial vehicle can detect along the safety distance set by each marking module, the accurate data acquisition of the position is promoted, and the longitudinal distance of the tree barrier to the power transmission line can be detected; the acquisition probes include, but are not limited to, the following listed ones: instruments such as a video camera, a detection sensor, and a camera having an imaging function;
acquiring the position of the marking module through an acquisition probe, and calculating the difference between the Kth frame image and the K-1 th frame image to obtain an image D after the train separationKThen, the image D after dividing the carKPerforming segmentation to make the image DKCarrying out binaryzation processing; by such an arrangement, the image D is differentiatedKA certain pixel DKIf the pixel point is larger than the set threshold value, the pixel point is regarded as a detected target, otherwise, the pixel point is regarded as a background pixel; in the differential image DKFiltering the binary image by using mathematical morphology after binarization, and then obtaining a final image; finally, pair DKPerforming region communication analysis on the image, and when the area of a certain communicated region is larger than a certain set threshold value, forming a detection target, setting the region as a detection region range, and determining a minimum circumscribed rectangle;
DK(x，y)＝|fk(x,y)-fk-1(x,y)|
wherein, fk(x,y)，fk-1(x, y) are two consecutive frames of images; dK(x, y) is a frame difference image;
wherein T is a threshold value which is set, and the value of T can be considered to be set;
in addition, in this embodiment, the detection or positioning of the marking module also filters noise of the power transmission line or other tree obstacles; the filtering method comprises the following steps:
s1: preprocessing the sequence image, and removing random noise of the image;
s2: selecting background image B from sequence image sequencek(x, y) such that only the fixed background image is contained in the background image;
s3: selecting two continuous frames of images in the image sequence of the video, wherein the previous frame of image Gk-1(x, y) the current frame image is Gk(x，y)；
S4: calculating a difference value FD (x, y) between the current frame and the background frame, and extracting a complete target from the image;
s5: calculating the difference FG (x, y) of the current frame to obtain the variation of the target;
s6: obtaining a rough motion area image of the motion target for the intersection of the frame difference FD (x, y) and FG (x, y);
s6: removing noise in the background through a noise reduction algorithm;
wherein, the first and the second end of the pipe are connected with each other,
in the formula, T is a threshold value, and for a given video sequence image, assuming that no motion exists at a pixel point K, the frame difference d iskObey mean 0 and variance δ2Normal distribution of (0, delta)2)：
Wherein H0Representing a hypothesis of no motion, δ2The statistical variance of the frame difference is 2 times of the noise variance of the sampling probe; t takes any positive integer value in the range of 5-15.
In the above embodiments, the description of each embodiment has its own emphasis, and reference may be made to the related description of other embodiments for parts that are not described or recited in any embodiment.
Although the invention has been described above with reference to various embodiments, it should be understood that many changes and modifications may be made without departing from the scope of the invention. That is, the methods, systems, and devices 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 than described, and/or various components may be added, omitted, and/or combined. Moreover, features described with respect to certain configurations may be combined in various other configurations, as different aspects and elements of the configurations may be combined in a similar manner. Further, elements therein may be updated as technology evolves, i.e., many elements are examples and do not limit the scope of the disclosure or claims.
Specific details are given in the description to provide a thorough understanding of the exemplary configurations including implementations. However, configurations may be practiced without these specific details, for example, well-known circuits, processes, 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 description of the 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 foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that these examples are illustrative only and are not intended to limit the scope of the invention. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.
Claims (5)
1. A power transmission tree obstacle recognition system based on image and laser point cloud data fusion is characterized by comprising a detection device, a collection 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 barrier and the power transmission line; the analysis device positions the power transmission line and performs auxiliary fusion with the data of the sampling device; the sampling device comprises a sampling mechanism and a data acquisition module, wherein the sampling mechanism is used for sampling the position data of the tree barrier and the power transmission line; the data acquisition module collects the data of the sampling mechanism and stores the data in a memory; the sampling mechanism comprises a sampling probe and a steering mechanism, and the sampling probe is used for identifying the tree barrier; the steering mechanism is used for adjusting the detection angle of the sampling mechanism;
collecting a plurality of groups of image data of the sampling probe, detecting the positions of abnormal points of the plurality of groups of data, and if the abnormal points exist, positioning the abnormal points;
acquiring basic data of the image, and calculating the amplitude and the argument of the image in the adjacent areas of a circle taking an abnormal point as the center of a circle and omega (r) × ρ as the radius in the range with the detection scale ρ; there are:
wherein G (x, y) is the magnitude of the image gradient;
wherein θ (x, y) is the argument of the image gradient; l represents the scale of the abnormal point;
wherein r is the step length of detection; r is a radical of hydrogenmaxThe maximum allowable step length is 1-4.5 times of r; the detection device comprises a moving mechanism and a stabilizing mechanism, and the moving mechanism is used for adjusting the acquisition device; the stabilizing mechanism is used for stabilizing the detection process of the moving mechanism; the mobile mechanism comprises a mobile platform, and the acquisition device is arranged on the mobile platform and acquires data on a mobile path along with the movement of the mobile platform; the stabilizing mechanism comprises a buffer component and an anti-shake module, and the buffer component is used for buffering vibration generated in the moving process of the moving mechanism; the anti-shake module is used for protecting the position of the acquisition device; the buffer component comprises a movable cavity, a movable piece, an elastic module and an inflation module, wherein the movable piece and the elastic module are nested to form a movable part, and the movable part is arranged in the movable cavity; the inflation module is communicated with the movable cavity through a pipeline.
2. The power transmission tree obstacle recognition system based on image and laser point cloud data fusion as claimed in claim 1, wherein the analysis device comprises a positioning mechanism and an auxiliary mechanism, and the positioning mechanism is used for positioning the position of the power transmission line; the auxiliary mechanism is used for performing auxiliary positioning on the positioning mechanism; the positioning mechanism comprises a positioning identification piece and a binding component, and the positioning identification piece is arranged on the binding component and performs data transmission with the acquisition device; the binding component is used for binding a power transmission frame of the power transmission line.
3. The power transmission tree obstacle recognition system based on image and laser point cloud data fusion as claimed in claim 2, wherein the auxiliary mechanism is used in pair with the positioning mechanism, the auxiliary mechanism comprises a plurality of auxiliary positioning pieces and supporting upright rods, each auxiliary positioning piece is arranged on the supporting upright rod and is used for calibrating the range of the power transmission rack; and one end of each supporting vertical rod is provided with a limiting member which is in contact with the ground and keeps a vertically upward state.
4. The system for identifying the transmission tree obstacle based on the fusion of the image and the laser point cloud data as claimed in claim 1, wherein the acquisition device comprises an acquisition mechanism and an adjustment mechanism, and the adjustment mechanism is used for adjusting the position of the acquisition mechanism; the acquisition mechanism is used for acquiring the position or image data of the power transmission line; the acquisition mechanism comprises an acquisition probe and a marking module, and the acquisition probe acquires point cloud data on the power transmission line; the marking module is used for marking a depth position or an abnormal detection position in the point cloud data.
5. A computer readable storage medium suitable for the power transmission tree barrier recognition system based on image and laser point cloud data fusion according to any one of claims 1 to 4, wherein the computer readable storage medium comprises a control method and a data processing program of the power transmission tree barrier recognition system based on image and laser point cloud data fusion, and when the control method and the data processing program of the power transmission tree barrier recognition system based on image and laser point cloud data fusion are executed by a processor, the steps of the control method and the data processing of the power transmission tree barrier recognition system based on image and laser point cloud data fusion are realized.
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| CN111578861A (en) * | 2020-05-25 | 2020-08-25 | 广东电网有限责任公司 | Power distribution network tree obstacle detection method and system |
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Effective date of registration: 20220812 Address after: 225700 No. 2, Fenghuang West Road, Taizhou City, Jiangsu Province Patentee after: STATE GRID JIANGSU ELECTRIC POWER Co.,Ltd. TAIZHOU POWER SUPPLY BRANCH Address before: 225300 Taizhou Power Supply Branch of State Grid Jiangsu Electric Power Co., Ltd., No. 2, Fenghuang West Road, Taizhou City, Jiangsu Province Patentee before: STATE GRID JIANGSU ELECTRIC POWER Co.,Ltd. TAIZHOU POWER SUPPLY BRANCH Patentee before: ZHONGXIN HANCHUANG (BEIJING) TECHNOLOGY CO.,LTD. |