Autonomous safety operation control method and system of power tree obstacle cleaning equipment

Abstract

The invention discloses an autonomous safety operation control method and system for power tree obstacle cleaning equipment. The method comprises the steps that unmanned aerial vehicle survey and data collection are carried out; analyzing and preprocessing data; positioning a geographic position and planning a path; accurate measurement and risk assessment are carried out; performing autonomous operation decision and adjustment; real-time sensing monitoring and safety alarm are realized; completing operation and feeding back data; three-dimensional accurate modeling of trees and branches is achieved, the branch lodging path is dynamically predicted in combination with environmental factors, and foreseeability and accuracy of pruning operation are improved. The equipment can automatically adjust the operation mode to adapt to variable weather conditions, and errors and risks caused by manual intervention are reduced. In addition, a built-in safety monitoring system of the equipment ensures real-time monitoring of the whole process of operation, operation is automatically stopped once abnormity is found, and operation safety is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power tree barrier clearing, and in particular to an autonomous safety operation control method and system for power tree barrier clearing equipment. Background Art

[0002] The growth of trees may invade the safe distance of power lines, causing problems such as branch discharge and line tripping, which in turn affects the stability and safety of power supply. The contact between trees and power lines may also cause serious accidents such as fires, threatening people's lives and property. Therefore, clearing power tree barriers is an important task in power system maintenance, aiming to ensure the safe operation of power lines and reduce failures and accidents caused by conflicts between trees and power lines. And clearing tree barriers can reduce power loss caused by the impact of trees and improve power supply quality.

[0003] The current control operation of tree obstacle clearing equipment only controls the clearing equipment to clear tree obstacles within a specified range. The range is simply demarcated in advance. The purpose is to reduce manpower and reduce labor intensity. However, in the actual clearing process, there are still many interference factors, such as the falling direction of branches, the impact of wind force and speed on branches, etc. Such influences may cause the cleared branches to leave the safe area during the falling process and hit the lines, thereby causing accidents. Therefore, directly clearing trees without doing calculations and analysis in advance is likely to cause unpredictable damage. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is to optimize the safety hazards existing in the existing tree obstacle clearing method.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: an autonomous safety operation control method for power tree barrier clearing equipment, comprising:

[0007] Install high-definition cameras, binocular vision systems, and wind speed and direction sensors on drones to collect real-time wind speed and direction data in the survey area, take high-definition images and videos of trees, and build three-dimensional models of trees and branches to be pruned through the binocular vision system;

[0008] Using 3D modeling technology and combined with wind speed and direction data analysis, we can predict the path of branch falls and calibrate the tree height and ground wire height measurement data based on wind speed and direction data.

[0009] Locate the geographical location of the tree obstacle clearing equipment, plan the equipment operation path, and instruct the equipment to move to the target location;

[0010] After the equipment arrives at the work site, measure the trees and ground wires again, taking into account wind speed and direction, 3D model data of branches, and possible paths of branch falls, and comprehensively assess the direction of tree fall and the risk of touching the ground wires at different wind speeds;

[0011] Based on the risk assessment results, the 3D model data of the tree branches and the wind speed and direction data, the equipment autonomously determines the operation mode and continuously monitors the changes in wind speed and direction during the operation to adjust the operation strategy in real time.

[0012] During the operation, the equipment continuously monitors the equipment parameters. If the parameters exceed the safety threshold, the safety alarm system will be triggered immediately to automatically stop the current operation.

[0013] After the work is completed, all data in the whole process will be counted and fed back.

[0014] As a preferred solution of the autonomous safety operation control method of the power tree obstacle clearing equipment described in the present invention, wherein: the wind speed and direction data include, by calculating the wind pressure, obtaining the influence of wind speed and direction on the tree morphology;

[0015]

[0016] Among them, V wind Indicates wind speed, H tree Indicates the tree height, H wire Indicates the height of the ground conductor, P wind represents wind pressure, ρ is air density, C d is the drag coefficient, A is the wind-exposed area of ​​the tree, calculate the crown projection area A0, consider the influence of leaf gap on wind resistance, set the weakening factor a, then A=a×A0; the weakening factor a is obtained according to the crown density identified by the image and historical experience;

[0017] The predicted path of the branch falling includes: branch Indicates the mass of the branch, L branch represents the length of the branch, g represents the acceleration due to gravity, θ wind represents the wind direction angle, α represents the angle between the trimming direction and the wind direction;

[0018] The formula for calculating the horizontal displacement of the predicted path of branch fall is expressed as:

[0019]

[0020] Among them, V fall represents the initial velocity of the branch when it starts to fall, determined by experiment or simulation;

[0021] Correction using the effect of wind speed on height measurement:

[0022] H c =Hm +ΔH;

[0023] Among them, H c Indicates the corrected height, H m It represents the measured height, and ΔH is the height deviation calculated based on wind speed and wind direction, which is calculated using historical experimental data.

[0024] As a preferred solution of the autonomous safety operation control method of the power tree barrier clearing equipment of the present invention, wherein: the planning of the equipment operation path includes, after the tree barrier clearing equipment receives the location information, using the built-in GPS and map data to accurately locate the geographical location;

[0025] Based on the positioning results and surrounding environment information, the equipment's built-in autonomous path planning algorithm calculates the operating path and instructs the equipment to move to the target location; the operating path avoids obstacles and maximizes the adherence to flat roads;

[0026] The surrounding environment information includes marking the obstacles actually existing in the environment through three-dimensional modeling technology and dividing the feasible domain; inserting the label of the area where the branch falls as the excluded part in the feasible domain through the prediction of the falling path of the branch, and redefining the feasible domain;

[0027] Path planning is performed in the updated feasible domain; when the area where the label is inserted is cleaned, the label is deleted and the feasible domain at the cleaned label is restored.

[0028] As a preferred embodiment of the autonomous safety operation control method of the power tree barrier clearing equipment of the present invention, the comprehensive evaluation of the falling direction of trees and the risk of touching the ground wire under different wind speeds includes: the risk evaluation formula is obtained by calculating the falling risk index R:

[0029]

[0030] Among them, P hit is the probability that the branch may touch the ground wire, P total is the total number of possible paths; τ represents the wind pressure factor which is calculated based on the wind pressure and obtained through optimization analysis of historical data.

[0031] As a preferred solution of the autonomous safety operation control method of the power tree barrier clearing equipment described in the present invention, wherein: the operation mode includes a dwarfing pruning operation mode and a high branch pruning operation mode;

[0032] The adjustment operation strategy includes dynamic adjustment of the gripper force:

[0033] F new =a×F old +b×V wind;

[0034] Among them, F new Indicates the new gripper force, F old represents the original gripper force, a and b are coefficients determined experimentally, which are used to balance the effect of the initial gripper force and the wind speed on the gripper force;

[0035] Cutting position recalculation:

[0036] p new =p old +Δp;

[0037] Among them, p new represents the new cutting position, p old represents the original cutting position, and Δp represents the offset of the cutting position;

[0038] Δp=f wind (V wind ,θ wind ,φ wind );

[0039] Among them, f wind (...) is a function that calculates the cutting position offset according to the change of wind speed and direction, θ wind The horizontal angle indicating the wind direction, φ wind The vertical angle indicating the wind direction.

[0040] As a preferred solution of the autonomous and safe operation control method of the electric tree barrier clearing equipment of the present invention, the dwarfing pruning operation mode includes: if the tree needs to be dwarfed as a whole, the equipment determines whether the tree's breast diameter exceeds the maximum clamping load capacity of the attachment, and if it does not exceed, the tree is cut in sections, and the gripper is used to control the direction of the tree's fall;

[0041] The high branch pruning operation mode includes: if only high branches need to be pruned, the equipment determines whether the high branches are higher than the wires, if lower, they are pruned directly; if higher, the falling direction of the tree or high branches is controlled by the clamps before pruning.

[0042] As a preferred solution of the autonomous safety operation control method of the power tree obstacle clearing equipment described in the present invention, wherein: the equipment continuously monitors equipment parameters including the equipment attitude angle, the mechanical arm displacement d, and the tree obstacle grabbing weight W, wherein the attitude angle includes the pitch angle, the roll angle, and the yaw angle, and a maximum safety threshold is designed for each parameter;

[0043] After the operation is completed, the equipment records and counts the number of operations, wind speed and direction data, 3D model prediction results, and information on the impact on the operation;

[0044] The statistical information is sent back to the ground control station for analysis and evaluation by management personnel, and used for subsequent optimization of operation processes and algorithms;

[0045] The optimization process aims to minimize the operation time T and maximize the operation safety S. The optimization objective function is expressed as:

[0046] F = βT + (1-β)(1-S);

[0047] Among them, β is the weight coefficient.

[0048] An autonomous safety operation control system for power tree obstacle clearing equipment using the method as claimed in any one of claims 1 to 7, comprising:

[0049] Modeling unit, which installs a high-definition camera, a binocular vision system, and a wind speed and direction sensor on the drone to collect wind speed and direction data in the survey area in real time, take high-definition images and videos of trees, and build a three-dimensional model of the tree and the branches to be pruned through the binocular vision system;

[0050] The analysis unit uses 3D modeling technology and wind speed and direction data analysis to predict the path of branch fall and calibrate the tree height and ground wire height measurement data based on the wind speed and direction data;

[0051] The planning unit locates the geographical location of the tree obstacle clearing equipment, plans the equipment's operation path, and instructs the equipment to move to the target location;

[0052] The prediction unit measures the trees and ground wires again after the equipment arrives at the work site, taking into account wind speed and direction factors, the 3D model data of the branches, and the possible falling paths of the branches, and comprehensively assesses the direction of the trees falling and the risk of touching the ground wires at different wind speeds;

[0053] The assessment unit autonomously determines the operation mode based on the risk assessment results, the 3D model data of the tree branches and the wind speed and direction data. It also continuously monitors the changes in wind speed and direction during the operation to adjust the operation strategy in real time.

[0054] During the operation, the equipment continuously monitors the equipment parameters. If the parameters exceed the safety threshold, the safety alarm system will be triggered immediately to automatically stop the current operation.

[0055] Feedback unit, after the work is completed, all data in the whole process will be counted and fed back.

[0056] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein: the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0057] A computer-readable storage medium stores a computer program, wherein: when the computer program is executed by a processor, the steps of any one of the methods of the present invention are implemented.

[0058] Beneficial effects of the present invention: The autonomous and safe operation control method of the power tree obstacle clearing equipment provided by the present invention integrates high-definition video, binocular vision system and real-time monitoring of wind speed and wind direction, which not only realizes the three-dimensional accurate modeling of trees and branches, but also dynamically predicts the path of branch fall in combination with environmental factors, thereby improving the predictability and accuracy of pruning operations. Through real-time data analysis and risk assessment, the equipment can autonomously adjust the operation mode to adapt to changing weather conditions, reducing the errors and risks of manual intervention. In addition, the built-in safety monitoring system of the equipment ensures real-time monitoring of the entire operation process, and automatically stops the operation immediately once an abnormality is found, significantly improving the safety of the operation. These improvements jointly improve the efficiency and safety of power tree obstacle clearing and realize a leap in intelligent branch pruning operations. By integrating wind speed and wind direction sensors with three-dimensional modeling technology, real-time prediction and dynamic adjustment of tree morphology and branch fall paths are realized, significantly improving the accuracy of pruning operations. At the same time, the correction of measurement data in combination with wind speed and wind direction ensures the accuracy of measurement results. In addition, the introduction of the risk assessment model comprehensively considers multiple factors, provides a scientific basis for operation decision-making, and reduces operation risks. These improvements not only improve the work efficiency, but also enhance the safety and reliability of the operation process, bringing significant beneficial effects to the clearing of power tree obstacles. The equipment can autonomously determine the operation mode and adjust the operation parameters in real time, such as the force of the clamp and the cutting position, to adapt to the changes in wind speed and direction, ensuring the safety and efficiency of the operation. The flexible switching between the dwarfing and high-branch pruning operation modes further improves the pertinence and accuracy of the operation. At the same time, the equipment parameters are continuously monitored and the safety threshold is set. Once an abnormality occurs, the alarm is immediately triggered and the operation is stopped, effectively preventing accidents. These improvements not only improve the work efficiency, but also significantly enhance the safety and reliability of the operation process, bringing a more intelligent and safe solution to the clearing of power tree obstacles. The equipment can autonomously determine the operation mode and adjust the operation parameters in real time, such as the force of the clamp and the cutting position, to adapt to the changes in wind speed and direction, ensuring the safety and efficiency of the operation. The flexible switching between the dwarfing and high-branch pruning operation modes further improves the pertinence and accuracy of the operation. At the same time, the equipment parameters are continuously monitored and the safety threshold is set. Once an abnormality occurs, the alarm is immediately triggered and the operation is stopped, effectively preventing accidents. These improvements not only improve work efficiency, but also significantly enhance the safety and reliability of the operation process, bringing a more intelligent and safe solution to power tree obstacle clearing work. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0060] Figure 1 An overall flow chart of an autonomous safety operation control method for power tree barrier clearing equipment provided in the first embodiment of the present invention;

[0061] Figure 2 A schematic diagram of two modes of high branch pruning operation in an autonomous safety operation control method for power tree barrier clearing equipment provided in the first embodiment of the present invention;

[0062] Figure 3 A schematic diagram of the segmented dwarfing of an autonomous safety operation control method for power tree barrier clearing equipment provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0064] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides an autonomous safety operation control method for power tree obstacle clearing equipment, comprising:

[0065] S1. Install a high-definition camera, a binocular vision system, and a wind speed and direction sensor on the drone to collect wind speed and direction data in the survey area in real time, take high-definition images and videos of the trees, and build a three-dimensional model of the tree and the branches to be pruned through the binocular vision system.

[0066] In addition to high-definition cameras and binocular vision systems, wind speed and direction sensors are also installed on the drone to collect wind speed and direction data in the survey area in real time and take high-definition images and videos of trees.

[0067] When the drone conducts high-altitude surveys in tree-blocking areas, it also records wind speed and direction information, and uses a binocular vision system to build a three-dimensional model of the tree and branches to be pruned, and transmits the collected data to the ground control station or tree-blocking clearing equipment.

[0068] The impact of wind speed and direction on tree morphology is assessed by calculating wind pressure:

[0069]

[0070] Among them, V wind Indicates wind speed, H tree Indicates the tree height, H wire Indicates the height of the ground conductor, P wind represents wind pressure, ρ is air density, C d is the drag coefficient, A is the wind-exposed area of ​​the tree, calculate the crown projection area A0, consider the influence of leaf gaps on wind resistance, set the weakening factor a, then A=a×A0; the weakening factor a is obtained based on the crown density identified by image and historical experience.

[0071] S2. Use 3D modeling technology combined with wind speed and direction data analysis to predict the path of falling branches, and correct the tree height and ground wire height measurement data based on wind speed and direction data.

[0072] After receiving the data, the ground control station or tree clearing equipment will analyze the wind speed and direction data to assess its possible impact on the shape and position of the trees.

[0073] Using 3D modeling technology, combined with factors such as wind speed, wind direction, gravity and pruning direction, physical simulation of the tree and the branches to be pruned is performed to predict the path of the branches falling.

[0074] Assume: M branch Indicates the mass of the branch, L branch represents the length of the branch, g represents the acceleration due to gravity, and is 9.81 m / s 2 Calculate, θ wind represents the wind direction angle, and α represents the angle between the trimming direction and the wind direction.

[0075] The formula for calculating the horizontal displacement of the predicted path of branch fall is expressed as:

[0076]

[0077] Among them, V fall is the initial velocity of the branch when it begins to fall, determined experimentally or by simulation.

[0078] The measurement data such as tree height and ground wire height are corrected according to the wind speed and direction data to eliminate or reduce the influence of wind speed and direction on the measurement results.

[0079] Correction for the effect of wind speed on altitude measurement:

[0080] H c =H m +ΔH;

[0081] Among them, H cIndicates the corrected height, H m It represents the measured height, and ΔH is the height deviation calculated based on wind speed and wind direction, which is calculated using historical experimental data.

[0082] S3. Locate the geographical location of the tree obstacle clearing equipment, plan the equipment's operating path, and instruct the equipment to move to the target location.

[0083] After receiving the location information, the tree obstacle clearing equipment uses the built-in GPS and map data to accurately locate the geographic location; based on the positioning results and surrounding environment information (such as obstacles, roads, etc.), the equipment's built-in autonomous path planning algorithm calculates the operating path and instructs the equipment to move to the target location; the operating path avoids obstacles and maximizes the adherence to flat roads.

[0084] Through 3D modeling technology, the obstacles actually existing in the environment are marked and the feasible domain is divided. Through the prediction of the falling path of the branches, the area where the branches fall is inserted into the label as the excluded part in the feasible domain, and the feasible domain is redefined. In the updated feasible domain, path planning is performed; when the area where the label is inserted is cleaned, the label is deleted and the feasible domain at the cleaned label is restored.

[0085] S4. After the equipment arrives at the work site, measure the trees and ground wires again (ground wires refer to the conductors (or "conductors") and ground wires (or "lightning conductors" or "lightning protection wires") in power lines), consider wind speed and direction factors, three-dimensional model data of tree branches, and possible falling paths of tree branches, and comprehensively assess the direction of tree falling under different wind speeds and the risk of touching the ground wires.

[0086] After the equipment arrives at the work site, the wind speed and direction data and the 3D model prediction results are combined to accurately measure the trees and ground wires again to verify the measurement data. In the risk assessment process, the wind speed and direction factors, the 3D model data of the branches, and the possible path of the branches falling are taken into consideration to comprehensively assess the direction of the trees falling and the risk of touching the ground wires at different wind speeds.

[0087] The risk assessment formula is obtained by calculating the lodging risk index R:

[0088]

[0089] Among them, P hit is the probability that the branch may touch the ground wire, P total is the total number of possible paths; τ represents the wind pressure factor which is calculated based on the wind pressure and obtained through optimization analysis of historical data.

[0090] By integrating wind speed and direction sensors with 3D modeling technology, real-time prediction and dynamic adjustment of tree morphology and branch falling paths are achieved, significantly improving the accuracy of pruning operations. At the same time, the correction of measurement data in combination with wind speed and direction ensures the accuracy of measurement results. In addition, the introduction of risk assessment models takes into account a variety of factors, provides a scientific basis for operational decision-making, and reduces operational risks. These improvements not only improve operational efficiency, but also enhance the safety and reliability of the operation process, bringing significant beneficial effects to the clearing of power tree obstacles.

[0091] S5. Based on the risk assessment results, the three-dimensional model data of the tree branches and the wind speed and direction data, the equipment autonomously determines the operation mode and continuously monitors the changes in wind speed and direction during the operation to adjust the operation strategy in real time.

[0092] According to the risk assessment results, the three-dimensional model data of the branches and the wind speed and direction data, the equipment independently determines the operation mode and adjusts the operation parameters (such as cutting position, clamping force, pruning direction, etc.) to adapt to the current wind speed and direction conditions and ensure that the branches fall safely; the operation mode includes dwarfing or high branch pruning operation mode, such as Figure 2 shown.

[0093] During the operation, the equipment continuously monitors changes in wind speed and direction, and adjusts the operation strategy in real time to ensure the safety and efficiency of the operation.

[0094] Dynamic adjustment of gripper force:

[0095] F new =a×F old +b×V wind ;

[0096] Among them, F new Indicates the new gripper force, F old represents the original gripper force, a and b are coefficients determined experimentally and used to balance the effects of the initial gripper force and wind speed on the gripper force.

[0097] Cutting position recalculation:

[0098] p new =p old +Δp;

[0099] Among them, p new represents the new cutting position, p old represents the original cutting position, and Δp represents the offset of the cutting position.

[0100] Δp=f wind (V wind ,θ wind ,φ wind );

[0101] Among them, f wind (...) is a function that calculates the cutting position offset according to the change of wind speed and direction, θ wind The horizontal angle indicating the wind direction, φ wind The vertical angle indicating the wind direction.

[0102] The dwarfing operation mode includes: if the tree needs to be dwarfed as a whole, the equipment first determines whether the tree's breast diameter exceeds the maximum clamping load capacity of the attachment, and then cuts the tree in sections (the section dwarfing mode is as follows Figure 3 ), and use the clamp to control the direction of the tree's fall to avoid touching the ground wire. The high branch pruning operation mode includes: if only high branches need to be pruned, the equipment first determines whether the high branches are higher than the wire, and if they are lower, they are pruned directly; if they are higher, the clamp is used to control the direction of the tree or high branches before pruning.

[0103] S6. During the operation, the equipment continuously monitors the equipment parameters. Once the parameters are detected to exceed the safety threshold, the safety alarm system is immediately triggered to automatically stop the current operation.

[0104] During the operation, the equipment continuously monitors equipment parameters, including: equipment attitude angle, robotic arm displacement d, and tree obstacle grabbing weight W. The attitude angle includes pitch angle, roll angle, and yaw angle, and a maximum safety threshold is designed for each parameter.

[0105] Once any parameter is detected to exceed the preset safety threshold, the safety alarm system will be triggered immediately and the current operation will be automatically stopped to prevent accidents.

[0106] The equipment can autonomously determine the operation mode and adjust the operation parameters in real time, such as the force of the clamp and the cutting position, to adapt to changes in wind speed and direction, thus ensuring the safety and efficiency of the operation. The flexible switching between dwarfing and high-branch pruning operation modes further improves the pertinence and accuracy of the operation. At the same time, the equipment parameters are continuously monitored and safety thresholds are set. Once an abnormality occurs, an alarm is immediately triggered and the operation is stopped, effectively preventing accidents. These improvements not only improve the efficiency of the operation, but also significantly enhance the safety and reliability of the operation process, bringing a more intelligent and safe solution to the clearing of power tree obstacles.

[0107] S7. After the operation is completed, all data of the entire process will be counted and fed back.

[0108] After the operation is completed, the equipment records and counts the number of operations, wind speed and direction data, three-dimensional model prediction results, and information on the impact on the operation.

[0109] The statistical information is transmitted back to the ground control station for management personnel to analyze and evaluate, and is used for subsequent optimization of operating processes and algorithms.

[0110] The optimization process aims to minimize the operation time T and maximize the operation safety S. The optimization objective function is expressed as:

[0111] F = βT + (1-β)(1-S);

[0112] Where β is the weight coefficient.

[0113] By collecting and analyzing wind speed and direction during the operation, the three-dimensional model prediction results and their impact on the operation, valuable data support is provided to managers. This improvement helps to optimize the operation process and algorithm, with the goal of minimizing operation time and maximizing operation safety, significantly improving operation efficiency and safety, and bringing a more intelligent and efficient solution to the clearing of power tree obstacles.

[0114] Embodiment 2: This embodiment also provides an autonomous safety operation control system for power tree obstacle clearing equipment, which includes:

[0115] The modeling unit installs a high-definition camera, a binocular vision system, and a wind speed and direction sensor on the drone to collect wind speed and direction data in the survey area in real time, take high-definition images and videos of the trees, and build a three-dimensional model of the tree and the branches to be pruned through the binocular vision system.

[0116] The analysis unit uses three-dimensional modeling technology combined with wind speed and direction data analysis to predict the path of falling branches, and corrects the tree height and ground wire height measurement data based on the wind speed and direction data.

[0117] The planning unit locates the geographical location of the tree obstacle clearing equipment, plans the equipment's operating path, and instructs the equipment to move to the target location.

[0118] The prediction unit measures the trees and ground wires again after the equipment arrives at the work site, taking into account factors such as wind speed and direction, the three-dimensional model data of the branches, and the possible falling paths of the branches, to comprehensively assess the direction of the trees' falling and the risk of touching the ground wires at different wind speeds.

[0119] The assessment unit autonomously determines the operation mode based on the risk assessment results, the three-dimensional model data of the tree branches, and the wind speed and direction data. It also continuously monitors changes in wind speed and direction during the operation to adjust the operation strategy in real time.

[0120] During the operation of the operation unit, the equipment continuously monitors the equipment parameters. If the parameters exceed the safety threshold, the safety alarm system will be triggered immediately to automatically stop the current operation.

[0121] Feedback unit, after the work is completed, all data in the whole process will be counted and fed back.

[0122] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0123] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0124] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0125] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0126] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An autonomous safety operation control method for power tree obstacle clearing equipment, characterized in that: include: Install high-definition cameras, binocular vision systems, and wind speed and direction sensors on drones to collect real-time wind speed and direction data in the survey area, take high-definition images and videos of trees, and build three-dimensional models of trees and branches to be pruned through the binocular vision system; Using 3D modeling technology and combined with wind speed and direction data analysis, we can predict the path of branch falls and calibrate the tree height and ground wire height measurement data based on wind speed and direction data. Locate the geographical location of the tree obstacle clearing equipment, plan the equipment operation path, and instruct the equipment to move to the target location; After the equipment arrives at the work site, measure the trees and ground wires again, taking into account wind speed and direction, 3D model data of branches, and possible paths of branch falls, and comprehensively assess the direction of tree fall and the risk of touching the ground wires at different wind speeds; Based on the risk assessment results, the 3D model data of the tree branches and the wind speed and direction data, the equipment autonomously determines the operation mode and continuously monitors the changes in wind speed and direction during the operation to adjust the operation strategy in real time. During the operation, the equipment continuously monitors the equipment parameters. If the parameters exceed the safety threshold, the safety alarm system will be triggered immediately to automatically stop the current operation. After the work is completed, all data in the whole process will be counted and fed back.

2. The autonomous safety operation control method of the power tree obstacle clearing equipment according to claim 1, characterized in that: The wind speed and direction data include, by calculating the wind pressure, obtaining the influence of wind speed and direction on the tree morphology; Among them, V wind Indicates wind speed, H tree Indicates the tree height, H wire Indicates the height of the ground conductor, P wind represents wind pressure, ρ is air density, C d is the drag coefficient, A is the wind-exposed area of ​​the tree, calculate the crown projection area A0, consider the influence of leaf gap on wind resistance, set the weakening factor a, then A=a×A0; the weakening factor a is obtained according to the crown density identified by the image and historical experience; The predicted path of the branch falling includes: branch Indicates the mass of the branch, L branch represents the length of the branch, g represents the acceleration due to gravity, θ wind represents the wind direction angle, α represents the angle between the trimming direction and the wind direction; The formula for calculating the horizontal displacement of the predicted path of branch fall is expressed as: Among them, V fall represents the initial velocity of the branch when it starts to fall, determined by experiment or simulation; Correction using the effect of wind speed on height measurement: H c =H m +ΔH; Among them, H c Indicates the corrected height, H m It represents the measured height, and ΔH is the height deviation calculated based on wind speed and wind direction, which is calculated using historical experimental data.

3. The autonomous safety operation control method of the power tree obstacle clearing equipment according to claim 2 is characterized in that: The planning of the equipment operation path includes, after the tree obstacle clearing equipment receives the location information, using the built-in GPS and map data to accurately locate the geographical location; Based on the positioning results and surrounding environment information, the equipment's built-in autonomous path planning algorithm calculates the operating path and instructs the equipment to move to the target location; the operating path avoids obstacles and maximizes the adherence to flat roads; The surrounding environment information includes marking the obstacles actually existing in the environment through three-dimensional modeling technology and dividing the feasible domain; inserting the label of the area where the branch falls as the excluded part in the feasible domain through the prediction of the falling path of the branch, and redefining the feasible domain; Path planning is performed in the updated feasible domain; when the area where the label is inserted is cleaned, the label is deleted and the feasible domain at the cleaned label is restored.

4. The autonomous safety operation control method of the power tree obstacle clearing equipment according to claim 3 is characterized by: The comprehensive assessment of the risk of tree lodging direction and touching the ground wire under different wind speeds includes: the risk assessment formula is obtained by calculating the lodging risk index R: Among them, P hit is the probability that the branch may touch the ground wire, P total is the total number of possible paths; τ represents the wind pressure factor which is calculated based on the wind pressure and obtained through optimization analysis of historical data.

5. The autonomous safety operation control method of the power tree obstacle clearing equipment according to claim 4, characterized in that: The operation modes include a dwarfing pruning operation mode and a high branch pruning operation mode; The adjustment operation strategy includes dynamic adjustment of the gripper force: F new =a×F old +b×V wind ; Among them, F new Indicates the new gripper force, F old represents the original gripper force, a and b are coefficients determined experimentally, which are used to balance the effect of the initial gripper force and the wind speed on the gripper force; Cutting position recalculation: p new =p old +Δp; Among them, p new represents the new cutting position, p old represents the original cutting position, and Δp represents the offset of the cutting position; Δp=f wind (V wind ,the wind ,f wind ); Among them, f wind (...) is a function that calculates the cutting position offset according to the change of wind speed and direction, θ wind The horizontal angle indicating the wind direction, φ wind The vertical angle indicating the wind direction.

6. The autonomous safety operation control method of the power tree obstacle clearing equipment according to claim 5, characterized in that: The dwarfing pruning operation mode includes: if the tree needs to be dwarfed as a whole, the equipment determines whether the tree's diameter at breast height exceeds the maximum clamping load capacity of the attachment. If it does not exceed, the tree is cut in sections and the gripper is used to control the direction of the tree's fall; The high branch pruning operation mode includes: if only high branches need to be pruned, the equipment determines whether the high branches are higher than the wires, if lower, they are pruned directly; if higher, the falling direction of the tree or high branches is controlled by the clamps before pruning.

7. The autonomous safety operation control method of the power tree obstacle clearing equipment according to claim 6, characterized in that: The equipment continuously monitors equipment parameters including the equipment attitude angle, the displacement of the mechanical arm d, and the tree obstacle grabbing weight W, wherein the attitude angle includes the pitch angle, the roll angle, and the yaw angle, and designs a maximum safety threshold for each parameter; After the operation is completed, the equipment records and counts the number of operations, wind speed and direction data, 3D model prediction results, and information on the impact on the operation; The statistical information is sent back to the ground control station for analysis and evaluation by management personnel, and used for subsequent optimization of operation processes and algorithms; The optimization process aims to minimize the operation time T and maximize the operation safety S. The optimization objective function is expressed as: F = βT + (1-β)(1-S); Among them, β is the weight coefficient.

8. An autonomous safety operation control system for power tree obstacle clearing equipment using the method as described in any one of claims 1 to 7, characterized in that: include: Modeling unit, which installs a high-definition camera, a binocular vision system, and a wind speed and direction sensor on the drone to collect wind speed and direction data in the survey area in real time, take high-definition images and videos of trees, and build a three-dimensional model of the tree and the branches to be pruned through the binocular vision system; The analysis unit uses 3D modeling technology and wind speed and direction data analysis to predict the path of branch fall and calibrate the tree height and ground wire height measurement data based on the wind speed and direction data; The planning unit locates the geographical location of the tree obstacle clearing equipment, plans the equipment's operation path, and instructs the equipment to move to the target location; The prediction unit measures the trees and ground wires again after the equipment arrives at the work site, taking into account wind speed and direction factors, the 3D model data of the branches, and the possible falling paths of the branches, and comprehensively assesses the direction of the trees falling and the risk of touching the ground wires at different wind speeds; The assessment unit autonomously determines the operation mode based on the risk assessment results, the 3D model data of the tree branches and the wind speed and direction data. It also continuously monitors the changes in wind speed and direction during the operation to adjust the operation strategy in real time. During the operation, the equipment continuously monitors the equipment parameters. If the parameters exceed the safety threshold, the safety alarm system will be triggered immediately to automatically stop the current operation. Feedback unit, after the work is completed, all data in the whole process will be counted and fed back.

9. A computer device comprising: A memory and a processor; the memory stores a computer program, wherein the processor implements the steps of any method as claimed in claim 1 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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