Distribution network power-on autonomous operation robot and intelligent operation method thereof

Abstract

The invention belongs to the field of electric power system automation and robots, and discloses a distribution network power-on autonomous operation robot and an intelligent operation method thereof, and aims to eliminate manual errors by accurately grabbing equipment and executing operation through a double-mechanical-arm cooperative system; the all-terrain mobile platform adapts to complex terrains such as electric pole climbing and wire walking, and the maneuverability is improved; the dynamic insulation protection system automatically switches an insulation mode to match a voltage grade, and the protection reliability is ensured; the multi-mode sensing system performs real-time three-dimensional modeling, detects discharge, monitors a safe distance and provides environment sensing; and the intelligent decision-making system fuses the sensing data and a pre-established knowledge graph, outputs an optimization instruction, and drives the mechanical arm and the mobile platform to cooperatively complete operation. By the adoption of the robot, the defects that manual operation is high in safety risk and low in efficiency and an existing robot is insufficient in intellectualization are overcome, and operation safety, operation efficiency and self-adaptability are remarkably improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of power system automation and robot technology, and relates to a distribution network non-power-off autonomous working robot and an intelligent working method thereof. BACKGROUND

[0002] At present, the safety and continuity of distribution network operation are directly related to the stability of user power consumption and the normal development of social and economic activities. The traditional distribution network operation generally adopts a power-off operation mode. Although this mode can ensure the safety of the operators to a certain extent, it will directly lead to the interruption of user power consumption, especially causing significant economic losses to industrial production, commercial operation and other scenarios, which has been difficult to meet the demand of "uninterrupted and high reliability" of power supply in modern society. In order to solve the drawbacks of power-off operation, live working has gradually become the mainstream development direction of distribution network operation and maintenance, and its core goal is to complete the maintenance and replacement of equipment and other operation and maintenance tasks under the premise of ensuring the continuous power supply of distribution network. At present, the industry has initially explored the implementation path of manual live working and part of robot-assisted working, and is committed to seeking a balance between operation safety and power supply continuity.

[0003] However, the existing live working technical system still has obvious shortcomings and is difficult to fully adapt to the actual needs of distribution network operation. The current live working mainly relies on manual operation and faces three major problems: first, the safety risk is extremely high. The operators need to be directly exposed to a high-voltage electric field environment, and it is difficult to wear and use the insulation protective equipment. Moreover, affected by factors such as operation space and weather conditions, the risk of accidents caused by accidental touching of live components and electric field interference always exists; second, the work efficiency is low. For complex operation and maintenance tasks, multiple professional personnel often need to cooperate, and complicated safety preparation work needs to be done before operation, which takes a long time. At the same time, the training period of professional personnel is long and the cost is high, which further restricts the expansion of operation scale; third, the intelligent level is insufficient. The existing few live working robots mostly rely on preset programs to execute operations, and the functions are single, which can only adapt to simple tasks in specific scenarios and lack the ability to adapt to different distribution network environments and different equipment models. When encountering changes in operation environment parameters or unexpected situations, manual intervention is often needed, and real autonomous operation cannot be realized. In specific core operation and maintenance scenarios, these problems are more prominent: when live replacing insulators, the operators need to perform high-altitude climbing operation, which not only has high labor intensity, but also is easily disturbed in a strong electric field environment, and the operation precision is difficult to guarantee; the live disconnecting and connecting of drain wires requires high precision of the timing sequence, and manual operation is easily affected by factors such as reaction speed and operation stability, and is prone to electric arc discharge caused by timing deviation, resulting in equipment damage and even safety accidents; when live replacing circuit breakers, the manual carrying and installation process is prone to accidental touching of surrounding live components due to the large size and complex wiring structure of the circuit breaker, which has great safety hazards.

[0004] In summary, the current distribution network live working usually adopts manual operation, and there are high safety risks, low efficiency, high cost, and problems such as insufficient intelligence of existing robots, single function, and poor scene adaptability, which are difficult to achieve the goal of "zero power failure, full autonomy, and high safety" of distribution network operation and maintenance. SUMMARY

[0005] The application provides a distribution network non-power failure autonomous working robot and an intelligent working method thereof, the robot integrates high-precision mechanical control, multi-modal environment perception, dynamic insulation protection, and man-machine collaborative decision-making technology, and realizes the goal of "zero power failure, full autonomy, and high safety" of distribution network operation and maintenance.

[0006] In order to achieve the above purpose, the application adopts the following technical contents: A distribution network non-power failure autonomous working robot, comprising a robot body; A double-robot arm collaborative system, an all-terrain mobile platform, a dynamic insulation protection system, a multi-modal perception system, and an intelligent decision-making system are arranged on the robot body; The double-robot arm collaborative system is used for grabbing electrical equipment and performing fine operations; The all-terrain mobile platform is used for climbing poles and walking along the wire; The dynamic insulation protection system is used for insulating the robot body and automatically switching the insulation mode according to the voltage level; The multi-modal perception system is used for three-dimensional modeling, discharge detection, and safety distance monitoring of the environment; The intelligent decision-making system is used for judging and outputting live working task instructions according to the perception data collected by the multi-modal perception system combined with the pre-constructed multi-task knowledge graph, and issuing the live working task instructions to the double-robot arm collaborative system and the all-terrain mobile platform, so that the double-robot arm collaborative system and the all-terrain mobile platform cooperatively complete the live working task.

[0007] Further, the double-robot arm collaborative system comprises a main robot arm and a secondary robot arm; The main robot arm is a seven-degree-of-freedom structure and is used for grabbing electrical equipment; The secondary robot arm is a six-degree-of-freedom structure and is used for performing fine operations, and the fine operations include screwing bolts and disconnecting drainage lines.

[0008] Further, the all-terrain mobile platform adopts a four-legged-track composite chassis; the four-legged-track composite chassis is equipped with an electromagnetic adsorption device and carries a visual SLAM navigation module, and is used for climbing poles or walking along the wire; the four-legged-track composite chassis is built-in with a gyroscope and a barometer, and can dynamically adjust the center of gravity to cope with strong winds or slopes.

[0009] Further, the dynamic insulation protection system comprises a silicone rubber composite insulation layer, a chargeable and dischargeable SF6 gas insulation cavity, and a double-layer epoxy resin insulation sleeve nested in the key joints of the robot body; The control method of the dynamic insulation protection system comprises: Mode switching operation: When the voltage level is ≤ preset voltage, air gap insulation is adopted; When the voltage level > preset voltage, the chargeable and dischargeable SF6 gas insulation cavity is activated; Real-time correction operation: According to the electric field intensity sensor data, the insulation strategy is dynamically adjusted, and if the detection value is out of limit, an alarm is triggered and the robot is returned to the safe area.

[0010] Further, the multi-modal perception system comprises binocular vision cameras, ultraviolet imagers, electric field intensity sensors, high-precision laser range finders, and voiceprint recognition modules, which are used for environment three-dimensional modeling, discharge detection, and safety distance monitoring.

[0011] Further, the intelligent decision-making system comprises: A multi-task knowledge graph for mapping insulator models, bolt torques, and lead line disconnection phase sequence rules, wherein the multi-task knowledge graph comprises an insulator bolt torque database, a lead line phase sequence rule library, and a circuit breaker voiceprint fault feature library; An embedded dynamic path planning algorithm that combines the task planning algorithm of the ROS framework and reinforcement learning, which is used to dynamically plan the motion path to avoid live parts and optimize the motion trajectory of the robot arm; An arc suppression model for limiting arc energy within a preset range through shunt diversion and laser ionization collaborative control; A man-machine collaborative interface for supporting remote monitoring and emergency intervention to allow the operator to view real-time operation pictures.

[0012] Further, the man-machine collaborative interface supports multiple modes: AR remote control mode, automatic mode, and emergency takeover mode, wherein: The AR remote control mode is that the operator obtains a first perspective picture through a head-mounted display and controls the robot arm coarsely using gestures; The automatic mode is that the robot completely autonomously executes a preset live working task; The emergency takeover mode is that when an anomaly occurs, the operator directly controls the robot arm finely through a handle.

[0013] Further, it also comprises a modular tool library. The modular tool library is arranged at the end of the mechanical arm quick-change interface, compatible with an insulating wrench, a laser wire stripper, a drainage wire holder, a hydraulic shearing device and an electromagnetic chuck tool. Further comprising: An emergency disengagement device, specifically including a mechanical arm disconnection device driven by gunpowder, for cutting off the physical connection between the mechanical arm and the end tool; A dynamic safety distance control module for real-time adjustment of the distance between the mechanical arm and the live body based on electric field intensity feedback; An autonomous return module for returning to the nearest safe point along the SLAM map when communication is interrupted; An insulation state self-checking unit for automatically testing the overall insulation resistance of the robot to be greater than or equal to the standard resistance value before operation.

[0014] An intelligent operation method of a distribution network non-power outage autonomous operation robot, based on the above-mentioned distribution network non-power outage autonomous operation robot, comprising: Using a multi-modal perception system to perform three-dimensional modeling, discharge detection and safety distance monitoring on the environment, and collecting perception data; Using an intelligent decision-making system to output live working task instructions based on the perception data collected by the multi-modal perception system and a pre-constructed multi-task knowledge graph, and issuing the live working task instructions to the dual-robot collaborative system and the all-terrain mobile platform; During the execution of the live working task, the robot body is insulated and protected by the dynamic insulation protection system, and the insulation mode is automatically switched according to the voltage level; Using the all-terrain mobile platform to climb the pole and walk along the wire; Using the dual-robot collaborative system to grasp the electrical equipment and perform fine operations, and finally collaboratively executing the live working task; the live working task includes live replacement of insulators, live disconnection of drainage lines and live replacement of circuit breakers.

[0015] Further, The specific method of live replacement of insulators includes: Step S11: Positioning the damaged insulator by fusing the binocular vision camera and the laser radar; Step S12: Loosen the locking pin using the insulating ratchet wrench by the secondary robot arm; Step S13: Transfer the old insulator using the electromagnetic chuck by the primary robot arm, and move along the S-shaped obstacle avoidance path to the insulator tray; Step S14: When installing the new insulator, detect the bolt fastening degree by the axial pressure feedback in real time by the force sensor; The specific method of live disconnection of drainage lines includes: Step S21: Establish a parallel drainage path by a telescopic copper shunt; Step S22: Use a secondary robotic arm to control a laser wire stripper to strip the insulation layer of the wire; Step S23: Use the main robotic arm to hold the hydraulic clamp to complete the connection of the drain wire, and use an ultraviolet imager to monitor the discharge pulse frequency; Step S24: Trigger pulsed laser to ionize air at the moment of disconnection; wherein, suppressing operating overvoltage ≤ 1.5 times the system rated voltage; The specific method for replacing the circuit breaker under energized conditions includes: Step S31: Collect the circuit breaker tripping sound wave through the acoustic sensor and input it into the trained convolutional neural network to diagnose the fault type; Step S32: Use two robotic arms to disassemble the bolts in a coordinated manner. The main robotic arm uses an impedance control algorithm to compensate for external disturbances. Step S33: Transfer the old circuit breaker to the insulating tray using an electromagnetic chuck, and verify phase consistency using a wireless phase comparator after installing the new equipment; Step S34: After the replacement is completed, perform an insulation resistance self-test.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention provides an autonomous live-line operation robot for power distribution networks. By integrating a dual-arm collaborative system, an all-terrain mobile platform, a dynamic insulation protection system, a multimodal perception system, and an intelligent decision-making system into the robot body, it achieves autonomous execution of live-line work. The dual-arm collaborative system precisely grasps equipment and executes operations, eliminating human error; the all-terrain mobile platform adapts to complex terrains such as pole climbing and conductor movement, improving mobility; the dynamic insulation protection system automatically switches insulation modes to match voltage levels, ensuring reliable protection; the multimodal perception system provides environmental awareness through real-time 3D modeling, discharge detection, and safety distance monitoring; and the intelligent decision-making system integrates perception data and a pre-built knowledge graph to output optimized instructions, driving the robotic arms and mobile platform to collaboratively complete the task. This robot overcomes the high safety risks and low efficiency of manual operation and the insufficient intelligence of existing robots, significantly improving operational safety, efficiency, and autonomous adaptability, achieving the goal of "zero power outages, full autonomy, and high safety" in power distribution network operation and maintenance.

[0017] Preferably, in this invention, the division of labor structure of the two robotic arms is refined. The high degree of freedom of the main robotic arm ensures the flexibility and stability of the equipment (heavy and large equipment) grasping, while the specific degree of freedom design of the secondary robotic arm focuses on performing precision operations with extremely high accuracy requirements, such as tightening bolts and disconnecting drain lines. This collaborative division of labor design significantly improves the execution accuracy and reliability of complex operation tasks and overcomes the defects of manual operation in terms of accuracy.

[0018] Preferably, in the present application, the specific structure of the all-terrain mobile platform adopts a four-legged-track composite chassis combined with an electromagnetic adsorption device, giving the robot strong pole climbing and wire following capabilities; visual SLAM navigation enables precise positioning and path planning; the built-in gyroscope and barometer cooperate with the dynamic adjustment mechanism of the center of gravity, effectively improving the stability and safety of the robot in strong winds, slopes and other harsh or complex terrains, ensuring the accessibility of the work position.

[0019] Preferably, in the present application, the dynamic insulation protection system adopts multi-layer composite insulation materials (silicone rubber, SF6 gas cavity, epoxy resin sleeve) and automatically switches the optimal insulation mode (air gap or SF6 insulation) according to the real-time detected voltage level, while having dynamic adjustment based on electric field intensity feedback and over-limit alarm and retreat mechanism, realizing the intelligence, self-adaptation and high reliability of insulation protection, greatly reducing the risk of breakdown in high-voltage electric field environment.

[0020] Preferably, in the present application, the multi-modal perception system integrates multiple sensing technologies, such as binocular vision, ultraviolet imaging, electric field intensity, laser ranging and voiceprint recognition, etc., achieving high-precision three-dimensional reconstruction of the working environment, effective capture of discharge phenomena, real-time accurate monitoring of safety distance and acoustic identification of potential faults, providing comprehensive, accurate and real-time perception data basis for intelligent decision-making and environmental interaction.

[0021] Preferably, in the present application, the core elements of the intelligent decision-making system include: a pre-constructed multi-task knowledge graph that stores key operation parameters and rules (such as bolt torque, disconnection sequence, fault characteristics) to provide knowledge support for decision-making; a dynamic path planning algorithm embedded with ROS and reinforcement learning that can optimize obstacle avoidance paths and robot arm trajectories in real time; an electric arc suppression model that can actively control electric arc energy; and a human-machine collaboration interface that ensures monitoring and intervention capabilities. These elements together realize autonomous, safe and optimized decision-making and execution of complex tasks.

[0022] Preferably, in the present application, multiple modes of human-machine collaboration interface are provided, i.e. flexible operation and control modes are provided: AR remote control mode realizes intuitive remote coarse adjustment through first-person view and gesture control; full-automatic mode supports the robot to execute completely autonomously; emergency takeover mode allows the operator to make fine adjustments through the handle in case of abnormality. This multi-mode design greatly enhances the operation flexibility, ability to respond to unexpected situations and overall human-machine collaboration efficiency of the system.

[0023] Preferably, in the present application, the robot also includes a modular tool library and a key safety module, the modular tool library supports fast switching of multiple special tools through a quick-change interface, greatly expanding the robot's ability to perform different live working tasks; the emergency disengagement device ensures physical disconnection in extreme danger; the dynamic safety distance control maintains a safe distance from the live body in real time; the autonomous return module ensures the safe withdrawal of the robot in the event of communication failure; and the insulation state self-checking unit verifies the overall insulation performance before operation. These designs significantly improve the functionality, emergency handling capability, and pre-operation safety level of the system.

[0024] The present application also provides an intelligent operation method of a distribution network non-stop autonomous operation robot, based on the above-mentioned distribution network non-stop autonomous operation robot, the method realizes the whole-process closed loop of distribution network live working through multi-sensing fusion and autonomous decision-making: first, the multi-modal sensing system constructs a three-dimensional environment model in real time, monitors the discharge state and safety distance, and provides a data basis for intelligent decision-making; then, the intelligent decision-making system analyzes the sensing data in combination with the pre-built knowledge graph, dynamically generates operation instructions, and distributes them to the execution unit; during the execution process, the dynamic insulation protection system adaptively switches the insulation mode according to the voltage level, the all-terrain mobile platform autonomously completes pole climbing and wire walking positioning, and the dual-robot arm coordination system accurately executes equipment grabbing and fine operation, finally, the complex tasks such as replacing insulators, disconnecting and connecting drainage lines, and replacing circuit breakers are completed in coordination. With environmental sensing data as input, the intelligent decision-making driven by the knowledge graph replaces the preset program, realizing dynamic optimization of operation instructions and multi-system collaborative control, while the insulation protection and motion execution form a closed loop safety protection. This method fundamentally solves the safety risks, efficiency bottlenecks and poor scene adaptability of manual operation, significantly improves the operation accuracy and operation continuity under complex conditions, and realizes the goal of fully autonomous and highly reliable non-stop operation of distribution network operation and maintenance.

[0025] Preferably, in the present application, specific operation steps for three core operation and maintenance scenarios are provided, which can specifically solve the prominent difficulties in the process of distribution network operation and maintenance: when replacing insulators, visual positioning, use of special tools, obstacle avoidance path transfer, and force feedback are integrated to ensure operation accuracy and equipment installation reliability in high-altitude strong electric fields; when disconnecting and connecting drainage lines, parallel drainage, laser stripping, ultraviolet monitoring, and pulsed laser ionization are used to effectively ensure the safety of high-precision timing operations and suppress arc hazards; when replacing circuit breakers, voiceprint diagnosis, impedance control anti-interference, electromagnetic safety transfer, and phase verification are used to solve the problems of fault identification, operation stability, and phase accuracy in the process of replacing complex equipment. These methods significantly improve the operation safety and task success rate in key live working scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1A whole structure schematic diagram of a network distribution non-power-off autonomous working robot provided by the embodiment of the present application is provided; Figure 2 A live replacement insulator method flow chart based on the network distribution non-power-off autonomous working robot provided by the embodiment of the present application is provided; Figure 3 A live disconnecting and connecting of a current lead method flow chart based on the network distribution non-power-off autonomous working robot provided by the embodiment of the present application is provided; Figure 4 A live replacement circuit breaker method flow chart based on the network distribution non-power-off autonomous working robot provided by the embodiment of the present application is provided. DETAILED DESCRIPTION

[0027] In order to make the technical problems solved by the present application, the technical solutions and beneficial effects clearer, the following specific embodiments are used to further describe the present application. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0028] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0029] Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative labor are within the scope of protection of the present application.

[0030] It should be noted that: similar reference numbers and letters represent similar items in the following drawings, therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0031] In the description of the embodiments of the present application, it should be noted that, if the orientation or position relationship indicated by the terms "upper", "lower", "horizontal", "inner" and the like is based on the orientation or position relationship shown in the drawings, or is the orientation or position relationship when the product of the present application is usually placed, which is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the indicated device or element must have a particular orientation, be constructed and operated in a particular orientation, therefore, it cannot be understood as a limitation on the present application. In addition, the terms "first", "second" and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0032] In addition, if the term "horizontal" is used, it is not meant to require absolutely horizontal surfaces, but rather can be slightly inclined. As such, the term "horizontal" is used to mean that the direction is more horizontal than vertical, and is not meant to require absolute horizontal surfaces.

[0033] In the description of the embodiments of the application, it should also be noted that, unless specifically defined and limited, if the terms "set", "install", "connect", "connect" appear, it should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or indirectly connected through an intermediate medium; it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0034] As mentioned in the background, the traditional distribution network operation needs to be operated with power off, resulting in interruption of user power and economic loss. The existing live working mainly relies on manual operation, which has the following problems: first, high safety risk: manual operation is vulnerable to high-voltage environment, and it is difficult to protect insulation; second, low work efficiency: complex tasks take a long time, and multiple people are needed to cooperate, with high personnel training cost; third, lack of intelligence: existing robots rely on preset programs and can only perform single tasks, which cannot adapt to multiple scene requirements and lack of environmental adaptive ability. In terms of specific live operation tasks, live replacement of insulators requires operators to climb high in the air, which takes a long time and is easily disturbed by strong electric field; live disconnecting of drain wire requires precise control of disconnecting timing, and manual operation is easy to cause electric arc discharge; live replacement of circuit breakers is large in size and complex in wiring, and manual replacement is easy to touch live parts.

[0035] To solve the above problems, the embodiment provides a distribution network non-power-off autonomous operation robot, that is, a fully autonomous and multifunctional live working robot, which can cover core scenes such as insulator replacement, drain wire disconnecting and circuit breaker replacement, and realize "zero power-off, high precision and full autonomy" of distribution network operation. For example, as shown in Figure 1 The embodiment provides a distribution network non-power-off autonomous operation robot, which includes a double-robot arm cooperative system, a modular tool library, an all-terrain mobile platform, a dynamic insulation protection system, a multi-modal perception system and an intelligent decision-making system; it also includes an emergency escape device, a dynamic safety distance control module, an autonomous return module and an insulation state self-checking unit, and the specific structure is as follows: In this embodiment, the dual-arm cooperative system includes a main arm and a secondary arm. The main arm is a seven-degree-of-freedom structure with a load capacity of ≥20 kg, and is used to grasp electrical equipment, preferably heavy equipment such as circuit breakers. The secondary arm is a six-degree-of-freedom structure with a positioning accuracy of ±0.1 mm, and is used to perform fine operations such as screwing bolts and disconnecting wires.

[0036] In this embodiment, the modular tool library is installed at the end of the mechanical arm and is compatible with tools such as insulated wrenches, laser wire strippers, wire clamps, hydraulic cutters, and electromagnetic suction cups, with a switching time of ≤1 second. An example of a full-terrain mobile platform uses a four-legged-track composite chassis, equipped with electromagnetic suction devices, and carries a visual SLAM navigation module, which can climb poles or walk along wires. It has an internal gyroscope and barometer, dynamically adjusts the center of gravity to respond to strong winds or slopes, and has a maximum climbing angle of 30° and a wind resistance level of ≥7.

[0037] The dynamic insulation protection system includes a silicon rubber composite insulation layer (thickness ≥8 mm) and a chargeable SF6 gas insulation cavity (pressure 0.3-0.5 MPa), and the key joints are nested with double-layer epoxy resin insulation sleeves. It automatically switches the insulation mode according to the voltage level. The multi-modal perception system includes binocular vision cameras, ultraviolet imagers, electric field intensity sensors, high-precision laser range finders, and voiceprint recognition modules, which are used for environmental three-dimensional modeling, discharge detection, and safety distance monitoring. The intelligent decision-making system can deploy a multi-task knowledge graph, including an insulator bolt torque database, a wire phase sequence rule library, and a circuit breaker voiceprint fault feature library. Based on the ROS framework, the task planning algorithm supports full-autonomous intelligent operation methods for live replacement of insulators, live disconnection and connection of wires, and live replacement of circuit breakers.

[0038] The emergency escape device is a powder-driven mechanical arm disconnect device (response time ≤0.2s) that cuts off the physical connection between the mechanical arm and the end tool. The dynamic safety distance control module adjusts the distance between the mechanical arm and the live body based on electric field intensity feedback, with a distance of ≥0.4m in a 10kV environment. The autonomous return module returns to the nearest safe point along the SLAM map when communication is interrupted (path planning frequency ≥10Hz). The insulation state self-checking unit automatically tests the overall insulation resistance of the robot to be ≥500MΩ (test voltage 1000V) before operation.

[0039] The control method of the dynamic insulation protection system includes: 1) Mode switching: When the voltage level is ≤10kV, an air gap insulation is used (the distance between the mechanical arm and the live body is ≥0.4m). When the voltage level > 10kV, the SF6 gas insulation cavity (pressure ≥ 0.3MPa) is activated.

[0040] 2) Real-time correction: dynamically adjust the insulation strategy according to the electric field intensity sensor data (threshold 3kV / cm), if the detection value is out of limit, trigger an alarm and return to the safe area.

[0041] For example, the intelligent decision system of the robot comprises: Multi-task knowledge graph: mapping insulator model and bolt torque, lead line disconnection phase sequence rule; Dynamic path planning algorithm: fusion of A* algorithm and reinforcement learning (reward function = task time × 0.6 + safety distance × 0.4), avoiding live bodies and optimizing the motion trajectory of the robot, obstacle avoidance response frequency ≥ 100Hz; Arc suppression model: through the diversion of the shunt and the cooperative control of the laser ionization, the arc energy is limited to ≤10J; Man-machine cooperative interface: supports remote monitoring and emergency intervention, and the operator can view the real-time operation picture through the AR glasses.

[0042] The man-machine cooperative interface supports: 1) AR remote control mode: the operator obtains the first perspective picture through the head-mounted display, and controls the robot arm with gestures; 2) Automatic mode: the robot completely autonomously executes the preset task; 3) Emergency takeover mode: when the system is abnormal, the operator directly controls the robot arm with a force feedback handle; The automatic mode, remote control mode and emergency takeover mode are seamlessly switched, with a delay < 200ms.

[0043] Based on the above distribution network non-stop autonomous operation robot, the embodiment further provides an intelligent operation method of the distribution network non-stop autonomous operation robot, which comprises specific operation methods of live insulator replacement, live lead line disconnection and connection, and circuit breaker replacement, and the specific implementation is as follows: As shown in Figure 2 The live insulator replacement method comprises the following steps: Step S1: locate the damaged insulator through fusion positioning of binocular vision camera and laser radar, with a coordinate error ≤ 2cm; Step S2: the auxiliary robot arm uses an insulating ratchet wrench (torque setting 20-30N·m) to loosen the locking pin, with a torque control error ±3%; Step S3: the main robot arm transfers the old insulator through an electromagnetic chuck, and moves along an S-shaped obstacle avoidance path (distance from the lead ≥ 0.4m) to the insulator tray; Step S4: When installing a new insulator, the force sensor provides real-time feedback of the axial pressure (180-220 N), ensuring that the bolt fastening meets the GB / T775.3 standard.

[0044] As shown in Figure 3 , the method for charging disconnecting and connecting the current-carrying wire includes the following steps: Step S1: Establish a parallel current-carrying path through a telescopic copper shunt (cross-sectional area ≥120 mm 2 ) to divert ≥90% of the load current (contact resistance ≤50 μΩ); Step S2: The secondary mechanical arm controls the laser wire stripper (pulse frequency 1 kHz) to strip the insulating layer of the wire, with a depth of 0.8±0.1 mm; Step S3: The main mechanical arm holds the hydraulic wire clamp to complete the butt joint of the current-carrying wire, and the ultraviolet imager monitors the discharge pulse frequency <5 times / minute; Step S4: Trigger pulsed laser ionization of air at the moment of disconnection to suppress the operating overvoltage ≤1.5 times the system rated voltage.

[0045] As shown in Figure 4 , the method for charging replacing the circuit breaker includes the following steps: Step S1: The voiceprint sensor collects the circuit breaker opening sound waves, and diagnoses the fault type through a convolutional neural network (CNN) (accuracy ≥95%); Step S2: The dual mechanical arms cooperatively disassemble the M16 bolts (torque 80±5 N·m), the main mechanical arm uses impedance control algorithm to compensate for external disturbances, and the positioning error of the secondary mechanical arm is ≤0.3 mm; Step S3: The electromagnetic chuck (holding force ≥200 N) transfers the old circuit breaker to the insulating tray, and after installing the new device, verifies the phase consistency through the wireless phase comparator (2.4 GHz frequency band), with a deviation ≤1°; Step S4: After replacement, perform self-insulation resistance test (test voltage 2500 V), with an inter-electrode resistance ≥1000 MΩ.

[0046] The above embodiments provide a distribution network non-stop autonomous operating robot and an intelligent operating method thereof, which are described in detail in the following specific embodiments: Embodiment 1: Charging replacement of insulator.

[0047] Operating scenario: 10 kV distribution network line, cement pole tower, single string suspension insulator damage Implementation steps: 1. Environmental perception and positioning.

[0048] The robot climbs to the work point of the pole, and the laser radar scans to build a 3D model of the insulator tower. The vision system identifies the broken insulator (model XP-70) and locates its hanging point coordinates (X=3.2m, Y=0.8m, Z=10.5m).

[0049] 2. Insulation barrier activation.

[0050] The electric field intensity sensor detects the electric field intensity in the work area as 2.8kV / cm, triggering the air gap insulation mode, and the mechanical arm automatically maintains a distance ≥0.45m from the live body.

[0051] 3. Bolt disassembly and replacement.

[0052] The secondary mechanical arm (precision ±0.1mm) uses an insulating ratchet wrench (torque set to 25N·m) to loosen the locking pin, with an error control of ±3%.

[0053] The main mechanical arm (load 20kg) absorbs the old insulator through an electromagnetic chuck, and moves it out to the insulation tray along the preset trajectory (S-shaped obstacle avoidance path).

[0054] When installing the new insulator, the force sensor provides real-time feedback on the bolt tightening state, ensuring that the axial pressure is stable within the range of 180-220N.

[0055] After the replacement is completed, the work video is returned to the monitoring center through the 5G module, and an electronic maintenance report is generated.

[0056] The effect verification of this embodiment is: Operation time: 12 minutes and 38 seconds (average manual operation time 45 minutes).

[0057] Safety data: Maximum leakage current during operation <0.1mA (standard limit value 0.5mA according to GB / T16927.1).

[0058] Positioning accuracy: error of insulator hanging point coordinates 1.7cm.

[0059] II. Example 2: Live disconnection of the current-carrying wire.

[0060] Work scenario: 35kV power transmission line, tension pole tower, need to disconnect and replace the C-phase current-carrying wire.

[0061] Implementation steps: 1. Current transfer preparation.

[0062] The robot carries a telescopic copper shunt (cross-sectional area 120mm 2 ) to contact the near end of the current-carrying wire, and confirms the shunt current ≥320A (accounting for 92% of the total load) through the Hall sensor.

[0063] UV imaging instrument continuously monitors the disconnection point, and the discharge pulse frequency is <5 times / minute to start the operation.

[0064] 2. Precise disconnection operation.

[0065] The secondary mechanical arm uses a laser wire stripper (wavelength 1064nm) to strip the wire insulation layer, with a depth control of 0.8±0.1mm and an exposed conductor length of 50mm.

[0066] The main mechanical arm holds the hydraulic clamp installer to complete the butt joint of the new and old drainage lines, with a contact resistance ≤20μΩ (actually measured 18μΩ).

[0067] 3. Arc suppression and verification.

[0068] The pulsed laser ionization guide is started at the moment of wire breakage, with an operating overvoltage peak of 52kV (system rated 35kV, 1.49 times).

[0069] After the disconnection is completed, the infrared thermal imager scans the connection point, with a temperature rise ≤3℃ (environmental temperature 25℃).

[0070] Effect verification of this embodiment: Arc control: visible arc duration 0.8 seconds (manual operation average 4.5 seconds).

[0071] Voltage safety: overvoltage duration <1ms, without triggering line protection action.

[0072] Efficiency improvement: total process time 9 minutes and 12 seconds (manual operation needs 25 minutes).

[0073] III. Example 3: Live replacement of circuit breaker.

[0074] Work scene: 10kV substation, vacuum circuit breaker (model ZN63A) contact ablation replacement Implementation steps: 1. Fault diagnosis and positioning.

[0075] The voiceprint sensor collects the circuit breaker opening sound, which is analyzed by the CNN model (training set contains 2000 groups of fault samples), and identifies the contact ablation fault (confidence 96.3%).

[0076] The laser range finder locates the circuit breaker mounting flange bolt hole, with a coordinate error of ±0.5mm.

[0077] 2. Cooperative disassembly and installation.

[0078] Dual mechanical arm cooperative work: the main mechanical arm fixes the circuit breaker body (impedance control anti-vibration interference), and the secondary mechanical arm disassembles the M16 bolts (8, torque set to 80N·m).

[0079] After the old circuit breaker is removed, a wireless phase detector (2.4 GHz frequency band) is installed at the end of the mechanical arm to verify the phase deviation of the new circuit breaker, which is 0.7° (the national standard allows ≤5°).

[0080] 3. Insulation recovery detection.

[0081] After replacement, the robot self-checks the insulation resistance (2500V megohm meter equivalent test), and the inter-pole resistance is ≥1000MΩ (standard ≥500MΩ).

[0082] The effect verification of the embodiment is as follows: Collaborative accuracy: bolt disassembly concentricity error ≤0.3mm.

[0083] Phase efficiency: phase verification time is 23 seconds (manual operation average 5 minutes).

[0084] Insulation performance: after replacement, the partial discharge amount is 8pC (the standard limit value of GB / T7354 is 10pC).

[0085] In summary, the application provides a distribution network autonomous working robot and an intelligent working method thereof, which has the following advantages compared with the existing power distribution operation mode: 1. Full working condition autonomy: combining environment perception, task planning and precise control to reduce manual intervention; 2. Multi-sensor collaboration: improving fault identification reliability through the fusion of vision, force sensation and partial discharge data; 3. Multi-task collaboration capability: through double mechanical arm division of labor and cooperation and tool quick change system, compatible with the differentiated operation needs of insulators, drain wires, circuit breakers and the like; 4. Man-machine co-fusion interaction: supporting remote virtual reality control and seamless switching between local autonomous mode; 5. Electromagnetic environment self-adaptation: combining electric field strength perception and dynamic insulation regulation to solve the problem of robot control stability under high electromagnetic interference, and the robot can automatically switch the insulation mode according to the voltage level; 6. Knowledge-driven decision making: based on the standard operation process of power equipment, an expert system is constructed to ensure operation compliance.

[0086] The application can be applied to urban distribution networks, substations, new energy stations and other scenes, and can perform live defect elimination, equipment installation, tree barrier cleaning and other tasks, significantly improving power supply reliability and operation economy.

[0087] The above embodiment is only one of the implementation manners of the technical scheme of the application, and the scope of protection claimed by the application is not limited to the above embodiment, but also includes any changes, substitutions and other implementation manners easily thought of by those skilled in the art within the technical scope disclosed by the application.

Claims

1. A power distribution network uninterrupted autonomous operation robot, characterized in that, Including the robot itself; The robot body is equipped with a dual-arm collaborative system, an all-terrain mobile platform, a dynamic insulation protection system, a multimodal perception system, and an intelligent decision-making system; The dual robotic arm collaborative system is used to grasp electrical equipment and perform delicate operations; The all-terrain mobile platform is used to climb utility poles and travel along power lines; The dynamic insulation protection system is used to provide insulation protection for the robot body and automatically switch the insulation mode according to the voltage level. The multimodal sensing system is used for three-dimensional environmental modeling, discharge detection, and safe distance monitoring. The intelligent decision-making system is used to output a live-line operation task instruction after judging based on the perception data collected by the multimodal perception system and the pre-constructed multi-task knowledge graph. The live-line operation task instruction is then sent to the dual-manipulator collaborative system and the all-terrain mobile platform, so that the dual-manipulator collaborative system and the all-terrain mobile platform can work together to complete the live-line operation task.

2. The power distribution network uninterrupted autonomous operation robot according to claim 1, characterized in that, The dual-manipulator collaborative system includes a main manipulator and a secondary manipulator; The main robotic arm has a seven-degree-of-freedom structure and is used to grasp electrical equipment; The auxiliary robotic arm is a six-degree-of-freedom structure used to perform fine operations, including tightening bolts and disconnecting drain wires.

3. The power distribution network uninterrupted autonomous operation robot according to claim 1, characterized in that, The all-terrain mobile platform adopts a quadruped-tracked composite chassis; the quadruped-tracked composite chassis is equipped with an electromagnetic adsorption device and a visual SLAM navigation module for climbing utility poles or walking along power lines; the quadruped-tracked composite chassis has a built-in gyroscope and barometer, which can dynamically adjust the center of gravity to cope with strong winds or slopes.

4. The power distribution network uninterrupted autonomous operation robot according to claim 1, characterized in that, The dynamic insulation protection system includes a silicone rubber composite insulation layer, a refillable SF6 gas insulation cavity, and a double-layer epoxy resin insulation sleeve nested in the key joints of the robot body. The control method of the dynamic insulation protection system includes: Mode switching operation: When the voltage level is less than or equal to the preset voltage, air gap insulation is used; When the voltage level is greater than the preset voltage, the refillable SF6 gas insulation chamber is activated. Real-time correction operation: The insulation strategy is dynamically adjusted based on the data from the electric field strength sensor. If the detected value exceeds the limit, an alarm is triggered and the system returns to a safe area.

5. The power distribution network uninterrupted autonomous operation robot according to claim 1, characterized in that, The multimodal perception system includes a binocular vision camera, an ultraviolet imager, an electric field strength sensor, a high-precision laser rangefinder, and a voiceprint recognition module, used for 3D environmental modeling, discharge detection, and safe distance monitoring.

6. The power distribution network uninterrupted autonomous operation robot according to claim 1, characterized in that, The intelligent decision-making system includes: A multi-task knowledge graph is used to map insulator models with bolt torque and drain wire disconnection phase sequence rules; wherein the multi-task knowledge graph includes an insulator bolt torque database, a drain wire phase sequence rule database, and a circuit breaker acoustic fault feature database. The embedded dynamic path planning algorithm integrates the task planning algorithm of the ROS framework with reinforcement learning to dynamically plan the motion path in order to avoid charged bodies and optimize the motion trajectory of the robotic arm. An arc suppression model is used to limit the arc energy within a preset range through the coordinated control of shunt current diversion and laser ionization. The human-machine interface is used to support remote monitoring and emergency intervention, allowing operators to view real-time operation footage.

7. The power distribution network uninterrupted autonomous operation robot according to claim 6, characterized in that, The human-machine interface supports multiple modes: AR remote control mode, automatic mode, and emergency takeover mode, among which: The AR remote control mode is as follows: the operator obtains a first-person view through a head-mounted display and uses gestures to control the robotic arm for coarse adjustments. The automatic mode is: the robot performs the preset live-line operation task completely autonomously; The emergency takeover mode is as follows: when an abnormality occurs, the operator can directly control the robotic arm for fine-tuning via a handle.

8. The power distribution network uninterrupted autonomous operation robot according to claim 1, characterized in that, It also includes a modular tool library; The modular tool library is located at the quick-change interface at the end of the robotic arm and is compatible with insulated wrenches, laser wire strippers, drain wire holders, hydraulic shears, and electromagnetic chucks. Also includes: Emergency disengagement device, specifically including a gunpowder-driven robotic arm disconnection device, used to sever the physical connection between the robotic arm and the end effector; The dynamic safety distance control module is used to adjust the distance between the robotic arm and the charged body in real time based on electric field strength feedback; The autonomous return-to-home module is used to retreat along the SLAM map to the nearest safe point when communication is interrupted; The insulation condition self-test unit is used to automatically test the overall insulation resistance of the robot before operation to ensure it is greater than or equal to the standard resistance value.

9. An intelligent operation method for an autonomous robot operating without power outages in a power distribution network, characterized in that, A power distribution network uninterrupted autonomous operation robot according to any one of claims 1-8 includes: A multimodal sensing system is used to perform 3D environmental modeling, discharge detection, and safe distance monitoring, and to collect sensing data. The intelligent decision-making system uses the perception data collected by the multimodal perception system and the pre-built multi-task knowledge graph to make judgments and outputs the live-line operation task instructions, which are then sent to the dual robotic arm collaborative system and the all-terrain mobile platform. During the execution of live-line work tasks, the robot body is insulated and protected by a dynamic insulation protection system, and the insulation mode is automatically switched according to the voltage level. Use an all-terrain mobile platform to climb utility poles and walk along the power lines; A dual-arm collaborative system is used to grasp electrical equipment and perform precise operations, ultimately completing the live-line work task in a coordinated manner; the live-line work task includes live-line replacement of insulators, live-line disconnection of lead wires, and live-line replacement of circuit breakers.

10. The intelligent operation method of a power distribution network uninterrupted autonomous operation robot according to claim 9, characterized in that, The specific method for replacing insulators under energized conditions includes: Step S11: Locate the damaged insulator by fusing binocular vision camera and lidar; Step S12: Use the auxiliary robotic arm and an insulated ratchet wrench to loosen the locking pin; Step S13: Use the main robotic arm to transfer the old insulator via an electromagnetic chuck, moving along an S-shaped obstacle avoidance path to the insulation tray; Step S14: When installing a new insulator, the bolt tightness is detected by the axial pressure feedback in real time through the force sensor; The specific method for disconnecting the live drain wire includes: Step S21: Establish a parallel conduction path using a retractable copper shunt; Step S22: Use a secondary robotic arm to control a laser wire stripper to strip the insulation layer of the wire; Step S23: Use the main robotic arm to hold the hydraulic clamp to complete the connection of the drain wire, and use an ultraviolet imager to monitor the discharge pulse frequency; Step S24: Trigger pulsed laser to ionize air at the moment of disconnection; wherein, suppressing operating overvoltage ≤ 1.5 times the system rated voltage; The specific method for replacing the circuit breaker under energized conditions includes: Step S31: Collect the circuit breaker tripping sound wave through the acoustic sensor and input it into the trained convolutional neural network to diagnose the fault type; Step S32: Use two robotic arms to disassemble the bolts in a coordinated manner. The main robotic arm uses an impedance control algorithm to compensate for external disturbances. Step S33: Transfer the old circuit breaker to the insulating tray using an electromagnetic chuck, and verify phase consistency using a wireless phase comparator after installing the new equipment; Step S34: After the replacement is completed, perform an insulation resistance self-test.

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