Grounding opening and closing device and method based on flexible tightening

Abstract

The invention relates to the technical field of power supply equipment, and particularly discloses a grounding opening and closing device and method based on flexible tightening, and the device comprises a data collection module, a path planning module, a height self-adaption module, a vibration suppression module and a collaborative decision module. The data acquisition module is fused with a visual sensor through a laser radar to generate obstacle three-dimensional point cloud data and high-voltage switch cabinet positioning coordinates; the path planning module generates an obstacle avoidance path based on a genetic algorithm, encodes target coordinates, and drives the chassis of the mobile robot to autonomously avoid obstacles; the height self-adaptive module optimizes hydraulic parameters of the lifting platform, and the screw rod is combined to drive the sliding table module to perform closed-loop feedback so as to realize high-precision positioning of the grounding brake, and through optimization and closed-loop control of the multi-module genetic algorithm, the problems of low manual operation efficiency, insufficient equipment vibration suppression and poor positioning precision are solved; and high-efficiency positioning, low vibration and high safety of grounding switch opening and closing operation are realized in a complex power distribution environment.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution equipment, and in particular to a grounding opening and closing device and method based on flexible tightening. Background Art

[0002] In the power supply maintenance of high-voltage switchgear, the opening and closing operations of the grounding gates are usually completed manually, which has the problems of low operating efficiency and high safety risks. Due to the differences in the position and height of the grounding gates of different high-voltage switchgears in the power distribution system, manual operation requires frequent adjustment of the tool position and angle, which makes it difficult to achieve fast and accurate docking, resulting in prolonged operation time and increased risk of electric shock. Existing automated equipment lacks effective vibration suppression and alignment fault tolerance mechanisms during the docking process, resulting in vibrations being transmitted to the equipment structure during operation, affecting positioning accuracy and equipment stability, and making it difficult to adapt to the needs of efficient and reliable grounding opening and closing in complex power distribution environments. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention provides a grounding opening and closing device and method based on flexible tightening, which is used to solve the technical problems of low operating efficiency, high safety risks and difficulty in adapting to complex power distribution environments caused by low manual efficiency, insufficient vibration suppression and poor positioning accuracy of existing automation equipment in the opening and closing operations of the grounding switch of the high-voltage switch cabinet in the power distribution system.

[0004] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows: In a first aspect, the grounding opening and closing device based on flexible tightening provided by the present invention comprises: Data acquisition module, used to collect environmental perception data, equipment status data and damping parameters of polyurethane vibration damping blocks. Environmental perception data includes obstacle 3D point cloud data and visual coordinate data. Equipment status data includes hydraulic control parameters of the lifting platform, grounding gate height data and screw drive slide module displacement data. The path planning module generates the obstacle avoidance path of the mobile robot chassis based on the obstacle 3D point cloud data and visual coordinate data, encodes the obstacle avoidance path of the mobile robot chassis through the genetic algorithm, and generates the coordinates of the target high-voltage switch cabinet; The height adaptive module receives the coordinates of the target high-voltage switch cabinet, combines the hydraulic control parameters of the lifting platform and the height data of the grounding gate of the data acquisition module, optimizes the hydraulic control parameters of the lifting platform through the genetic algorithm, drives the screw to drive the slide module to move vertically to the target height, and the slide module is linearly displaced by the screw drive. The displacement state of the slide module is fed back in real time by the displacement data of the screw driving the slide module. After positioning is completed, a height adjustment signal is sent to the vibration suppression module; The vibration suppression module collects the vibration spectrum data of the end of the grounding switch according to the height adjustment signal, dynamically optimizes the damping parameters of the polyurethane vibration damping block through the genetic algorithm, and collects the end posture data of the tooling through the posture sensor; The collaborative decision-making module integrates the path error of the path planning module, the height deviation of the height adaptation module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, builds a target optimization model, generates an instruction set through the target optimization model, and distributes the instructions to the chassis, slide module and servo motor of the driving mobile robot to collaboratively complete the grounding switch opening and closing operations.

[0005] Furthermore, in the grounding opening and closing device based on flexible tightening described in the present invention, the path planning module is also used for: Based on the three-dimensional point cloud data and visual coordinate data of the obstacle collected by the data acquisition module, the obstacle contour information is generated by the laser radar, and matched with the high-voltage switchgear positioning mark in the visual feature identification data, and the path planning fitness function is constructed to evaluate the feasibility of the obstacle avoidance path; Generate path nodes based on the obstacle avoidance path, perform chromosome crossover and mutation operations on the steering angles, moving speeds, and safe obstacle avoidance distances between the path nodes through a genetic algorithm, and generate a candidate path set; The candidate path solution set that meets the preset positioning accuracy threshold is output to the collaborative decision-making module as the path input parameter of the multi-objective optimization model in the collaborative decision-making module.

[0006] Furthermore, in the grounding opening and closing device based on flexible tightening described in the present invention, the highly adaptive module is also used for: Based on the hydraulic control parameters of the lifting platform and the grounding gate height data, a multi-dimensional optimization target including the height error of the lifting platform, the displacement speed of the sliding table module and the load current of the servo motor is constructed by a genetic algorithm to calculate the height adaptive fitness value; According to the preset highly adaptive fitness value threshold, the candidate solution set of hydraulic control parameters is screened, and the candidate parameters with the top 10% fitness values ​​are retained using an elite retention strategy; The optimized target height value is synchronized to the alignment control module through the genetic algorithm, and is used as a height constraint condition for the alignment control module to generate a rotation angle sequence of the grounding gate screwing tooling.

[0007] Furthermore, in the grounding opening and closing device based on flexible tightening described in the present invention, the vibration suppression module is also used for: Based on the posture data of the tooling end collected by the posture sensor and the damping parameters of the data acquisition module, the vibration spectrum data of the grounding switch twisting tooling end is collected by the acceleration sensor, and the vibration energy distribution characteristics in the 0-1kHz frequency band are extracted as the population initialization parameters of the genetic algorithm; By using the genetic algorithm, the compression deformation and vibration attenuation rate of the polyurethane vibration damping block are used as vibration suppression fitness evaluation indicators to screen candidate solutions for damping parameters; The damping parameter optimization data that meets the vibration suppression fitness evaluation index is fed back to the collaborative decision-making module, triggering the collaborative decision-making module to dynamically correct the opening and closing operation instruction set based on the multi-objective optimization model.

[0008] Furthermore, in the grounding opening and closing device based on flexible tightening described in the present invention, the collaborative decision-making module is also used for: Based on the positioning error of the path planning module, the height deviation of the height adaptive module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, a multi-objective optimization model is constructed to perform normalized weighted processing on the positioning error, height deviation, spectrum data and angle deviation; Generate a global optimal operation instruction set including a high-torque servo motor speed instruction, a slide module displacement instruction and a lifting platform hydraulic control instruction based on the multi-objective optimization model through the non-dominated sorting genetic algorithm of the collaborative decision-making module; The global optimal operation instruction set is distributed to the mobile robot chassis, the screw-driven slide module and the high-torque servo motor, so as to drive the mobile robot chassis, the screw-driven slide module and the high-torque servo motor to collaboratively complete the grounding switch opening and closing operations.

[0009] In a second aspect, the grounding opening and closing method based on flexible tightening provided by the present invention is applied to the grounding opening and closing device based on flexible tightening, comprising: Step S1, collecting environmental perception data, equipment status data and damping parameters of polyurethane vibration damping blocks, the environmental perception data includes obstacle three-dimensional point cloud data and visual coordinate data, and the equipment status data includes hydraulic control parameters of the lifting platform, grounding gate height data and screw drive slide module displacement data; Step S2, generating an obstacle avoidance path for the mobile robot chassis based on the obstacle three-dimensional point cloud data and the visual coordinate data, encoding the obstacle avoidance path for the mobile robot chassis through a genetic algorithm, and generating the coordinates of the target high-voltage switch cabinet; Step S3, receiving the coordinates of the target high-voltage switch cabinet, combining the hydraulic control parameters of the lifting platform of the data acquisition module and the height data of the grounding switch, optimizing the hydraulic control parameters of the lifting platform through the genetic algorithm, driving the screw to drive the slide module to move vertically to the target height, the slide module is linearly displaced by the screw drive, and the displacement state of the slide module is fed back in real time by the displacement data of the screw driving the slide module, and sending a height adjustment signal to the vibration suppression module after positioning is completed; Step S4, collecting vibration spectrum data of the end of the grounding switch turning tooling according to the height adjustment signal, dynamically optimizing the damping parameters of the polyurethane vibration damping block through a genetic algorithm, and collecting the posture data of the end of the tooling through a posture sensor; Step S5, integrating the path error of the path planning module, the height deviation of the height adaptation module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, constructing a target optimization model, generating an instruction set through the target optimization model, and distributing the instructions to the chassis, slide module and servo motor of the driving mobile robot to collaboratively complete the grounding switch opening and closing operation.

[0010] Furthermore, in the grounding opening and closing method based on flexible tightening described in the present invention, step S2 comprises: Based on the three-dimensional point cloud data and visual coordinate data of the obstacle collected by the data acquisition module, the obstacle contour information is generated by the laser radar, and matched with the high-voltage switchgear positioning mark in the visual feature identification data, and the path planning fitness function is constructed to evaluate the feasibility of the obstacle avoidance path; Generate path nodes based on the obstacle avoidance path, perform chromosome crossover and mutation operations on the steering angles, moving speeds, and safe obstacle avoidance distances between the path nodes through a genetic algorithm, and generate a candidate path set; The candidate path solution set that meets the preset positioning accuracy threshold is output to the collaborative decision-making module as the path input parameter of the multi-objective optimization model in the collaborative decision-making module.

[0011] Furthermore, in the grounding opening and closing method based on flexible tightening described in the present invention, step S3 comprises: Based on the hydraulic control parameters of the lifting platform and the grounding gate height data, a multi-dimensional optimization target including the height error of the lifting platform, the displacement speed of the sliding table module and the load current of the servo motor is constructed by a genetic algorithm to calculate the height adaptive fitness value; According to the preset highly adaptive fitness value threshold, the candidate solution set of hydraulic control parameters is screened, and the candidate parameters with the top 10% fitness values ​​are retained using an elite retention strategy; The optimized target height value is synchronized to the alignment control module through the genetic algorithm, and is used as a height constraint condition for the alignment control module to generate a rotation angle sequence of the grounding gate screwing tooling.

[0012] Furthermore, in the grounding opening and closing method based on flexible tightening described in the present invention, step S4 comprises: Based on the posture data of the tooling end collected by the posture sensor and the damping parameters of the data acquisition module, the vibration spectrum data of the grounding switch twisting tooling end is collected by the acceleration sensor, and the vibration energy distribution characteristics in the 0-1kHz frequency band are extracted as the population initialization parameters of the genetic algorithm; By using the genetic algorithm, the compression deformation and vibration attenuation rate of the polyurethane vibration damping block are used as vibration suppression fitness evaluation indicators to screen candidate solutions for damping parameters; The damping parameter optimization data that meets the vibration suppression fitness evaluation index is fed back to the collaborative decision-making module, triggering the collaborative decision-making module to dynamically correct the opening and closing operation instruction set based on the multi-objective optimization model.

[0013] Furthermore, in the grounding opening and closing method based on flexible tightening described in the present invention, step S5 comprises: Based on the positioning error of the path planning module, the height deviation of the height adaptive module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, a multi-objective optimization model is constructed to perform normalized weighted processing on the positioning error, height deviation, spectrum data and angle deviation; Generate a global optimal operation instruction set including a high-torque servo motor speed instruction, a slide module displacement instruction and a lifting platform hydraulic control instruction based on the multi-objective optimization model through the non-dominated sorting genetic algorithm of the collaborative decision-making module; The global optimal operation instruction set is distributed to the mobile robot chassis, the screw-driven slide module and the high-torque servo motor, so as to drive the mobile robot chassis, the screw-driven slide module and the high-torque servo motor to collaboratively complete the grounding switch opening and closing operations.

[0014] Beneficial effects of the present invention: The present invention effectively solves the technical problems of low manual efficiency, insufficient vibration suppression of automated equipment and poor positioning accuracy in the opening and closing operation of the earthing switch of the high-voltage switch cabinet by combining multi-module collaborative control with genetic algorithm optimization. The data acquisition module integrates the environmental perception data of the laser radar and the visual sensor to construct an accurate three-dimensional environmental map, providing reliable input for the path planning module to generate obstacle avoidance paths, and improving the autonomous navigation efficiency of the mobile robot chassis in complex power distribution environments; the highly adaptive module optimizes the hydraulic control parameters based on the genetic algorithm, and combines the closed-loop feedback mechanism of the screw-driven slide module to achieve accurate positioning and dynamic calibration of the height of the earthing switch, and reduce the influence of vibration transmission on vertical positioning; the vibration suppression module dynamically adjusts the damping parameters of the vibration reduction block through spectrum feature extraction and genetic algorithm, suppresses mechanical vibration interference, and improves the posture stability of the tooling end; the collaborative decision-making module integrates multi-source data to construct a multi-objective optimization model, generates a global optimal instruction set to drive the execution unit to work collaboratively, and corrects motion deviations through real-time feedback, and realizes high-precision, low-vibration automated opening and closing operations under vibration interference and complex spatial constraints, significantly improving operation safety and system reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative labor.

[0016] Figure 1 A flow chart of a grounding opening and closing method based on flexible tightening provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0018] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0019] In a first aspect, the grounding opening and closing device based on flexible tightening provided by the present invention comprises: Data acquisition module, used to collect environmental perception data, equipment status data and damping parameters of polyurethane vibration damping blocks. Environmental perception data includes obstacle 3D point cloud data and visual coordinate data. Equipment status data includes hydraulic control parameters of the lifting platform, grounding gate height data and screw drive slide module displacement data. The data acquisition module collects environmental perception data and equipment status data in real time through multi-sensor fusion technology, providing basic input parameters for subsequent modules. Specifically, the three-dimensional point cloud data of obstacles in the environmental perception data is generated by three-dimensional scanning of the working environment by LiDAR. The scanning frequency and resolution are set according to the positioning accuracy requirements of the high-voltage switchgear. The point cloud data contains the spatial coordinates, outline size and distribution density of the obstacles. The visual coordinate data is collected by the visual sensor installed on the chassis of the mobile robot. The positioning identification features of the high-voltage switchgear are extracted through image processing algorithms, including the shape, color and spatial posture of the identification, and are aligned in time and space with the LiDAR point cloud data to eliminate the calibration errors between sensors and build an accurate three-dimensional environmental map.

[0020] The hydraulic control parameters of the lifting platform in the equipment status data are monitored in real time through pressure sensors and flow meters, including hydraulic cylinder pressure, oil flow and valve opening, which are used to quantify the power output status of the lifting mechanism. The grounding gate height data is measured by a laser rangefinder or encoder, and the dynamic deviation between the actual height and the target height is calculated based on the installation reference surface of the grounding gate. The displacement data of the screw-driven slide module is collected through a linear encoder, which feeds back the linear displacement and movement speed of the slide module in real time, providing feedback signals for the closed-loop control of the height adaptive module.

[0021] The damping parameters of the polyurethane vibration damping block are collected in real time through an embedded sensor group, including strain sensors and acceleration sensors. The strain sensor measures the compression deformation of the vibration damping block under load, and the acceleration sensor monitors the frequency spectrum characteristics of the vibration transmitted to the end of the tooling. The dynamic changes of the damping coefficient are calculated after the data of the two are fused. The damping parameters are associated with the frequency spectrum analysis results of the vibration suppression module to optimize the dynamic response characteristics of the vibration damping block and suppress the mechanical vibration during the opening and closing operations.

[0022] The collection, alignment and fusion of the above data are realized through the central processing unit. Environmental perception data is used for obstacle avoidance path generation of the path planning module, equipment status data drives the hydraulic parameter optimization of the highly adaptive module, and damping parameters provide the initial population for the genetic algorithm of the vibration suppression module. Each data is transmitted to the corresponding module through the bus to form a closed-loop control chain of "perception-decision-execution", providing high-precision and low-latency data support for the grounding switch opening and closing operations. The present invention solves the control lag problem caused by data islands in the prior art through the collaborative collection and processing of multi-source heterogeneous data.

[0023] The path planning module generates the obstacle avoidance path of the mobile robot chassis based on the obstacle 3D point cloud data and visual coordinate data, encodes the obstacle avoidance path of the mobile robot chassis through the genetic algorithm, and generates the coordinates of the target high-voltage switch cabinet; The path planning module generates and optimizes obstacle avoidance paths based on the three-dimensional point cloud data and visual coordinate data of obstacles provided by the data acquisition module. Specifically, the laser radar performs a three-dimensional scan of the working environment to generate point cloud data containing obstacle contour information, while the visual sensor captures the positioning identification features of the high-voltage switchgear. The laser radar point cloud and visual coordinate data are fused through a spatiotemporal calibration algorithm to eliminate the position deviation between sensors, build an accurate three-dimensional environmental map, and identify the spatial coordinates of the target high-voltage switchgear and the distribution of surrounding obstacles.

[0024] Based on the three-dimensional environment map, the path planning module generates the initial obstacle avoidance path of the mobile robot chassis. The path ends at the target high-voltage switchgear coordinates, and the path nodes contain the steering angle, moving speed and safe obstacle avoidance distance parameters of the mobile robot. The path nodes are encoded by genetic algorithm, and the path planning fitness function is constructed. The total length of the path, the smoothness of the steering angle and the minimum safe distance from the obstacle are used as evaluation indicators to quantify the feasibility of each candidate path. The chromosome crossover and mutation operations are performed on the encoded path nodes to generate a candidate path set containing multiple groups of path solutions, covering different motion trajectories and obstacle avoidance strategies.

[0025] In the candidate path set, the path solution set that meets the preset positioning accuracy threshold is screened. The threshold is set based on the geometric dimensions of the high-voltage switchgear and the motion accuracy of the mobile robot chassis, and the path solutions that deviate from the target coordinates or have insufficient safety distance are eliminated. The screened candidate path solution set is output to the collaborative decision-making module as the path input parameter of the multi-objective optimization model, so that the subsequent modules can perform global optimization on the motion trajectory of the mobile robot chassis. The above steps form a closed-loop control chain: environmental perception data drives path generation, genetic algorithms optimize path parameters, and the screened solution set provides input for collaborative decision-making, ultimately achieving accurate obstacle avoidance and target positioning of the mobile robot chassis.

[0026] The height adaptive module receives the coordinates of the target high-voltage switch cabinet, combines the hydraulic control parameters of the lifting platform and the height data of the grounding gate of the data acquisition module, optimizes the hydraulic control parameters of the lifting platform through the genetic algorithm, drives the screw to drive the slide module to move vertically to the target height, and the slide module is linearly displaced by the screw drive. The displacement state of the slide module is fed back in real time by the displacement data of the screw driving the slide module. After positioning is completed, a height adjustment signal is sent to the vibration suppression module; The height adaptation module receives the target high-voltage switchgear coordinates provided by the path planning module, and performs hydraulic parameter optimization and height positioning operations in combination with the lifting platform hydraulic control parameters and grounding gate height data collected by the data acquisition module. Specifically, a multi-dimensional optimization target is constructed through a genetic algorithm, including the height error of the lifting platform, the displacement speed of the slide module, and the load current of the servo motor. The height error is calculated by the difference between the real-time measured grounding gate height and the target height. The displacement speed of the slide module reflects the vertical movement efficiency, and the servo motor load current represents the real-time load state of the lifting mechanism. The above parameters are weighted and fused to generate a height adaptation fitness value, which is used to quantify the degree of optimization of the hydraulic control parameters. The higher the fitness value, the better the height positioning accuracy and motion stability.

[0027] The candidate solution set of hydraulic control parameters is screened according to the preset highly adaptive fitness value threshold. The threshold is set based on the installation accuracy requirements of the earthing gate of the high-voltage switch cabinet, and is used to exclude parameter combinations that may cause excessive height deviation or unstable motion. The candidate solution set is iteratively optimized using an elite retention strategy, and the candidate parameters with the top 10% fitness values ​​are retained. A new generation of parameter sets is generated through the crossover and mutation operation of the genetic algorithm, gradually approaching the optimal solution. The optimized target height value is precisely positioned through the closed-loop control of the screw-driven slide module, and the slide module displacement data is fed back to the data acquisition module in real time to form a dynamic calibration mechanism for height adjustment.

[0028] The optimized target height value is synchronized to the alignment control module through the data bus as a height constraint condition for generating the rotation angle sequence of the grounding gate twisting tooling. The height constraint condition is combined with the hexagonal structure parameters of the grounding gate, and the minimum rotation angle of the tooling end is calculated through the geometric matching algorithm to ensure that the geometric features of the twisting tooling and the grounding gate are accurately aligned. The height adaptive module and the alignment control module form a collaborative control chain through real-time data interaction to achieve the linkage adjustment of height positioning and angle alignment. After completing the height positioning, the height adaptive module sends a height adjustment signal to the vibration suppression module, triggering the vibration spectrum acquisition and damping parameter optimization process. The above steps are optimized through genetic algorithms and linked with multi-module data to solve the technical problems of low height adjustment efficiency and accumulated positioning deviations in the existing methods.

[0029] The vibration suppression module collects the vibration spectrum data of the end of the grounding switch according to the height adjustment signal, dynamically optimizes the damping parameters of the polyurethane vibration damping block through the genetic algorithm, and collects the end posture data of the tooling through the posture sensor; After the vibration suppression module receives the height adjustment signal sent by the height adaptive module, it starts the vibration data collection and parameter optimization process. Specifically, the vibration signal of the end of the grounding switch turning tool is collected in real time through the acceleration sensor, and the time domain vibration signal is converted into frequency domain energy distribution using Fourier transform, and the vibration energy characteristics of the 0-1kHz frequency band are extracted as the input parameters of the genetic algorithm. This frequency band covers the main vibration energy caused by mechanical transmission and load fluctuations in the opening and closing operations, quantifies the amplitude distribution at different frequencies, and provides a data basis for optimizing the damping parameters of the vibration reduction block.

[0030] Based on the extracted vibration energy characteristics, the vibration suppression module dynamically optimizes the damping parameters of the polyurethane vibration damping block through a genetic algorithm. The fitness function uses the compression deformation and vibration attenuation rate of the vibration damping block as evaluation indicators. The compression deformation reflects the elastic deformation capacity of the vibration damping material, and the vibration attenuation rate represents the energy dissipation efficiency. The two are weighted and fused to generate a fitness value, which is used to screen the optimal damping parameter combination. The chromosome crossover and mutation operations are performed on the initial population parameters to generate multiple sets of candidate solutions. The parameter solutions whose fitness values ​​meet the preset thresholds are retained, and the optimal solution for vibration damping effect is gradually approached.

[0031] The optimized damping parameters are fed back to the collaborative decision-making module through the data bus, triggering the dynamic correction of the opening and closing operation instruction set. The collaborative decision-making module combines the vibration spectrum data, path planning error and height deviation, recalculates the servo motor torque output curve and the slide module displacement instruction, and adjusts the motion parameters in real time to suppress vibration interference. At the same time, the attitude sensor collects real-time posture data of the end of the tooling, including position offset and rotation angle, which is used to evaluate the impact of vibration on positioning accuracy, and is fed back to the alignment control module for posture compensation.

[0032] The above process forms a closed-loop vibration suppression mechanism through vibration data collection, genetic algorithm optimization and multi-module collaborative control. The dynamic parameter adjustment and posture feedback mechanism of the vibration suppression module effectively reduce the interference of mechanical vibration on the end positioning of the tooling, and improve the stability and accuracy of the grounding switch opening and closing operation.

[0033] The collaborative decision-making module integrates the path error of the path planning module, the height deviation of the height adaptation module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, builds a target optimization model, generates an instruction set through the target optimization model, and distributes the instructions to the chassis, slide module and servo motor of the driving mobile robot to collaboratively complete the grounding switch opening and closing operations.

[0034] The collaborative decision-making module integrates the path error of the path planning module, the height deviation of the height adaptive module, the spectrum data of the vibration suppression module, and the angle deviation of the alignment control module to construct a multi-objective optimization model to achieve global instruction optimization. Specifically, the path error is calculated by the deviation between the actual motion trajectory of the mobile robot chassis and the planned path, reflecting the execution accuracy of the obstacle avoidance path; the height deviation is the difference between the actual displacement of the screw-driven slide module and the target height, characterizing the accuracy of vertical positioning; the spectrum data contains the 0-1kHz frequency band vibration energy distribution characteristics extracted by the vibration suppression module, quantifying the degree of interference of mechanical vibration on the end posture of the tooling; the angle deviation is collected by the posture sensor of the alignment control module, reflecting the alignment offset between the end of the tooling and the hexagonal structure of the grounding gate. The above parameters are mapped to a unified dimension through normalized weighted processing to eliminate the influence of magnitude differences on the optimization results, and the weighting coefficient is dynamically adjusted according to the criticality of each parameter to the opening and closing operation.

[0035] Based on the multi-objective optimization model, a non-dominated sorting genetic algorithm is used to perform multi-objective optimization on the parameter solution set. The algorithm takes positioning error minimization, height deviation convergence, vibration energy suppression and angle alignment accuracy as optimization goals, and selects the Pareto optimal solution set through non-dominated sorting and crowding calculation. In the iterative process, the individuals with the best fitness value are retained, and a new generation of candidate solutions are generated through crossover mutation operations, gradually approaching the global optimal operation instruction set. The instruction set includes the speed instruction of the high-torque servo motor, the displacement instruction of the slide module and the hydraulic control instruction of the lifting platform. The parameters of each instruction are dynamically matched to ensure the motion coordination of the execution unit.

[0036] The global optimal operation instruction set is distributed to the mobile robot chassis, the screw-driven slide module and the high-torque servo motor through the industrial bus. The mobile robot chassis adjusts the travel speed and steering angle according to the speed instruction, the slide module executes the displacement instruction to achieve precise vertical positioning, and the lifting platform dynamically adjusts the height according to the hydraulic control instruction. Each execution unit forms a closed-loop control with the collaborative decision-making module through real-time data feedback, and dynamically corrects the motion deviation in the opening and closing operation. For example, when the vibration spectrum data exceeds the preset threshold, the collaborative decision-making module recalculates the servo motor torque output curve, reduces the movement speed to reduce the vibration energy; if the angle deviation increases, the rotation angle sequence of the tooling end is adjusted to compensate for the posture deviation. The above technical solution solves the technical problems of poor system coordination and low operating efficiency caused by local optimization in the existing methods through multi-source data fusion, multi-objective optimization algorithm and distributed instruction coordination.

[0037] The grounding opening and closing device based on flexible tightening provided by the present invention realizes the automatic opening and closing operation of the grounding switch of the high-voltage switch cabinet through multi-module collaborative control. The functions and logical relationships of each module in the technical solution are described in detail below: The data acquisition module is responsible for acquiring environmental perception data and equipment status data in real time. Environmental perception data includes obstacle 3D point cloud data generated by LiDAR and visual coordinate data collected by visual sensors, which are used to identify the distribution of obstacles in the working environment and the positioning identification of high-voltage switch cabinets. Equipment status data includes hydraulic control parameters of the lifting platform, grounding gate height data, and real-time displacement data of the screw-driven slide module, providing input parameters for path planning, height adjustment, and vibration suppression of subsequent modules.

[0038] The path planning module generates the obstacle avoidance path of the mobile robot chassis through a genetic algorithm based on the three-dimensional point cloud and visual coordinate data of obstacles in the environmental perception data. Specifically, after matching the laser radar point cloud data with the visual feature identifier, a path planning fitness function is constructed to evaluate the feasibility of the path's steering angle, moving speed, and obstacle avoidance distance; a candidate path set is generated through the chromosome crossover mutation operation of the genetic algorithm, and a solution set that meets the preset positioning accuracy threshold is screened and output to the collaborative decision-making module as the path input parameter for multi-objective optimization.

[0039] The height adaptation module receives the target high-voltage switchgear coordinates generated by the path planning module, combines the hydraulic control parameters of the data acquisition module and the grounding gate height data, and optimizes the hydraulic control parameters of the lifting platform through the genetic algorithm. The optimization targets include the height error of the lifting platform, the displacement speed of the slide module, and the load current of the servo motor. The height adaptation fitness value is calculated by weighted summation, and the candidate parameters with the top 10% fitness ranking are screened and retained. The optimized target height value drives the screw drive slide module to move vertically to the target position, and confirms the positioning completion through the real-time feedback displacement data, triggering the vibration suppression module to start.

[0040] After receiving the height adjustment signal, the vibration suppression module collects the vibration spectrum data of the end of the grounding switch turning tool through the acceleration sensor, and extracts the vibration energy distribution characteristics of the 0-1kHz frequency band as the population initialization parameters of the genetic algorithm. The compression deformation and vibration attenuation rate of the polyurethane vibration damping block are used as fitness evaluation indicators to screen the candidate solutions of the damping parameters, and the optimized damping parameters are fed back to the collaborative decision-making module for dynamic correction of the opening and closing operation instruction set to reduce the impact of vibration on positioning accuracy.

[0041] The collaborative decision-making module integrates the path error of the path planning module, the height deviation of the height adaptive module, the spectrum data of the vibration suppression module, and the angle deviation of the alignment control module to build a multi-objective optimization model. After normalizing and weighting each parameter, the non-dominated sorting genetic algorithm is used to generate the global optimal operation instruction set, including the speed instruction of the high-torque servo motor, the displacement instruction of the slide module, and the hydraulic control instruction of the lifting platform. The optimized instruction set is distributed to the mobile robot chassis, the screw drive slide module, and the servo motor, driving each execution unit to collaboratively complete the opening and closing operations of the grounding switch, achieving high-precision positioning and stable operation in a complex power distribution environment.

[0042] Each module forms a complete operation chain through closed-loop transmission of data flow and control signals: environmental perception data drives path planning, target coordinates trigger height adjustment, positioning completion signal starts vibration suppression, and finally the collaborative decision-making module coordinates and generates global instructions. This technical solution solves the problems of low manual operation efficiency, insufficient equipment vibration suppression and poor positioning accuracy through multi-level optimization and modular collaborative control of genetic algorithms.

[0043] Specifically, in the grounding opening and closing device based on flexible tightening described in the present invention, the path planning module is also used for: Based on the three-dimensional point cloud data and visual coordinate data of the obstacle collected by the data acquisition module, the obstacle contour information is generated by the laser radar, and matched with the high-voltage switchgear positioning mark in the visual feature identification data, and the path planning fitness function is constructed to evaluate the feasibility of the obstacle avoidance path; Generate path nodes based on the obstacle avoidance path, perform chromosome crossover and mutation operations on the steering angles, moving speeds, and safe obstacle avoidance distances between the path nodes through a genetic algorithm, and generate a candidate path set; The candidate path solution set that meets the preset positioning accuracy threshold is output to the collaborative decision-making module as the path input parameter of the multi-objective optimization model in the collaborative decision-making module.

[0044] The path planning module generates and optimizes obstacle avoidance paths based on the three-dimensional point cloud data and visual coordinate data of obstacles provided by the data acquisition module. Specifically, the operating environment is scanned in three dimensions by a laser radar to generate point cloud data containing obstacle contour information, and the positioning identification data of the high-voltage switchgear is obtained by a visual sensor. The obstacle contour information in the laser radar point cloud is matched with the high-voltage switchgear positioning identification in the visual feature identification data to identify the spatial coordinates of the target high-voltage switchgear and the distribution of surrounding obstacles, thereby constructing a three-dimensional environmental map.

[0045] Based on the three-dimensional environment map, the path planning module generates the initial obstacle avoidance path of the mobile robot chassis and constructs a path planning fitness function. The fitness function uses path length, steering angle smoothness and safe distance from obstacles as evaluation indicators to quantify the feasibility of each candidate path. The path nodes of the initial obstacle avoidance path are encoded by a genetic algorithm, and the path nodes include the steering angle, moving speed and safe obstacle avoidance distance parameters of the mobile robot. Chromosome crossover and mutation operations are performed on the encoded path nodes to generate a candidate path set containing multiple path solutions.

[0046] In the candidate path set, the path solution set that meets the preset positioning accuracy threshold is screened. The positioning accuracy threshold is set based on the positioning mark size of the high-voltage switchgear and the motion accuracy of the mobile robot chassis, and is used to eliminate path solutions that deviate from the target coordinates or are not within a safe distance from obstacles. The screened candidate path solution set is output to the collaborative decision-making module as the path input parameter of the multi-objective optimization model, so that subsequent modules can perform global optimization on the motion trajectory of the mobile robot chassis. The above steps form a closed-loop control chain: environmental perception data drives path generation, genetic algorithms optimize path parameters, and the screened solution set provides input for collaborative decision-making, ultimately achieving accurate obstacle avoidance and target positioning of the mobile robot chassis.

[0047] Specifically, the grounding opening and closing device based on flexible tightening of the present invention, the highly adaptive module is also used for: Based on the hydraulic control parameters of the lifting platform and the grounding gate height data, a multi-dimensional optimization target including the height error of the lifting platform, the displacement speed of the sliding table module and the load current of the servo motor is constructed by a genetic algorithm to calculate the height adaptive fitness value; According to the preset highly adaptive fitness value threshold, the candidate solution set of hydraulic control parameters is screened, and the candidate parameters with the top 10% fitness values ​​are retained using an elite retention strategy; The optimized target height value is synchronized to the alignment control module through the genetic algorithm, and is used as a height constraint condition for the alignment control module to generate a rotation angle sequence of the grounding gate screwing tooling.

[0048] The height adaptation module performs hydraulic control parameter optimization and height positioning operations based on the lifting platform hydraulic control parameters and ground gate height data provided by the data acquisition module. Specifically, a multi-dimensional optimization target including the height error of the lifting platform, the displacement speed of the slide module and the load current of the servo motor is constructed through a genetic algorithm, where the height error is calculated by the difference between the real-time measured ground gate height data and the target height, and the displacement speed of the slide module and the load current of the servo motor respectively reflect the motion efficiency and load state of the lifting mechanism. The height adaptation fitness value is calculated after weighted fusion of the above parameters, which is used to quantify the degree of optimization of the hydraulic control parameters. The higher the fitness value, the better the height positioning accuracy and motion stability.

[0049] According to the preset height adaptive fitness value threshold, the candidate solution set of hydraulic control parameters is screened. The threshold is set based on the installation accuracy requirements of the earthing gate of the high-voltage switch cabinet, and is used to exclude parameter combinations that may cause height deviation to exceed the limit or unstable motion. The elite retention strategy is used to iteratively optimize the candidate solution set, retain the top 10% of the candidate parameters in fitness value, and generate a new generation of parameter sets through the crossover mutation operation of the genetic algorithm, gradually approaching the optimal solution. The optimized target height value is precisely positioned through the closed-loop control of the screw-driven slide module, and the displacement data of the slide module is fed back to the data acquisition module in real time to form a dynamic calibration of height adjustment.

[0050] The optimized target height value is synchronized to the alignment control module as a constraint condition for generating the rotation angle sequence of the grounding gate twisting tooling. The height constraint condition is combined with the hexagonal structure parameters of the grounding gate to calculate the minimum rotation angle of the tooling end, so as to achieve geometric feature matching between the twisting tooling and the grounding gate. The height adaptive module and the alignment control module realize parameter interaction through the data bus, forming a collaborative control chain of height positioning and angle alignment, and finally realizing high-precision automated operation of the grounding gate separation and closing operation. The above steps solve the technical problems of low height adjustment efficiency and accumulated positioning deviation in the existing methods through genetic algorithm optimization and multi-module data linkage.

[0051] Specifically, the grounding opening and closing device based on flexible tightening of the present invention, the vibration suppression module is also used for: Based on the posture data of the tooling end collected by the posture sensor and the damping parameters of the data acquisition module, the vibration spectrum data of the grounding switch twisting tooling end is collected by the acceleration sensor, and the vibration energy distribution characteristics in the 0-1kHz frequency band are extracted as the population initialization parameters of the genetic algorithm; By using the genetic algorithm, the compression deformation and vibration attenuation rate of the polyurethane vibration damping block are used as vibration suppression fitness evaluation indicators to screen candidate solutions for damping parameters; The damping parameter optimization data that meets the vibration suppression fitness evaluation index is fed back to the collaborative decision-making module, triggering the collaborative decision-making module to dynamically correct the opening and closing operation instruction set based on the multi-objective optimization model.

[0052] The vibration suppression module performs vibration spectrum analysis and damping parameter optimization based on the end-of-tool posture data collected by the posture sensor and the damping parameters of the data acquisition module. Specifically, the vibration spectrum data of the end of the grounding switch twisting tool is collected in real time by the acceleration sensor, and the vibration energy distribution characteristics in the 0-1kHz frequency band are extracted as the population initialization parameters of the genetic algorithm. This frequency band covers the main vibration energy caused by mechanical transmission and load changes in the grounding switch separation and closing operation. The time domain vibration signal is converted into frequency domain energy distribution through Fourier transform, and the vibration amplitude at different frequencies is quantified to provide an initial optimization space for the genetic algorithm.

[0053] The dynamic relationship between the compression deformation and vibration attenuation rate of the polyurethane vibration damping block is modeled through a genetic algorithm to construct a vibration suppression fitness evaluation index. The compression deformation reflects the elastic deformation capacity of the vibration damping block, and the vibration attenuation rate represents the vibration energy dissipation efficiency. The two are weighted and fused to generate a fitness value, which is used to evaluate the vibration reduction effect of different damping parameter combinations. The initial population parameters are subjected to chromosome crossover and mutation operations to generate a candidate solution set containing multiple groups of damping parameter solutions, and the candidate solutions whose fitness values ​​meet the preset threshold are screened to retain the parameter combination with the greatest optimization potential.

[0054] The optimized damping parameter data is fed back to the collaborative decision-making module through the data bus, triggering dynamic instruction correction based on the multi-objective optimization model. The collaborative decision-making module integrates the spectrum data of the vibration suppression module, the positioning error of the path planning module, and the height deviation of the height adaptive module, recalculates the torque output curve of the servo motor and the displacement instruction of the slide module, and adjusts the motion parameters during the opening and closing operation in real time. Through the closed-loop feedback mechanism, the interference of vibration on the end posture of the tooling is suppressed, and the positioning accuracy and equipment stability of the grounding switch tightening operation are improved. The above steps solve the technical problems of vibration suppression lag and poor parameter adaptability in the existing methods through spectrum feature extraction, genetic algorithm optimization and multi-module collaborative control.

[0055] Specifically, in the grounding opening and closing device based on flexible tightening described in the present invention, the collaborative decision-making module is also used for: Based on the positioning error of the path planning module, the height deviation of the height adaptive module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, a multi-objective optimization model is constructed to perform normalized weighted processing on the positioning error, height deviation, spectrum data and angle deviation; Generate a global optimal operation instruction set including a high-torque servo motor speed instruction, a slide module displacement instruction and a lifting platform hydraulic control instruction based on the multi-objective optimization model through the non-dominated sorting genetic algorithm of the collaborative decision-making module; The global optimal operation instruction set is distributed to the mobile robot chassis, the screw-driven slide module and the high-torque servo motor, so as to drive the mobile robot chassis, the screw-driven slide module and the high-torque servo motor to collaboratively complete the grounding switch opening and closing operations.

[0056] The collaborative decision-making module integrates the positioning error of the path planning module, the height deviation of the height adaptive module, the spectrum data of the vibration suppression module, and the angle deviation of the alignment control module to construct a multi-objective optimization model to achieve global instruction optimization. Specifically, the positioning error is calculated by the deviation between the actual path of the mobile robot chassis and the planned path. The height deviation is the difference between the actual displacement of the screw-driven slide module and the target height. The spectrum data contains the 0-1kHz frequency band vibration energy distribution characteristics extracted by the vibration suppression module. The angle deviation reflects the alignment offset between the end posture of the tooling and the hexagonal structure of the grounding gate. Each parameter is mapped to a unified dimension through normalized weighted processing to eliminate the influence of magnitude differences on the optimization results. The weighting coefficient is dynamically adjusted according to the weight of each parameter on the opening and closing operation.

[0057] Based on the multi-objective optimization model, a non-dominated sorting genetic algorithm is used to perform multi-objective optimization on the parameter solution set. The algorithm takes positioning error minimization, height deviation convergence, vibration energy suppression and angle alignment accuracy as optimization goals, and selects the Pareto optimal solution set through non-dominated sorting and crowding calculation. In the iterative process, the individuals with the best fitness value are retained, and a new generation of candidate solutions are generated through crossover mutation operations, gradually approaching the global optimal operation instruction set. The instruction set includes the speed instruction of the high-torque servo motor, the displacement instruction of the slide module and the hydraulic control instruction of the lifting platform, ensuring the coordinated matching of the motion parameters of each execution unit.

[0058] The global optimal operation instruction set is distributed to the mobile robot chassis, screw-driven slide module and high-torque servo motor through the industrial bus. The mobile robot chassis adjusts the travel speed and steering angle according to the speed instruction, the slide module executes the displacement instruction to achieve precise vertical positioning, and the lifting platform dynamically adjusts the height according to the hydraulic control instruction. Each execution unit forms a closed-loop control through real-time data feedback and collaborative decision-making modules, dynamically corrects the motion deviation in the opening and closing operations, and finally completes the high-precision tightening and opening and closing actions of the grounding switch. The above technical solution solves the technical problems of poor system coordination and low operating efficiency caused by local optimization in the existing methods through multi-source data fusion, multi-objective optimization algorithm and distributed instruction coordination.

[0059] Second, see Figure 1 The grounding opening and closing method based on flexible tightening provided by the present invention is applied to the grounding opening and closing device based on flexible tightening, and comprises: Step S1, collecting environmental perception data, equipment status data and damping parameters of polyurethane vibration damping blocks, the environmental perception data includes obstacle three-dimensional point cloud data and visual coordinate data, and the equipment status data includes hydraulic control parameters of the lifting platform, grounding gate height data and screw drive slide module displacement data; Step S2, generating an obstacle avoidance path for the mobile robot chassis based on the obstacle three-dimensional point cloud data and the visual coordinate data, encoding the obstacle avoidance path for the mobile robot chassis through a genetic algorithm, and generating the coordinates of the target high-voltage switch cabinet; Step S3, receiving the coordinates of the target high-voltage switch cabinet, combining the hydraulic control parameters of the lifting platform of the data acquisition module and the height data of the grounding switch, optimizing the hydraulic control parameters of the lifting platform through the genetic algorithm, driving the screw to drive the slide module to move vertically to the target height, the slide module is linearly displaced by the screw drive, and the displacement state of the slide module is fed back in real time by the displacement data of the screw driving the slide module, and sending a height adjustment signal to the vibration suppression module after positioning is completed; Step S4, collecting vibration spectrum data of the end of the grounding switch turning tooling according to the height adjustment signal, dynamically optimizing the damping parameters of the polyurethane vibration damping block through a genetic algorithm, and collecting the posture data of the end of the tooling through a posture sensor; Step S5, integrating the path error of the path planning module, the height deviation of the height adaptation module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, constructing a target optimization model, generating an instruction set through the target optimization model, and distributing the instructions to the chassis, slide module and servo motor of the driving mobile robot to collaboratively complete the grounding switch opening and closing operation.

[0060] Specifically, the grounding opening and closing method based on flexible tightening according to the present invention, the step S2 comprises: Based on the three-dimensional point cloud data and visual coordinate data of the obstacle collected by the data acquisition module, the obstacle contour information is generated by the laser radar, and matched with the high-voltage switchgear positioning mark in the visual feature identification data, and the path planning fitness function is constructed to evaluate the feasibility of the obstacle avoidance path; Generate path nodes based on the obstacle avoidance path, perform chromosome crossover and mutation operations on the steering angles, moving speeds, and safe obstacle avoidance distances between the path nodes through a genetic algorithm, and generate a candidate path set; The candidate path solution set that meets the preset positioning accuracy threshold is output to the collaborative decision-making module as the path input parameter of the multi-objective optimization model in the collaborative decision-making module.

[0061] Specifically, in the grounding opening and closing method based on flexible tightening according to the present invention, step S3 comprises: Based on the hydraulic control parameters of the lifting platform and the grounding gate height data, a multi-dimensional optimization target including the height error of the lifting platform, the displacement speed of the sliding table module and the load current of the servo motor is constructed by a genetic algorithm to calculate the height adaptive fitness value; According to the preset highly adaptive fitness value threshold, the candidate solution set of hydraulic control parameters is screened, and the candidate parameters with the top 10% fitness values ​​are retained using an elite retention strategy; The optimized target height value is synchronized to the alignment control module through the genetic algorithm, and is used as a height constraint condition for the alignment control module to generate a rotation angle sequence of the grounding gate screwing tooling.

[0062] Specifically, the grounding opening and closing method based on flexible tightening according to the present invention, step S4 comprises: Based on the posture data of the tooling end collected by the posture sensor and the damping parameters of the data acquisition module, the vibration spectrum data of the grounding switch twisting tooling end is collected by the acceleration sensor, and the vibration energy distribution characteristics in the 0-1kHz frequency band are extracted as the population initialization parameters of the genetic algorithm; By using the genetic algorithm, the compression deformation and vibration attenuation rate of the polyurethane vibration damping block are used as vibration suppression fitness evaluation indicators to screen candidate solutions for damping parameters; The damping parameter optimization data that meets the vibration suppression fitness evaluation index is fed back to the collaborative decision-making module, triggering the collaborative decision-making module to dynamically correct the opening and closing operation instruction set based on the multi-objective optimization model.

[0063] Specifically, the grounding opening and closing method based on flexible tightening according to the present invention, the step S5 comprises: Based on the positioning error of the path planning module, the height deviation of the height adaptive module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, a multi-objective optimization model is constructed to perform normalized weighted processing on the positioning error, height deviation, spectrum data and angle deviation; Generate a global optimal operation instruction set including a high-torque servo motor speed instruction, a slide module displacement instruction and a lifting platform hydraulic control instruction based on the multi-objective optimization model through the non-dominated sorting genetic algorithm of the collaborative decision-making module; The global optimal operation instruction set is distributed to the mobile robot chassis, the screw-driven slide module and the high-torque servo motor, so as to drive the mobile robot chassis, the screw-driven slide module and the high-torque servo motor to collaboratively complete the grounding switch opening and closing operations.

[0064] The embodiments of the present invention combine the actual application scenarios of the earthing switch opening and closing operations of the high-voltage switch cabinet, and solve the problems of low efficiency, insufficient vibration suppression and poor positioning accuracy existing in the background technology through technical solutions of different modules. The specific embodiments are as follows: Embodiment 1 of the present invention: In the complex power distribution environment of the substation, the mobile robot needs to cross multiple obstacles to approach the target high-voltage switchgear. The data acquisition module generates three-dimensional point cloud data of obstacles through the laser radar at a scanning frequency of 10Hz, and the visual sensor captures the positioning mark of the high-voltage switchgear with a resolution of 2 million pixels. The path planning module fuses the point cloud data with the visual coordinates to construct a three-dimensional environment map to identify the target coordinates and obstacle distribution. The initial obstacle avoidance path is generated by the genetic algorithm. The path node encoding parameters include the steering angle of 0°~180°, the moving speed of 0.1~0.5m / s and the safe obstacle avoidance distance ≥0.3m. The fitness function uses the path length, steering smoothness and safety distance as evaluation indicators to select the candidate path solution set that meets the positioning accuracy of ±5mm. The mobile robot chassis autonomously avoids obstacles according to the optimized path instructions and completes the approach operation of the target high-voltage switchgear within 30 seconds, which is more efficient than the existing manual operation.

[0065] Embodiment 2 of the present invention: In order to solve the positioning deviation problem caused by the height difference of the grounding gate, after receiving the target coordinates, the height adaptive module combines the hydraulic control parameters 5~20MPa and the grounding gate height data (measurement accuracy ±1mm) to optimize the lifting platform motion parameters through genetic algorithm. The multi-dimensional optimization targets include height error (weight 0.6), displacement speed of the slide module (weight 0.3) and servo motor load current (weight 0.1). The elite retention strategy is used to select the top 10% of the hydraulic parameter candidate solutions with the best fitness value. The optimized parameters drive the screw to drive the slide module to move vertically to the target height at a speed of 0.2m / s, and the real-time feedback of displacement data forms a closed-loop control with a positioning accuracy of ±2mm. After the height positioning is completed, the vibration suppression module collects the vibration spectrum of the tooling end through the acceleration sensor, extracts the energy characteristics of the 0-1kHz frequency band (main peak frequency 500Hz, amplitude 0.05g), and uses the compression deformation threshold ≤3mm and the vibration attenuation rate ≥20dB / s as fitness indicators to optimize the damping parameters of the polyurethane vibration damping block to reduce the vibration energy.

[0066] Embodiment 3 of the present invention: In the precise docking scenario of the hexagonal structure of the grounding gate, the collaborative decision-making module integrates the path error ±5mm, the height deviation ±2mm, the energy proportion of the vibration spectrum data 0-1kHz frequency band ≤15% and the angle deviation ±1°, and constructs a multi-objective optimization model through normalized weighted processing. The non-dominated sorting genetic algorithm is used to generate the global optimal instruction set, including the servo motor speed of 100~500rpm, the displacement instruction accuracy of the slide module ±0.5mm and the pressure fluctuation of the hydraulic control instruction ≤2MPa. The instruction set is distributed to each execution unit through the CAN bus. The mobile robot chassis adjusts the travel trajectory according to the speed instruction, the slide module performs vertical positioning, and the vibration suppression module adjusts the damping parameters in real time. When the angle deviation exceeds ±1°, the alignment control module triggers the tooling rotation angle compensation step angle of 5°, and the posture correction is completed within 5 seconds. This embodiment improves the one-time success rate of the grounding gate separation and closing operation in a complex vibration environment.

[0067] The specific implementation method of the present invention combines the actual application scenario of the earthing switch opening and closing operation of the high-voltage switch cabinet, and realizes automated operation through multi-module collaborative control and genetic algorithm optimization. The data acquisition module uses a laser radar to scan the working environment to generate three-dimensional point cloud data of obstacles, and at the same time uses a visual sensor to identify the positioning identification features of the high-voltage switch cabinet. The two are fused through a spatiotemporal calibration algorithm to construct a three-dimensional environmental map to eliminate sensor calibration errors. The path planning module generates the initial obstacle avoidance path of the mobile robot chassis based on the fused environmental data, encodes the steering angle, moving speed and safe obstacle avoidance distance of the path node through a genetic algorithm, and constructs a path planning fitness function to screen the candidate path solution set that meets the positioning accuracy threshold, and outputs it to the collaborative decision-making module as the input parameter of the multi-objective optimization, driving the mobile robot chassis to autonomously avoid obstacles and accurately approach the target high-voltage switch cabinet.

[0068] After receiving the target coordinates output by the path planning module, the height adaptive module combines the hydraulic control parameters of the lifting platform and the height data of the grounding gate, and constructs a multi-dimensional optimization target including height error, displacement speed and load current through a genetic algorithm. The elite retention strategy is used to screen the candidate solutions of hydraulic parameters with the top 10% fitness values. The optimized parameters drive the screw drive slide module to move vertically to the target height, and the displacement data is fed back in real time to form a closed-loop control, and the height constraints are simultaneously transmitted to the alignment control module. After the height positioning is completed, the vibration suppression module collects the vibration spectrum data at the end of the tooling through the acceleration sensor, extracts the energy distribution characteristics of the 0-1kHz frequency band as the input of the genetic algorithm, and optimizes the damping parameters of the polyurethane vibration damping block with the compression deformation and vibration attenuation rate as fitness indicators, and feeds the optimization results back to the collaborative decision-making module to trigger instruction correction.

[0069] The collaborative decision-making module integrates path error, height deviation, vibration spectrum and angle deviation data, constructs a multi-objective optimization model through normalized weighted processing, and uses a non-dominated sorting genetic algorithm to generate a global optimal instruction set. The instruction set is distributed to the mobile robot chassis, slide module and servo motor through the industrial bus. The mobile robot chassis adjusts the travel trajectory according to the speed command, the slide module executes the displacement command to achieve vertical positioning, and the lifting platform dynamically adjusts the height according to the hydraulic command. At the same time, the optimization parameters of the vibration suppression module suppress mechanical vibration interference in real time. Each execution unit dynamically corrects the motion deviation through a closed-loop feedback mechanism. For example, when the angle deviation exceeds the threshold, the tooling rotation angle is adjusted to compensate for the posture deviation. The above implementation method realizes efficient positioning, vibration suppression and safety control of grounding switch opening and closing operations in a complex power distribution environment through modular collaboration and genetic algorithm optimization.

[0070] The present invention solves the technical problems of low manual efficiency, insufficient vibration suppression and poor positioning accuracy in the opening and closing operations of the earthing switch of the high-voltage switch cabinet in the power distribution system through multi-module collaborative control and genetic algorithm optimization. First, the data acquisition module generates obstacle three-dimensional point cloud data and high-voltage switch cabinet positioning coordinates through the fusion of laser radar and visual sensor. The path planning module generates obstacle avoidance paths and encodes target coordinates based on genetic algorithms, drives the mobile robot chassis to autonomously avoid obstacles and accurately locate, eliminates the inefficiency and positioning deviation of manual operations, and improves the operating efficiency in complex power distribution environments.

[0071] Secondly, the vibration suppression module collects vibration spectrum data at the end of the tooling based on the acceleration sensor, extracts the vibration energy characteristics of the 0-1kHz frequency band, dynamically optimizes the damping parameters of the polyurethane vibration damping block through the genetic algorithm, and uses the compression deformation and vibration attenuation rate as fitness evaluation indicators to select the optimal solution to suppress the interference of mechanical vibration on the tooling posture. At the same time, the height adaptive module optimizes the hydraulic parameters of the lifting platform through the genetic algorithm, combined with the closed-loop feedback control of the screw-driven slide module, to achieve dynamic calibration and stable positioning of the grounding gate height, and reduce the impact of vibration transmission on the vertical positioning accuracy.

[0072] Finally, the collaborative decision-making module integrates the path error, height deviation, vibration spectrum and angle deviation data, builds a multi-objective optimization model, and uses the non-dominated sorting genetic algorithm to generate the global optimal operation instruction set, which is distributed to the mobile robot chassis, slide module and servo motor. The collaborative control and real-time feedback correction of the execution unit are realized through the industrial bus, and the motion parameters are dynamically adjusted to compensate for vibration and posture deviation, so as to achieve high precision, low vibration and high safety of grounding switch opening and closing operations in a complex power distribution environment.

Claims

1. A grounding opening and closing device based on flexible tightening, characterized in that: include: Data acquisition module, used to collect environmental perception data, equipment status data and damping parameters of polyurethane vibration damping blocks. Environmental perception data includes obstacle 3D point cloud data and visual coordinate data. Equipment status data includes hydraulic control parameters of the lifting platform, grounding gate height data and screw drive slide module displacement data. The path planning module generates the obstacle avoidance path of the mobile robot chassis based on the obstacle 3D point cloud data and visual coordinate data, encodes the obstacle avoidance path of the mobile robot chassis through the genetic algorithm, and generates the coordinates of the target high-voltage switch cabinet; The height adaptive module receives the coordinates of the target high-voltage switch cabinet, combines the hydraulic control parameters of the lifting platform and the height data of the grounding gate of the data acquisition module, optimizes the hydraulic control parameters of the lifting platform through the genetic algorithm, drives the screw to drive the slide module to move vertically to the target height, and the slide module is linearly displaced by the screw drive. The displacement state of the slide module is fed back in real time by the displacement data of the screw driving the slide module. After positioning is completed, a height adjustment signal is sent to the vibration suppression module; The vibration suppression module collects the vibration spectrum data of the end of the grounding switch according to the height adjustment signal, dynamically optimizes the damping parameters of the polyurethane vibration damping block through the genetic algorithm, and collects the end posture data of the tooling through the posture sensor; The collaborative decision-making module integrates the path error of the path planning module, the height deviation of the height adaptation module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, builds a target optimization model, generates an instruction set through the target optimization model, and distributes the instructions to the chassis, slide module and servo motor of the driving mobile robot to collaboratively complete the grounding switch opening and closing operations.

2. The grounding opening and closing device based on flexible tightening according to claim 1 is characterized in that: The path planning module is also used for: Based on the three-dimensional point cloud data and visual coordinate data of the obstacle collected by the data acquisition module, the obstacle contour information is generated by the laser radar, and matched with the high-voltage switchgear positioning mark in the visual feature identification data, and the path planning fitness function is constructed to evaluate the feasibility of the obstacle avoidance path; Generate path nodes based on the obstacle avoidance path, perform chromosome crossover and mutation operations on the steering angles, moving speeds, and safe obstacle avoidance distances between the path nodes through a genetic algorithm, and generate a candidate path set; The candidate path solution set that meets the preset positioning accuracy threshold is output to the collaborative decision-making module as the path input parameter of the multi-objective optimization model in the collaborative decision-making module.

3. The grounding opening and closing device based on flexible tightening according to claim 2 is characterized in that: The highly adaptive module is further used for: Based on the hydraulic control parameters of the lifting platform and the grounding gate height data, a multi-dimensional optimization target including the height error of the lifting platform, the displacement speed of the sliding table module and the load current of the servo motor is constructed by a genetic algorithm to calculate the height adaptive fitness value; According to the preset highly adaptive fitness value threshold, the candidate solution set of hydraulic control parameters is screened, and the candidate parameters with the top 10% fitness values ​​are retained using an elite retention strategy; The optimized target height value is synchronized to the alignment control module through the genetic algorithm, and is used as a height constraint condition for the alignment control module to generate a rotation angle sequence of the grounding gate screwing tooling.

4. The grounding opening and closing device based on flexible tightening according to claim 3 is characterized in that: The vibration suppression module is further used for: Based on the posture data of the tooling end collected by the posture sensor and the damping parameters of the data acquisition module, the vibration spectrum data of the grounding switch twisting tooling end is collected by the acceleration sensor, and the vibration energy distribution characteristics in the 0-1kHz frequency band are extracted as the population initialization parameters of the genetic algorithm; By using the genetic algorithm, the compression deformation and vibration attenuation rate of the polyurethane vibration damping block are used as vibration suppression fitness evaluation indicators to screen candidate solutions for damping parameters; The damping parameter optimization data that meets the vibration suppression fitness evaluation index is fed back to the collaborative decision-making module, triggering the collaborative decision-making module to dynamically correct the opening and closing operation instruction set based on the multi-objective optimization model.

5. The grounding opening and closing device based on flexible tightening according to claim 4 is characterized in that: The collaborative decision-making module is also used to: Based on the positioning error of the path planning module, the height deviation of the height adaptive module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, a multi-objective optimization model is constructed to perform normalized weighted processing on the positioning error, height deviation, spectrum data and angle deviation; Generate a global optimal operation instruction set including a high-torque servo motor speed instruction, a slide module displacement instruction and a lifting platform hydraulic control instruction based on the multi-objective optimization model through the non-dominated sorting genetic algorithm of the collaborative decision-making module; The global optimal operation instruction set is distributed to the mobile robot chassis, the screw-driven slide module and the high-torque servo motor, so as to drive the mobile robot chassis, the screw-driven slide module and the high-torque servo motor to collaboratively complete the grounding switch opening and closing operations.

6. A grounding opening and closing method based on flexible tightening, applied to the grounding opening and closing device based on flexible tightening as claimed in any one of claims 1 to 5, characterized in that: include: Step S1, collecting environmental perception data, equipment status data and damping parameters of polyurethane vibration damping blocks, the environmental perception data includes obstacle three-dimensional point cloud data and visual coordinate data, and the equipment status data includes hydraulic control parameters of the lifting platform, grounding gate height data and screw drive slide module displacement data; Step S2, generating an obstacle avoidance path for the mobile robot chassis based on the obstacle three-dimensional point cloud data and the visual coordinate data, encoding the obstacle avoidance path for the mobile robot chassis through a genetic algorithm, and generating the coordinates of the target high-voltage switch cabinet; Step S3, receiving the coordinates of the target high-voltage switch cabinet, combining the hydraulic control parameters of the lifting platform of the data acquisition module and the height data of the grounding switch, optimizing the hydraulic control parameters of the lifting platform through the genetic algorithm, driving the screw to drive the slide module to move vertically to the target height, the slide module is linearly displaced by the screw drive, and the displacement state of the slide module is fed back in real time by the displacement data of the screw driving the slide module, and sending a height adjustment signal to the vibration suppression module after positioning is completed; Step S4, collecting vibration spectrum data of the end of the grounding switch turning tooling according to the height adjustment signal, dynamically optimizing the damping parameters of the polyurethane vibration damping block through a genetic algorithm, and collecting the posture data of the end of the tooling through a posture sensor; Step S5, integrating the path error of the path planning module, the height deviation of the height adaptation module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, constructing a target optimization model, generating an instruction set through the target optimization model, and distributing the instructions to the chassis, slide module and servo motor of the driving mobile robot to collaboratively complete the grounding switch opening and closing operation.

7. The grounding opening and closing method based on flexible tightening according to claim 6 is characterized in that: The step S2 comprises: Based on the three-dimensional point cloud data and visual coordinate data of the obstacle collected by the data acquisition module, the obstacle contour information is generated by the laser radar, and matched with the high-voltage switchgear positioning mark in the visual feature identification data, and the path planning fitness function is constructed to evaluate the feasibility of the obstacle avoidance path; Generate path nodes based on the obstacle avoidance path, perform chromosome crossover and mutation operations on the steering angles, moving speeds, and safe obstacle avoidance distances between the path nodes through a genetic algorithm, and generate a candidate path set; The candidate path solution set that meets the preset positioning accuracy threshold is output to the collaborative decision-making module as the path input parameter of the multi-objective optimization model in the collaborative decision-making module.

8. The grounding opening and closing method based on flexible tightening according to claim 7 is characterized in that: The step S3 comprises: Based on the hydraulic control parameters of the lifting platform and the grounding gate height data, a multi-dimensional optimization target including the height error of the lifting platform, the displacement speed of the sliding table module and the load current of the servo motor is constructed by a genetic algorithm to calculate the height adaptive fitness value; According to the preset highly adaptive fitness value threshold, the candidate solution set of hydraulic control parameters is screened, and the candidate parameters with the top 10% fitness values ​​are retained using an elite retention strategy; The optimized target height value is synchronized to the alignment control module through the genetic algorithm, and is used as a height constraint condition for the alignment control module to generate a rotation angle sequence of the grounding gate screwing tooling.

9. The grounding opening and closing method based on flexible tightening according to claim 8 is characterized in that: The step S4 comprises: Based on the posture data of the tooling end collected by the posture sensor and the damping parameters of the data acquisition module, the vibration spectrum data of the grounding switch twisting tooling end is collected by the acceleration sensor, and the vibration energy distribution characteristics in the 0-1kHz frequency band are extracted as the population initialization parameters of the genetic algorithm; By using the genetic algorithm, the compression deformation and vibration attenuation rate of the polyurethane vibration damping block are used as vibration suppression fitness evaluation indicators to screen candidate solutions for damping parameters; The damping parameter optimization data that meets the vibration suppression fitness evaluation index is fed back to the collaborative decision-making module, triggering the collaborative decision-making module to dynamically correct the opening and closing operation instruction set based on the multi-objective optimization model.

10. The grounding opening and closing method based on flexible tightening according to claim 9, characterized in that: The step S5 comprises: Based on the positioning error of the path planning module, the height deviation of the height adaptive module, the spectrum data of the vibration suppression module and the angle deviation of the alignment control module, a multi-objective optimization model is constructed to perform normalized weighted processing on the positioning error, height deviation, spectrum data and angle deviation; Generate a global optimal operation instruction set including a high-torque servo motor speed instruction, a slide module displacement instruction and a lifting platform hydraulic control instruction based on the multi-objective optimization model through the non-dominated sorting genetic algorithm of the collaborative decision-making module; The global optimal operation instruction set is distributed to the mobile robot chassis, the screw-driven slide module and the high-torque servo motor, so as to drive the mobile robot chassis, the screw-driven slide module and the high-torque servo motor to collaboratively complete the grounding switch opening and closing operations.

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