A live working simulation and rehearsal system based on digital twinning

Abstract

This invention proposes a live-line work simulation and pre-drill system based on digital twins. A 3D data acquisition module collects 3D point cloud data and real-scene image data of the live-line work site and its surrounding environment. A digital twin model construction module outputs a 1:1 live-line work digital twin scene model based on the dataset output by the 3D data acquisition module. A work simulation and pre-drill module binds physical rigid bodies to each model component and assigns realistic physical parameters. Combined with a pre-set live-line work rule library, it performs multi-scheme simulation and deduction, and outputs the optimal work scheme. A risk warning module compares collision detection data and distance detection data output by the work simulation and pre-drill module with the live-line work rule library, triggering a warning when a potential hazard is detected. A collaborative control unit enables data interaction, command transmission, and collaborative work between different modules, effectively improving the reliability of live-line work simulation and pre-drill.

Description

Technical Field

[0001] This invention relates to the field of live-line working simulation technology, and in particular to a live-line working simulation and pre-simulation system based on digital twins. Background Technology

[0002] Currently, the implementation of live-line work on 10kV and above power distribution lines generally suffers from technical deficiencies such as insufficient operational safety, poor training effectiveness, and crude plan formulation, as detailed below: 1. Lack of precise support for work plan formulation: Currently, before live-line work, the work plan is determined only through on-site manual survey and two-dimensional drawing analysis. It is impossible to conduct visual simulation and pre-drill of the entire work process, making it difficult to predict potential safety risks such as electric shock, falls from heights, insufficient safety distance, and limited operating space during the work process. This can easily lead to unreasonable work plans and cause safety accidents.

[0003] 2. The operation simulation mode has obvious shortcomings: The simulation of live-line workers is not only costly and has great safety risks, but also the scenarios are mostly fixed models, which deviate greatly from the actual operation scenarios (such as different tower models, line layouts, and surrounding environment). It cannot simulate the operation process under complex working conditions, resulting in poor simulation effect.

[0004] 3. Lack of dynamic simulation capability between virtual and real: In the existing technology, the digital twin model is not deeply integrated with the physical engine, which makes it impossible to realize the virtual-real mapping and dynamic simulation of the operation scenario and operation action, to detect safety hazards in the operation process in real time, and to optimize the operation plan based on the simulation results, making it difficult to meet the needs of refined and safe live-line operation.

[0005] To address the shortcomings of the prior art, this invention provides a digital twin system and implementation method that can recreate the scene 1:1, support full-process simulation and pre-play, and automatically identify risks, thus filling the gap in the prior art and improving the safety and efficiency of live-line work. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention innovatively proposes a live-line work simulation and pre-drill system based on digital twins, which effectively solves the problem of low reliability in live-line work simulation and pre-drill caused by the prior art, and effectively improves the reliability of live-line work simulation and pre-drill.

[0007] This invention provides a live-line working simulation and pre-performance system based on digital twins, comprising: a 3D data acquisition module, a digital twin model construction module, a work simulation and pre-performance module, a risk warning module, and a collaborative control unit; the 3D data acquisition module is used to acquire 3D point cloud data and real-scene image data of poles, lines, switches, and the surrounding environment at the live-line working site, and outputs a structured dataset with spatial coordinates, geometric dimensions, and electrical attributes; the digital twin model construction module is used to output a 1:1 live-line working digital twin scene model based on the dataset output by the 3D data acquisition module; the work simulation and pre-performance module is used to... After the digital twin model is imported, physical rigid bodies are bound to each model component and real physical parameters are assigned. Combined with the preset live-line working rule library, real-time dynamic calculation, collision detection, and distance measurement of the working actions are realized. Multiple scheme simulations are performed, and the optimal working scheme is output. The risk warning module compares the collision detection data and distance detection data output by the working simulation pre-simulation module with the live-line working rule library and triggers a warning when a hidden danger is found. The collaborative control unit is used to realize the data interaction, command transmission, and collaborative work of the three-dimensional data acquisition module, the digital twin model construction module, the working simulation pre-simulation module, and the risk warning module.

[0008] Optionally, the live-line working rule base includes national live-line working procedures, industry standard operating rules, model simulation interaction rules, simulation pre-running process rules, and multi-scheme deduction and adaptation rules.

[0009] Furthermore, the model simulation interaction rules include rigid body attribute matching rules, model collision determination rules, and simulation step size matching rules; wherein, The rigid body property matching rules are as follows: static rigid bodies are only allowed to undergo position calibration before simulation, and modification of rigid body properties and spatial coordinates is prohibited during simulation; the elastic coefficient and swing amplitude of flexible rigid bodies are matched with the model and tension of the actual line; when the conductor deformation exceeds the first preset multiple of the maximum deformation under actual working conditions during simulation, a model anomaly warning is triggered; the motion acceleration of dynamic rigid bodies does not exceed the actual operation action acceleration threshold; among them, static rigid bodies include towers, crossarms, insulators, hardware, and switches; flexible rigid bodies include conductors; and dynamic rigid bodies include insulated bucket trucks, tools, and workers. The model collision judgment rules include: when models with different phase charged attribute labels collide in contact, or when models with grounded attribute labels collide in contact with charged attribute labels, it is judged as a risk of short circuit / electric shock; when a non-contact distance is less than the safety threshold and continues for more than a first preset time, it is judged as a risk of insufficient safety distance; and when non-essential collisions between insulated arms, work buckets, tools and poles, or crossarms are judged as a risk of limited operating space. The simulation step size matching rule includes matching the simulation calculation step size of the operation action with the detection frequency; when performing multi-step continuous operation, the simulation interval between adjacent actions is not less than the second preset time, so as to simulate the operation connection time in actual operation.

[0010] Optionally, the simulation pre-run process rules include simulation start-up pre-rules, job step editing rules, and simulation data recording rules; wherein, The pre-simulation start rules include that after the digital twin model is imported into the simulation platform, model attribute verification, rigid body binding correctness detection, and rule base threshold matching verification must be completed. The simulation can only be started after all verifications are passed. If they fail, the problem points will be automatically prompted and the simulation will be prohibited. The rules for editing work steps include that the work steps in the simulation should be edited hierarchically according to the actual work process, and no sub-steps at each level should be missing; the number of work actions in a single step should not exceed the first preset number. The simulation data recording rules include recording the model space coordinates, motion trajectory data, distance detection data, and collision judgment results for each frame during the simulation process. When a risk warning is triggered, the time, location, and cause of the warning frame are automatically marked, and the complete data of the preset number of frames before and after the warning is saved.

[0011] Optionally, the multi-scheme simulation and adaptation rules include simulation mode switching rules and scheme validity determination rules; wherein, The simulation mode switching rules include automatically pausing the simulation and supporting switching to the reverse verification mode when a level 1 risk is triggered during the forward simulation; when comparing multiple schemes, the simulation environment of different operation schemes must be kept consistent to ensure the objectivity of the comparison results; The rules for determining the effectiveness of a solution include: after the simulation is completed, a solution that does not trigger any risk warnings is considered a valid solution; a solution that only triggers a level 2 risk and can be corrected is considered a solution to be optimized; and a solution that triggers a level 1 risk is directly considered an invalid solution, wherein the risk level of level 1 risk is greater than that of level 2 risk.

[0012] Optionally, the multi-scheme simulation includes forward simulation, reverse simulation, and multi-scheme comparison. The forward simulation follows a preset live-line work procedure, simulating the entire process from work preparation to work completion. The reverse simulation addresses the risks and hidden dangers discovered in the forward simulation or the risk scenarios that are likely to occur in actual work, and reversely simulates the optimal risk avoidance path. The multi-scheme comparison is a simulation mode that, for the same live-line work task, presets multiple different complete work schemes and comprehensively compares the feasibility, safety, and work efficiency of each scheme through full-process simulation.

[0013] Furthermore, multi-scheme simulations are conducted, and the optimal operation plan is output, specifically including: Establish a screening index system for the optimal operation path. The screening index system includes primary indexes and secondary indexes, and each primary index includes several secondary indexes. Extract the deduction data of all effective schemes in the multi-scheme comparison, score each scheme item by item according to the quantitative screening index system, and calculate the comprehensive score of each effective scheme. The solutions are sorted from highest to lowest based on their overall scores, and those with overall scores higher than a preset score threshold are selected as candidate solutions for the optimal operation path. Based on the selected candidate solutions and the optimization results of reverse verification, the operation plan is adjusted and optimized. The optimized candidate scheme is then imported back into the job simulation pre-run module for forward simulation verification. If the verification passes, the scheme is determined to be the optimal job scheme; if the verification fails, the job scheme is readjusted and optimized again until the verification passes.

[0014] Furthermore, adjustments and optimizations to the work plan include: optimization of motion parameters, station and path positioning, tooling, and step sequence; among these, Motion parameter optimization includes adjusting the operator's operating angle, movement range, and movement speed to ensure that the safety distance redundancy of all movements is greater than the second preset multiple. Positioning and path optimization includes optimizing the positions of workers in each step to ensure unobstructed views; and adjusting the work path to reduce pauses between steps. Tool optimization includes changing the tool type if the tool usage in the candidate solution does not conform to the preset operation rule library, based on the reverse verification results; Step sequence optimization involves adjusting the order of task steps to minimize the total task time.

[0015] Optionally, the risk warning module collects distance data, collision data, and action specification data in real time and compares them with the live-line working rule base in real time. When there is insufficient safe distance, collision risk, or non-standard action, an early warning is immediately triggered and pushed to the work simulation and pre-play module through the collaborative control unit to trigger the optimization of the work plan.

[0016] Furthermore, it also includes a virtual training module, which is used to conduct immersive virtual practical training for live-line workers based on the optimal operation plan output by the operation simulation and pre-drill module, using a digital twin scene and physics engine.

[0017] The technical solution adopted in this invention has the following technical effects: 1. In the technical solution of this invention, the three-dimensional data acquisition module is used to collect three-dimensional point cloud data and real-scene image data of the live-line working site and its surrounding environment, and output a structured dataset; the digital twin model construction module is used to output a 1:1 live-line working digital twin scene model based on the dataset output by the three-dimensional data acquisition module; the operation simulation and pre-play module is used to import the digital twin model, bind physical rigid bodies to each model component and assign real physical parameters, and combine it with the preset live-line working rule library to realize real-time dynamic calculation, collision detection and distance measurement of the operation action, perform multi-scheme simulation and deduction, and output the optimal operation scheme; the risk warning module compares the collision detection data and distance detection data output by the operation simulation and pre-play module with the live-line working rule library, and triggers a warning when a hidden danger occurs; the collaborative control unit is used to realize the data interaction, command transmission and collaborative work of the three-dimensional data acquisition module, the digital twin model construction module, the operation simulation and pre-play module and the risk warning module, effectively solving the problem of low reliability of live-line working simulation and pre-play caused by the existing technology, and effectively improving the reliability of live-line working simulation and pre-play.

[0018] 2. The live-line working rule library in the technical solution of this invention includes national live-line working regulations, industry standard operating rules, model simulation interaction rules, simulation pre-running process rules, and multi-scheme deduction and adaptation rules. Through 1:1 digital twin scenario simulation pre-running and various rules, risks such as electric shock, falls from heights, and insufficient safety distances can be predicted in advance. Combined with real-time risk warning and scheme optimization, the incidence of live-line working safety accidents can be effectively reduced, and the problem of the extensiveness of existing operation schemes can be solved.

[0019] 3. The technical solution of this invention automatically outputs the optimal operation plan through multi-scheme simulation comparison, reducing the time for on-site survey and scheme adjustment, while avoiding rework due to unreasonable schemes, and improving the efficiency of live-line work.

[0020] 4. The technical solution of this invention establishes a screening index system for the optimal operation path; extracts the deduction data of all effective schemes in the multi-scheme comparison, scores each scheme item by item according to the quantitative screening index system, and calculates the comprehensive score of each effective scheme; sorts the schemes from high to low based on the comprehensive score to screen candidate schemes; for the screened candidate schemes, the operation schemes are adjusted and optimized in combination with the optimization results of reverse verification; the optimized candidate schemes are then imported back into the operation simulation pre-play module for forward deduction simulation verification. If the verification passes, the scheme is determined to be the optimal operation scheme; if the verification fails, the operation scheme is readjusted and optimized again until the verification passes; through the closed loop of field data acquisition → simulation pre-play → field application → data feedback, the digital twin model and the live-line operation rule base are continuously optimized to improve the system's adaptability and accuracy.

[0021] 5. The technical solution of the present invention also includes a virtual training module. The virtual training module is used to conduct immersive virtual practical training for live-line workers based on the optimal operation plan output by the operation simulation and pre-drill module, based on the digital twin scene and physical engine. It constructs an immersive virtual training scene, restores the real operation conditions 1:1, and realizes zero-risk, repeatable and standardized training. It solves the problems of high cost, high risk and large scene deviation of existing on-site training, and quickly improves the practical skills of workers.

[0022] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of the system structure in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the process of constructing a digital twin model in the system of Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the forward deduction process in the system of Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the reverse deduction process in the system of Embodiment 1 of the present invention; Figure 5 This is a flowchart illustrating the comparison of multiple solutions in the system of Embodiment 1 of the present invention; Figure 6 This is a flowchart illustrating the simulation and deduction of multiple schemes in the system of Embodiment 1 of the present invention, and outputting the optimal operation scheme. Figure 7 This is a schematic diagram of the execution flow of each module in the system of Embodiment 1 of the present invention. Detailed Implementation

[0025] To clearly illustrate the technical features of this solution, the invention will be described in detail below through specific embodiments and in conjunction with the accompanying drawings. The following disclosure provides many different embodiments or examples for implementing different structures of the invention. To simplify the disclosure of the invention, components and arrangements of specific examples are described below. Furthermore, reference numerals and / or letters may be repeated in different examples. This repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. It should be noted that the components illustrated in the drawings are not necessarily drawn to scale. Descriptions of well-known components, processing techniques, and processes are omitted in this invention to avoid unnecessarily limiting the invention.

[0026] Example 1 The purpose of this invention is to solve the technical problems of existing live-line work lacking accurate simulation and pre-visualization, real-time risk warning, and poor training effect. It constructs a high-precision digital twin scenario to realize visualized simulation of live-line work process, real-time risk prediction, automatic optimization of scheme and immersive virtual training, thereby reducing work safety risks and improving work efficiency and personnel skill level.

[0027] like Figure 1 As shown, the present invention provides a live-line work simulation and pre-drill system based on digital twin, including: a three-dimensional data acquisition module 1, a digital twin model construction module 2, a work simulation and pre-drill module 3, a risk warning module 4, and a collaborative control unit 6; Among them, the three-dimensional data acquisition module 1 is used to acquire three-dimensional point cloud data and real-scene image data of poles, lines, switches and surrounding environment at the live-line working site, and output a structured dataset with spatial coordinates, geometric dimensions and electrical attributes; The digital twin model building module 2 is used to output a 1:1 digital twin scene model of live-line operation based on the dataset output by the 3D data acquisition module 1. The operation simulation and pre-show module 3 is used to import the digital twin model, bind physical rigid bodies to each model component and assign real physical parameters, combine with the preset live operation rule library, realize real-time dynamic calculation of operation actions, collision detection and distance measurement, perform multi-scheme simulation and deduction, and output the optimal operation scheme. Risk warning module 4 compares the collision detection data and distance detection data output by the operation simulation and pre-drill module with the live-line operation rule base, and triggers a warning when a potential hazard is found. The collaborative control unit 6 is used to realize data interaction, instruction transmission and collaborative work of the three-dimensional data acquisition module 1, digital twin model construction module 2, operation simulation and pre-drilling module 3, and risk warning module 4.

[0028] The 3D data acquisition module 1 employs a combination of LiDAR and a high-definition industrial camera to collect 3D point cloud data and real-scene image data of poles, crossarms, lines, hardware, insulators, switches, and surrounding terrain and obstacles at live-line working sites. During acquisition, the spatial coordinates, geometric dimensions, and electrical properties (such as insulation class and live-line parameters) of each element are recorded simultaneously. After noise reduction, deduplication, and alignment processing, a standardized and structured 3D dataset is output (a structured dataset with spatial coordinates, geometric dimensions, and electrical properties), providing accurate data support for the construction of the digital twin model. The LiDAR sampling accuracy is ±2cm, and the high-definition camera resolution is no less than 4K. After distortion correction and enhancement processing, the acquired dataset ensures that the accuracy of the digital twin model reaches the centimeter level.

[0029] The digital twin model building module 2 utilizes ContextCapture real-scene modeling software, SolidWorks parametric modeling software, and 3ds Max lightweight processing software in collaboration. Based on the dataset output by the 3D data acquisition module 1, it goes through point cloud lightweighting, real-scene model construction, parametric model construction, lightweight optimization, and model fusion steps to output a 1:1 high-precision digital twin scene model of live-line operation. The model supports export in common formats such as FBX, OBJ, and STL, and includes geometric, physical, and electrical multi-dimensional attributes; details are as follows: (1) Modeling toolchain: ContextCapture real scene modeling software, SolidWorks parametric modeling software and 3ds Max lightweight processing software work together to form a complete modeling process of "real scene restoration - parametric modeling - lightweight optimization"; (2) Format standard: After modeling is completed, it supports the export of three common model formats: FBX, OBJ and STL, to ensure that the model can be seamlessly imported into the subsequent physics engine and realize the compatible interaction between the model and the engine. (3) Construction logic: First, the collected 3D point cloud data is lightened (redundant data is removed and the point cloud density is simplified). The real scene 3D model is generated by Context Capture software to restore the real layout of the towers, lines and surrounding environment. Then, the parametric models of the operation tools and personnel are established by SolidWorks software, and the models are given accurate geometric dimensions, physical properties and electrical properties. Then, the real scene model and the parametric model are reduced in number, texture is optimized and the hierarchy is simplified by 3ds Max software to realize the model lightening and reduce the pressure of subsequent simulation calculation. Finally, all models are merged and aligned, electrical properties and physical properties are bound, the model hierarchy LOD (Level of Detail) is optimized, and a 1:1 digital twin scene model of live-line operation is output, and the model accuracy meets the centimeter level requirement.

[0030] (4) Model Dimension: The constructed digital twin model includes geometric dimension (restores the appearance and size of the scene and equipment), physical dimension (assigns physical parameters such as mass and stiffness to the model), and electrical dimension (assigns electrical parameters such as insulation level, voltage and current, and grounding attributes to the model), providing a foundation for subsequent physical engine interaction and risk warning.

[0031] like Figure 2 As shown, the digital twin model construction process may include: Step 1: On-site Data Acquisition – Using a LiDAR (model: Velodyne VLP-16) and a high-definition industrial camera (resolution: 4K), comprehensive data acquisition is conducted on the 10kV power distribution line live-line work site. The acquisition range includes poles (model: 12m straight pole), conductors (model: JKLYJ-10-120), crossarms, hardware, insulators (model: XP-70), switches (drop-out fuses, disconnect switches, or pole-mounted switches, etc.), work tools (insulated operating rods, insulated gloves, electric wrenches, etc.), and surrounding terrain and obstacles. The LiDAR acquires 3D point cloud data with a sampling accuracy of ±2cm, and the high-definition camera acquires real-scene images, simultaneously recording the electrical parameters and geometric dimensions of each device to form the original dataset. Step 2: Data preprocessing - Denoise the original 3D point cloud data (remove environmental noise and redundant points), remove duplicates, and perform coordinate alignment. Perform distortion correction and enhancement on the real-world images to output a standardized structured dataset. Step 3: Real-world model construction – Import the preprocessed point cloud data and real-world images into ContextCapture software, set the modeling parameters (resolution: 1cm, texture mapping accuracy: 0.5mm), generate a real-world 3D model, and restore the real layout of the towers, lines and surrounding environment; Step 4: Parametric Model Construction – Using SolidWorks software, based on the collected dimensions of tools and workers, construct parametric models of the insulated operating rod, insulated bucket truck, and workers, and assign corresponding physical parameters (e.g., mass of the insulated operating rod: 2.5kg, coefficient of friction: 0.3) and electrical parameters (insulation class: 10kV). Step 5: Model Lightweight Optimization - Import the real-world model generated by ContextCapture and the parametric model created by SolidWorks into 3ds Max software, and perform polygon reduction processing (remove redundant faces of the model and retain core geometric features), texture optimization (use low-poly textures to reduce rendering pressure), layer simplification, and optimize the model's LOD detail level to ensure that the model is lightweight and does not lose accuracy. Step 6: Model Fusion and Export – Fusion and alignment of all optimized models, binding of physical and electrical properties of each model, exporting in FBX format to obtain a 1:1 high-precision live-line operation digital twin scene model, which is then imported into the UE5 platform for later use.

[0032] The operation simulation and pre-show module 3 is responsible for realizing the visualization simulation and pre-show of the entire live-line operation process based on the digital twin model and physics engine. It explicitly adopts Unreal Engine 5 (UE5) as the simulation platform, and its built-in PhysX 5 physics engine as the core driver. The specific interaction logic is as follows: 1. Physics Engine Selection: The PhysX 5 physics engine built into UE5 is adopted. This engine has efficient rigid body dynamics calculation, collision detection, and distance measurement capabilities, which can meet the real-time and accuracy requirements of live-line operation simulation. 2. Model and Engine Binding: After importing different digital twin models (FBX format, including towers, lines, insulated bucket trucks, tools, and workers) into the UE5 platform, UE5's rigid body component function is used to bind corresponding physical rigid body components to each model component. This assigns the model physical parameters consistent with the real scene (such as the flexibility of the conductor, the position of the insulated bucket truck, the motion inertia of the human body, and the closed state of the switch), ensuring that the model's motion and collisions conform to real physical laws. Static rigid bodies (fixed and immobile, with rigid collision parameters) are bound to towers, crossarms, insulators, hardware, and switches. The system assigns attributes to various components, including: flexible rigid bodies (simulating the bending and swaying characteristics of conductors, with an elastic coefficient of 100 N / m) for conductors; dynamic rigid bodies (assigning parameters such as position, mass, inertia, and friction coefficient to simulate real motion) for insulated bucket trucks, tools, and workers; and corresponding attribute tags for live equipment, insulated equipment, and grounding bodies. Specifically, it assigns "insulation attribute tags" to insulated arms, insulators, and insulated tools; "live attribute tags" to live conductors; and "grounding body attribute tags" to poles, crossarms, and fittings, for subsequent electrical distance detection.

[0033] 3. Establishment of operation rule base: A live-line operation rule base is preset in the physics engine, which includes the safety distance thresholds stipulated in the national live-line operation regulations (such as the minimum safe distance between the human body and the live conductor, and the safe distance between the live conductor and the grounding conductor), operation action specifications (such as operation sequence and action range), and equipment constraints (such as the usage specifications of tools and the opening and closing sequence of switches), as the basis for simulation and risk assessment.

[0034] Specifically, in the UE5 platform, a rule library for live-line work is configured: the minimum safe distance for 10kV live-line work (e.g., between the human body and the live conductor: 0.4m, etc.), work action specifications (e.g., test for voltage before operation, prohibit crossing the live conductor, etc.), and equipment constraints (e.g., maximum load capacity of the insulating bucket: 275kg, etc.).

[0035] 4. Collaborative Work: Upon receiving work action instructions, the PhysX 5 physics engine calculates the motion trajectory in real time, updates the model's spatial position, and simultaneously performs collision detection and distance measurement; the detection results are fed back to the collaborative control unit to trigger risk warnings and scheme optimization, and a simulation report is output after the simulation is completed.

[0036] Specifically, interactive command settings—using UE5's blueprint function, set operation action commands (such as the swinging and raising / lowering of a virtual person holding an insulated operating rod, and the lifting and resetting of a wire). Commands can be triggered by VR controllers, mice, or keyboards, and are synchronously bound to the dynamics calculation logic of the physics engine. Real-time calculation and detection—After triggering the operation action command, the PhysX 5 physics engine receives the command in real time, performs dynamic calculations on the movement trajectory of virtual workers and tools, and synchronously updates the spatial position of each model in the digital twin scene; at the same time, the engine performs two detections per frame: first, collision detection, which detects collisions between models through the "collision body component" (such as the collision between the insulated arm and the tower); second, distance detection, which calculates the minimum distance between the human body and the live wire, the tool and the grounding body, and the phases in real time through the "distance sensor component", with a detection frequency of 10 frames / second; Status feedback and early warning linkage—The physics engine feeds back the collision detection results and distance detection results to the collaborative control unit in real time. The collaborative control unit compares the data with the thresholds and specifications in the rule base. If insufficient distance or collision risk is detected, the collaborative control unit triggers the risk warning module, outputs audible and visual warnings and text warnings, and highlights the potential danger area. At the same time, it generates an avoidance plan (such as adjusting the operating angle or increasing the height of the insulated bucket) and pushes it to the operation simulation interface. Simulation report generation—After the simulation pre-run is completed, the physics engine automatically records motion data, detection data, and risk data of the entire operation process. The collaborative control unit integrates the data and generates a simulation report, which includes the operation sequence, risk list, optimal operation path, and tool usage suggestions, providing a basis for the formulation of actual operation plans.

[0037] Specifically, the live-line working rule library constructed in this solution includes not only the general working rules stipulated in the national live-line working regulations and industry standards, but also unique working rules adapted to this solution based on the simulation characteristics of digital twin models, the operation characteristics of the physical engine, and the actual needs of live-line working simulation pre-runs. These rules are the core rules that ensure a high degree of fit between digital twin simulation pre-runs and actual operations, accurate and controllable simulation process, and efficient and reliable risk warning.

[0038] Specifically, the live-line working rule library includes national live-line working regulations, industry standard operating rules, model simulation interaction rules (these rules are formulated for the binding characteristics of digital twin models and the PhysX 5 physics engine and the simulation operation logic, to ensure that the model's movement and interaction during the simulation process conform to the actual physical laws of live-line working, and at the same time adapt to the computing characteristics of the simulation platform), simulation pre-run process rules, and multi-scheme deduction and adaptation rules.

[0039] National regulations for live-line working and industry standard operating rules are all existing rules and specifications, which can be directly imported into the rule base.

[0040] Among them, (i) the model simulation interaction rules include: 1. Rigid Body Property Matching Rules: Static rigid bodies (towers, crossarms, insulators, fittings, switches) are only allowed to undergo position calibration before simulation. Modification of rigid body properties and spatial coordinates is prohibited during simulation. The elastic coefficient and swing amplitude of flexible rigid bodies (conductors) must match the model and tension of the actual line. When the conductor deformation exceeds 1.2 times the maximum deformation under actual working conditions (first preset multiple) during simulation, a model anomaly warning will be triggered. The motion acceleration of dynamic rigid bodies (insulated bucket trucks, tools, workers) shall not exceed the actual operation action acceleration threshold (maximum acceleration of upper limb operation ≤ 0.8 m / s², maximum acceleration of high-altitude movement ≤ 0.3 m / s²) to avoid the simulation action from being out of sync with the actual operation.

[0041] 2. Model Collision Judgment Rules: When models with different phase live attribute labels collide in contact, or when models with grounding attribute labels collide in contact, they are directly judged as "live short circuit / electric shock risk"; when the non-contact distance is less than the safety threshold and the "quasi-collision" state lasts for more than 2 frames (based on a detection frequency of 10 frames / second, i.e. 0.2 seconds, the first preset duration), it is judged as "safe distance insufficient risk"; non-necessary collisions between insulated arms, work buckets, tools and fixed facilities such as poles and crossarms are judged as "operation space limited risk".

[0042] 3. Simulation step size matching rules: The simulation calculation step size of the operation action must match the detection frequency. The simulation step size of a single operation action shall not exceed 0.1 seconds to ensure that there is no data omission in collision detection and distance measurement. When multiple steps are performed continuously, the simulation interval between adjacent actions shall not be less than 0.5 seconds (second preset duration) to simulate the operation connection time in actual operation.

[0043] (II) Simulation and pre-simulation process rules (based on the closed-loop process of simulation and pre-simulation - risk warning - solution optimization, standardizing the operation process, data recording and result judgment criteria of simulation and simulation) include: 1. Pre-simulation startup rules: After the digital twin model is imported into the Unreal Engine 5 platform, the model attribute verification (geometric, physical, and electrical attribute integrity), rigid body binding correctness detection, and rule base threshold matching verification must be completed first. The simulation can only be started after all three verifications are passed. If they fail, the problem points will be automatically prompted and the simulation will be prohibited.

[0044] 2. Operation Step Editing Rules: The operation steps in the simulation pre-run must be edited hierarchically according to the actual operation process of "site survey - safety measure deployment - operation - cleanup and evacuation". Each level of sub-steps must not be missing; the operation actions of a single step shall not exceed 3 (first preset number) to avoid simulation calculation errors due to overly complex actions.

[0045] 3. Simulation data recording rules: During the simulation, the model space coordinates, motion trajectory data, distance detection data, and collision judgment results of each frame must be recorded in real time. When a risk warning is triggered, the time, location, and cause of the warning frame are automatically marked, and the complete data of 5 frames before and after the warning (preset number of frames) are saved to provide a basis for scheme optimization.

[0046] (III) Multi-scheme simulation adaptation rules (These rules are formulated for the simulation modes of forward simulation, reverse verification, and multi-scheme comparison of this scheme, and clarify the applicable standards and result judgment dimensions for different simulation modes) include: 1. Simulation mode switching rules: When a Level 1 risk (electric shock, short circuit, fall from height) is triggered during the forward simulation, the simulation will be automatically paused and the system will be able to switch to the reverse verification mode. When comparing multiple schemes, the simulation environment (model parameters, physics engine settings, rule base thresholds) of different operation schemes must be kept completely consistent to ensure the objectivity of the comparison results.

[0047] 2. Rules for determining the effectiveness of a solution: After the simulation is completed, a solution that does not trigger any risk warnings is determined to be a "effective solution"; a solution that only triggers a level 2 risk (non-standard operation, limited temporary space) and can be adjusted and corrected is determined to be a "solution to be optimized"; a solution that triggers a level 1 risk is directly determined to be an "ineffective solution". Among them, the risk level of level 1 risk is greater than that of level 2 risk.

[0048] Preferably, the operation simulation pre-play module 3 can also be used for real-time interaction and deduction: the operator can edit the operation steps and control the movement path of the virtual operator through VR device, mouse or keyboard. The physics engine receives the action instructions in real time, performs dynamic calculation on the movement trajectory of the virtual operator and tools, and updates the spatial position of each model in the digital twin scene in a synchronous manner. At the same time, the engine performs collision detection (such as collision between tools and lines, collision between human body and grounding body, the collision detection and distance detection frequency of the physics engine is not less than 10 frames / second to ensure real-time identification and feedback of risks and hazards) and distance measurement (such as the real-time distance between human body and live wire), and feeds back the detection results to the collaborative control unit 6 in real time. Preferably, the operation simulation and pre-drill module 3 can also be used for multi-scheme deduction: it supports forward deduction (simulating the entire operation process according to preset operation steps), reverse verification (deducing the optimal avoidance path in reverse for possible risk scenarios), and multi-scheme comparison (simulation comparison of different operation paths and different combinations of tools and equipment). After the deduction is completed, the optimal operation path, operation sequence and tool and equipment usage scheme will be automatically output.

[0049] Specifically, the multi-solution simulation in this solution includes three core modes: forward simulation, reverse verification, and multi-solution comparison. Forward simulation is the basic simulation mode, reverse verification is a risk-specific simulation mode, and multi-solution comparison is a comprehensive simulation mode for selecting the optimal solution. All three modes are implemented based on the Unreal Engine 5 platform + PhysX 5 physics engine, relying on a 1:1 digital twin scene model and operation rule library. The specific simulation process of each mode is as follows: (I) Forward Simulation: Forward simulation is a full-process simulation of live-line working procedures, from preparation to completion, following a pre-set standardized procedure. Its core purpose is to verify the feasibility of the pre-set work plan and to predict potential risks and hazards during the work process, such as... Figure 3 The specific process is as shown: 1. Scheme Import: Import the initial live-line working scheme (including work steps, action paths, types and sequences of tools and equipment, and positions of workers) based on the site survey into the work simulation pre-play module 3, and complete the hierarchical editing of the work steps and the setting of action parameters according to the specific rules of this scheme.

[0050] 2. Simulation Initialization: Complete the attribute verification and rigid body binding detection of the digital twin model, load the general thresholds and specific rules in the operation rule library, initialize the virtual insulated bucket, operators, and tools to the operation preparation position, and ensure that the simulation environment is consistent with the actual operation site.

[0051] 3. Step-by-step simulation calculation: The operation action command is triggered by VR controller, mouse or keyboard. The PhysX 5 physics engine performs real-time dynamic calculation of each step of the operation action according to the simulation step size of 0.1 seconds, and updates the spatial position and movement trajectory of the virtual insulated bucket, operator and tool in real time. The collision detection and distance detection modules perform real-time detection at a frequency of 10 frames / second and feed the detection data back to the collaborative control unit 6.

[0052] 4. Real-time risk assessment: The collaborative control unit 6 compares the detection data with the thresholds and specifications in the operation rule library in real time. If a potential risk is detected, the corresponding early warning mechanism is triggered according to the risk level (Level 1: fatal risks such as electric shock, short circuit, and fall from height; Level 2: general risks such as non-standard operation and critical safety distance). The simulation is then paused or continued (Level 1 risks are paused, while Level 2 risks are continued and marked).

[0053] 5. Simulation Result Recording: After the simulation is completed, the system automatically records the simulation data of the entire process, including the completion time of each step, the type and location of risk warnings, the key parameters of model movement, and generates a "Forward Simulation Result Report" to clarify the effective / optimizable / ineffective judgment results of the preset scheme.

[0054] (II) Reverse Verification: Reverse verification is a deductive model that reverse-engineers the optimal risk avoidance path for risks and hidden dangers discovered in forward simulation or typical risk scenarios that are likely to occur in actual operations. Its core purpose is to develop targeted solutions for specific risk points, supplementing and optimizing forward simulation. For example... Figure 4 The specific process is as shown: 1. Risk Location: Based on the results report of forward simulation, extract the specific locations of risk warnings (such as insufficient distance between the human body and the live wire in a certain operation step, collision between the insulated arm and the tower, etc.), risk type, trigger time and related simulation data, and accurately mark the spatial location and action node of the risk in the digital twin scenario.

[0055] 2. Risk scenario solidification: In the operation simulation pre-play module, the simulation scenario (including model position, action status, environmental parameters, etc.) one second before the risk occurs is solidified as the initial scenario for reverse verification, ensuring that the verification process revolves around the specific risk point.

[0056] 3. Risk Mitigation Plan Pre-set: In response to this risk point, and in combination with the live-line working specifications and the actual on-site working conditions, multiple possible risk mitigation plans are pre-set, mainly including: adjusting the position / operating angle of the operator, changing the position of the work bucket, modifying the range / sequence of the work actions, adding auxiliary safety measures, etc. The work action parameters are edited separately for each plan.

[0057] 4. Single-point reverse calculation: Starting from the initial node of the fixed risk scenario, single-point simulation calculation is performed for each preset avoidance scheme. The physics engine only performs dynamic calculation on the operation actions related to the risk point, focusing on checking whether the adjusted actions have eliminated the risk hazards, and at the same time verifying whether the adjusted actions will cause new risks.

[0058] 5. Optimization of Avoidance Paths: Detailed optimization of all avoidance schemes that can eliminate risks, such as fine-tuning the operating angle and shortening / extending the range of motion, to ensure that the optimized operation actions not only comply with the live-line working specifications but also have practical feasibility; finally, record the action parameters and step adjustment scheme of the optimal avoidance path and generate a "Reverse Verification Optimization Report".

[0059] (III) Multi-scheme comparison: Multi-scheme comparison is a simulation mode that, for the same live-line work task, pre-sets multiple different complete work schemes and comprehensively compares the feasibility, safety, and work efficiency of each scheme through full-process simulation. The core objective is to select the scheme with the best overall performance from multiple effective schemes, such as... Figure 5 The specific process is as shown: 1. Multiple solutions development: For the same live-line work task, 3-5 different complete work solutions are developed based on factors such as site terrain, equipment parameters, and the skill level of the workers. The core differences between the solutions are reflected in the work path, tool combination, worker configuration, and work step sequence, ensuring the diversity and comparability of the solutions.

[0060] 2. Unified simulation benchmark: In the job simulation pre-run module, a completely consistent simulation benchmark is set for all preset schemes, including digital twin model parameters, physics engine solution rules, job rule library thresholds, detection frequency, simulation step size, etc., to eliminate the impact of simulation environment differences on comparison results.

[0061] 3. Batch simulation and deduction: Following the forward deduction process, the system performs full-process simulation and deduction for each scheme in sequence. The system automatically records the complete simulation data of each scheme, including: risk warning status (no / yes, level 1 / level 2), total operation time, length of operator movement trajectory, operation difficulty coefficient (based on the complexity of the action) and other core indicators.

[0062] 4. Multi-dimensional quantitative comparison: Based on the recorded simulation data, a quantitative comparison system is established from four dimensions: safety, efficiency, economy, and operability. Each solution is scored (out of 100 points, including 40 points for safety, 25 points for efficiency, 15 points for economy, and 20 points for operability). The scoring criteria strictly follow the general standards and specific rules of the operation rule library.

[0063] 5. Comparison and Analysis of Results: Generate a "Multi-Solution Comparison and Analysis Report" to clarify the scores, advantages and disadvantages of each scheme, providing quantitative data support for the subsequent output of the optimal operation path.

[0064] It should be noted that this solution outputs the optimal work path based on the results of multiple scenario simulations, not solely on the result of a single simulation model. Instead, it integrates feasibility verification from forward simulations, risk optimization schemes from reverse verification, and quantitative scoring from multiple scenario comparisons. This is achieved through four core steps: quantitative indicator system screening, key parameter optimization, adaptation to actual working conditions, and path verification. The final output optimal work path is a standardized work path that can directly guide actual operations and combines safety, efficiency, economy, and operability. Figure 6 As shown, the specific implementation process is as follows: Step 1: Establish a quantitative screening index system for the optimal work path: Guided by the core needs of live-line work and based on recorded data from multiple scenario simulations, a quantitative screening index system was established, comprising four primary indicators—safety, efficiency, economy, and operability—and eleven secondary indicators. Each indicator has clearly defined scoring criteria and weights to ensure the objectivity and accuracy of the screening results. The specific index system is shown in Table 1 below: Table 1: Quantitative Screening Index System

[0065] Step 2: Quantitative scoring and initial screening of indicators based on the simulation results: Extract the projection data of all effective schemes (without a first-level risk warning) in the multi-scheme comparison, score each scheme item by item according to the above quantitative screening index system, and calculate the comprehensive score of each scheme (comprehensive score = Σ score of each secondary indicator × corresponding weight of the primary indicator / 10).

[0066] The solutions are sorted from highest to lowest based on their overall scores, and the top two solutions are selected as candidates for the optimal work path. If there is only one valid solution, it is compared and scored with the solution to be optimized after reverse verification, and a candidate solution is selected.

[0067] Step 3: Optimize key parameters of candidate solutions based on reverse verification results: Based on the selected candidate solutions and the optimization results of reverse verification, the operational parameters in the work plans are finely adjusted to eliminate potential minor risks or operational inconveniences. The optimization mainly includes: Motion parameter optimization: Adjust the operator's operating angle, movement range, and movement speed to ensure that the safety distance redundancy of all movements is ≥1.2 times and conforms to the actual operating habits of the human body.

[0068] Positioning and path optimization: Optimize the position of operators in each step, shorten the ineffective movement trajectory, and ensure that the position is unobstructed and the operating space is sufficient; at the same time, adjust the operation path to reduce the pause time between steps.

[0069] Tool optimization: If there are unreasonable tool usage situations in the candidate solutions, replace them with more suitable tool types based on the reverse verification results.

[0070] Step sequence optimization: Fine-tune the order of the steps to improve the smoothness of the steps and shorten the total time spent on the task.

[0071] Step 4: Perform final simulation verification on the optimized candidate solutions: The optimized candidate solutions are then imported back into the job simulation pre-run module for full-process closed-loop simulation verification. The verification process strictly follows the forward deduction process, with a focus on the following: Does the optimized plan completely eliminate all risks and ensure that no level one or level two risk warnings are triggered? Whether the optimized parameters conform to the general standards and specific rules of the operation rule base, and whether they are highly adapted to the actual operation conditions; Whether the optimized solution improves or remains stable in terms of security, efficiency, and other indicators compared to the original solution.

[0072] If the verification passes, the solution is determined to be the optimal operation solution; if the verification fails, return to step 3 to re-optimize the parameters until the verification passes.

[0073] Step 5: Output the standardized optimal work path and supporting documents: Based on the validated optimal work plan, the system automatically extracts the core information of the work path, outputs a standardized optimal work path, and generates a corresponding work instruction document. The specific output includes: Visualized Work Path Map: Mark the complete movement trajectory of the virtual worker, the position of each step, and the action nodes of key operations in the digital twin scene, and generate a scalable and detailed visualized path map to intuitively display the work path.

[0074] Standardized Work Procedure Manual: Clearly defines each step of the optimal work path, action requirements, operating parameters (such as operating angle and amplitude), tool selection and use, and safety precautions. The manual is concise and clear, and can directly guide on-site workers.

[0075] Operation Parameter Details Table: Records the core parameters of the optimal operation path, including total operation time, tool and equipment list, personnel configuration, and safety distance data for each step, providing data support for the preparation and execution of on-site operations.

[0076] Risk prevention and control checklist: Identify key risk prevention and control points in the optimal work path, clarify prevention and control measures and precautions, and ensure that on-site workers are prepared for risk prevention and control in advance.

[0077] At the same time, the optimal work path and supporting documents will be pushed to the virtual training module and the on-site work terminal, respectively for immersive training and actual work guidance. The feedback data from the on-site work will be continuously transmitted back to the system to dynamically optimize the work path.

[0078] The risk warning module 4 works in collaboration with the operation simulation and pre-drill module 3 and the digital twin model construction module 2. Based on the real-time detection data of the physics engine and the preset live-line operation rule library, it realizes real-time prediction and warning of operation risks. Specifically, it collects distance data (human body-conductor, tool-grounding body, phase-to-phase distance), collision data, and action specification data in real time and compares them with the live-line operation rule library in real time. When there is insufficient safety distance, collision risk, or non-standard action, an early warning is immediately triggered and pushed to the operation simulation and pre-drill module through the collaborative control unit to trigger operation plan optimization.

[0079] Preferably, when potential hazards such as insufficient safety distance, collision risk, or non-standard actions occur, an audible and visual warning, a text warning, and a scene highlight warning (highlighting the location of the hazard) are immediately triggered. At the same time, the cause of the hazard is automatically analyzed, and targeted avoidance plans and action correction suggestions are generated and pushed to the operation simulation interface and collaborative control unit to guide the optimization of the operation plan.

[0080] Preferably, the live-line work simulation and rehearsal system based on digital twins in this embodiment further includes a virtual training module 5. The virtual training module 5 is used to provide immersive virtual practical training for live-line workers based on the optimal work plan output by the work simulation and rehearsal module 3, using a digital twin scene and physics engine. Specifically, it can provide immersive virtual practical training for live-line workers based on a digital twin scene and physics engine, supporting both VR and PC operation. It includes a standardized work process teaching module, an error action recognition module, an automatic scoring module, and a replay and review module. During training, the virtual scene replicates the real work environment 1:1, allowing trainees to simulate the entire live-line work process. The physics engine provides real-time feedback on the operation results, the error action recognition module automatically identifies non-standard operations and provides correction prompts, and after training, it automatically generates a scoring report and operation replay, achieving zero-risk, repeatable, and standardized immersive training, improving training efficiency and trainees' practical skills.

[0081] The collaborative control unit 6, as the control core of the system, connects all the above modules and is responsible for data interaction, command transmission, and collaborative work among the modules. It receives the dataset from the 3D data acquisition module 1 and pushes it to the digital twin model construction module 2; it receives the digital twin model and pushes it to the operation simulation pre-play module 3; it receives the detection data from the physics engine and pushes it to the risk warning module 4, while simultaneously receiving the warning information from the risk warning module 4 and feeding it back to the operation simulation pre-play module for optimization and adjustment (this optimization and adjustment process can also be carried out in the risk warning module 4); it receives the optimized operation plan output by the operation simulation pre-play module and feeds it back to the virtual training module 5; it synchronously coordinates the linkage between the virtual training module 5 and the digital twin scene to achieve consistency between the training scene and the real operation scene.

[0082] In this embodiment, the overall implementation flow (full-process closed loop) of different modules of the system is as follows: Figure 7 As shown: Step 1: Data Acquisition – Using the 3D data acquisition module, complete the acquisition of 3D point cloud and real-scene data of the live-line working site, and output a structured dataset; Step 2: Model Building – Using the digital twin model building module, Context Capture + SolidWorks + 3ds Max collaborative modeling is used to generate a 1:1 high-precision digital twin scene model, which is then imported into the UE5 physics engine. Step 3: Simulation and Pre-run – Through the operation simulation and pre-run module, edit the operation steps and motion paths, start the physics engine to perform real-time simulation and deduction, view the operation process and potential risks in real time, and adjust and optimize the operation plan based on the early warning information until the optimal operation plan is formed. Step 4: Risk Warning and Solution Optimization – The risk warning module detects potential hazards in real time, outputs warning information, and re-simulates and re-runs the scenario based on the optimized solution; Step 5: Virtual Training – Synchronize the optimal work plan to the virtual training module, organize workers for immersive virtual hands-on training, and improve workers’ practical skills through error recognition, automatic scoring, and replay review. Step 6: Field Application – Push the optimal work instructions generated by the simulation to the field operators to guide the actual live-line work. At the same time, feed the field work data back to the system to update the digital twin model and the work rule library to achieve continuous optimization.

[0083] In summary, compared with existing technologies, this invention possesses reproducibility and scalability: it clarifies the interaction logic between the digital twin model construction toolchain and the physics engine, ensuring accurate reproduction of each step, adapting to different voltage levels and types of live-line working scenarios, and facilitating widespread application in the power industry; through a closed loop of on-site data acquisition → simulation pre-run → on-site application → data feedback, it continuously optimizes the digital twin model and the operation rule base, improving the system's adaptability and accuracy.

[0084] In this invention, the 3D data acquisition module collects 3D point cloud data and real-scene image data of the live-line work site and its surrounding environment, and outputs a structured dataset. The digital twin model construction module outputs a 1:1 digital twin scene model of the live-line work based on the dataset output by the 3D data acquisition module. The work simulation and pre-play module imports the digital twin model, binds physical rigid bodies to each model component and assigns real physical parameters, and combines it with a preset live-line work rule library to realize real-time dynamic calculation, collision detection, and distance measurement of work actions, perform multi-scheme simulation and deduction, and output the optimal work scheme. The risk warning module compares the collision detection data and distance detection data output by the work simulation and pre-play module with the live-line work rule library and triggers a warning when a hidden danger is found. The collaborative control unit realizes data interaction, command transmission, and collaborative work among the 3D data acquisition module, digital twin model construction module, work simulation and pre-play module, and risk warning module, effectively solving the problem of low reliability of live-line work simulation and pre-play caused by existing technologies, and effectively improving the reliability of live-line work simulation and pre-play.

[0085] The live-line working rule library in this invention includes national live-line working regulations, industry standard operating rules, model simulation interaction rules, simulation pre-running process rules, and multi-scheme deduction and adaptation rules. Through 1:1 digital twin scenario simulation pre-running and various rules, risks such as electric shock, falls from heights, and insufficient safety distances can be predicted in advance. Combined with real-time risk warning and scheme optimization, the incidence of live-line working safety accidents can be effectively reduced, solving the problem of the extensiveness of existing operating schemes.

[0086] The technical solution of this invention automatically outputs the optimal operation plan through multi-scheme simulation comparison, reducing the time for on-site survey and scheme adjustment, while avoiding rework due to unreasonable schemes, and improving the efficiency of live-line work.

[0087] The technical solution of this invention establishes a screening index system for the optimal operation path; extracts the deduction data of all effective schemes in the multi-scheme comparison, scores each scheme item by item according to the quantitative screening index system, and calculates the comprehensive score of each effective scheme; sorts the schemes from high to low based on the comprehensive score to screen candidate schemes; for the screened candidate schemes, the operation schemes are adjusted and optimized in combination with the optimization results of reverse verification; the optimized candidate schemes are then imported back into the operation simulation pre-play module for forward deduction simulation verification. If the verification passes, the scheme is determined to be the optimal operation scheme; if the verification fails, the operation scheme is readjusted and optimized again until the verification passes; through the closed loop of field data acquisition → simulation pre-play → field application → data feedback, the digital twin model and the live-line operation rule base are continuously optimized to improve the system's adaptability and accuracy.

[0088] The technical solution of this invention also includes a virtual training module. The virtual training module is used to conduct immersive virtual practical training for live-line workers based on the optimal operation plan output by the operation simulation and pre-operation module, using a digital twin scene and physical engine. It constructs an immersive virtual training scene, restores the real operation conditions 1:1, and achieves zero-risk, repeatable, and standardized training. This solves the problems of high cost, high risk, and large scene deviation in existing on-site training, and rapidly improves the practical skills of workers.

[0089] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A live working simulation and pre-play system based on digital twinning, characterized in that, include: The system includes a 3D data acquisition module, a digital twin model construction module, a job simulation and pre-visualization module, a risk warning module, and a collaborative control unit. The 3D data acquisition module is used to collect 3D point cloud data and real-scene image data of poles, lines, switches and surrounding environment at the live-line working site, and output a structured dataset with spatial coordinates, geometric dimensions and electrical attributes; the digital twin model construction module is used to output a 1:1 live-line working digital twin scene model based on the dataset output by the 3D data acquisition module; the operation simulation and pre-play module is used to import the digital twin model, bind physical rigid bodies to each model component and assign real physical parameters, and combine it with a preset live-line working rule library to realize real-time dynamic calculation, collision detection and distance measurement of operation actions, perform multi-scheme simulation and deduction, and output the optimal operation scheme; the risk warning module compares the collision detection data and distance detection data output by the operation simulation and pre-play module with the live-line working rule library, and triggers a warning when a hidden danger is found. The collaborative control unit is used to realize data interaction, instruction transmission and collaborative work of the three-dimensional data acquisition module, digital twin model construction module, operation simulation and pre-drilling module and risk warning module.

2. The live working simulation and rehearsal system based on digital twinning of claim 1, wherein, The live-line working rule base includes national live-line working procedures, industry standard operating rules, model simulation interaction rules, simulation pre-running process rules, and multi-scheme deduction and adaptation rules.

3. The live working simulation and rehearsal system based on digital twinning of claim 2, wherein, The model simulation interaction rules include rigid body attribute matching rules, model collision determination rules, and simulation step size matching rules; among which... The rigid body property matching rules are as follows: static rigid bodies are only allowed to undergo position calibration before simulation, and modification of rigid body properties and spatial coordinates is prohibited during simulation; the elastic coefficient and swing amplitude of flexible rigid bodies are matched with the model and tension of the actual line; when the conductor deformation exceeds the first preset multiple of the maximum deformation under actual working conditions during simulation, a model anomaly warning is triggered; the motion acceleration of dynamic rigid bodies does not exceed the actual operation action acceleration threshold; among them, static rigid bodies include towers, crossarms, insulators, hardware, and switches; flexible rigid bodies include conductors; and dynamic rigid bodies include insulated bucket trucks, tools, and workers. The model collision judgment rules include: when models with different phase charged attribute labels collide in contact, or when models with grounded attribute labels collide in contact with charged attribute labels, it is judged as a risk of short circuit / electric shock; when a non-contact distance is less than the safety threshold and continues for more than a first preset time, it is judged as a risk of insufficient safety distance; and when non-essential collisions between insulated arms, work buckets, tools and poles, or crossarms are judged as a risk of limited operating space. The simulation step size matching rule includes matching the simulation calculation step size of the operation action with the detection frequency; when performing multi-step continuous operation, the simulation interval between adjacent actions is not less than the second preset time, so as to simulate the operation connection time in actual operation.

4. The live working simulation and rehearsal system based on digital twinning of claim 2, wherein, The simulation pre-run process rules include simulation start-up pre-requirement rules, job step editing rules, and simulation data recording rules; among them... The pre-simulation start rules include that after the digital twin model is imported into the simulation platform, model attribute verification, rigid body binding correctness detection, and rule base threshold matching verification must be completed. The simulation can only be started after all verifications are passed. If they fail, the problem points will be automatically prompted and the simulation will be prohibited. The rules for editing work steps include that the work steps in the simulation should be edited hierarchically according to the actual work process, and no sub-steps at each level should be missing; the number of work actions in a single step should not exceed the first preset number. The simulation data recording rules include recording the model space coordinates, motion trajectory data, distance detection data, and collision judgment results for each frame during the simulation process. When a risk warning is triggered, the time, location, and cause of the warning frame are automatically marked, and the complete data of the preset number of frames before and after the warning is saved.

5. The live-line work simulation and rehearsal system based on digital twinning of claim 2, wherein, The multi-scheme simulation and adaptation rules include simulation mode switching rules and scheme validity determination rules; among them... The simulation mode switching rules include automatically pausing the simulation and supporting switching to the reverse verification mode when a level 1 risk is triggered during the forward simulation; when comparing multiple schemes, the simulation environment of different operation schemes must be kept consistent to ensure the objectivity of the comparison results; The rules for determining the effectiveness of a solution include: after the simulation is completed, a solution that does not trigger any risk warnings is considered a valid solution; a solution that only triggers a level 2 risk and can be corrected is considered a solution to be optimized; and a solution that triggers a level 1 risk is directly considered an invalid solution, wherein the risk level of level 1 risk is greater than that of level 2 risk.

6. The live-line work simulation and rehearsal system based on digital twinning of claim 1, wherein, The multi-scheme simulation includes forward simulation, reverse simulation, and multi-scheme comparison. The forward simulation follows the preset live-line working process, simulating the entire process from work preparation to work completion. The reverse simulation is a simulation mode that reversely deduces the optimal risk avoidance path for the risks and hidden dangers found in the forward simulation or the risk scenarios that are likely to occur in actual operations. The multi-scheme comparison is a simulation mode that, for the same live-line work task, pre-sets multiple different complete work schemes and comprehensively compares the feasibility, safety, and work efficiency of each scheme through full-process simulation.

7. The live-line work simulation and rehearsal system based on digital twinning of claim 6, wherein, The process of conducting multi-scheme simulations and outputting the optimal operation plan specifically includes: Establish a screening index system for the optimal operation path. The screening index system includes primary indexes and secondary indexes, and each primary index includes several secondary indexes. Extract the deduction data of all effective schemes in the multi-scheme comparison, score each scheme item by item according to the quantitative screening index system, and calculate the comprehensive score of each effective scheme. The solutions are sorted from highest to lowest based on their overall scores, and those with overall scores higher than a preset score threshold are selected as candidate solutions for the optimal operation path. Based on the selected candidate solutions and the optimization results of reverse verification, the operation plan is adjusted and optimized. The optimized candidate scheme is then imported back into the job simulation pre-run module for forward simulation verification. If the verification passes, the scheme is determined to be the optimal job scheme; if the verification fails, the job scheme is readjusted and optimized again until the verification passes.

8. The live-line work simulation and rehearsal system based on digital twinning of claim 7, wherein, The adjustments and optimizations to the work plan include: motion parameter optimization, station and path optimization, tool and equipment optimization, and step sequence optimization; among these, Motion parameter optimization includes adjusting the operator's operating angle, movement range, and movement speed to ensure that the safety distance redundancy of all movements is greater than the second preset multiple. Positioning and path optimization includes optimizing the positions of workers in each step to ensure unobstructed views; and adjusting the work path to reduce pauses between steps. Tool optimization includes changing the tool type if the tool usage in the candidate solution does not conform to the preset operation rule library, based on the reverse verification results; Step sequence optimization involves adjusting the order of task steps to minimize the total task time.

9. The live-line work simulation and rehearsal system based on digital twinning of claim 1, wherein, The risk warning module collects distance data, collision data, and action standard data in real time and compares them with the live-line working rule library in real time. When there is insufficient safe distance, collision risk, or non-standard action, an early warning is immediately triggered and pushed to the work simulation and pre-play module through the collaborative control unit to trigger the optimization of the work plan.

10. The live working simulation and rehearsal system based on digital twinning according to any one of claims 1-9, characterized in that, It also includes a virtual training module, which is used to conduct immersive virtual practical training for live-line workers based on the optimal operation plan output by the operation simulation and pre-operation module, using digital twin scenarios and a physics engine.

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