Methods, systems, equipment and media for collaborative management and control of power construction progress

Abstract

This application relates to a method, system, equipment, and medium for collaborative management and control of power construction progress. The method includes: constructing an enhanced BIM (Body Model) based on electrical parameters and spatial layout data of the construction area; the enhanced BIM includes electromagnetic field distribution data and gradient information; dynamically compensating the acquired wireless positioning signals based on the electromagnetic field distribution data to generate machine pose data, wherein the machine pose data includes machine coordinates and attitude angles; generating global paths for multiple machines using a path planning algorithm based on the gradient information, all global paths constituting a collaborative operation path, the global path including path point coordinates and corresponding allowable deviation thresholds; comparing the machine pose data with the collaborative operation path to obtain a deviation value; when the deviation value exceeds a preset threshold, dynamically adjusting the construction schedule plan, wherein the construction schedule plan is used to update the enhanced BIM. This method enables precise collaborative operation of construction machinery in environments with strong interference.

Description

Technical Field

[0001] This invention belongs to the field of power construction technology, and in particular relates to a method, system, equipment and medium for collaborative management and control of power construction progress. Background Technology

[0002] With the advancement of smart grid construction, BIM-based construction progress visualization and industrial robot collaborative operation technologies have been gradually applied in power engineering. Existing technologies typically employ ultra-wideband (UWB) positioning systems to achieve real-time position tracking of construction machinery and use algorithms such as Rapid Expanding Random Tree (RRT) for obstacle avoidance path planning for multiple robotic arms. Traditional methods, by independently optimizing the positioning system and path planning module, can meet basic collaborative requirements in conventional construction environments.

[0003] However, during construction in high-voltage energized areas of 500kV and above, the coupling between the power frequency electromagnetic field (50 / 60Hz) and the harmonic components of the UWB signal center frequency (3.5-6.5GHz) causes nonlinear distortion in the UWB channel impulse response, resulting in the cumulative amplification of mechanical positioning deviations. Simultaneously, changes in the electric field gradient interfere with the obstacle avoidance decision-making logic of traditional path planning algorithms, leading to path conflicts during collaborative mechanical operations. Current technologies have not effectively solved the problem of mismatch in the positioning-planning system under the coupling effect of electromagnetic interference, severely restricting the accuracy of construction progress control and operational safety in high-voltage energized areas. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, system, equipment, and medium for collaborative management and control of power construction progress to address the aforementioned technical problems. This method can enable precise collaborative operation of construction machinery in environments with strong interference, thereby improving the real-time performance and operational safety of progress management in high-voltage energized areas.

[0005] Firstly, this application provides a method for collaborative management and control of power construction progress, including:

[0006] Based on the electrical parameters and spatial layout data of the construction area, an enhanced BIM is constructed, which includes electromagnetic field distribution data and gradient information.

[0007] Based on the electromagnetic field distribution data, the acquired wireless positioning signal is dynamically compensated to generate mechanical pose data, which includes mechanical coordinates and attitude angles.

[0008] Based on gradient information, a global path for multiple machines is generated through a path planning algorithm. All global paths constitute a collaborative operation path. The global path includes the coordinates of the path points and the allowable deviation thresholds corresponding to the path point coordinates.

[0009] The deviation value is obtained by comparing the mechanical pose data with the collaborative operation path. When the deviation value exceeds the preset threshold, the construction schedule is dynamically adjusted. The construction schedule is used to update the enhanced BIM.

[0010] In one embodiment, the acquired wireless positioning signal is dynamically compensated based on electromagnetic field distribution data to generate mechanical pose data, including:

[0011] Extract electric field strength and magnetic field strength data along the propagation path of wireless positioning signals from electromagnetic field distribution data;

[0012] Based on the path integral of electric field strength data and the curl modulus of magnetic field strength data, a channel distortion factor is constructed, which is used to characterize the degree of influence of electromagnetic interference on the positioning signal.

[0013] Based on an adaptive filter constructed using the channel distortion factor, the wireless positioning signal is filtered and compensated to generate mechanical pose data.

[0014] In one embodiment, based on gradient information, a path planning algorithm generates global paths for multiple machines. All global paths constitute a collaborative operation path. The path planning algorithm is a fast expanding random tree, comprising:

[0015] The path planning weight coefficients are calculated based on gradient information, where the path planning weight coefficients are inversely proportional to the magnitude of the gradient information.

[0016] In the node expansion phase of the rapidly expanding random tree, the path planning weight coefficients are embedded into the cost function to generate a node expansion priority queue.

[0017] Path search is performed based on the node expansion priority queue to generate a set of conflict-free paths that avoid regions with high electric field strength.

[0018] Spatially bind the set of conflict-free paths to the equipment installation locations in the enhanced BIM to generate global paths.

[0019] In one embodiment, the machine pose data is compared with the collaborative operation path to obtain a deviation value. When the deviation value exceeds a preset threshold, the construction schedule is dynamically adjusted, including:

[0020] Extract the path target point with the corresponding timestamp from the global path based on the machine coordinates;

[0021] Spatially align the machine coordinates with the path target points and calculate the Euclidean distance deviation between the machine coordinates and the path target points. Specifically, spatial alignment involves transforming the coordinate system to the global coordinate system of the enhanced BIM.

[0022] When the Euclidean distance deviation exceeds the allowable deviation threshold, a local path replanning is performed using a path planning algorithm to generate a new path point sequence.

[0023] The duration of affected processes is adjusted based on the new path point sequence, and the critical path duration is recalculated using the forward-backward method. The critical path duration is used to generate a dynamically adjusted construction schedule.

[0024] In one embodiment, when the Euclidean distance deviation exceeds the allowable deviation threshold, a local path replanning is performed using a path planning algorithm to generate a new sequence of path points, including:

[0025] Based on Euclidean distance deviation and gradient information, the search radius of local path replanning is calculated, and a spherical search region centered on the machine coordinates is generated. The radius of the spherical search region is inversely proportional to the gradient magnitude and directly proportional to the Euclidean distance deviation.

[0026] Within the spherical search region, the node expansion direction weights are calculated based on gradient information to generate a candidate node sequence;

[0027] The candidate node sequence is smoothed and then connected with the unaffected path segments in the global path by tangent lines to obtain a new path point sequence.

[0028] Secondly, this application also provides a collaborative management and control system for power construction progress, including:

[0029] The BIM modeling module is used to build an enhanced BIM based on the electrical parameters and spatial layout data of the construction area. The enhanced BIM includes electromagnetic field distribution data and gradient information.

[0030] The positioning compensation module is used to dynamically compensate the acquired wireless positioning signal based on electromagnetic field distribution data to generate mechanical pose data, which includes mechanical coordinates and attitude angles.

[0031] The collaborative control module is used to generate global paths for multiple machines based on gradient information and through path planning algorithms. All global paths constitute the collaborative operation path. The global path includes the coordinates of the path points and the allowable deviation thresholds corresponding to the path point coordinates.

[0032] The dynamic adjustment module is used to compare the mechanical pose data with the collaborative operation path to obtain the deviation value. When the deviation value exceeds the preset threshold, the construction schedule is dynamically adjusted. The construction schedule is used to update the enhanced BIM.

[0033] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-mentioned collaborative management and control method for power construction progress.

[0034] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned collaborative management and control method for power construction progress.

[0035] The aforementioned collaborative management method, system, equipment, and medium for power construction progress, by constructing an enhanced BIM containing electromagnetic field distribution data and gradient information, provides an environmental data foundation for construction in high-voltage energized areas. Based on electromagnetic field distribution data, it dynamically compensates for wireless positioning signals, generating mechanical pose data including machine coordinates and attitude angles to eliminate the impact of strong electromagnetic interference on positioning accuracy. Using gradient information, it generates global paths for multiple machines through path planning algorithms, with all global paths constituting a collaborative operation path. The global path includes path point coordinates and allowable deviation thresholds, ensuring the safety of machine operations in complex electromagnetic environments. By comparing the deviation values ​​between the machine pose data and the collaborative operation path in real time, it dynamically adjusts the construction schedule and updates the enhanced BIM, achieving closed-loop management of construction progress. This technical solution, through a collaborative mechanism of electromagnetic environment modeling, positioning error compensation, gradient-driven path planning, and dynamic progress adjustment, improves the accuracy of collaborative machine operations in strong interference environments, enhancing real-time management capabilities and operational safety during construction in high-voltage energized areas. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 A flowchart illustrating a collaborative management method for power construction progress provided by the present invention;

[0038] Figure 2 A schematic flowchart of a positioning compensation method provided by the present invention;

[0039] Figure 3 This is a schematic diagram of a collaborative management and control system for power construction progress provided by the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0041] First, a brief introduction to the terms used in the embodiments of this application will be given.

[0042] Building Information Modeling (BIM) is a digital management tool based on 3D digital technology that integrates multi-dimensional data throughout the entire lifecycle of an engineering project. By constructing virtual building models, it integrates geometric information, physical attributes, and spatial relationships to support collaborative operations and dynamic management across the design, construction, and operation and maintenance phases. In power construction scenarios, BIM models can link data such as electromagnetic environment, construction equipment, and schedule plans, providing a unified information carrier for visualized collaborative management under complex working conditions, enabling precise mapping and dynamic optimization of construction elements.

[0043] Path planning algorithms are intelligent decision-making methods that determine safe and efficient movement trajectories for mobile devices or machinery based on environmental perception and constraints. They calculate the optimal or feasible path sequence from the starting point to the target point by analyzing the spatial topology, obstacle distribution, and dynamic constraint parameters of the work scenario. In power construction scenarios, path planning algorithms can combine electromagnetic field distribution, equipment kinematic characteristics, and multi-machine collaborative rules to generate work paths that avoid high-field-strength areas and meet construction sequence requirements, ensuring the obstacle avoidance capability and collaborative efficiency of machinery movement in complex electromagnetic environments.

[0044] Rapidly-exploring Random Tree (RRT) is a path planning algorithm based on random sampling and tree-structure expansion, suitable for trajectory searching in high-dimensional spaces and complex constraints. Its core principle is to randomly generate target points in the configuration space and incrementally expand branches from tree nodes towards the target points, gradually building a tree-like topology covering feasible regions, ultimately generating a collision-free path connecting the starting point and the target point. This algorithm is probabilistically complete and can converge quickly under dynamic obstacles, unstructured environments, and multiple constraints. It is particularly suitable for complex path planning needs in power construction scenarios, such as multi-machine collaborative obstacle avoidance and avoidance of high-field-strength areas, balancing planning efficiency and path feasibility.

[0045] Based on the above definitions, the implementation environment of the power construction progress collaborative management method provided in this application embodiment will be described. Indicatively, the implementation environment includes: multimodal sensors, terminals, and processors. The processor, multimodal sensors, and terminals are connected via network signals. Multimodal sensors include, but are not limited to, electromagnetic field sensors, UWB positioning base stations, inertial measurement units (IMUs), environmental monitoring sensors, lidar, and optical cameras. The processor can be a central processing unit, a multi-core processor, or an artificial intelligence chip, etc., and is not limited here.

[0046] Based on the above definitions and implementation environment, the application scenarios of the embodiments of this application are described. The power construction progress collaborative management method provided in the embodiments of this application can be applied to scenarios including but not limited to the following:

[0047] In the construction of ultra-high voltage substations (500kV and above), multiple live-line working machines need to work together to complete equipment installation and maintenance in a strong electromagnetic field environment. This technology constructs an enhanced BIM model that includes electromagnetic field distribution characteristics, and combines it with dynamic positioning compensation technology to correct the machine posture data in real time, solving the trajectory deviation problem caused by power frequency electromagnetic interference to UWB positioning signals. At the same time, it generates multi-machine collaborative paths based on electric field gradient information, avoiding safety risks caused by path conflicts between hoisting robotic arms and welding robots, and ensuring construction accuracy and progress synchronization in complex electromagnetic environments.

[0048] Underground cable tunnel construction requires shield tunneling and pipeline laying within a confined space. Construction machinery is prone to positioning drift due to the combined effects of geological vibrations and electromagnetic interference. This technology integrates ground-penetrating radar data and an electromagnetic field distribution model to dynamically map the geological structure and electromagnetic environment within a BIM framework. This guides machinery path planning to avoid areas with high vibration and high field strength. Simultaneously, real-time pose deviations trigger local path replanning, ensuring the safe collaborative operation of the shield machine within a confined space and reducing construction interruptions caused by mechanical collisions or positioning errors.

[0049] In live-line maintenance scenarios for power transmission lines, drones and robotic arms need to perform insulator replacement or conductor repair work near high-voltage conductors. This technology integrates conductor potential distribution data through an enhanced BIM model to generate drone inspection paths that avoid arc discharge areas; the robotic arm's operating path dynamically adjusts the end effector's trajectory based on the electric field gradient, combined with real-time pose compensation technology, to ensure that the mechanical operating parts maintain a safe clearance from live conductors, reducing the risk of personnel exposure to strong electromagnetic radiation.

[0050] This is merely an illustrative example; the power construction progress collaborative management method provided in this application embodiment can also be applied to other application scenarios. It is only an example and does not limit the specific application scenarios.

[0051] In one exemplary embodiment, such as Figure 1 As shown, a method for collaborative management and control of power construction progress is provided. This embodiment illustrates the application of this method to a terminal in the aforementioned implementation environment. It is understood that this method can also be applied to a server, and further to a system including both a terminal and a server, and is implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps 101 to 104:

[0052] Step 101: Based on the electrical parameters and spatial layout data of the construction area, construct an enhanced BIM, which includes electromagnetic field distribution data and gradient information.

[0053] Specifically, an enhanced BIM model can be constructed using 3D modeling tools based on the electrical parameters and spatial layout data of the construction area. The electrical parameters, including voltage levels, conductor materials, and power frequency parameters, are obtained through on-site measurements or design drawings; the spatial layout data is generated through laser scanning or total station mapping. This data is then input into finite element analysis software to solve the electromagnetic field distribution equations, obtaining 3D spatial data of the electric and magnetic field strengths. Further, the spatial gradient information of the electric field strength is calculated, generating a gradient distribution matrix. For example, multiphysics coupling simulation technology can be used to dynamically correlate the conductor layout with the electromagnetic field distribution, achieving a high-precision mapping between the BIM model and the electromagnetic environment. The enhanced BIM generated in this step provides environmental data support for subsequent positioning compensation and path planning, guiding machinery to avoid high-field-strength areas and reducing the risk of electromagnetic interference.

[0054] Step 102: Based on the electromagnetic field distribution data, dynamically compensate the acquired wireless positioning signal to generate mechanical pose data, which includes mechanical coordinates and attitude angles.

[0055] Specifically, wireless positioning signals of construction machinery can be collected in real time using front-end positioning devices (such as UWB positioning base stations, satellite positioning terminals, or visual recognition cameras). Due to the multipath effect and attenuation interference of wireless signals in high-voltage construction environments, this method dynamically compensates the original positioning signal based on electromagnetic field distribution data in enhanced BIM. For example, when machinery enters a strong electromagnetic field area, the positioning algorithm parameters are adjusted in real time based on the pre-stored electromagnetic shielding coefficient and signal attenuation model of that area, generating machinery pose data containing precise machinery coordinates (X, Y, Z three-dimensional coordinates) and attitude angles (pitch angle, roll angle, yaw angle). For instance, for 500kV line erection operations, the compensated positioning signal can improve the machinery positioning accuracy to the centimeter level, ensuring the accuracy of the machinery's position information under strong electromagnetic interference.

[0056] Step 103: Based on gradient information, a global path for multiple machines is generated through a path planning algorithm. All global paths constitute a collaborative operation path. The global path includes the coordinates of path points and the allowable deviation thresholds corresponding to the path point coordinates.

[0057] For example, based on gradient information in enhanced BIM, improved path planning algorithms (such as ant colony optimization, genetic algorithms, or deep reinforcement learning algorithms) can be used to generate global paths for multiple construction machines. Specifically, the path planning algorithm uses gradient information as constraints, comprehensively considering factors such as electromagnetic field safety thresholds, machine operation sequence, and spatial collision avoidance requirements. The generated collaborative operation path includes the coordinate sequence of path points for each machine and the allowable deviation threshold for each path point (such as lateral deviation ±5cm, attitude angle deviation ±3 degrees). For instance, in the installation operation of the valve hall in a converter station, paths without electromagnetic interference conflicts can be planned separately for hoisting and transport machinery to ensure electromagnetic safety and spatial collision avoidance during multi-machine collaborative operation. Furthermore, a spatiotemporal corridor constraint method can be used to define a dynamic safety margin for each path point to ensure that the machines operate collaboratively within the allowable deviation range. The collaborative operation path generated in this step can effectively avoid electromagnetic interference hotspots and improve the safety of multi-machine collaboration.

[0058] Step 104: Compare the mechanical pose data with the collaborative operation path to obtain the deviation value. When the deviation value exceeds the preset threshold, dynamically adjust the construction schedule plan. The construction schedule plan is used to update the enhanced BIM.

[0059] Specifically, the system compares the machine's pose data with the collaborative work path in real time to calculate the deviation between the actual position and the planned path. When the deviation exceeds a preset threshold (e.g., three consecutive path points deviate beyond the allowable range), a dynamic adjustment mechanism is triggered. Specifically, the system intelligently adjusts subsequent work plans based on the type of deviation (positional or attitude deviation) and the construction stage (foundation construction, equipment installation, or cable laying). For example, during the GIS equipment installation stage, if the hoisting machinery's attitude angle deviation causes equipment docking failure, the system can automatically extend the time for that process, adjust the start time of the subsequent cable laying process, and feed the updated construction progress parameters back to the enhanced BIM model, achieving closed-loop linkage between the model and the actual progress.

[0060] The aforementioned collaborative management and control method for power construction progress provides an environmental data foundation for construction in high-voltage energized areas by constructing an enhanced BIM containing electromagnetic field distribution data and gradient information. Based on the electromagnetic field distribution data, it dynamically compensates for wireless positioning signals, generating mechanical pose data including machine coordinates and attitude angles to eliminate the impact of strong electromagnetic interference on positioning accuracy. Using gradient information, it generates global paths for multiple machines through path planning algorithms, forming a collaborative operation path. Each global path includes path point coordinates and allowable deviation thresholds, ensuring the safety of machinery operation in complex electromagnetic environments. By comparing the deviation values ​​between the machine pose data and the collaborative operation path in real time, it dynamically adjusts the construction schedule and updates the enhanced BIM, achieving closed-loop management and control of construction progress. This technical solution, through a collaborative mechanism of electromagnetic environment modeling, positioning error compensation, gradient-driven path planning, and dynamic progress adjustment, improves the accuracy of collaborative mechanical operations in strong interference environments, enhancing real-time management and control capabilities and operational safety in high-voltage energized areas.

[0061] like Figure 2 As shown, in one embodiment, based on electromagnetic field distribution data, the acquired wireless positioning signal is dynamically compensated to generate mechanical pose data, including:

[0062] Step 201: Extract electric field strength data and magnetic field strength data along the propagation path of the wireless positioning signal from the electromagnetic field distribution data.

[0063] Specifically, the propagation path of the wireless signal in the construction area can be determined using a path tracing algorithm. Electric and magnetic field strength values ​​are sampled along the path to generate an electromagnetic field strength sequence. For example, the signal propagation path is simulated using ray casting, combined with finite element mesh interpolation technology to obtain field strength data at discrete points along the path. Furthermore, attenuation compensation is applied to the field strength of interference sources outside the path to avoid the indirect impact of far-field electromagnetic noise on the positioning signal. This step provides high-precision electromagnetic environment characteristic parameters for subsequent dynamic compensation, unlike the static compensation strategy in traditional methods that ignores differences in the spatial distribution of the electromagnetic field.

[0064] Step 202: Based on the path integral of the electric field strength data and the curl modulus of the magnetic field strength data, construct the channel distortion factor, which is used to characterize the degree of influence of electromagnetic interference on the positioning signal.

[0065] Specifically, the electric field strength can be linearly integrated along the signal propagation path to calculate the cumulative electric field interference; simultaneously, the magnitude of the curl of the magnetic field strength can be calculated to characterize the degree of disturbance of the signal phase caused by changes in the magnetic field. For example, these two types of parameters can be fused as follows: the path integral result and the curl magnitude are linearly weighted to generate a dynamically changing channel distortion factor. Furthermore, a nonlinear function (such as an exponential decay model) is introduced to optimize the weighting coefficients, causing the distortion factor to exhibit nonlinear growth characteristics in the high field strength region. This step, through multi-physics coupling modeling, accurately quantifies the combined distortion effect of electromagnetic interference on the positioning signal, overcoming the limitations of conventional techniques that rely solely on a single field strength parameter.

[0066] Step 203: Based on the adaptive filter constructed based on the channel distortion factor, the wireless positioning signal is filtered and compensated to generate mechanical pose data.

[0067] Specifically, the channel distortion factor is used as a time-varying parameter input to the filter, and the filter gain is adjusted to suppress positioning errors introduced by electromagnetic interference. For example, an extended Kalman filter is used to dynamically update the process noise covariance matrix with the distortion factor, achieving iterative correction of the positioning error. Furthermore, attitude angle data from the inertial measurement unit (IMU) can be combined, and the compensated coordinate data can be calibrated using a sensor fusion algorithm to output pose information containing mechanical three-dimensional coordinates and attitude angles. For example, quaternion interpolation can be used to eliminate the timing deviation between coordinate compensation and attitude angle measurement. This step, through a dynamically parameter-driven filtering mechanism, can improve positioning accuracy in environments with strong interference and enhance robustness under complex operating conditions.

[0068] In one embodiment, based on gradient information, a path planning algorithm generates global paths for multiple machines. All global paths constitute a collaborative operation path. The path planning algorithm is a fast expanding random tree, comprising:

[0069] The path planning weight coefficients are calculated based on gradient information, where the path planning weight coefficients are inversely proportional to the magnitude of the gradient information.

[0070] Specifically, electric field gradient magnitude data is extracted, and weight coefficients inversely proportional to the gradient magnitude are generated through normalization. For example, an inverse proportional function or an exponential decay function is used to map the gradient magnitude to weight values, making the weight coefficients for high gradient regions (strong electric field regions) approach zero, and the weight coefficients for low gradient regions approach one. Furthermore, a nonlinear piecewise function is introduced to optimize weight allocation, enhancing obstacle avoidance priority in regions with abrupt gradient changes. By fusing electromagnetic environment data with gradient weight coefficients, deep coupling between path planning and electromagnetic interference avoidance is achieved, addressing the technical blind spot of neglecting electromagnetic field distribution in traditional methods.

[0071] In the node expansion phase of the rapidly expanding random tree, the path planning weight coefficients are embedded into the cost function to generate a node expansion priority queue.

[0072] Specifically, the node expansion cost is defined as the product of the path length and the weight coefficient, generating a node expansion priority queue. For example, during random sampling, candidate nodes in low-gradient regions are prioritized for expansion, while a probability sampling mechanism balances search efficiency and obstacle avoidance requirements. Furthermore, the node expansion vector is optimized by incorporating the gradient direction, naturally deviating the path from high-field-strength regions. This step, through a dynamic priority adjustment mechanism, significantly improves path search efficiency and avoids ineffective exploration in high-gradient regions by traditional RRT algorithms.

[0073] Path search is performed based on the node expansion priority queue to generate a set of conflict-free paths that avoid regions with high electric field strength.

[0074] Specifically, a multi-tree parallel search strategy can be employed to independently construct the Remote Timing Response (RRT) for each machine and detect spatiotemporal conflicts between paths. For example, a safe zone for machine movement can be defined using the spatiotemporal corridor constraint method, and synchronous waiting nodes can be inserted into the path point sequence to eliminate conflicts. Furthermore, a conflict backtracking mechanism can be introduced, where weight coefficients are reallocated and paths are locally reconstructed when path intersections are detected. The set of conflict-free paths is spatially bound to the equipment installation locations in the enhanced BIM to generate global paths.

[0075] Specifically, a spatial registration algorithm aligns the coordinates of path points with the equipment coordinates in the BIM model, generating the final sequence of path points for the global path. For example, the Iterative Closest Point (ICP) algorithm can be used to correct coordinate deviations between path points and equipment installation locations, ensuring precise matching between mechanical movement trajectories and construction tasks. Furthermore, each path point is associated with a construction process number, achieving a logical binding between the path and the schedule. This embodiment, by deeply integrating gradient information with a fast expanding random tree algorithm, achieves intelligent planning of multi-machine collaborative operation paths, ensuring a high degree of matching between path planning results and the actual construction scenario, providing accurate path basis for construction progress control.

[0076] In one embodiment, the machine pose data is compared with the collaborative operation path to obtain a deviation value. When the deviation value exceeds a preset threshold, the construction schedule is dynamically adjusted, including:

[0077] Extract the path target point with the corresponding timestamp from the global path based on the machine coordinates.

[0078] Specifically, based on the time nodes in the construction schedule, the timestamp of the machine's current position is matched with the time sequence marker of the global path to determine the target path point for the current construction stage. For example, a dynamic time warping algorithm can be used to align the machine's motion trajectory with the path's time sequence, eliminating time sequence offsets caused by machine acceleration or deceleration. Furthermore, a sliding window mechanism can be introduced to update the target point sequence of multiple future timestamps in real time, enhancing the forward-looking nature of path tracking.

[0079] The machine coordinates are spatially aligned with the path target points, and the Euclidean distance deviation between the machine coordinates and the path target points is calculated. Specifically, the spatial alignment involves transforming the coordinate system to the global coordinate system of the enhanced BIM.

[0080] Specifically, a coordinate transformation matrix can be used to convert the coordinates in the machine's local coordinate system to the global coordinate system of the enhanced BIM, eliminating positioning errors caused by coordinate system differences. For example, a feature point registration algorithm can be used to extract marker points of the equipment installation location in the BIM model and match them with feature points collected by the machine's sensors, achieving millimeter-level spatial alignment accuracy. Furthermore, Kalman filtering is introduced to dynamically calibrate the coordinate transformation parameters, suppressing coordinate jitter caused by construction vibrations. The Euclidean distance deviation output in this step reflects the real-time deviation between the machine's actual pose and the planned path, providing a quantitative basis for dynamic adjustments.

[0081] When the Euclidean distance deviation exceeds the allowable deviation threshold, a local path replanning is performed using a path planning algorithm to generate a new path point sequence.

[0082] Specifically, when the Euclidean distance deviation exceeds the allowable deviation threshold corresponding to a path point, a local path replanning is performed using a path planning algorithm to generate a new path point sequence. For example, during the erection of ultra-high voltage power lines, if the traction machinery deviates from the original path and enters an area with excessive electromagnetic field strength, the system triggers local replanning. An improved A* algorithm or artificial potential field algorithm can be used, combined with the current machinery position, surrounding electromagnetic environment, and obstacle information, to quickly generate a new path point sequence that bypasses the dangerous area, ensuring the machinery continues to move safely towards the target location.

[0083] The duration of affected processes is adjusted based on the new path point sequence, and the critical path duration is recalculated using the forward-backward method. The critical path duration is used to generate a dynamically adjusted construction schedule.

[0084] Specifically, the logical relationship network diagram of each process in the enhanced BIM can be extracted to identify process nodes that are delayed due to path adjustments. For example, a resource-constrained schedule model is used to dynamically allocate mechanical resources and compress the float time of non-critical path processes. Furthermore, Monte Carlo simulation is used to predict the range of schedule fluctuations and optimize the buffer time setting of the critical path. The dynamically adjusted construction schedule output from this step is synchronously updated to the enhanced BIM model, achieving closed-loop coordination between construction schedule and mechanical path, avoiding schedule delays caused by rigid schedules in traditional methods.

[0085] Furthermore, when the Euclidean distance deviation exceeds the allowable deviation threshold, a local path replanning is performed using a path planning algorithm to generate a new sequence of path points, including:

[0086] Based on Euclidean distance deviation and gradient information, the search radius of local path replanning is calculated, generating a spherical search region centered on the machine coordinates. The radius of the spherical search region is inversely proportional to the gradient magnitude and directly proportional to the Euclidean distance deviation.

[0087] Specifically, the Euclidean distance deviation can be used as a baseline parameter, and the gradient magnitude as a constraint parameter. An initial value for the search radius is determined using an inverse proportional function. For example, a nonlinear piecewise function is employed to optimize the radius calculation logic, expanding the search range in low-gradient regions to improve planning efficiency and reducing the radius in high-gradient regions to avoid strong electric field interference. Furthermore, a dynamic attenuation factor can be introduced to adaptively adjust the search radius as the deviation value continues to exceed the limit for an extended period. The spherical search region generated in this step balances planning efficiency with electromagnetic safety requirements, resolving the conflict between real-time performance and safety in path replanning under complex electromagnetic environments.

[0088] Within the spherical search region, the node expansion direction weights are calculated based on gradient information to generate a candidate node sequence.

[0089] Specifically, the magnitude of the electric field gradient at each location within the search area is extracted, and weight coefficients are generated through normalization. These weight coefficients are inversely proportional to the gradient magnitude. For example, a probabilistic sampling mechanism is used to prioritize candidate nodes in low-gradient regions for expansion, and a gradient direction bias angle is introduced into the node expansion vector to guide the path naturally away from high-field regions. Furthermore, a dynamic weight adjustment strategy is employed to increase the weight coefficient threshold when the path detours, balancing the relationship between path length and safety.

[0090] The candidate node sequence is smoothed and then connected with the unaffected path segments in the global path by tangent lines to obtain a new path point sequence.

[0091] Specifically, B-spline curves can be used to fit discrete candidate nodes to generate new path segments with continuous curvature. For example, a tangent continuity constraint algorithm can be used to ensure that the first derivative of the new path segment is continuous with the original global path at the connection point, avoiding abrupt changes in the direction of mechanical motion. Furthermore, a dynamic buffering mechanism can be introduced to insert transition path points before and after the connection point, eliminating minor deviations caused by coordinate system transformation.

[0092] In summary, the power construction progress collaborative management method provided in this application provides environmental data support for construction in high-voltage energized areas by constructing an enhanced BIM model that integrates electromagnetic field distribution data and gradient information; dynamically compensates wireless positioning signals based on electromagnetic field distribution data to generate high-precision mechanical pose data, eliminating positioning errors caused by strong electromagnetic interference; improves the path planning algorithm by combining gradient information to generate multi-machine collaborative operation paths, avoiding high field strength areas and setting allowable deviation thresholds to ensure the safety and collaborative efficiency of mechanical movement; and triggers a local path replanning and dynamic adjustment mechanism for construction progress by comparing the deviation values ​​between mechanical pose and planned path in real time, feeding back the updated path and schedule plan to the enhanced BIM model to achieve real-time collaborative optimization of construction progress and mechanical pose. This technical solution enables precise collaborative operation of construction machinery in strong interference environments, improves the timeliness of management and control of construction in high-voltage energized areas through real-time path optimization and progress linkage updates, and significantly reduces the risk of machinery accidentally entering high-risk areas by relying on electromagnetic safety path planning and a visual early warning mechanism, comprehensively ensuring construction safety and operational efficiency in complex electromagnetic environments.

[0093] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0094] Based on the same inventive concept, this application also provides a power construction progress collaborative management and control system 10 for implementing the power construction progress collaborative management and control method described above. The solution provided by this system is similar to the solution described in the above method; therefore, the specific limitations of one or more embodiments of the power construction progress collaborative management and control system 10 provided below can be found in the limitations of the power construction progress collaborative management and control method described above, and will not be repeated here.

[0095] In one exemplary embodiment, such as Figure 3 As shown, a collaborative management and control system 10 for power construction progress is provided, including:

[0096] BIM modeling module 11 is used to build an enhanced BIM based on the electrical parameters and spatial layout data of the construction area. The enhanced BIM includes electromagnetic field distribution data and gradient information.

[0097] The positioning compensation module 12 is used to dynamically compensate the acquired wireless positioning signal based on the electromagnetic field distribution data to generate mechanical pose data, wherein the mechanical pose data includes mechanical coordinates and attitude angles.

[0098] The collaborative management module 13 is used to generate a global path for multiple machines based on gradient information and a path planning algorithm. All global paths constitute a collaborative operation path. The global path includes the coordinates of the path points and the allowable deviation thresholds corresponding to the path point coordinates.

[0099] The dynamic adjustment module 14 is used to compare the mechanical pose data with the collaborative operation path to obtain the deviation value. When the deviation value exceeds the preset threshold, the construction schedule is dynamically adjusted. The construction schedule is used to update the enhanced BIM.

[0100] In one embodiment, the positioning compensation module 12 includes:

[0101] The electromagnetic field data extraction unit is used to extract electric field strength data and magnetic field strength data along the propagation path of wireless positioning signals from electromagnetic field distribution data.

[0102] The distortion factor construction unit is used to construct the channel distortion factor based on the path integral of the electric field strength data and the curl modulus of the magnetic field strength data. The channel distortion factor is used to characterize the degree of influence of electromagnetic interference on the positioning signal.

[0103] The filtering and compensation unit is used to filter and compensate the wireless positioning signal according to the adaptive filter constructed based on the channel distortion factor, and generate mechanical pose data.

[0104] In one embodiment, the path planning algorithm in the collaborative management module 13 employs a fast expanding random tree, specifically including:

[0105] The weight calculation unit is used to calculate the path planning weight coefficients based on gradient information, where the path planning weight coefficients are inversely proportional to the magnitude of the gradient information.

[0106] The node expansion unit is used to embed path planning weight coefficients into the cost function during the node expansion phase of the fast-expanding random tree, and to generate a node expansion priority queue.

[0107] The path search unit is used to perform path search based on the node expansion priority queue to generate a set of conflict-free paths that avoid regions with high electric field strength.

[0108] The path binding unit is used to spatially bind a set of conflict-free paths to the equipment installation locations in the enhanced BIM, generating a global path.

[0109] In one embodiment, the dynamic adjustment module 14 includes:

[0110] The target point extraction unit is used to extract the path target points with the corresponding timestamps in the global path based on the machine coordinates.

[0111] The deviation calculation unit is used to spatially align the machine coordinates with the path target point and calculate the Euclidean distance deviation between the machine coordinates and the path target point. Specifically, spatial alignment involves transforming the coordinate system to the global coordinate system of the enhanced BIM.

[0112] The local replanning unit is used to perform local path replanning through a path planning algorithm to generate a new path point sequence when the Euclidean distance deviation exceeds the allowable deviation threshold.

[0113] The schedule update unit is used to adjust the duration of affected processes based on the new path point sequence and recalculate the critical path duration using the forward-backward method. The critical path duration is used to generate a dynamically adjusted construction schedule.

[0114] Furthermore, the local replanning unit includes:

[0115] The search region generation unit is used to calculate the search radius of local path replanning based on Euclidean distance deviation and gradient information, and generate a spherical search region centered on the machine coordinates. The radius of the spherical search region is inversely proportional to the gradient magnitude and directly proportional to the Euclidean distance deviation.

[0116] The node expansion unit is used to calculate the node expansion direction weights based on gradient information within a spherical search region, and generate a sequence of candidate nodes.

[0117] The path connection unit is used to smooth the candidate node sequence and connect it with the unaffected path segments in the global path to obtain a new path point sequence.

[0118] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the power construction progress collaborative management method as described above.

[0119] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0120] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The components described as separate parts may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this disclosure according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0121] The above-described embodiments are merely illustrative of several implementation methods of the embodiments of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the embodiments of this application, and these modifications and improvements all fall within the protection scope of the embodiments of this application.

Claims

1. A power construction progress collaborative management method, characterized in that, The method comprises: Based on the electrical parameters and spatial layout data of the construction area, an enhanced BIM is constructed, which includes electromagnetic field distribution data and gradient information; According to the electromagnetic field distribution data, the obtained wireless positioning signal is dynamically compensated to generate mechanical pose data, wherein the mechanical pose data includes mechanical coordinates and attitude angles; Based on the gradient information, a global path of multiple machines is generated through a path planning algorithm, and all the global paths constitute a collaborative work path, which includes path point coordinates and corresponding allowed deviation thresholds; The mechanical pose data and the collaborative work path are compared to obtain a deviation value, and when the deviation value exceeds a preset threshold, the construction progress plan is dynamically adjusted, wherein the construction progress plan is used to update the enhanced BIM; Wherein, according to the electromagnetic field distribution data, the obtained wireless positioning signal is dynamically compensated to generate mechanical pose data, including: Extract the electric field intensity data and magnetic field intensity data on the propagation path of the wireless positioning signal from the electromagnetic field distribution data; Based on the path integral of the electric field intensity data and the length of the curl of the magnetic field intensity data, a channel distortion factor is constructed, which is used to represent the influence degree of electromagnetic interference on the positioning signal; According to the adaptive filter constructed based on the channel distortion factor, the wireless positioning signal is filtered and compensated to generate the mechanical pose data; The path planning algorithm is a rapidly expanding random tree, including: Based on the gradient information, the path planning weight coefficient is calculated, wherein the path planning weight coefficient is inversely proportional to the length of the gradient information; In the node expansion stage of the rapidly expanding random tree, the path planning weight coefficient is embedded into the cost function to generate a node expansion priority queue; According to the node expansion priority queue, the path search is performed to generate a conflict-free path set that avoids high electric field intensity areas; The conflict-free path set is spatially bound with the equipment installation position in the enhanced BIM to generate the global path.

2. The method of claim 1, wherein, The mechanical pose data and the collaborative work path are compared to obtain a deviation value, and when the deviation value exceeds a preset threshold, the construction progress plan is dynamically adjusted, including: According to the mechanical coordinates, the path target point corresponding to the time stamp in the global path is extracted; The mechanical coordinates and the path target point are spatially aligned, and the Euclidean distance deviation between the mechanical coordinates and the path target point is calculated, wherein the spatial alignment specifically converts the coordinate system to the global coordinate system of the enhanced BIM; When the Euclidean distance deviation exceeds the allowed deviation threshold, local path re-planning is performed through a path planning algorithm to generate a new path point sequence; Adjust the duration of the affected process according to the new path point sequence, and recalculate the critical path duration by the forward-backward method, the critical path duration is used to generate a dynamically adjusted construction schedule.

3. The method of claim 2, wherein, When the Euclidean distance deviation value exceeds the allowed deviation threshold, a local path re-planning is performed by a path planning algorithm to generate a new path point sequence, including: Based on the Euclidean distance deviation and the gradient information, a search radius of the local path re-planning is calculated to generate a spherical search area centered on the mechanical coordinates, wherein the radius of the spherical search area is inversely proportional to the gradient modulus and proportional to the Euclidean distance deviation; Within the spherical search area, a node expansion direction weight is calculated based on the gradient information to generate a candidate node sequence; The candidate node sequence is smoothed and connected to the unaffected path segment in the global path by a tangent line to obtain the new path point sequence.

4. A power construction progress collaborative management and control system, characterized in that, The system comprises: A BIM modeling module for constructing an enhanced BIM based on electrical parameters and spatial layout data of a construction area, the enhanced BIM including electromagnetic field distribution data and gradient information; A positioning compensation module for dynamically compensating the obtained wireless positioning signal according to the electromagnetic field distribution data to generate mechanical pose data, wherein the mechanical pose data includes mechanical coordinates and attitude angles; A collaborative management module for generating global paths of multiple machines based on the gradient information by a path planning algorithm, all the global paths forming a collaborative work path, the global path including path point coordinates and an allowed deviation threshold corresponding to the path point coordinates; A dynamic adjustment module for comparing the mechanical pose data with the collaborative work path to obtain a deviation value, and dynamically adjusting a construction schedule when the deviation value exceeds a preset threshold, wherein the construction schedule is used to update the enhanced BIM; The positioning compensation module comprises: An electromagnetic field data extraction unit for extracting electric field intensity data and magnetic field intensity data on the wireless positioning signal propagation path from the electromagnetic field distribution data; A distortion factor construction unit for constructing a channel distortion factor based on path integration of the electric field intensity data and modulus length of the curl of the magnetic field intensity data, wherein the channel distortion factor is used to represent the influence degree of electromagnetic interference on the positioning signal; A filter compensation unit for filtering and compensating the wireless positioning signal based on an adaptive filter constructed based on the channel distortion factor to generate the mechanical pose data; The path planning algorithm in the collaborative management module uses a rapid expansion random tree, including: A weight calculation unit for calculating a path planning weight coefficient based on the gradient information, wherein the path planning weight coefficient is inversely proportional to the modulus length of the gradient information; A node expansion unit for embedding the path planning weight coefficient into a cost function in the node expansion stage of the rapid expansion random tree to generate a node expansion priority queue; a path searching unit configured to perform path searching according to the node expansion priority queue to generate a conflict-free path set that avoids a high electric field intensity area; a path binding unit configured to spatially bind the conflict-free path set with a device installation position in the enhanced BIM to generate the global path. 5.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-4 when the computer program is executed by the processor. The processor implements the method in any one of claims 1 to 3 when executing the computer program.

6. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, implements the method in any one of claims 1 to 3.

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