Power transmission mechanized construction simulation analysis method based on GIM and related products

Abstract

The invention relates to the technical field of power system construction and mechanical construction, in particular to a GIM-based power transmission mechanical construction simulation analysis method and related products, and the method comprises the steps: collecting GIM model data, satellite image data and laser radar data of a construction area; collecting equipment parameter data of the construction engineering mechanical equipment; combining the GIM model data, the satellite image data and the laser radar data to construct a construction site model; constructing a mechanical equipment model according to the equipment parameter data; determining path planning and equipment scheduling through the construction site model and the mechanical equipment model, and loading the path planning and the equipment scheduling to the simulation platform to simulate the construction process; through the three-dimensional visualization and simulation analysis of the construction site, the construction management personnel can intuitively know the construction progress and potential risks and make an adjustment decision in time. Meanwhile, manual intervention is reduced through automatic data analysis and optimization suggestions, and the accuracy and reliability of analysis are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system construction and mechanized construction, and in particular to a GIM-based power transmission mechanized construction simulation analysis method and related products. Background Art

[0002] With the continuous development of the power system, the scale and complexity of transmission line construction are gradually increasing. Traditional construction methods mainly rely on manual judgment and on-site experience, which has limitations in dealing with complex terrain, optimizing construction resources and ensuring construction safety. Especially in the face of changing natural environments and different construction requirements, manual judgment is often difficult to conduct comprehensive and accurate analysis.

[0003] Mechanized construction is gaining more and more attention as a means to effectively improve construction efficiency and safety. However, the existing mechanized construction methods still lack systematic analysis and simulation tools for the construction process during implementation. Traditional construction preparation and planning rely on experience and often cannot effectively cope with complex construction environments, leading to unexpected situations during the construction process, affecting project progress and safety.

[0004] At present, the analysis of the construction process in the industry mainly relies on empirical rules and simple planning tools, which makes it particularly difficult to dynamically manage and optimize the construction process. In particular, there is a lack of efficient and automated solutions in the integration and processing of multi-source data. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a GIM-based power transmission mechanization construction simulation analysis method and related products, which realizes refined modeling, dynamic simulation and automated analysis of the construction site.

[0006] The present invention is achieved through the following technical solutions:

[0007] A three-dimensional power transmission mechanization construction simulation analysis method based on GIM model data, comprising:

[0008] Collect GIM model data, satellite image data, and LiDAR data of the construction area; collect equipment parameter data of construction engineering machinery and equipment;

[0009] Combine GIM model data, satellite image data and lidar data to build a construction site model;

[0010] Build mechanical equipment models based on equipment parameter data;

[0011] The path planning and equipment scheduling are determined through the construction site model and mechanical equipment model, and loaded into the simulation platform to simulate the construction process.

[0012] Specifically, the tower information of the transmission circuit is obtained from the GIM model data, and the tower information includes: three-dimensional coordinates and structural information of the tower;

[0013] Obtain topographic information of the construction area from satellite image data and LiDAR data, including digital elevation model and digital orthophoto;

[0014] The environmental parameter information of the construction area is obtained through GIS integration, including vegetation, buildings and other land features;

[0015] The tower information, topographic information and environmental parameter information are converted into the global geodetic coordinate system, and the data are fused to obtain a fused data set.

[0016] Abnormal data points are detected through density-based clustering algorithm, and the abnormal data points are removed from the fused data set to obtain the cleaned data set.

[0017] Use cokriging to interpolate missing data points in clean datasets for multi-source datasets

[0018] Wavelet transform is performed on multi-source data sets, and features at different scales are obtained to construct a multi-source data feature set.

[0019] Specifically, the method of constructing the construction site model includes:

[0020] A set of ground points is extracted from the lidar data using a random sampling consensus algorithm;

[0021] Construct a triangular irregular network on the ground point set, and use the Laplace equation to smooth the terrain of the triangular irregular network;

[0022] Solving partial differential equations using boundary conditions and the finite element method Obtain a smooth terrain model, where H(x, y) is the terrain elevation function, is the Laplace operator, ρ(x, y) is the source function representing the density of terrain elevation change;

[0023] Perform image segmentation on satellite image data, extract environmental parameter information, and obtain classification results; model vegetation, buildings, and other landforms separately and fuse them with the terrain model to obtain a rough construction site model;

[0024] The rough model is enhanced with multi-scale details using three-dimensional wavelet transform to obtain the final construction site model M(x, y, z). Among them, W l(x, y, z) is the wavelet coefficient of the lth scale, Ψ l (x, y, z) is the corresponding wavelet basis function, and L is the number of layers of wavelet decomposition.

[0025] Specifically, other landforms include: water systems, roads, and bridges; the modeling methods include:

[0026] Using shape from outline reconstruction algorithm on the extracted building area, and constructing building model according to the building outline and height information;

[0027] The fractal set algorithm is used to simulate the three-dimensional structure of vegetation, and the vegetation morphology is generated through an iterative function system to construct a plant model;

[0028] Determine the outline of low-lying areas or water basins from the digital elevation model, use the water body outline to curve the water surface shape, and build a water body model;

[0029] Obtaining the binary path information of the road from the image segmentation, performing curve fitting on the extracted binary path information, mapping the road path to the terrain model according to the digital elevation model, and constructing the road model;

[0030] The bridge outline is extracted from the image segmentation, and the shape from outline reconstruction algorithm is used to build the bridge model based on the bridge contour line, design height and span.

[0031] Specifically, the methods for modeling mechanical equipment include:

[0032] The collected construction machinery and equipment form an equipment set EQ = {EQ 1 , EQ 2 , ..., EQ N}, where N is the number of construction engineering machinery and equipment; and obtain the i-th equipment E i Equipment parameter data: length L i , Width W i , height H i 、Mass m i , inertia tensor I i 、Engine power P i , maximum torque τ max，i , maximum speed v max，i , minimum turning radius R min，i ;

[0033] Use CAD software and according to the length L i , Width W i and height H i Create the EQ of the i-th device i 3D models of construction machinery and equipment;

[0034] Combine kinematic equations and dynamic equations to create a dynamic model of construction engineering machinery and equipment;

[0035] Use engine power to establish the EQ of the i-th device i Energy efficiency model.

[0036] Optionally, the kinematic equations of the construction machinery are determined by the Denavit-Hartenberg parameter method to determine the transformation matrix T of each j joint. j , Among them, θ j is the rotation angle of the joint, d j is the position of the joint along the axis, a j is the displacement between joints, α j is the rotation angle of the joint;

[0037] Use the joint posture transformation matrix to determine the angular velocity of each joint and angular acceleration

[0038] Use the Newton-Euler equation to determine the dynamic equation of construction engineering machinery and equipment and determine the linear acceleration a of the equipment i and the moment M of the equipment i , Among them, F i is the resultant force acting on the equipment, ω i is the angular velocity of the device, I i is the inertia tensor of the device;

[0039] Methods that combine the equations of kinematics and dynamics include:

[0040] The angular velocity and acceleration of each joint are used as inputs of the Newton-Euler equation, and the force and torque of each joint are calculated by the Newton-Euler equation. The force and torque are calculated step by step from the base to the end through the recursive formula in the Newton-Euler method;

[0041] Determine the final kinetic model Where q is the displacement of the joint, is the acceleration of the joint, M(q) is the inertia matrix, is the Coriolis force and centrifugal force matrix, G(q) is the gravity term, and τ is the driving torque of the joint.

[0042] Specifically, the method for determining equipment scheduling and path planning includes:

[0043] Define a set of construction tasks Where M is the total number of construction tasks; where construction tasks τ i Includes: Task Type Mission Location Required Equipment EQ j ;

[0044] Establish dependencies between tasks to form a directed acyclic graph The edge set ε is the order of tasks;

[0045] The construction site model is converted into an environmental map required for path planning, including obstacle information and drivable areas, to minimize the total construction time T total and total energy consumption E total As the goal, establish an optimization model for equipment scheduling and path planning, and obtain the optimal equipment scheduling and path planning;

[0046] Load the construction site model and mechanical equipment model into the simulation platform, and load the equipment scheduling and path planning into the simulation platform;

[0047] Dynamic simulation is performed through the simulation platform.

[0048] Specifically, the method for performing dynamic simulation includes:

[0049] Divide the construction process into discrete time steps Δt and determine the total number of simulation steps

[0050] The dynamic model is used to calculate each time step t k The displacement q of the lower device j (t k ) and speed

[0051] The calculated speed and acceleration Update the device's location,

[0052] When the device EQ j After arriving at the task location, the task begins to be executed, and the task τ is updated in real time according to the execution efficiency of the equipment i degree of completion;

[0053] At each time step t k , collision detection is performed through bounding box or directed bounding box algorithm; if collision risk is detected, the speed obstacle avoidance method is used to replan the local path;

[0054] Using the energy efficiency model of the device, calculate the energy efficiency of the device at time step t k Energy consumption E j (t k ), accumulate the energy consumption of all equipment and obtain the total energy consumption of the construction process

[0055] Optionally, the method of establishing an optimization model for equipment scheduling and path planning and performing target optimization includes:

[0056] Establishing the objective function Where x = [x ij ] is the equipment scheduling matrix, x ij =1 means device EQ j Execute task τ i , γ={γ j (t)} is the device EQ j , α and β are weight coefficients for balancing construction time and construction energy consumption;

[0057] Determine the constraints and task allocation constraints: Device Capability Constraintsx ij ≤c ij , c ij =1 means device EQ j Can perform tasks i , c ij =0 means device EQ j Unable to perform taskτ i ; Task dependency constraints τ k is τ i The prerequisite task is is the start time of the task, is the completion time of the task; path feasibility constraint: F safe It is the safe area in the construction site model; equipment dynamics constraints: f j EQ for your device j The dynamic equations of

[0058] Encode the device scheduling matrix as part of the chromosome and encode the device path γ j (t) discretized into control points and encoded as another part of the chromosome; construct the genetic algorithm fitness function in, is the penalty term for violating the constraint, λ 1 , 2 and λ 3 is the weight coefficient of different constraints;

[0059] The chromosomes are processed by inheritance, crossover and mutation, and after multiple iterations, the individual with the highest fitness is selected as the optimal solution to obtain the optimal equipment scheduling and path planning.

[0060] A computer program product comprises a computer program / instruction, wherein when the computer program / instruction is executed by a processor, the method described in any one of the above items is implemented.

[0061] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0062] The method provided by the present invention first collects GIM model data, satellite image data and lidar data of the construction area to build a comprehensive model of the construction site; secondly, a mechanical equipment model is built according to the equipment parameter data, and the optimization analysis of path planning and equipment scheduling is performed through a simulation platform.

[0063] Through the three-dimensional visualization and simulation analysis of the construction site, the present invention enables construction managers to intuitively understand the construction progress and potential risks and make timely adjustment decisions. At the same time, automated data analysis and optimization suggestions reduce manual intervention and improve the accuracy and reliability of analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings illustrate exemplary embodiments of the present invention and, together with the description thereof, are used to explain the principles of the present invention. These drawings are included to provide a further understanding of the present invention, and the accompanying drawings are included in and constitute a part of this specification and do not constitute a limitation of the embodiments of the present invention.

[0065] Figure 1 It is a flow chart of the GIM-based power transmission mechanization construction simulation analysis method according to the present invention.

[0066] Figure 2 It is a schematic flow chart of the method for the construction site model according to the present invention.

[0067] Figure 3 It is a flowchart of the method for determining device scheduling and path planning according to the present invention. DETAILED DESCRIPTION

[0068] To make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and implementation methods. It is understood that the specific implementation methods described herein are only used to explain the relevant content, rather than to limit the present invention.

[0069] It should also be noted that, for the convenience of description, only the parts related to the present invention are shown in the drawings.

[0070] In the absence of conflict, the embodiments and features of the embodiments of the present invention may be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0071] The full name of the GIM model is Grid Information Model, which is a special term in the power industry and refers to a technical standard developed by State Grid Corporation of China to meet the needs of three-dimensional design of power transmission and transformation projects. In 2017, State Grid began to prepare for the formulation; in 2018, State Grid Economic Research Institute independently developed a scalable State Grid GIM standard system suitable for power transmission and transformation project construction by formulating a unified data architecture, coding system, interaction method, design depth and results form; in 2019, State Grid issued 7 technical standards such as model interaction specifications, which together with the "Technical Guidelines for Three-Dimensional Design of Power Transmission and Transformation Projects Part 1: Substation (Converter Station)" issued in 2018 formed the three-dimensional design technical standards of State Grid.

[0072] Embodiment 1

[0073] like Figure 1 As shown, a three-dimensional power transmission mechanization construction simulation analysis method based on GIM model data is provided, including:

[0074] GIM model data, satellite image data, and lidar data are collected for the construction area; the GIM model contains data on various power equipment. Satellite image data is images taken from satellites that can reflect the surface features of a wide area and help understand the environmental conditions of the construction area. Lidar data contains three-dimensional spatial information obtained using laser ranging technology, which can accurately depict the height and shape of terrain and objects.

[0075] Collect equipment parameter data of construction engineering machinery and equipment; equipment parameter data includes the physical characteristics of the machinery and equipment, such as size, weight, power, maximum torque, etc.

[0076] The GIM model data, satellite image data and LiDAR data are combined to build a construction site model; through data fusion technology, the above three types of data are integrated to build a comprehensive construction site model. The model not only includes terrain features, but also covers the surrounding environment and landforms to ensure a true reflection of the actual situation during the construction process.

[0077] Build mechanical equipment models based on equipment parameter data; use computer-aided design (CAD) software to build 3D models of various types of construction machinery based on previously collected equipment parameters. Simulate the shape and motion characteristics of the equipment, providing a basis for path planning and scheduling.

[0078] Path planning and equipment scheduling are determined through the construction site model and mechanical equipment model, and loaded into the simulation platform to simulate the construction process. Path planning refers to the formulation of the optimal driving path for mechanical equipment based on terrain and obstacle information in the construction site model. Equipment scheduling is the arrangement and time planning of different equipment in construction tasks. After completing path planning and scheduling, this information is input into the simulation platform for dynamic simulation of the construction process to evaluate key indicators such as construction efficiency, safety, and resource utilization.

[0079] This embodiment integrates data from different sources to form a comprehensive view of the construction environment, and then combines the mechanical equipment model for path planning and scheduling, thereby achieving optimized management and dynamic simulation of the construction process.

[0080] Embodiment 2

[0081] Because the data sources for collecting data are different, in order to provide a basis for subsequent construction simulation and optimization analysis, it is necessary to obtain information from different data sources and perform data processing.

[0082] The tower information of the transmission circuit is obtained from the GIM model data. The tower information includes: the three-dimensional coordinates and structural information of the tower; the three-dimensional coordinates provide the spatial position of the tower in the construction area, and the structural information includes the height, type, material and other attributes of the tower.

[0083] The topographic information of the construction area is obtained from satellite image data and LiDAR data. The topographic information includes: digital elevation model and digital orthophoto. Digital elevation model (DEM) is generated by LiDAR or other measurement technology, which indicates the elevation change of the surface and provides a topographic basis for construction. Digital orthophoto is a satellite image that has been geometrically corrected, which can truly reflect the position and shape of ground objects and provide a detailed environmental view for construction.

[0084] Environmental parameter information of the construction area is obtained through GIS integration, including vegetation, buildings and other landforms. Geographic Information System (GIS) is sometimes called "geographic information system". It is a specific and very important spatial information system. With the support of computer hardware and software systems, it is a technical system for collecting, storing, managing, calculating, analyzing, displaying and describing the geographical distribution data in the entire or part of the earth's surface (including the atmosphere).

[0085] In order to ensure that all data are analyzed in the same coordinate system, thus avoiding data fusion errors caused by inconsistent coordinates, the tower information, topographic information and environmental parameter information are converted to the global geodetic coordinate system (WGS84), and the data are fused to obtain a fused data set. Among them, T k (·) is the data conversion function, is the dataset of the kth data source, w k is the weight of the data source (satisfying that the sum of the weights is 1), satisfying is the weighted norm, C k is the covariance matrix of the kth data source, K is the total number of data sources;

[0086] The abnormal data points O are detected by density-based clustering algorithm, and the abnormal data points are removed from the fused data set to obtain the cleaned data set. Abnormal data points are removed from the fused data set through a density-based clustering algorithm. The algorithm analyzes the distribution of data points and identifies isolated points with low density as anomalies, ensuring the quality and consistency of the remaining data. n ε (x i ) is x i The number of data points in the neighborhood with a radius of ε and a center of n. avg is the average number of neighborhood data points. δ is the anomaly threshold.

[0087] Use cokriging to interpolate missing data points in clean datasets for multi-source datasets Cokriging interpolation is a statistical method that estimates the values ​​of missing data points by building a spatial correlation model between variables and using the information of known data points to infer the values ​​of missing points. By using information from other related variables, this method can provide more accurate interpolation results and form a multi-source dataset. in, is the target variable at position s 0 The estimated value at V(s i ) and U(u j ) are the observed values ​​of the main variable and the covariate, respectively. i , μ j are weight coefficients, which are determined by solving the Kriging system equation of the covariance matrix.

[0088] Wavelet transform is performed on multi-source data sets, and features at different scales are obtained to construct a multi-source data feature set. Wavelet transform is a signal processing technology that can decompose data into different frequency components to extract important features. The constructed multi-source data feature set provides a basis for subsequent construction analysis and decision-making.

[0089] Embodiment 3

[0090] like Figure 2 As shown, the method of building a construction site model includes:

[0091] A set of ground points is extracted from the LiDAR data using the Random Sampling Consensus Algorithm (RANSAC), a method for extracting model parameters from noisy data. In this step, the algorithm randomly selects points from the LiDAR data and estimates the parameters of the plane in which they lie, repeating the process to eventually obtain a set of ground points.

[0092] A triangular irregular network is constructed on a set of ground points, and the Laplace equation is used to smooth the terrain of the triangular irregular network; a triangular irregular network is a modeling method that connects spatial points into triangles, which can effectively represent the ups and downs of the terrain. After the TIN is constructed, the Laplace equation is applied for smoothing. This process minimizes the elevation difference between points, making the terrain model smoother and more natural.

[0093] Solving partial differential equations using boundary conditions and the finite element method Obtain a smooth terrain model, where H(x, y) is the terrain elevation function, is the Laplace operator, which represents the quadratic partial derivative of elevation. ρ(x, y) is the source function representing the density of terrain elevation change. The equation is numerically solved under given boundary conditions by the finite element method, and a smooth terrain model is finally obtained.

[0094] The satellite image data is segmented using a fully convolutional neural network (FCN). Image segmentation technology extracts information about vegetation, buildings, and other landforms by dividing satellite images into different regions. Other landform regions include water systems, roads, and bridges.

[0095] Environmental parameter information is extracted and classification results are obtained; vegetation, buildings and other landforms are modeled separately and then integrated with the terrain model to obtain a rough construction site model; this model combines terrain and environmental characteristics and can more accurately reflect the actual situation of the construction area.

[0096] The rough model is enhanced with multi-scale details using three-dimensional wavelet transform to obtain the final construction site model M(x, y, z). Among them, Wl (x, y, z) is the wavelet coefficient of the lth scale, Ψ l (x, y, z) is the corresponding wavelet basis function, and L is the number of layers of wavelet decomposition.

[0097] The specific modeling method is provided below

[0098] Methods for modeling include:

[0099] The shape from outline reconstruction algorithm is used for the extracted building area, and the building model is constructed based on the building's outline and height information; the shape from outline reconstruction algorithm converts the two-dimensional outline information into a three-dimensional model by analyzing the geometric characteristics of the outline. During the reconstruction process, the height information of the building must also be combined to ensure that the constructed model is consistent with the actual building in terms of spatial position and proportion. The final building model can truly reflect the structural layout of the construction site.

[0100] The fractal set algorithm is used to simulate the three-dimensional structure of vegetation, and the vegetation morphology is generated through an iterative function system to construct a plant model; the fractal set algorithm is a modeling method based on mathematical fractal theory that can generate complex and natural shapes. In this step, an iterative function system (IFS) is used to generate the three-dimensional morphology of vegetation. This method defines a set of transformation functions to gradually generate a vegetation model with self-similar characteristics, which can effectively express the layering and richness of vegetation, making the generated model more natural.

[0101] Determine the outline of low-lying areas or water basins from the digital elevation model, use the water body outline to curve the water surface shape, and build a water body model; by analyzing the digital elevation model (DEM), it is possible to identify low-lying areas and water basins in the terrain. After determining the water body outline, use this outline information to curve the water surface shape. This process usually uses surface fitting technology to accurately represent the morphological characteristics of the water surface and build a realistic water body model.

[0102] The binary path information of the road is obtained from image segmentation, and curve fitting is performed on the extracted binary path information. The road path is mapped to the terrain model according to the digital elevation model to construct a road model; the contour will be mapped to the actual terrain according to the digital elevation model to ensure that the elevation change of the road matches the surrounding terrain, and finally the road model is constructed.

[0103] The bridge outline is extracted from the image segmentation, and the shape from outline reconstruction algorithm is used to build the bridge model based on the bridge's outline, design height and span. After extracting the bridge's outline information through image segmentation, the shape from outline reconstruction algorithm is used to combine the bridge's design height and span and other parameters for modeling. This modeling process not only ensures that the bridge's appearance conforms to the actual design, but also takes into account the bridge's structural characteristics, so that the final model can accurately reflect the bridge layout at the construction site.

[0104] Embodiment 4

[0105] Methods for modeling mechanical equipment include:

[0106] The collected construction machinery and equipment form an equipment set EQ = {EQ 1 , EQ 2 , ..., EQ N}, where N is the number of construction engineering machinery and equipment; and obtain the i-th equipment E i Equipment parameter data: length L i , Width W i , height H i 、Mass m i , inertia tensor I i 、Engine power P i , maximum torque τ max，i , maximum speed v max，i , minimum turning radius R min，i ; Parameters define the physical characteristics and performance of each device and form the basis for modeling mechanical equipment.

[0107] Use CAD software and according to the length L i , Width W i and height H i Create the EQ of the i-th device i The 3D model of construction engineering machinery equipment; according to the size parameters of the equipment, designers can draw the 3D structure model of the equipment in computer-aided design (CAD) software. In addition, the key components of the equipment can be accurately described using **Non-Uniform Rational B-Spline (NURBS)** surfaces:

[0108] S(u, v) is a parametric surface, u and v are variables on the parameter domain. are the p-order and q-order B-spline basis functions. ij is the control vertex. ij is the weight factor.

[0109] Combine kinematic equations and dynamic equations to create a dynamic model of construction engineering machinery and equipment; establish a dynamic model of the equipment based on the kinematic and dynamic characteristics of the equipment. Kinematic equations are used to describe the motion state of the equipment, such as position, velocity, and acceleration; while dynamic equations take into account the forces applied to the equipment during motion, including gravity, friction, and inertia. By combining these two equations, the behavior of the equipment during the construction process can be simulated more accurately.

[0110] Use engine power to establish the EQ of the i-th device i Energy efficiency model. The model can be used to calculate the energy consumption of the equipment under different working conditions and evaluate its working efficiency.

[0111] Among them, the kinematic equations of construction engineering machinery are determined by the Denavit-Hartenberg parameter method. The Denavit-Hartenberg (DH) parameter method is a commonly used robotics method used to describe the kinematic characteristics of robotic arms and other chain mechanisms. By defining the four DH parameters of each joint, the transformation matrix of the joint can be constructed, that is, the transformation matrix Tjj of each j joint is determined. Among them, θ j is the rotation angle of the joint, d j is the position of the joint along the axis, a j is the displacement between joints, α j is the rotation angle of the joint.

[0112] Use the joint posture transformation matrix to determine the angular velocity of each joint and angular acceleration

[0113] Use the Newton-Euler equation to determine the dynamic equation of construction engineering machinery and equipment and determine the linear acceleration a of the equipment i and the moment M of the equipment i , Among them, F i is the resultant force acting on the equipment, ω i is the angular velocity of the device, I i is the inertia tensor of the device;

[0114] Methods that combine the equations of kinematics and dynamics include:

[0115] The angular velocity and acceleration of each joint are used as inputs to the Newton-Euler equations, and the forces and moments of each joint are calculated using the Newton-Euler equations. The forces and moments are calculated step by step from the base to the end using the recursive formula in the Newton-Euler method, ensuring the overall consistency of the model.

[0116] Determine the final kinetic model Where q is the displacement of the joint, is the acceleration of the joint, M(q) is the inertia matrix, is the Coriolis force and centrifugal force matrix, G(q) is the gravity term, and τ is the driving torque of the joint.

[0117] Embodiment 5

[0118] like Figure 3 As shown, the method for determining equipment scheduling and path planning includes:

[0119] Define a set of construction tasks Where M is the total number of construction tasks; where construction tasks τ i Includes: Task Type Mission Location Required Equipment EQ j ;Task type indicates the specific nature of the task, such as transportation, installation, etc.; Task location specifies the specific location of the task at the construction site, usually expressed in coordinates; Required equipment indicates the specific mechanical equipment required to complete the task.

[0120] Establish dependencies between tasks to form a directed acyclic graph The edge set ε is the order of tasks; the nodes in the graph represent construction tasks, and the edge sets represent the dependencies and order between tasks. This representation method makes it clear which tasks must be completed before other tasks, thus providing a basis for subsequent scheduling and planning.

[0121] The construction site model is converted into an environmental map required for path planning, including obstacle information and drivable areas, to minimize the total construction time T total and total energy consumption E total The model of the construction site is converted into an environmental map with obstacle information and drivable areas. This conversion process ensures that the path planning takes into account the actual conditions of the site, such as the undulating terrain and the distribution of obstacles. By achieving the optimization goal, the efficiency and economy of the construction process are ensured.

[0122] Establish an optimization model for equipment scheduling and path planning, and obtain the optimal equipment scheduling and path planning; build an optimization model based on the defined construction tasks and the converted environment map. The model takes into account the priority of the task, the capacity of the equipment and the resource constraints, and obtains the optimal equipment scheduling plan and path planning through algorithm solution, thereby ensuring that the construction task can be carried out efficiently and smoothly.

[0123] Load the construction site model and mechanical equipment model to the simulation platform, and load the equipment scheduling and path planning to the simulation platform; the simulation platform can be AnyLogic, MATLAB / Simulink, F1exSim, Arena, etc.

[0124] Dynamic simulation is performed through the simulation platform. The methods for dynamic simulation include:

[0125] Divide the construction process into discrete time steps Δt to facilitate the step-by-step calculation of the motion state of the equipment. Determine the total number of simulation steps At each time step t k will correspond to a discrete moment in the time series.

[0126] The dynamic model is used to calculate each time step t k The displacement q of the lower device j (t k ) and speed

[0127] The calculated speed and acceleration Update the device's location, Based on the current velocity and acceleration, combined with discrete time steps, the device's position information is gradually updated to accurately simulate its motion trajectory.

[0128] When the device EQ j After arriving at the task location, the task begins to be executed, and the task τ is updated in real time according to the execution efficiency of the equipment i degree of completion;

[0129] At each time step t k , collision detection is performed through bounding box or directed bounding box algorithm; if collision risk is detected, the speed obstacle avoidance method is used to replan the local path;

[0130] Using the energy efficiency model of the device, calculate the energy efficiency of the device at time step t k Energy consumption E j (t k ), accumulate the energy consumption of all equipment and obtain the total energy consumption of the construction process Energy consumption data provides an important basis for evaluating the energy consumption of construction projects, which helps to optimize resource allocation and reduce construction costs.

[0131] Embodiment 6

[0132] A specific method is provided for establishing an optimization model for equipment scheduling and path planning and performing target optimization in Example 5:

[0133] Establishing the objective function Where x = [x ij ] is the equipment scheduling matrix, x ij =1 means device EQ j Execute task τ i , γ={γ j (t)} is the device EQ j , α and β are weight coefficients for balancing construction time and construction energy consumption;

[0134] Identify constraints.

[0135] Task allocation constraints: Make sure each task can only be performed by one device.

[0136] Device Capability Constraintsx ij ≤c ij , c ij =1 means device EQ j Can perform tasks i , c ij =0 means device EQ j Unable to perform taskτ i ; Ensure that the device can only perform tasks within its capabilities.

[0137] Task dependency constraints τ k is τ i The prerequisite task is is the start time of the task, The completion time of the task; ensure that the sequence between tasks is followed.

[0138] Path feasibility constraints: F safe is a safe area in the construction site model; ensure that the path is within the safe area.

[0139] Device dynamics constraints: f j EQ for your device j dynamic equations to ensure that the device's behavior is dynamic and realistic.

[0140] Encode the device scheduling matrix as part of the chromosome and encode the device path γ j (t) discretized into control points and encoded as another part of the chromosome; construct the genetic algorithm fitness function in, is the penalty term for violating the constraint, λ 1 , 2 and λ 3 is the weight coefficient of different constraints;

[0141] Penalty term P penalty The purpose of is to impose additional penalties on solutions that violate constraints in the optimization problem, thereby guiding the genetic algorithm or other optimization algorithm to prioritize solutions that satisfy the constraints. The penalty term can be designed based on different constraints, such as task allocation, path feasibility, equipment capacity, etc. In the penalty term formula:

[0142] The first term: the penalty term of the task allocation constraint, The goal is to ensure that each task is assigned to at most one device, x ij =1 means device EQ j Execute task τ i , Assign constraints to tasks. If the constraint is violated (i.e. ), the penalty term is positive, otherwise it is 0. 1 is the penalty weight coefficient of the task allocation constraint, which is used to control the importance of the constraint.

[0143] The second term: the penalty term for task dependency constraints, The purpose is to ensure that the task τ i Only in the predecessor task τ k Start after you finish. For the task τ i The start time of For the task τ k The completion time, is the task dependency constraint. If the constraint is violated (i.e. ), the penalty term is positive, otherwise it is 0. 2 is the penalty weight coefficient of the task dependency constraint.

[0144] The third term: the penalty term for path feasibility constraints, The purpose is to ensure that the equipment EQ j The path is within the safe area of ​​the construction site model. γ j (t) is the device EQ j The path planning at time t, F safe is a safe area for driving. If the path feasibility constraint (i.e. ), indicating function Return 1, indicating that the path is not in the safe area, thus accumulating penalty terms. 3 is the penalty weight coefficient of the path feasibility constraint.

[0145] The chromosomes are processed by inheritance, crossover and mutation, and after multiple iterations, the individual with the highest fitness is selected as the optimal solution to obtain the optimal equipment scheduling and path planning.

[0146] Embodiment 7

[0147] A GIM-based power transmission mechanized construction simulation and analysis device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned antenna interface unit testing method are implemented.

[0148] The memory can be used to store software programs and modules. The processor executes various functional applications and data processing of the terminal by running the software programs and modules stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an execution program required for at least one function, etc.

[0149] The data storage area can store data created according to the use of the terminal, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0150] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0151] Without loss of generality, computer readable media may include computer storage media and communication media. Computer storage media include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer readable instruction data structures, program modules or other data. Computer storage media include RAM, ROM, EPROM, EEPROM, flash memory or other solid-state storage technology, CD-ROM, DVD or other optical storage, cassettes, magnetic tapes, disk storage or other magnetic storage devices. Of course, those skilled in the art will appreciate that computer storage media are not limited to the above. The above-mentioned system memory and mass storage devices can be collectively referred to as memory.

[0152] A computer program product comprises a computer program / instruction, wherein when the computer program / instruction is executed by a processor, any one of the above methods is implemented.

[0153] A computer program product includes a computer program or set of instructions for performing specific tasks or implementing specific functions. These programs or instructions are designed to be executed by a processor to implement a series of predefined steps or operations. The program product may be stored in various forms of computer storage media, such as memory, hard disk, solid-state drive, optical disk or other forms of digital storage devices. It may exist in the form of compiled binary code or in the form of scripts or bytecodes that can be executed by an interpreter. The program product uses carefully designed algorithms and logical instructions to enable the processor to process data in a specific order and manner to complete various functions such as data analysis, user interaction, device control, etc.

[0154] In the description of this specification, the description with reference to the terms "one embodiment / method", "some embodiments / methods", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment / method or example are included in at least one embodiment / method or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment / method or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments / methods or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments / methods or examples described in this specification and the features of the different embodiments / methods or examples, unless they are contradictory.

[0155] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0156] It should be understood by those skilled in the art that the above embodiments are only for the purpose of clearly illustrating the present invention, and are not intended to limit the scope of the present invention. For those skilled in the art, other changes or modifications may be made based on the above invention, and these changes or modifications are still within the scope of the present invention.

Claims

1. A GIM-based power transmission mechanization construction simulation analysis method, characterized in that: include: Collect GIM model data, satellite image data, and LiDAR data of the construction area; collect equipment parameter data of construction engineering machinery and equipment; Combine GIM model data, satellite image data and lidar data to build a construction site model; Build mechanical equipment models based on equipment parameter data; The path planning and equipment scheduling are determined through the construction site model and mechanical equipment model, and loaded into the simulation platform to simulate the construction process.

2. The GIM-based power transmission mechanization construction simulation analysis method according to claim 1 is characterized in that: Obtaining the tower information of the transmission circuit from the GIM model data, the tower information includes: the three-dimensional coordinates and structural information of the tower; Obtain topographic information of the construction area from satellite image data and LiDAR data, including digital elevation model and digital orthophoto; The environmental parameter information of the construction area is obtained through GIS integration, including vegetation, buildings and other land features; The tower information, topographic information and environmental parameter information are converted into the global geodetic coordinate system, and the data are fused to obtain a fused data set. Abnormal data points are detected through density-based clustering algorithm, and the abnormal data points are removed from the fused data set to obtain the cleaned data set. Use cokriging to interpolate missing data points in clean datasets for multi-source datasets Wavelet transform is performed on multi-source data sets, and features at different scales are obtained to construct a multi-source data feature set.

3. The GIM-based power transmission mechanization construction simulation analysis method according to claim 1 is characterized in that: Methods for building construction site models include: A set of ground points is extracted from the lidar data using a random sampling consensus algorithm; Construct a triangular irregular network on the ground point set, and use the Laplace equation to smooth the terrain of the triangular irregular network; Solving partial differential equations using boundary conditions and the finite element method Obtain a smooth terrain model, where H(x, y) is the terrain elevation function, is the Laplace operator, ρ(x, y) is the source function representing the density of terrain elevation change; Perform image segmentation on satellite image data, extract environmental parameter information, and obtain classification results; model vegetation, buildings, and other landforms separately and merge them with the terrain model to obtain a rough construction site model; The rough model is enhanced with multi-scale details using three-dimensional wavelet transform to obtain the final construction site model M(x, y, z). Among them, W l (x, y, z) is the wavelet coefficient of the lth scale, Ψ l (x, y, z) is the corresponding wavelet basis function, and L is the number of layers of wavelet decomposition.

4. The GIM-based power transmission mechanization construction simulation analysis method according to claim 3 is characterized in that: Other terrain features include: water systems, roads, and bridges; modeling methods include: Using shape from outline reconstruction algorithm on the extracted building area, and constructing building model according to the building outline and height information; The fractal set algorithm is used to simulate the three-dimensional structure of vegetation, and the vegetation morphology is generated through an iterative function system to construct a plant model; Determine the outline of low-lying areas or water basins from the digital elevation model, use the water body outline to curve the water surface shape, and build a water body model; Obtaining the binary path information of the road from the image segmentation, performing curve fitting on the extracted binary path information, mapping the road path to the terrain model according to the digital elevation model, and constructing the road model; The bridge outline is extracted from the image segmentation, and the shape from outline reconstruction algorithm is used to build the bridge model based on the bridge contour line, design height and span.

5. The GIM-based power transmission mechanization construction simulation analysis method according to claim 1 is characterized in that: Methods for modeling mechanical equipment include: The collected construction machinery and equipment form an equipment set EQ = {EQ1, EQ2, ..., EQ N }, where N is the number of construction engineering machinery and equipment; and obtain the i-th equipment E i Equipment parameter data: length L i , Width W i , height H i 、Mass m i , inertia tensor I i 、Engine power P i , maximum torque τ max，i , maximum speed v max，i , Minimum turning radius R min，i ; Use CAD software and according to the length L i , Width W i and height H i Create the EQ of the i-th device i 3D models of construction machinery and equipment; Combine kinematic equations and dynamic equations to create a dynamic model of construction engineering machinery and equipment; Use engine power to establish the EQ of the i-th device i Energy efficiency model.

6. The GIM-based power transmission mechanization construction simulation analysis method according to claim 5 is characterized in that: The kinematic equations of construction machinery are determined by the Denavit-Hartenberg parameter method, and the transformation matrix T of each j joint is determined. j , Among them, θ j is the rotation angle of the joint, d j is the position of the joint along the axis, a j is the displacement between joints, α j is the rotation angle of the joint; Use the joint posture transformation matrix to determine the angular velocity of each joint and angular acceleration Use the Newton-Euler equation to determine the dynamic equation of construction engineering machinery and equipment and determine the linear acceleration a of the equipment i and the moment M of the equipment i , Among them, F i is the resultant force acting on the equipment, ω i is the angular velocity of the device, I i is the inertia tensor of the device; Methods that combine the equations of kinematics and dynamics include: The angular velocity and acceleration of each joint are used as inputs of the Newton-Euler equation, and the force and torque of each joint are calculated by the Newton-Euler equation. The force and torque are calculated step by step from the base to the end through the recursive formula in the Newton-Euler method. Determine the final kinetic model Where q is the displacement of the joint, is the acceleration of the joint, M(q) is the inertia matrix, is the Coriolis force and centrifugal force matrix, G(q) is the gravity term, and τ is the driving torque of the joint.

7. The GIM-based power transmission mechanization construction simulation analysis method according to claim 1 is characterized in that: Methods for determining equipment scheduling and path planning include: Define a set of construction tasks Where M is the total number of construction tasks; where construction tasks τ i Includes: Task Type Mission Location Required Equipment EQ j ; Establish dependencies between tasks to form a directed acyclic graph The edge set ε is the order of tasks; The construction site model is converted into an environmental map required for path planning, including obstacle information and drivable areas, to minimize the total construction time T total and total energy consumption E total As the goal, establish an optimization model for equipment scheduling and path planning, and obtain the optimal equipment scheduling and path planning; Load the construction site model and mechanical equipment model into the simulation platform, and load the equipment scheduling and path planning into the simulation platform; Dynamic simulation is performed through the simulation platform.

8. The GIM-based power transmission mechanization construction simulation analysis method according to claim 7 is characterized in that: Methods for performing dynamic simulation include: Divide the construction process into discrete time steps Δt and determine the total number of simulation steps The dynamic model is used to calculate each time step t k The displacement q of the lower device j (t k ) and speed The calculated speed and acceleration Update the device's location, When the device EQ j After arriving at the task location, the task begins to be executed, and the task τ is updated in real time according to the execution efficiency of the equipment i degree of completion; At each time step t k , collision detection is performed through bounding box or directed bounding box algorithm; if collision risk is detected, the speed obstacle avoidance method is used to replan the local path; Using the energy efficiency model of the device, calculate the energy efficiency of the device at time step t k Energy consumption E j (t k ), accumulate the energy consumption of all equipment and obtain the total energy consumption of the construction process 9. The GIM-based power transmission mechanization construction simulation analysis method according to claim 7 is characterized in that: Methods for establishing optimization models for equipment scheduling and path planning and performing target optimization include: Establishing the objective function Where x = [x ij ] is the equipment scheduling matrix, x ij =1 means device EQ j Execute task τ i , γ={γ i (t)} is the device EQ j , α and β are weight coefficients for balancing construction time and construction energy consumption; Determine the constraints and task allocation constraints: Device Capability Constraintsx ij ≤c ij , c ij =1 means device EQ j Can perform tasks i , c ij =0 means device EQ j Unable to perform taskτ i ; Task dependency constraints τ k is τ i The prerequisite task is is the start time of the task, is the completion time of the task; path feasibility constraint: γ j (t)∈F safe , F safe It is the safe area in the construction site model; equipment dynamics constraints: f j EQ for your device j The dynamic equations of Encode the device scheduling matrix as part of the chromosome and encode the device path γ j (t) discretized into control points and encoded as another part of the chromosome; construct the genetic algorithm fitness function Among them, P penalty is the penalty term for violating the constraint; The chromosomes are processed by inheritance, crossover and mutation, and after multiple iterations, the individual with the highest fitness is selected as the optimal solution to obtain the optimal equipment scheduling and path planning.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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