Unmanned tower crane dynamic simulation method and system based on virtual simulation technology

Abstract

The invention discloses an unmanned tower crane dynamic simulation method and system based on a virtual simulation technology, and relates to the technical field of intelligent construction. Comprising the following steps: constructing an unmanned tower crane BIM model and collecting point cloud data, and establishing a simulation model based on the unmanned tower crane BIM model and the point cloud data; developing a customized physical engine based on the simulation model, and constructing a multi-body dynamic model; constructing a three-dimensional wind field model, adjusting parameters, performing climate coupling simulation with the multi-body dynamic model, and obtaining structure response data under different wind fields; constructing an unmanned tower crane path planning model, and generating and executing an unmanned tower crane motion path in combination with the wind field parameters and the structure response data; running state data are obtained and visualized, and multi-dimensional risk monitoring is carried out on the path execution process according to the running state data. According to the method, the problems of scene distortion, rough simulation and risk missed judgment in the existing unmanned tower crane virtual rehearsal are solved, and the authenticity and effectiveness of the virtual rehearsal are improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent construction technology, and in particular to a method and system for dynamic simulation of unmanned tower cranes based on virtual simulation technology. Background Technology

[0002] As a core heavy equipment in intelligent construction scenarios, unmanned tower cranes undertake critical tasks such as hoisting building components and transferring materials. Their operational safety and efficiency directly determine the progress and safety level of the project. With the deep penetration of automation and intelligent technologies in the field of construction machinery, unmanned tower cranes have gradually developed towards "autonomous path planning, adaptive operation in complex working conditions, and multi-machine collaborative operation." Virtual pre-deployment simulations, as a key preliminary step to verify the feasibility of algorithms, identify construction risks, and optimize operating procedures, are crucial for the engineering application of unmanned tower cranes.

[0003] In existing technologies, virtual pre-simulation of unmanned tower cranes still suffers from the following shortcomings: First, the technical tools are still mainly general-purpose building simulation software, which builds virtual scenes based on static BIM models. This fails to effectively integrate dynamic data such as UAV oblique photogrammetry point clouds and prefabricated component libraries, resulting in virtual scenes that can only reproduce fixed working conditions and cannot simulate dynamic changes such as "addition of temporary obstacles and adjustment of construction areas." Consequently, the pre-simulation results deviate significantly from the actual construction plan. Second, it does not consider the nonlinear characteristics of the tower crane's transmission system, such as joint clearances and gear backlash, nor does it employ flexible rigging simulation technology. Furthermore, the simulation methods are inadequate for accurately simulating mechanical behaviors such as the swinging of the hoisted object and the deformation of the tower structure. Using only simplified climate parameters (such as average wind speed) makes it difficult to reproduce the dynamic interaction between wind, tower crane, and hoisted object under strong wind conditions, and the simulation results fail to reflect the stress and motion state of the equipment under real-world operating conditions. Additionally, the risk assessment relies solely on geometric collision detection (determining whether the tower crane is in contact with an obstacle), neglecting implicit safety indicators such as sudden stress changes and structural resonance in key parts of the tower. Finally, the lack of a multi-tower crane spatiotemporal conflict pre-simulation mechanism makes it difficult to support scientific decision-making and training optimization before commissioning.

[0004] How to solve the above-mentioned technical problems is the challenge facing this invention. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a dynamic simulation method and system for unmanned tower cranes based on virtual simulation technology, which solves the problems of scene distortion, rough simulation, and missed risk assessment in existing virtual pre-simulation of unmanned tower cranes, and improves the authenticity and effectiveness of virtual pre-simulation.

[0006] The technical solution adopted by this invention to solve its technical problem is as follows: This invention provides a dynamic simulation method for unmanned tower cranes based on virtual simulation technology, comprising the following steps: Construct a BIM model of the unmanned tower crane and collect point cloud data of the unmanned tower crane. Based on the BIM model and point cloud data of the unmanned tower crane, build a simulation model of the unmanned tower crane in Unity. Based on the simulation model of unmanned tower cranes, a customized physics engine was developed to construct a multibody dynamics model of unmanned tower cranes in Unity; A 3D wind field model was built in Unity, and the parameters of the 3D wind field model were adjusted. Climate coupling simulation was performed on the multibody dynamics model of the unmanned tower crane to obtain structural response data under different 3D wind field model parameters. Construct an unmanned tower crane path planning model, combine the parameters of the three-dimensional wind field model and the structural response data under different three-dimensional wind field model parameters to generate the unmanned tower crane motion path, and execute the unmanned tower crane motion path; The system acquires and visualizes the operational status data of unmanned tower cranes, thus obtaining visualized operational status data. Based on this visualized operational status data, it performs multi-dimensional risk monitoring of the unmanned tower crane's motion path execution process.

[0007] Preferably, the step of establishing an unmanned tower crane simulation model in Unity includes: Build a BIM model of the unmanned tower crane and collect point cloud data of the unmanned tower crane, then import the BIM model and point cloud data of the unmanned tower crane into Unity; In Unity, a scene coordinate system is constructed, and adaptive mesh generation technology is used to fuse the unmanned tower crane BIM model and unmanned tower crane point cloud data to obtain the unmanned tower crane static model. Construct a prefabricated variable collision body for the unmanned tower crane, and then overlap the prefabricated variable collision body in the static model of the unmanned tower crane to obtain the simulation model of the unmanned tower crane.

[0008] Preferably, the unmanned tower crane simulation model is also equipped with several virtual intelligent devices, including a height sensor, a torque sensor, a gyroscope, an amplitude sensor, an anemometer, a radar camera, and an intelligent control cabinet.

[0009] Preferably, the development of the customized physics engine adopts the DOTS architecture, specifically including: A rigid body chain is constructed using the Articulation Body component for the main body of the unmanned tower crane; For the transmission components of the unmanned tower crane, a dynamic model is constructed based on the improved Newton-Euler equations, and the formula is expressed as follows:

[0010] In the formula, For the generalized mass matrix, The acceleration vector is the generalized coordinate system. The matrix of Coriolis force and centrifugal force. For generalized coordinates, For generalized speed, It is the external torque vector. For the transpose of the Jacobian matrix of the transmission system, , These are the gear contact stiffness and damping coefficient, respectively. This represents the normal deformation of the gear tooth surface. The rate of normal deformation of the gear tooth surface; The gear backlash of the unmanned tower crane was simulated using Hertz contact theory; the slings of the unmanned tower crane were simulated using the discrete element method and Verlet integral; and the joint clearance of the unmanned tower crane was simulated using a compensation algorithm based on PID control.

[0011] Preferably, the climate-coupled simulation of the multibody dynamics model of the unmanned tower crane includes: A 3D wind field model is constructed using the WindZone component, and then the 3D wind field model is associated with the Unity particle system. The script applies a 3D wind field model to the multibody dynamics model of the unmanned tower crane, adjusts the parameters of the 3D wind field model, and calculates structural response data under different 3D wind field model parameters based on a customized physical architecture. The structural response data under different 3D wind field model parameters includes structural spatial pose, motion parameters, joint moments, cable loads, and wind-induced loads.

[0012] Preferably, the step of generating the motion path of the unmanned tower crane by combining the parameters of the three-dimensional wind field model and the structural response data under different three-dimensional wind field model parameters includes: A time-varying configuration space for an unmanned tower crane construction scenario is constructed based on the parameters of a three-dimensional wind field model and structural response data under different three-dimensional wind field model parameters. The time-varying configuration space for the unmanned tower crane construction scenario includes a static scene, a three-dimensional wind disturbance potential field, and a dynamic obstacle set. Based on the time-varying configuration space of unmanned tower crane construction scenarios, an improved RRT* algorithm is used to construct an unmanned tower crane path planning model. Constraints are introduced during the random tree node expansion process to generate candidate paths. The constraints include load swing constraints and stress fluctuation constraints. A spatiotemporal cost function is constructed, and the cost of candidate paths is calculated based on the spatiotemporal cost function. The node connection relationship of the random tree is optimized by Monte Carlo tree search to obtain the optimized candidate path. The candidate path with the minimum cost is retained as the movement path of the unmanned tower crane. The spatiotemporal cost function is expressed as follows:

[0013] in, The weighting coefficient is the path length. For path length, The weighting coefficient for time. Path execution time Expected value The weighting coefficient for the swing angle. The maximum swing angle in the path, This is the weighting coefficient for stress fluctuations. This represents the sum of structural stress fluctuations along the path.

[0014] Preferably, the unmanned tower crane operation status data includes real-time three-dimensional wind field model parameters and real-time structural response data; The process involves acquiring and visualizing the operational status data of the unmanned tower crane to obtain visualized operational status data; and then conducting multi-dimensional risk monitoring of the unmanned tower crane's motion path execution process based on this visualized operational status data. Real-time three-dimensional wind field model parameters are obtained based on a three-dimensional wind field model, and real-time structural response data is calculated based on a customized physics engine; the real-time structural response data includes real-time structural spatial pose, real-time motion parameters, real-time joint moments, real-time cable loads, and real-time wind-induced loads. The parameters of the real-time 3D wind field model and the real-time structural response data are mapped to the virtual intelligent device to obtain the virtual intelligent device readings. A data cockpit interface is designed, and the virtual intelligent device readings are visualized through the configuration UI panel to obtain visualized operating status data. Based on visualized operational status data, stress distribution is monitored in real time, resonance risk is assessed, and structural fatigue life is estimated, resulting in multi-dimensional risk monitoring results.

[0015] This invention also provides a dynamic simulation system for unmanned tower cranes based on virtual simulation technology, including... The simulation model building module is used to build a BIM model of the unmanned tower crane, collect point cloud data of the unmanned tower crane, and build a simulation model of the unmanned tower crane in Unity based on the BIM model and point cloud data of the unmanned tower crane. The multibody dynamics model building module is used to develop a customized physics engine based on the unmanned tower crane simulation model and to build the unmanned tower crane multibody dynamics model in Unity; The climate coupling simulation module is used to build a three-dimensional wind field model in Unity, adjust the parameters of the three-dimensional wind field model, and perform climate coupling simulation on the multibody dynamics model of the unmanned tower crane to obtain structural response data under different three-dimensional wind field model parameters. The path planning and execution module is used to construct an unmanned tower crane path planning model, generate the unmanned tower crane motion path by combining the parameters of the three-dimensional wind field model and the structural response data under different three-dimensional wind field model parameters, and execute the motion path. The operation status monitoring and risk assessment module is used to acquire and visualize the operation status data of the unmanned tower crane to obtain visualized operation status data, and to perform multi-dimensional risk monitoring on the execution process of the unmanned tower crane's movement path based on the visualized operation status data.

[0016] The present invention 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 steps of the method described above.

[0017] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described above.

[0018] The beneficial effects of this invention are as follows: It solves the problems of scene distortion, rough simulation, and missed risk assessment in existing virtual pre-simulation of unmanned tower cranes, thereby improving the realism and effectiveness of virtual pre-simulation. By integrating BIM models, point cloud data, and prefabricated components, and combining adaptive mesh technology to construct dynamic scenes, it can flexibly reproduce temporary working conditions, solving the problem of disconnect between pre-simulation and reality, and improving scene fit; through climate coupling simulation using the multi-body dynamics model of the unmanned tower crane and the three-dimensional wind field model, it reproduces nonlinear mechanical behavior and extreme climate interaction effects, reducing the deviation between simulation and real working conditions; it monitors implicit indicators such as stress and resonance, constructs a multi-dimensional risk assessment, and avoids missed assessment of hidden safety hazards; and it relies on intelligent path planning to realize pre-simulation of spatiotemporal conflicts among multiple tower cranes, supporting collaborative optimization and training decisions. Attached Figure Description

[0019] Figure 1 This is a diagram illustrating the method steps of the present invention.

[0020] Figure 2 This is a system module diagram of the present invention.

[0021] Figure 3 This is a schematic diagram of the unmanned tower crane simulation model of Embodiment 1 of the present invention.

[0022] Figure 4 This is a schematic diagram of the movement path of the unmanned tower crane in Embodiment 1 of the present invention. Detailed Implementation

[0023] To clearly illustrate the technical features of this solution, the following detailed implementation method will be used to explain the solution.

[0024] Example 1: See Figure 1 , Figure 3 , Figure 4 As shown, this embodiment is a dynamic simulation method for unmanned tower cranes based on virtual simulation technology, including the following steps: S1. Construct a BIM model of the unmanned tower crane and collect point cloud data of the unmanned tower crane. Based on the BIM model and point cloud data of the unmanned tower crane, build a simulation model of the unmanned tower crane in Unity. Build a BIM model of the unmanned tower crane and collect point cloud data of the unmanned tower crane, then import the BIM model and point cloud data of the unmanned tower crane into Unity; In Unity, a scene coordinate system is constructed, and adaptive mesh generation technology is used to fuse the unmanned tower crane BIM model and unmanned tower crane point cloud data to obtain the unmanned tower crane static model. Construct a prefabricated variable collision body for the unmanned tower crane, and then overlap the prefabricated variable collision body in the static model of the unmanned tower crane to obtain the simulation model of the unmanned tower crane.

[0025] The unmanned tower crane simulation model is also equipped with several virtual intelligent devices, including height sensors, torque sensors, slewing sensors, amplitude sensors, anemometers, radar cameras, and intelligent control cabinets.

[0026] It should be noted that Autodesk Revit 2024 software was used to build a BIM model at a 1:1 scale, including core components such as the tower body, boom, luffing trolley, slings, hooks, and hoisted objects. LiDAR was used to scan the unmanned tower crane construction scene to acquire point cloud data, and oblique photography by a drone was used to supplement the blind spots of the LiDAR scan.

[0027] In Unity, a scene coordinate system is constructed (with the center point of the tower crane foundation as the origin, the X-axis along the direction of the crane boom, and the Y-axis perpendicular to the ground and upward). An octree adaptive mesh generation algorithm is used. Point cloud data is imported through Unity's Point Cloud Plugin and aligned with the BIM model to generate a static model of the unmanned tower crane. The octree adaptive mesh generation algorithm balances "modeling accuracy" and "computational efficiency," with fine meshes for core components to ensure accurate collision detection, and coarse meshes for secondary components to reduce the Unity rendering load.

[0028] Using Unity's Mesh Collider component, flexible collider prefabricated bodies are constructed for the movable parts of the tower crane (such as the luffing trolley and hook). The collider prefabricated bodies are then overlapped with the static model, and the motion logic of the parts is associated through scripts (such as the colliders following synchronously when the luffing trolley moves along the boom track).

[0029] S2. Based on the unmanned tower crane simulation model, develop a customized physics engine and build a multibody dynamics model of the unmanned tower crane in Unity; The development of the custom physics engine adopts the DOTS architecture, specifically including: A rigid body chain is constructed using the Articulation Body component for the main body of the unmanned tower crane; For the transmission components of the unmanned tower crane, a dynamic model is constructed based on the improved Newton-Euler equations, and the formula is expressed as follows:

[0030] In the formula, For the generalized mass matrix, The acceleration vector is the generalized coordinate system. The matrix of Coriolis force and centrifugal force. For generalized coordinates, For generalized speed, It is the external torque vector. For the transpose of the Jacobian matrix of the transmission system, , These are the gear contact stiffness and damping coefficient, respectively. This represents the normal deformation of the gear tooth surface. The rate of normal deformation of the gear tooth surface; The gear backlash of the unmanned tower crane was simulated using Hertz contact theory; the slings of the unmanned tower crane were simulated using the discrete element method and Verlet integral; and the joint clearance of the unmanned tower crane was simulated using a compensation algorithm based on PID control.

[0031] It should be noted that by constructing a dynamic model of the transmission components using the improved Newton-Euler equations, and considering the nonlinear characteristics of the transmission components such as "elasticity and damping", the "force-motion" transmission of the transmission system is made closer to reality.

[0032] When gears mesh, there is "backlash" (a tiny gap between the teeth), which causes the driven gear to start moving only after the driving gear has rotated a short distance (i.e., "idle travel"). Traditional rigid models cannot simulate this "force transmission delay". When gear backlash exists (the two teeth are not in contact), the contact force is 0, and the driven gear does not move temporarily (simulating "idle travel"). When the driving gear rotates to "fill the backlash" (the two teeth are in contact), the "tooth surface contact force" (related to the contact area and material hardness) is calculated according to Hertz theory, which drives the driven gear to move. This realistically reproduces the "transmission lag" caused by gear backlash and avoids the distortion of "synchronous gear rotation" in the simulation.

[0033] The discrete element method is used to decompose the sling into multiple mass points (nodes). Each mass point has mass, position, and velocity. The mass points are connected by "virtual forces". Combined with Verlet integral, the position of the mass point at the next moment is predicted by "the position at the previous moment + the current acceleration", avoiding the need to solve complex differential equations and accurately reproducing the flexible behavior of the sling.

[0034] The PID algorithm is used to calculate the "driving torque that needs additional compensation", which fills the torque loss caused by the gap, avoids the problem of the control command and the actual action being out of sync due to the joint gap, and ensures the motion accuracy of the virtual simulation of the unmanned tower crane.

[0035] S3. Construct a three-dimensional wind field model in Unity, adjust the parameters of the three-dimensional wind field model, and perform climate coupling simulation on the multibody dynamics model of the unmanned tower crane to obtain structural response data under different three-dimensional wind field model parameters. Climate-coupled simulation of the multibody dynamics model of the unmanned tower crane includes: A 3D wind field model is constructed using the WindZone component, and then the 3D wind field model is associated with the Unity particle system. The script applies a 3D wind field model to the multibody dynamics model of the unmanned tower crane, adjusts the parameters of the 3D wind field model, and calculates structural response data under different 3D wind field model parameters based on a customized physical architecture. The structural response data under different 3D wind field model parameters includes structural spatial pose, motion parameters, joint moments, cable loads, and wind-induced loads.

[0036] It should be noted that, breaking away from the traditional simplified model of "using average wind speed to replace the real wind field," a three-dimensional wind field model that reflects the spatiotemporal changes in wind speed and direction is constructed. The wind field is "visualized" using Unity's particle system, improving the accuracy of virtual simulation. By configuring rigid body components and collision body components, physical properties such as "mass and inertia" are assigned to each component of the tower crane (tower body, boom, slings, and load), ensuring that wind forces can drive them to produce realistic motion. Simultaneously, the "physical boundaries" of each component of the tower crane (such as the boom's outline range) are defined to detect whether the tower crane collides with surrounding objects (such as buildings or other tower cranes) under the influence of the wind field. By writing scripts to define "wind-force" conversion rules, after "wind force" is applied to the rigid body components of the tower crane, Unity automatically calculates the tower crane's motion response (such as boom angle changes and load swing angles) and structural stress (such as tower body stress and sling tension) based on the multibody dynamics model. Meanwhile, the collision component will monitor in real time whether the tower crane comes into contact with the surrounding environment during its movement (such as the load swinging and hitting the tower body), and record the collision location and force.

[0037] S4. Construct an unmanned tower crane path planning model, combine the parameters of the three-dimensional wind field model and the structural response data under different three-dimensional wind field model parameters to generate the unmanned tower crane motion path, and execute the unmanned tower crane motion path. The motion path of the unmanned tower crane is generated by combining the parameters of the 3D wind field model and the structural response data under different 3D wind field model parameters. A time-varying configuration space for an unmanned tower crane construction scenario is constructed based on the parameters of a three-dimensional wind field model and structural response data under different three-dimensional wind field model parameters. The time-varying configuration space of the unmanned tower crane construction scenario includes a static scene, a three-dimensional wind disturbance potential field, and a dynamic obstacle set; the formula is expressed as follows:

[0038] In the formula, For static scenes, This represents a three-dimensional wind disturbance potential field. A collection of dynamic obstacles; It should be noted that the time-varying configuration space defines the "range of motion" of the tower crane at "any time t"—including both static obstacles and time-varying factors such as wind fields and dynamic obstacles, thus avoiding the "planned path being infeasible in reality" caused by the "assumption of a fixed scenario" in traditional path planning. Among these, the static scenario... This refers to fixed, unchanging obstacle areas in a construction scenario, such as surrounding buildings, tower crane foundations, and permanent equipment, determined based on BIM models and point cloud data. Three-dimensional wind disturbance potential field. Based on the parameters of the 3D wind field model and the structural response data under different wind field model parameters, the wind disturbance potential field is dynamically adjusted over time (e.g., its range expands as wind speed increases), and its spatial extent is updated in real time through Unity wind field components and dynamic simulation. Dynamic obstacle set. Obstacles that move with time / working conditions in the construction scenario, including areas where hoisted objects sway due to wind, and mobile equipment (such as concrete pump trucks and workers), are identified based on real-time BIM models and point cloud data.

[0039] Based on the time-varying configuration space of unmanned tower crane construction scenarios, an improved RRT* algorithm is used to construct an unmanned tower crane path planning model. Constraints are introduced during the random tree node expansion process to generate candidate paths. The constraints include load swing constraints and stress fluctuation constraints. It should be noted that the swing constraint of the hoisted object is defined as the maximum swing angle of the hoisted object. The unmanned tower crane has a sling length of l and a hoisted object mass of m. A swing dynamics model is established based on the Lagrange equation, and the swing angle at the path nodes is derived. The formula is as follows:

[0040] in, For wind-induced acceleration, For acceleration of motion, Let be the acceleration due to gravity; let ≤ .

[0041] Stress fluctuation constraint defines the maximum allowable stress fluctuation variance of the structure. By calculating stress distribution in real time, path segments are defined. Stress fluctuation variance The formula is expressed as follows:

[0042] in, Discrete sampling points The stress value, The number of discrete sampling points. For path segment The average stress value, let .

[0043] A spatiotemporal cost function is constructed, and the cost of candidate paths is calculated based on the spatiotemporal cost function. The node connection relationship of the random tree is optimized by Monte Carlo tree search to obtain the optimized candidate path. The candidate path with the minimum cost is retained as the movement path of the unmanned tower crane. The spatiotemporal cost function is expressed as follows:

[0044] in, The weighting coefficient is the path length. For path length, The weighting coefficient for time. Path execution time Expected value The weighting coefficient for the swing angle. The maximum swing angle in the path, This is the weighting coefficient for stress fluctuations. The sum of structural stress fluctuations along the path; weighting coefficients ( , , , The dynamic analytic hierarchy process (AHP) is used for calibration, which combines real-time wind level, task priority, and other parameters to generate an "adaptive weight matrix"—for example, when the wind level is ≥7. (Oscillation angle weight) and The stress fluctuation weight will increase significantly, prioritizing structural safety; in urgent situations, (Time weight) will be increased, prioritizing the efficiency of path execution.

[0045] It should be noted that the swing of the suspended load is driven by the resultant acceleration in the horizontal direction (the thrust of the wind + the inertial force of the tower crane's movement), while the vertical direction is constrained by gravity. The swing angle is derived through force analysis and geometric relationships, and then forced... ≤ ( Determined by the safety distance, this ensures that: the swinging load will not collide with the tower crane body, jib, or surrounding buildings; and the acceleration of the tower crane's movements (such as slewing and luffing) will not cause the load to "fly away." During tower crane movement, the stress on the tower body (such as bending moment and tensile / compressive stress) will fluctuate with changes in attitude and load. Variance is an indicator of the "degree of intensity of stress fluctuation," and is a mandatory... This ensures: minimal stress fluctuations in the tower body to avoid fatigue damage (repeated stress abrupt changes accelerate structural aging); and avoids instantaneous stress overloads (such as impact stress exceeding yield strength during sudden rotation, leading to tower deformation). By defining a 4D spatiotemporal cost function, the motion path planning of unmanned tower cranes balances four major objectives: path length, time, attitude, and energy consumption / stress, to find the motion path with the minimum overall cost.

[0046] S5. Acquire and visualize the unmanned tower crane's operating status data to obtain visualized operating status data; conduct multi-dimensional risk monitoring of the unmanned tower crane's motion path execution process based on the visualized operating status data.

[0047] The operational status data of unmanned tower cranes includes real-time 3D wind field model parameters and real-time structural response data; Acquire and visualize the operational status data of the unmanned tower crane to obtain visualized operational status data; based on the visualized operational status data, conduct multi-dimensional risk monitoring of the unmanned tower crane's motion path execution process, including... Real-time three-dimensional wind field model parameters are obtained based on a three-dimensional wind field model, and real-time structural response data is calculated based on a customized physics engine; the real-time structural response data includes real-time structural spatial pose, real-time motion parameters, real-time joint moments, real-time cable loads, and real-time wind-induced loads. The parameters of the real-time 3D wind field model and the real-time structural response data are mapped to the virtual intelligent device to obtain the virtual intelligent device readings. A data cockpit interface is designed, and the virtual intelligent device readings are visualized through the configuration UI panel to obtain visualized operating status data. Based on visualized operational status data, stress distribution is monitored in real time, resonance risk is assessed, and structural fatigue life is estimated, resulting in multi-dimensional risk monitoring results.

[0048] It should be noted that the system calculates stress distribution in key structural components in real time based on visualized operational status data to assess stress abrupt changes, analyzes the matching degree between wind load excitation frequency and the structure's natural frequency to assess resonance risk, and estimates structural fatigue life based on cumulative damage algorithm, thereby achieving dynamic monitoring and quantitative assessment of implicit safety indicators such as structural stress, resonance risk, and energy dissipation.

[0049] Example 2: See Figure 2As shown, this embodiment is a dynamic simulation system for unmanned tower cranes based on virtual simulation technology, including: The simulation model building module is used to build a BIM model of the unmanned tower crane, collect point cloud data of the unmanned tower crane, and build a simulation model of the unmanned tower crane in Unity based on the BIM model and point cloud data of the unmanned tower crane. The multibody dynamics model building module is used to develop a customized physics engine based on the unmanned tower crane simulation model and to build the unmanned tower crane multibody dynamics model in Unity; The climate coupling simulation module is used to build a three-dimensional wind field model in Unity, adjust the parameters of the three-dimensional wind field model, and perform climate coupling simulation on the multibody dynamics model of the unmanned tower crane to obtain structural response data under different three-dimensional wind field model parameters. The path planning and execution module is used to construct an unmanned tower crane path planning model, generate the unmanned tower crane motion path by combining the parameters of the three-dimensional wind field model and the structural response data under different three-dimensional wind field model parameters, and execute the motion path. The operation status monitoring and risk assessment module is used to acquire and visualize the operation status data of the unmanned tower crane to obtain visualized operation status data, and to perform multi-dimensional risk monitoring on the execution process of the unmanned tower crane's movement path based on the visualized operation status data.

[0050] Example 3: This is the third embodiment of the present invention, which differs from the first two embodiments in that: If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art or the current technical solution, can be embodied in the form of a software product. This current computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0051] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0052] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0053] The technical features of this invention not described can be implemented by or using existing technology, and will not be repeated here. Of course, the above description is not a limitation of this invention, and this invention is not limited to the examples above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of this invention should also be within the protection scope of this invention.

Claims

1. A dynamic simulation method for unmanned tower cranes based on virtual simulation technology, characterized in that, Includes the following steps: Construct a BIM model of the unmanned tower crane and collect point cloud data of the unmanned tower crane. Based on the BIM model and point cloud data of the unmanned tower crane, build a simulation model of the unmanned tower crane in Unity. Based on the simulation model of unmanned tower cranes, a customized physics engine was developed to construct a multibody dynamics model of unmanned tower cranes in Unity; A 3D wind field model was built in Unity, and the parameters of the 3D wind field model were adjusted. Climate coupling simulation was performed on the multibody dynamics model of the unmanned tower crane to obtain structural response data under different 3D wind field model parameters. Construct an unmanned tower crane path planning model, combine the parameters of the three-dimensional wind field model and the structural response data under different three-dimensional wind field model parameters to generate the unmanned tower crane motion path, and execute the unmanned tower crane motion path; Acquire and visualize the operational status data of unmanned tower cranes to obtain visualized operational status data; Multi-dimensional risk monitoring is conducted on the execution process of the unmanned tower crane's movement path based on visualized operational status data.

2. The method for dynamic simulation of unmanned tower cranes based on virtual simulation technology according to claim 1, characterized in that, The process of creating an unmanned tower crane simulation model in Unity includes: Build a BIM model of the unmanned tower crane and collect point cloud data of the unmanned tower crane, then import the BIM model and point cloud data of the unmanned tower crane into Unity; In Unity, a scene coordinate system is constructed, and adaptive mesh generation technology is used to fuse the unmanned tower crane BIM model and unmanned tower crane point cloud data to obtain the unmanned tower crane static model. Construct a prefabricated variable collision body for the unmanned tower crane, and then overlap the prefabricated variable collision body in the static model of the unmanned tower crane to obtain the simulation model of the unmanned tower crane.

3. The method for dynamic simulation of unmanned tower cranes based on virtual simulation technology according to claim 2, characterized in that, The unmanned tower crane simulation model is also equipped with several virtual intelligent devices, including a height sensor, a torque sensor, a slewing sensor, an amplitude sensor, an anemometer, a radar camera, and an intelligent control cabinet.

4. The method for dynamic simulation of unmanned tower cranes based on virtual simulation technology according to claim 3, characterized in that, The custom physics engine developed adopts the DOTS architecture, specifically including: A rigid body chain is constructed using the Articulation Body component for the main body of the unmanned tower crane; For the transmission components of the unmanned tower crane, a dynamic model is constructed based on the improved Newton-Euler equations, and the formula is expressed as follows: In the formula, For the generalized mass matrix, The acceleration vector is the generalized coordinate system. The matrix of Coriolis force and centrifugal force. For generalized coordinates, For generalized speed, It is the external torque vector. For the transpose of the Jacobian matrix of the transmission system, , These are the gear contact stiffness and damping coefficient, respectively. This represents the normal deformation of the gear tooth surface. The rate of normal deformation of the gear tooth surface; The gear backlash of the unmanned tower crane was simulated using Hertz contact theory; the slings of the unmanned tower crane were simulated using the discrete element method and Verlet integral; and the joint clearance of the unmanned tower crane was simulated using a compensation algorithm based on PID control.

5. The method for dynamic simulation of unmanned tower cranes based on virtual simulation technology according to claim 4, characterized in that, The climate-coupled simulation of the multibody dynamics model of the unmanned tower crane includes: A 3D wind field model is constructed using the WindZone component, and then the 3D wind field model is associated with the Unity particle system. The script applies a 3D wind field model to the multibody dynamics model of the unmanned tower crane, adjusts the parameters of the 3D wind field model, and calculates structural response data under different 3D wind field model parameters based on a customized physical architecture. The structural response data under different 3D wind field model parameters includes structural spatial pose, motion parameters, joint moments, cable loads, and wind-induced loads.

6. The method for dynamic simulation of unmanned tower cranes based on virtual simulation technology according to claim 5, characterized in that, The process of generating the motion path of the unmanned tower crane by combining three-dimensional wind field model parameters and structural response data under different three-dimensional wind field model parameters includes... A time-varying configuration space for an unmanned tower crane construction scenario is constructed based on the parameters of a three-dimensional wind field model and structural response data under different three-dimensional wind field model parameters. The time-varying configuration space for the unmanned tower crane construction scenario includes a static scene, a three-dimensional wind disturbance potential field, and a dynamic obstacle set. Based on the time-varying configuration space of unmanned tower crane construction scenarios, an improved RRT* algorithm is used to construct an unmanned tower crane path planning model. Constraints are introduced during the random tree node expansion process to generate candidate paths. The constraints include load swing constraints and stress fluctuation constraints. A spatiotemporal cost function is constructed, and the cost of candidate paths is calculated based on the spatiotemporal cost function. The node connection relationship of the random tree is optimized by Monte Carlo tree search to obtain the optimized candidate path. The candidate path with the minimum cost is retained as the movement path of the unmanned tower crane. The spatiotemporal cost function is expressed as follows: in, The weighting coefficient is the path length. For path length, The weighting coefficient for time. Path execution time Expected value The weighting coefficient for the swing angle. The maximum swing angle in the path, This is the weighting coefficient for stress fluctuations. This represents the sum of structural stress fluctuations along the path.

7. The method for dynamic simulation of unmanned tower cranes based on virtual simulation technology according to claim 6, characterized in that, The unmanned tower crane's operating status data includes real-time three-dimensional wind field model parameters and real-time structural response data; The process involves acquiring and visualizing the operational status data of the unmanned tower crane to obtain visualized operational status data. Multi-dimensional risk monitoring of the unmanned tower crane's motion path execution process based on visualized operational status data, including... Real-time 3D wind field model parameters are obtained based on the 3D wind field model, and real-time structural response data is calculated based on a customized physics engine. The real-time structural response data includes real-time structural spatial pose, real-time motion parameters, real-time joint torque, real-time cable load, and real-time wind-induced load. The parameters of the real-time 3D wind field model and the real-time structural response data are mapped to the virtual intelligent device to obtain the virtual intelligent device readings. A data cockpit interface is designed, and the virtual intelligent device readings are visualized through the configuration UI panel to obtain visualized operating status data. Based on visualized operational status data, stress distribution is monitored in real time, resonance risk is assessed, and structural fatigue life is estimated, resulting in multi-dimensional risk monitoring results.

8. A dynamic simulation system for unmanned tower cranes based on virtual simulation technology, characterized in that... The method for performing the unmanned tower crane dynamic simulation based on virtual simulation technology as described in any one of claims 1-7 includes: The simulation model building module is used to build a BIM model of the unmanned tower crane, collect point cloud data of the unmanned tower crane, and build a simulation model of the unmanned tower crane in Unity based on the BIM model and point cloud data of the unmanned tower crane. The multibody dynamics model building module is used to develop a customized physics engine based on the unmanned tower crane simulation model and to build the unmanned tower crane multibody dynamics model in Unity. The climate coupling simulation module is used to build a three-dimensional wind field model in Unity, adjust the parameters of the three-dimensional wind field model, and perform climate coupling simulation on the multibody dynamics model of the unmanned tower crane to obtain structural response data under different three-dimensional wind field model parameters. The path planning and execution module is used to construct an unmanned tower crane path planning model, generate the unmanned tower crane motion path by combining the parameters of the three-dimensional wind field model and the structural response data under different three-dimensional wind field model parameters, and execute the motion path. The operation status monitoring and risk assessment module is used to acquire and visualize the operation status data of the unmanned tower crane to obtain visualized operation status data, and to perform multi-dimensional risk monitoring on the execution process of the unmanned tower crane's movement path based on the visualized operation status data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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