An intelligent path planning and dynamic control method, system and medium for tower cranes in bridge construction

Abstract

The present invention discloses an intelligent path planning and dynamic control method, system and medium for tower cranes in bridge construction, belonging to the field of bridge construction. The method includes: constructing a digital twin model of bridge construction to describe the state and position of the tower crane; incorporating the construction progress data into the constructed digital twin model, synchronously updating the operation tasks and hoisting targets of the tower crane according to the construction progress plan, and adjusting the state of the tower crane in the digital twin model according to the construction progress; constructing an optimization control system in combination with the tower crane path planning algorithm, and obtaining the changes in the surrounding environment of the tower crane in real time through the real-time data of the sensor and the digital twin model, so that the digital twin model can reflect the relative position between the tower crane and the obstacles; and according to the relative position between the tower crane and the obstacles and the data real-time feedback by the sensor, if it is found that the position of the tower crane deviates from the predetermined path or there is a potential collision risk, automatically adjust the movement direction or decelerate the tower crane. The present invention can effectively avoid the collision risk.

Description

Technical Field

[0001] The present invention relates to the field of bridge construction, and particularly to an intelligent path planning and dynamic control method, system and medium for tower cranes in bridge construction. Background Art

[0002] During bridge construction, tower cranes are usually used for heavy object hoisting operations, but there are certain defects in traditional tower crane path planning methods. When planning the path of a tower crane, the prior art often fails to fully consider factors such as the dynamic changes in the construction environment and the influence of the load state, resulting in insufficient accuracy and safety of path planning, and problems such as path deviation and collision risk.

[0003] Specifically, traditional methods lack real-time perception and dynamic update of the construction site environment during tower crane path planning, and cannot timely detect and avoid dynamic obstacles on the construction site, such as construction workers, vehicles, other construction machinery, etc., which may lead to collision risks. At the same time, traditional methods do not fully consider the influence of the load state during path planning, such as load size, weight distribution, etc., and these factors will directly affect the movement trajectory, speed, acceleration, etc. of the tower crane, thereby affecting the accuracy of path planning. In addition, traditional methods cannot perform dynamic adjustment based on real-time data after path planning. Once the construction environment or load state changes, the planned path may deviate, and the operation safety cannot be guaranteed.

[0004] Therefore, a new tower crane path planning and control method is needed, which can real-time perceive the dynamic changes in the construction environment, fully consider the influence of the load state, and dynamically optimize and adjust the planned path in combination with real-time data, so as to improve the safety and efficiency of tower crane construction and avoid path deviation and collision risk. Summary of the Invention

[0005] One object of the present invention is to provide an intelligent path planning and dynamic control method for tower cranes in bridge construction, so as to solve the shortcoming in the prior art that it is difficult to dynamically optimize and adjust the planned path in combination with real-time data.

[0006] The present invention is realized through the following technical solutions. A method for intelligent path planning and dynamic control of tower cranes in bridge construction includes the following steps: S100. Construct a digital twin model of bridge construction, which includes the environmental and dynamic factors during the construction process and can describe the state and position of the tower crane; S200. Incorporate the construction progress data into the constructed digital twin model of bridge construction. According to the construction progress data, synchronously update the operation tasks and lifting targets of the tower crane, and adjust the state of the tower crane in the digital twin model of bridge construction according to the construction progress data. Calculate the path of the tower crane based on the real-time sensor data and the tower crane path planning algorithm to obtain the optimal safe path of the tower crane in space and time; S300. Construct an optimization control system in combination with the tower crane path planning algorithm, and obtain the real-time changes in the environment around the tower crane through the real-time data collection of sensors and the digital twin model of bridge construction, so that the digital twin model of bridge construction can reflect the relative position between the tower crane and the obstacles; S400. According to the relative position between the tower crane and the obstacles and the real-time feedback data of the sensors, if it is found that the position of the tower crane deviates from the predetermined path or there is a potential collision risk, automatically adjust the movement direction of the tower crane or decelerate.

[0007] Further, constructing the digital twin model of bridge construction includes the following steps: S110. Conduct high-precision scanning of the bridge construction site and collect the static and dynamic element data of the construction site; S120. Generate a three-dimensional digital model of the construction site based on the scanned three-dimensional point cloud data, and construct a fine model of the tower crane. The construction of the fine model of the tower crane includes the lifting path drawn according to the maximum lifting radius and the movable range of the tower crane, and based on the installation position and the lifting path of the tower crane, create the tower crane working models in different stages; S130. Model each stage of the bridge construction to construct a dynamic digital twin model of bridge construction including the evolution of the construction stage, and associate the dynamic digital twin model of bridge construction including the evolution of the construction stage with the tower crane working models in different stages; S140. After completing the construction of the fine model of the tower crane, install sensors at the key positions of the tower crane, the lifted object, and the components of the bridge to collect data such as position information, load, state, and weather conditions in real time. Arrange environmental monitoring sensors at the construction site to obtain meteorological data and detect the dynamic changes in the construction area, and transmit the collected data to the digital twin platform; S150. After receiving the data, the digital twin platform constructs a tower crane sensor database, a construction site sensor database, and a lifted object sensor database according to the type of sensor data. The data in all databases will be used as input information to dynamically update the digital twin model of bridge construction to display the real-time relationship between the tower crane and the construction site.

[0008] Furthermore, the tower crane path planning algorithm includes: a tower crane dynamic motion model and a constraint model. Based on the tower crane dynamic motion model and the constraint model, combined with the sensor data in the digital twin model of bridge construction according to the actual usage of the tower crane, fine planning of the tower crane path is realized.

[0009] Furthermore, the tower crane dynamic motion model is constructed by considering three main motions of the tower crane, horizontal motion, vertical motion, and the change of the boom angle. Let x be the horizontal position of the tower crane, in meters; y be the vertical position of the tower crane, in meters; θ be the angle of the boom, in degrees or radians. Among them, the horizontal motion of the tower crane is expressed as:

[0010] , where is the force in the horizontal direction of the tower crane, and m is the mass of the tower crane; the horizontal acceleration of the tower crane is determined by the horizontal force applied to it. The horizontal position of the tower crane changes with time, and the magnitude and direction of the force directly affect its motion state; the vertical motion of the tower crane is expressed as:

[0011] , where is the force in the vertical direction of the tower crane; the change of the boom angle of the tower crane is expressed as: , where I is the moment of inertia of the boom; T is the control moment of the tower crane; τ wind is the disturbing moment caused by the wind force; t represents time. All variables with t in the above formula are functions of time. x(t) represents the change of the horizontal position of the tower crane with time, y(t) represents the change of the vertical position of the tower crane with time, represents the force in the horizontal direction changing with time, F y (t) represents the force in the vertical direction changing with time, θ(t) represents the change of the boom angle with time, T(t) represents the change of the control moment of the tower crane with time, τ wind (t) represents the change of the disturbing moment caused by the wind force with time.

[0012] Furthermore, the constraint model includes: boom force constraint, boom angle constraint, motion limit constraint, and wind force influence constraint. Among them, the boom force constraint is used to show that the gravity of the load will affect the force condition of the boom, thereby indirectly affecting the vertical and horizontal accelerations of the tower crane, and is expressed by the following formula:

[0013] , where m load ( t ) is the load mass; g is the acceleration due to gravity; F load ( t) is the force borne at time t due to the gravity of the load, which affects the motion state of the tower crane; the boom angle constraint is used to represent that the boom angle changes with the position of the tower crane and is expressed by the following formula:

[0014] , where x is the horizontal position of the tower crane in meters; y is the vertical position of the tower crane in meters; θ ( t ) represents the change of the boom angle with time; x ( t ) represents the change of the horizontal position of the tower crane with time, y ( t ) represents the change of the vertical position of the tower crane with time;

[0015] The motion limit constraint is used to describe the speed limit of the tower crane and is expressed by the following formula:

[0016] , where v max ( m load ( t )) is the maximum motion speed under the load state at time t; the wind influence constraint enables the control system to make more precise adjustments by considering the influence of the wind, ensuring that the boom remains stable under the action of the wind and preventing excessive swing or unstable state of the boom:

[0017] , where τ wind is the disturbing torque caused by the wind, τ wind ( t ) represents the change of the disturbing torque caused by the wind with time, ρ is the air density, A wind is the windward area of the tower crane boom, v wind represents the wind speed, v wind ( t ) represents the change of the wind speed with time.

[0018] Further, an optimized control system is constructed to dynamically adjust the motion parameters of the tower crane by combining the real-time data of the sensors with the dynamic optimization function, ensuring that the tower crane always moves along the optimal path, avoiding collisions and path deviations at the same time, and realizing the dynamic and precise control of the tower crane boom based on the control data calculated by the optimized control system.

[0019] Furthermore, the dynamic optimization function is as follows:

[0020] , where u is the control input; the time interval [t, t + T] is the time window from the current time t to the future time t + T, which is used to represent the path to be optimized within this period of time;

[0021] , which is used to penalize the speed change of the path, so as to achieve path smoothness; and are the speeds of the tower crane in the x and y directions at time t respectively. The sum of the squares of the speeds reflects the magnitude of the speed change, which is used to penalize the rapid changes in the path and encourage path smoothness. α is the weight coefficient used to adjust the influence degree of speed smoothness; is used to penalize the influence of wind, is the disturbing torque caused by the wind at time t, which is used to reduce the influence of the wind; β is the weight coefficient used to adjust the penalty degree of the wind influence; is the collision penalty, is the indicator function, which is used to detect whether the path enters the collision area. If a collision occurs, that is, the tower crane path enters the conflict area, then ; if there is no collision, that is, the tower crane path does not enter the conflict area, then , and γ is the weight coefficient used to adjust the influence degree of the collision penalty.

[0022] On the other hand, the present invention provides an intelligent path planning and dynamic control system for tower cranes in bridge construction. The system includes: a digital twin model module for bridge construction, a safety path planning module, an optimization control module, and a dynamic control module. Among them, the digital twin model module for bridge construction is configured to perform high-precision scanning of the bridge construction site, collect static and dynamic element data of the construction site; generate a three-dimensional digital model of the construction site based on the scanned three-dimensional point cloud data, construct a fine model of the tower crane, and the construction of the fine model of the tower crane includes a lifting path drawn according to the maximum lifting radius and movable range of the tower crane, and based on the installation position and lifting path of the tower crane, create tower crane working models for different stages; model each stage of bridge construction, construct a dynamic bridge construction digital twin model including the evolution of construction stages, and associate the dynamic bridge construction digital twin model including the evolution of construction stages with the tower crane working models for different stages; after completing the construction of the fine model of the tower crane, install sensors at the key positions of the tower crane, the lifted object, and the components of the bridge to collect position information, load, status, and weather condition data in real time, arrange environmental monitoring sensors at the construction site to obtain meteorological data, and detect the dynamic changes in the construction area, and transmit the collected data to the digital twin platform; after receiving the data, the digital twin platform constructs a tower crane sensor database, a construction site sensor database, and a lifted object sensor database according to the type of sensor data, and uses the data in all databases as input information to dynamically update the digital twin model of bridge construction to display the real-time relationship between the tower crane and the construction site; the safety path planning module is connected to the digital twin model module for bridge construction, and the safety path planning module is configured to incorporate the construction progress data into the constructed digital twin model of bridge construction, synchronously update the operation tasks and lifting targets of the tower crane according to the construction progress data, adjust the state of the tower crane in the digital twin model of bridge construction according to the construction progress data, and calculate the path of the tower crane according to the real-time sensor data in combination with the tower crane path planning algorithm to obtain the optimal safe path of the tower crane in space and time; the optimization control module is connected to the safety path planning module, and the optimization control module is configured to construct an optimization control system in combination with the tower crane path planning algorithm, and obtain the changes in the environment around the tower crane in real time through the real-time data of the sensor and the digital twin model of bridge construction, so that the digital twin model of bridge construction can reflect the relative position between the tower crane and the obstacles; the dynamic control module is connected to the optimization control module, and the dynamic control module is configured to automatically adjust the movement direction or decelerate of the tower crane according to the relative position between the tower crane and the obstacles and the real-time feedback data of the sensor. When there are multiple tower cranes working together at the construction site, through the collaborative control method of the digital twin platform, ensure the mutual coordination and avoidance between the tower cranes and avoid conflicts.

[0023] Furthermore, the safe path planning module includes: a tower crane dynamic motion sub-unit and a constraint sub-unit. Among them, the tower crane dynamic motion sub-unit is constructed by considering three main motions of the tower crane, namely horizontal motion, vertical motion, and the change of the boom angle. Let x(t) be the horizontal position of the tower crane in meters; y(t) be the vertical position of the tower crane in meters; θ(t) be the angle of the boom in degrees or radians. Among them, the horizontal motion of the tower crane is expressed as: , where F x (t) is the force of the tower crane in the horizontal direction, and m is the mass of the tower crane; the horizontal acceleration of the tower crane is determined by the horizontal force applied to it. The horizontal position of the tower crane changes with time, and the magnitude and direction of the force directly affect its motion state; the vertical motion of the tower crane is expressed as: , where F y (t) is the force of the tower crane in the vertical direction; the change of the boom angle of the tower crane is expressed as: , where I is the moment of inertia of the boom; T(t) is the control torque of the tower crane; τ wind (t) is the disturbing torque caused by the wind force; the constraint sub-unit includes: boom force constraint, boom angle constraint, motion limit constraint, and wind force influence constraint. Among them, the boom force constraint is used to show that the gravity of the load will affect the force on the boom, thereby indirectly affecting the vertical and horizontal accelerations of the tower crane, and is expressed by the following formula: F load (t)=m load (t)·g. In the formula, m load (t) is the load mass; g is the acceleration due to gravity; the boom angle constraint is used to represent that the boom angle changes with the position of the tower crane, and is expressed by the following formula: θ(t)=arctan ( ), where x(t) is the horizontal position of the tower crane in meters; y(t) is the vertical position of the tower crane in meters; the motion limit constraint is used to describe the speed limit of the tower crane, and is expressed by the following formula: , where v max (m load (t)) is the maximum motion speed in the load state; the wind force influence constraint can make the control system perform more precise adjustment by considering the influence of the wind, ensuring that the boom remains stable under the action of the wind force and preventing excessive swing or unstable state of the boom: , where τ wind (t) is the disturbing torque caused by the wind force, ρ is the air density, and A wind is the windward area of the tower crane boom.

[0024] On the other hand, the present invention provides a computer-readable storage medium storing a computer program / instructions, which can implement the steps of the intelligent path planning and dynamic control method for tower cranes in bridge construction as described above when the computer program / instructions are executed by a processor.

[0025] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0026] 1. By constructing a digital twin model of bridge construction including tower cranes, construction environments, and hoisted objects, and using multi-source sensors to collect real-time dynamic data such as the position of tower cranes, load states, and environmental data to update the model, the present invention can accurately reflect the dynamic changes on the construction site, timely detect and avoid dynamic obstacles, and effectively avoid collision risks.

[0027] 2. When planning paths, the present invention fully considers the influence of load states, such as load size, weight distribution, etc., and incorporates them into tower crane dynamics models, load influence models, etc., thereby improving the accuracy of path planning. Through a dynamic optimization function and combined with real-time data, the planned path is dynamically adjusted. Once the construction environment or load state changes, the path can be optimized and adjusted in a timely manner to avoid path deviation, ensure that the tower crane operates along the optimal path, and improve operation safety.

[0028] 3. Through the collaborative control method of the digital twin platform, the present invention can achieve the coordination and avoidance between multiple tower cranes, avoid conflicts between tower cranes, and further improve the safety and efficiency of construction operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, form a part of this application, and do not limit the embodiments of the present invention. In the drawings:

[0030] Figure 1 is a flowchart of the method provided in Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations.

[0032] Embodiment 1

[0033] In this embodiment, a method for intelligent path planning and dynamic control of tower cranes in bridge construction is provided. Figure 1The flowchart of the path intelligent planning and dynamic control method in this embodiment is shown. It can be seen from the figure that this embodiment includes the following steps:

[0034] Step 1: Construction and data collection of the digital twin model for bridge construction. First, create an accurate and real-time synchronized digital twin model for bridge construction to reflect dynamic information such as the working state of tower cranes, construction progress, and environmental changes during the entire bridge construction process, providing accurate real-time environmental data and construction site models for tower crane path planning. In bridge construction, the main role of tower cranes is to hoist various heavy objects, such as precast bridge segments, reinforced concrete components, bridge steel structures, etc., to ensure that these materials can be efficiently and safely moved to the designated positions. Therefore, when constructing the digital twin model of the bridge under construction, not only the state and position of the tower crane need to be accurately described, but also environmental and dynamic factors during the entire construction process need to be considered.

[0035] Specifically, it includes the following contents:

[0036] First, use lidar and a collocated unmanned aerial vehicle (UAV) to perform high-precision scanning of the bridge construction site and collect data on all static and dynamic elements. These elements include: bridge structures, tower crane equipment, steel materials, precast beams, concrete structures, etc.

[0037] Based on the scanned three-dimensional point cloud data, generate a three-dimensional digital model of the construction site through modeling software. It should be particularly noted that the details of the model need to be accurate enough in key areas such as tower crane installation, hoisting points, and construction roads.

[0038] In particular, detailed modeling of the tower crane itself is required, including the structure of the tower crane (tower body, boom, lifting and lowering mechanism of the crane, hook, etc.). And it is necessary to draw the lifting path according to the maximum lifting radius and movable range of the tower crane. At the same time, based on the installation position and movement trajectory of the tower crane, create tower crane working models at different stages. For example, during different construction stages of the bridge, the position and lifting height of the tower crane will change, and these changes need to be gradually updated into the digital twin model of bridge construction.

[0039] At the same time, each stage of bridge construction also needs to be modeled. Considering the structural changes during bridge construction, such as the installation of precast bridge segments, concrete pouring, deck paving, etc., create a dynamic digital twin model of bridge construction that includes the evolution of construction stages. After constructing the models of each stage during the bridge construction process, it is necessary to ensure that these stage models can be associated with the tower crane model. For example, during hoisting, it is necessary to consider the bridge position, weight of the lifted object, shape of the lifted object, access point, etc.

[0040] After completing the model construction of the tower crane, install sensors at key positions such as the tower crane, the lifted object, and various components of the bridge to collect data on position information, load, status, weather conditions, etc. in real time, and transmit the data to the central control system through the Internet of Things (IoT) system.

[0041] Install position sensors (such as GPS, IMU), load sensors (for monitoring the lifting weight), angle sensors (for monitoring the boom angle), and vibration sensors (detecting dynamic vibrations during the lifting process) at key positions of the tower crane. These sensors are used to obtain the position, load status, and operating speed data of the tower crane in real time, and transmit this data to the central control system through Internet of Things (IoT) devices.

[0042] At the same time, arrange environmental monitoring sensors at the construction site to obtain meteorological data (wind speed, temperature, humidity, etc.) and the dynamic changes in the construction area (such as material stacking, construction road conditions, traffic conditions, etc.).

[0043] If the construction site is large, especially when the bridge spans a river or complex terrain, drones equipped with lidar can also be used to perform real-time scanning of the surrounding environment to update the obstacle information in the model.

[0044] Each bridge component to be lifted (such as bridge precast segments, steel beams, etc.) should be equipped with sensors to monitor its weight, lifting position, and dynamic response.

[0045] The data collected by the sensors is transmitted to the digital twin platform in real time through the Internet of Things (IoT) system to provide real-time feedback on the lifting operation. After receiving the data sent by the sensors, the digital twin platform constructs a tower crane sensor database, a construction site sensor database, and a lifted object sensor database according to the type of sensor data respectively. The sensor data in all databases will be used as input information to dynamically update the tower crane position, the state of the lifted object, environmental conditions, etc. Through data fusion technology, integrate multi-source data (tower crane sensors, environmental sensors, construction data, etc.) to achieve accurate synchronization and sharing of data, and use it to generate a visual interface on the digital twin platform to display the real-time relationship between the tower crane and the construction site.

[0046] Step 2: Incorporate the construction progress data into the constructed digital twin model of bridge construction. For example, at different construction stages, the corresponding bridge structure and tower crane position in the model will change dynamically. The bridge construction plan and the digital twin model of bridge construction can be combined through building information modeling to achieve full-process visualization of the construction process.

[0047] Synchronously update the operation tasks and lifting targets of the tower crane according to the construction progress data. For example, each task in the construction progress data (such as precast bridge segment lifting, concrete pouring, etc.) is associated with the tower crane operation and integrated with the dynamic environmental conditions (such as wind speed, temperature).

[0048] Meanwhile, as the construction progress advances, the path and load status of the tower crane will change. For example, at different stages, the lifting radius of the tower crane may change, and the objects of the lifting tasks are also different. The digital twin model for bridge construction needs to automatically adjust the working area, boom angle, lifting path, etc. of the tower crane according to the construction progress data.

[0049] During the actual operation of the tower crane, the digital twin model for bridge construction will calculate the path of the tower crane based on real-time data and in combination with the tower crane path planning algorithm, and plan and dynamically correct the tower crane path according to the calculated results. If there are emergencies during the lifting process (such as excessive wind speed, abnormal load, etc.), the digital twin model for bridge construction will adjust the lifting path according to the real-time data of the sensors and reflect it to the construction site through the digital twin platform.

[0050] Specifically, the tower crane path planning algorithm is a mathematical model that fully considers the actual use of the tower crane and combines the sensor data (such as tower crane position, load status, and environmental data) in the digital twin model for bridge construction to finely plan the tower crane path.

[0051] This mathematical model includes a tower crane dynamic motion model (including changes in tower crane position and boom angle); the influence of load status on the tower crane path (such as restrictions on boom angle and movement speed due to load size and position); the influence of environmental factors on tower crane movement (such as wind speed, temperature, humidity, etc.); and path planning optimization goals (such as shortest path, safety optimization, load stability, etc.).

[0052] In this embodiment, a tower crane path planning mathematical model is constructed by combining partial differential equations, sensor data, and load influence. This model takes into account the dynamic motion of the tower crane, the influence of load and environmental factors, and the optimization goals of path planning (such as shortest path, safety, load stability). In practical applications, through this algorithm and in combination with digital twin technology, the path planning is adjusted in real time to ensure the efficient and safe operation of the tower crane.

[0053] Specifically, it includes:

[0054] 1) Construct the position and velocity model: To construct the position and velocity model of the tower crane, three main motions of the tower crane need to be considered: horizontal motion, vertical motion, and the change of the boom angle. Let: x be the horizontal position of the tower crane, in meters. y be the vertical position of the tower crane, in meters; θ be the angle of the boom, in degrees or radians. Then the dynamic motion of the tower crane can be described by the following motion equations:

[0055] The horizontal motion of the tower crane can be expressed as:

[0056] ,

[0057] where, is the force on the tower crane in the horizontal direction, m is the mass of the tower crane; the horizontal acceleration of the tower crane is determined by the horizontal force applied to it. The horizontal position of the tower crane changes with time, and the magnitude and direction of the force directly affect its motion state.

[0058] The vertical motion of the tower crane can be expressed as:

[0059] ,

[0060] F y is the force on the tower crane in the vertical direction.

[0061] where, the change of the boom angle of the tower crane can be expressed as:

[0062] ,

[0063] where, I is the moment of inertia of the boom; T is the control torque of the tower crane; τ wind is the disturbing torque caused by the wind force. Through this equation, the change of the boom angle can be described. The angle of the boom is not only affected by the tower crane control system but may also be disturbed by external factors (such as wind).

[0064] It should be noted that in the above formulas, t represents time. All variables with t in the above formulas are functions of time. x(t) represents the change of the horizontal position of the tower crane with time, y(t) represents the change of the vertical position of the tower crane with time, represents the force in the horizontal direction changing with time, F y (t) represents the force in the vertical direction changing with time, θ(t) represents the change of the boom angle with time, T(t) represents the change of the control torque of the tower crane with time, τ wind (t) represents the change of the disturbing torque caused by the wind force with time.

[0065] 2) During the operation of the tower crane, considering that the tower crane is not just a simple motion system, it also needs to take into account the influence of the load on the tower crane's trajectory. Generally, the weight and distribution of the load will affect multiple aspects of the tower crane's motion trajectory, speed, acceleration, etc., especially for the angle of the jib and the motion limitations of the tower crane.

[0066] Assume the mass m of the load load (t) changes with time, and the state of the load will affect the motion model of the tower crane. Specifically, the change of the load will affect the mass m of the tower crane and the moment of inertia I of the jib, thus changing the motion response of the tower crane under different working conditions.

[0067] It should be noted that, generally, the load mass m load (t) on the tower crane is constant, especially in the following two cases: Fixed load: If there is a fixed heavy object on the tower crane and no loading or unloading operation is carried out within a certain period of time, then the load mass can be regarded as constant. In some simplified models, for the convenience of analysis, it can be assumed that the load mass of the tower crane is constant, that is, the change of the load during the hoisting process is not considered.

[0068] However, considering that the situation of the tower crane hoisting materials during the construction process is relatively complex, the load during the hoisting process may change. For example: Unloading: The tower crane may unload part or all of the load at certain locations (for example, unload part of the goods from the jib). Loading: The tower crane may also lift more materials at certain moments, resulting in an increase in the load mass. The unloading and loading rates of the load: The change rate of the load mass may be very small and sometimes can be regarded as a continuous change. But in actual construction, the change of the load is sometimes also regarded as a discrete change (for example, loading or unloading an item with a fixed mass at one time). At the same time, considering different loads, if the tower crane hoists multiple independent items, the masses of these items can also be different, and the hoisting time of each item is different, resulting in the change of the load mass over time. Therefore, in this embodiment, by assuming that the load mass of the tower crane will change over time, the influence of the load state on the jib trajectory can be described more precisely.

[0069] Specifically, the influence of the load state on the jib trajectory can be described by the following constraint conditions:

[0070] 1. Jib force constraint:

[0071] ,

[0072] In the formula, m load is the load mass, m load (t) is the change of the load mass over time; g is the acceleration due to gravity; F load(t) is the force borne due to the gravity of the load at time t, and this force affects the motion state of the tower crane; this constraint is used to indicate that the gravity of the load will affect the force on the boom, thereby indirectly affecting the vertical and horizontal accelerations of the tower crane. This gravitational force will change the dynamic response of the system when the load of the tower crane changes, making the motion of the tower crane more complex. That is, F load (t) will affect the acceleration and angular acceleration of the tower crane, and thus affect the motion response of the tower crane.

[0073] 2. Boom angle constraint:

[0074] ,

[0075] where x(t) is the horizontal position of the tower crane in meters; y(t) is the vertical position of the tower crane in meters; θ(t) represents the change of the boom angle over time; this constraint is used to indicate that the position changes of the tower crane in the horizontal and vertical directions will affect the boom angle. And the boom angle will affect how the tower crane carries the load. Especially when the load is heavy, the boom angle may need to be further adjusted to maintain stability. This is very important for path planning because the motion trajectory of the tower crane must ensure that the boom angle remains within a safe range under the action of the load. That is, θ(t) changes with the horizontal and vertical positions of the tower crane, and the boom angle is closely related to the stability of the load, affecting how the tower crane carries the load.

[0076] 3. Motion limit constraint:

[0077] ,

[0078] where v max (m load (t)) is the maximum motion speed under the load state at time t; it depends on the size of the load. This constraint is used to describe the speed limit of the tower crane. That is, the load size directly affects the maximum motion speed v max in the horizontal direction of the tower crane. When the load is large, the speed of the tower crane must be limited to prevent the boom from becoming unstable or the load from being unable to be precisely controlled due to excessive speed, and v max (m load (t)) is a load-related speed upper limit, and its value depends on the current load m load (t). The larger the load, the smaller the speed upper limit of the tower crane usually is because a larger load will increase the difficulty of controlling and moving the tower crane.

[0079] 4. Wind force influence constraint:

[0080] ,

[0081] where τ windis the disturbing torque caused by wind, τ wind (t) represents the variation of the disturbing torque caused by wind with time, ρ is the air density, A wind is the windward area of the tower crane's jib, that is, the surface area of the tower crane's jib directly impacted by the wind. Usually, this area is related to the length and structural shape of the tower crane's jib. A larger windward area means a stronger influence of the wind. v wind represents the wind speed, v wind (t) represents the variation of the wind speed with time. This constraint indicates that the greater the wind speed, the greater the torque on the tower crane affected by the wind. The square relationship of the wind speed means that the influence of the wind speed on the jib is non-linear, that is, the influence will increase rapidly when the wind speed increases. By considering the influence of the wind, the control system of the tower crane needs to be adjusted more precisely to ensure that the jib remains stable under the action of the wind and prevent excessive swinging or unstable states of the jib.

[0082] It should be noted that t represents time, and all variables with t in the above formula are functions of time. Through the position and velocity model and constraint conditions, a mathematical model for the tower crane path planning is constructed. Through this model, the digital twin model of bridge construction will consider the influence of various variables when performing tower crane path planning, so as to determine the speed, acceleration, and jib angle of the movement. This makes the path planning not only about the idle movement of the tower crane, but also must consider the influence of the load to ensure the stability and efficiency of the tower crane under different conditions.

[0083] By combining the constructed tower crane path planning algorithm, the data in the tower crane sensor database, the construction site sensor database, and the hoisted object sensor database are input into the tower crane path planning algorithm for real-time processing, and the processed data is fed back into the digital twin model of bridge construction to achieve the intelligent path planning of the tower crane. By combining real-time data with the tower crane path planning algorithm, dynamic adjustment of the path planning can be achieved to ensure the safety and efficiency of the tower crane movement. The specific control strategy can process the results calculated by the tower crane path planning algorithm by combining methods such as PID controllers or fuzzy control.

[0084] Step 3: After obtaining the optimal safe path of the tower crane in space and time by combining the tower crane path planning algorithm with sensor data, in order to achieve real-time dynamic adjustment of the tower crane during construction, it is necessary to combine the previous tower crane path planning algorithm and the dynamic optimization function to construct an optimization control system that can monitor, analyze, and adjust the movement path of the tower crane in real time. Through real-time data feedback, combined with the dynamic optimization function, the movement parameters such as the speed and jib angle of the tower crane are dynamically adjusted to ensure that the tower crane always moves along the optimal path while avoiding possible collisions and path deviations.

[0085] In actual operation, the movement of the tower crane is affected by various factors, such as wind speed, load size, tower crane position, etc. Therefore, it is necessary to combine the data in the sensor database and feedback it to the path control system in real time. Based on the real-time sensor data, the path control system needs to dynamically adjust the path to avoid path deviation or collision and ensure the safety of tower crane operation.

[0086] Specifically, the dynamic optimization function is:

[0087] ,

[0088] where u represents the control input, usually referring to physical quantities such as the speed and acceleration of the tower crane, which affect the behavior and path of the system.

[0089] It should be noted that the design idea of the dynamic optimization function is to make the movement path of the tower crane reach a certain optimal goal within the specified time interval [t, t+T] by optimizing the control variable u. Each term in this function corresponds to different goals that need to be optimized in path planning, such as path smoothness, wind influence, and collision avoidance.

[0090] Specifically, the time interval [t, t+T] is a time window from the current time t to the future time t+T, indicating that the path needs to be optimized within this period. , which is used to penalize the speed change of the path, thus achieving path smoothness. and respectively represent the speeds of the tower crane in the x and y directions at time t (speed is the derivative of position with respect to time). The sum of the squares of the speeds reflects the magnitude of the speed change. Such a setting can penalize rapid changes in the path and encourage path smoothness. α is a weight coefficient used to adjust the influence degree of speed smoothness. The larger the value, the more the system tends to choose a smooth path.

[0091] is used to penalize the influence of wind, where τ wind (t) is the disturbing torque caused by the wind at time t. The influence of wind on the tower crane is usually not negligible, especially in outdoor environments. By optimizing the control path, the influence of wind can be minimized as much as possible. β is a weight coefficient that determines the penalty degree of wind influence. The larger the value, the more the path planning tends to avoid areas with strong wind when the wind influence is greater.

[0092] is the collision penalty, is an indicator function used to detect whether the path enters the collision area. If a collision occurs, that is, the tower crane path enters the conflict area, then ; if there is no collision, that is, the tower crane path does not enter the conflict area, then , γ is a weight coefficient used to adjust the influence degree of the collision penalty. It should be noted that The specific manifestation form of can be defined by those skilled in the art according to the actual construction situation to define the collision area and calculate whether the tower crane path enters these areas according to the construction conditions. For example, the spatial determination can be defined according to the specific construction situation. Commonly used methods include: Bounding box method: Construct a bounding box or other simple geometric shape for the tower crane and the obstacle respectively, and then detect the collision by judging whether the path of the tower crane intersects with the bounding box of the obstacle. Or the distance threshold method can be adopted. If the distance between the path point and the obstacle is less than a certain set threshold, it is considered that a collision has occurred. This method is applicable to a dynamic environment. When the tower crane approaches the obstacle, a collision may be triggered.

[0093] Based on the dynamic optimization function and combined with real-time data, the digital twin model of the bridge construction can obtain the changes in the environment around the tower crane in real time, especially dynamic obstacles (such as construction workers, vehicles, other construction machinery, etc.). Through this dynamic update, the digital twin model of the bridge construction can accurately reflect the relative position between the tower crane and the obstacle, helping to detect potential collision risks in a timely manner.

[0094] And based on the digital twin technology, the motion model of the tower crane and the three-dimensional environment model of the construction site can be docked in real time. Through the dynamic optimization function, the relative distance between each component of the tower crane and the obstacles in the environment can be accurately calculated. When these distances are less than a certain threshold, the model will immediately issue a collision alarm and feedback it to the tower crane path planning algorithm to adjust the motion trajectory of the tower crane to avoid collisions.

[0095] Step 4: Based on the control data calculated by the optimization control system, the digital twin platform realizes the dynamic and precise control of the tower crane boom by using the PID control algorithm. And based on the data real-time feedback by the sensor, if it is found that the position of the tower crane deviates from the predetermined path or there is a potential collision risk, the system will automatically adjust the motion direction of the tower crane or decelerate. And if there are multiple tower cranes working together at the construction site, the collaborative control method of the digital twin platform can be used to ensure the mutual coordination and avoidance between the tower cranes and avoid conflicts. By adopting distributed control, each tower crane can make autonomous decisions through the dynamic optimization function according to its own local information data, but also maintain global coordination with other tower cranes.

[0096] If changes occur at the construction site (such as the appearance of new obstacles, weather changes, etc.), the path of the tower crane can be automatically corrected according to the sensor data. Through real-time data update, the path planning algorithm can recalculate the optimal path and immediately instruct the tower crane to execute the correction action.

[0097] The specific embodiments described above further elaborate on the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only for the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for intelligent planning and dynamic control of tower crane paths in bridge construction, characterized in that: The dynamic control method comprises: S100, constructing a bridge construction digital twin model, wherein the bridge construction digital twin model includes environmental and dynamic factors in the construction process and is used to describe the state and position of the tower crane; S200, incorporating the construction progress data into the constructed digital twin model of bridge construction, synchronously updating the operation tasks and lifting targets of the tower crane according to the construction progress data, adjusting the state of the tower crane in the digital twin model of bridge construction according to the construction progress data, and calculating the path of the tower crane according to the real-time data of the sensor combined with the tower crane path planning algorithm to obtain the optimal safe path of the tower crane in space and time; S300, build an optimization control system in combination with the tower crane path planning algorithm, and use the sensor real-time data collection bridge construction digital twin model to obtain real-time changes in the tower crane's surrounding environment, so that the bridge construction digital twin model can reflect the relative position between the tower crane and obstacles; S400, based on the relative position between the tower crane and the obstacle and the real-time feedback data from the sensor, If the crane is found to deviate from the planned path or there is a potential risk of collision, the crane will automatically adjust its direction of movement or slow down. When there are multiple tower cranes working together at the construction site, the collaborative control method of the digital twin platform can ensure mutual coordination and avoidance between the tower cranes to avoid conflicts; A tower crane dynamic motion model and a constraint model, based on which the tower crane path is finely planned according to the actual use of the tower crane and the sensor data in the bridge construction digital twin model; The tower crane dynamic motion model is constructed by considering the three main motions of the tower crane, horizontal motion, vertical motion and the change of the boom angle, with x being the horizontal position of the tower crane in meters; y being the vertical position of the tower crane in meters; θ being the angle of the boom in degrees or radians, wherein, The horizontal movement of the tower crane is expressed as: ， In the formula, is the horizontal force of the tower crane, and m is the mass of the tower crane. The horizontal acceleration of the tower crane is determined by the horizontal force applied to it. The horizontal position of the tower crane will change over time, and the magnitude and direction of the force will directly affect its motion state. The vertical movement of the tower crane is expressed as: ， In the formula, is the force of the tower crane in the vertical direction; The change of the tower crane's boom angle is expressed as: ， Where, I is the inertia moment of the boom; T is the control moment of the tower crane; τ wind is the disturbance torque caused by wind; t represents time. All variables with t in the above formula are functions of time. x(t) represents the change of the horizontal position of the tower crane over time, and y(t) represents the change of the vertical position of the tower crane over time. represents the horizontal force that changes with time, F y (t) represents the vertical force that changes with time, θ(t) represents the angle of the boom that changes with time, T(t) represents the control torque of the tower crane that changes with time, and τ wind (t) represents the variation of the disturbance torque caused by wind with time; The constraint model includes: boom force constraint, boom angle constraint, motion restriction constraint and wind impact constraint, among which, The arm force constraint is used to indicate that the gravity of the load will affect the force of the arm, thereby indirectly affecting the vertical and horizontal acceleration of the tower crane, which is expressed by the following formula: ， In the formula, m load (t) is the load mass; g is the gravitational acceleration; F load (t) is the force due to the weight of the load at time t, which affects the motion state of the tower crane; The boom angle constraint is used to indicate that the boom angle changes with the position of the tower crane, which is expressed by the following formula: ， Where x is the horizontal position of the tower crane, in meters; y is the vertical position of the tower crane, in meters; θ(t) represents the change of the boom angle over time; x(t) represents the change of the horizontal position of the tower crane over time, and y(t) represents the change of the vertical position of the tower crane over time; The motion limit constraint is used to describe the speed limit of the tower crane and is expressed by the following formula: ， In the formula, v max (m load (t)) is the maximum motion speed under load at time t; Wind impact constraints By taking into account the impact of wind, the control system can make more precise adjustments to ensure that the boom remains stable under the action of wind and prevent excessive swing or instability of the boom: ， In the formula, τ wind is the disturbance torque caused by wind, τ wind (t) represents the change of disturbance torque caused by wind over time, ρ is the air density, A wind is the windward surface area of ​​the tower crane boom, v wind represents wind speed, v wind (t) represents the change of wind speed over time; The construction of the optimization control system dynamically adjusts the motion parameters of the tower crane by combining the real-time data of the sensor with the dynamic optimization function, ensuring that the tower crane always moves along the optimal path while avoiding collisions and path deviations, and realizing dynamic and precise control of the tower crane boom based on the control data calculated by the optimization control system; The dynamic optimization function is: ， Wherein, u is the control input; the time interval [t, t+T] is the time window from the current time t to the future time t+T, which is used to indicate that the path should be optimized within this period of time; ， It is used to penalize the speed change of the path, so as to achieve path smoothness; where x(t) represents the change of the horizontal position of the tower crane over time, and y(t) represents the change of the vertical position of the tower crane over time; and are the speeds of the tower crane in the x and y directions at time t, respectively. The sum of the squares of the speeds reflects the magnitude of the speed change, which is used to penalize rapid changes in the path and encourage path smoothness. α is a weight coefficient used to adjust the degree of influence of speed smoothness. Used to penalize the effects of wind, is the disturbance torque caused by wind force at time t, which is used to reduce the impact of wind; β is the weight coefficient used to adjust the penalty degree of wind impact; Penalty for collision, is an indicator function used to detect whether the path enters the collision area. If a collision occurs, that is, the tower crane path enters the conflict area, then ; If there is no collision, that is, the crane path does not enter the conflict area, then , γ is the weight coefficient used to adjust the impact of collision penalty.

2. The method for intelligent planning and dynamic control of tower crane paths in bridge construction according to claim 1 is characterized in that: The construction of the bridge construction digital twin model includes the following steps: S110, conduct high-precision scanning of the bridge construction site to collect static and dynamic element data of the construction site; S120, generating a three-dimensional digital model of the construction site according to the three-dimensional point cloud data obtained by scanning, and constructing a detailed model of the tower crane, wherein the detailed model of the tower crane is constructed by drawing a lifting path according to the maximum lifting radius and movable range of the tower crane, and creating working models of the tower crane at different stages based on the installation position and lifting path of the tower crane; S130, modeling each stage of bridge construction, constructing a dynamic bridge construction digital twin model including the evolution of the construction stage, and associating the dynamic bridge construction digital twin model including the evolution of the construction stage with the tower crane working models at different stages; S140. After completing the construction of the detailed model of the tower crane, sensors are installed at key locations of the tower crane, hoisted objects, and bridge components to collect location information, load, status, and weather condition data in real time. Environmental monitoring sensors are arranged at the construction site to obtain meteorological data and detect dynamic changes in the construction area, and the collected data is transmitted to the digital twin platform. S150. After receiving the data, the digital twin platform constructs a tower crane sensor database, a construction site sensor database, and a hoisted object sensor database according to the type of sensor data. The data in all databases will be used as input information to dynamically update the bridge construction digital twin model to display the real-time relationship between the tower crane and the construction site.

3. An intelligent planning and dynamic control system for tower crane paths in bridge construction, characterized in that: The dynamic control system includes a bridge construction digital twin model module, a safe path planning module, an optimization control module and a dynamic control module, wherein: The bridge construction digital twin model module is configured to perform high-precision scanning of the bridge construction site and collect static and dynamic element data of the construction site; generate a three-dimensional digital model of the construction site based on the three-dimensional point cloud data obtained from the scan, and construct a detailed model of the tower crane. The detailed model of the tower crane includes drawing a lifting path based on the maximum lifting radius and movable range of the tower crane, and creating tower crane working models at different stages based on the tower crane installation position and lifting path; modeling each stage of bridge construction, constructing a dynamic bridge construction digital twin model that includes the evolution of the construction stages, and integrating the dynamic bridge construction digital twin model that includes the evolution of the construction stages with the tower crane working models at different stages. After the detailed model of the tower crane is built, sensors are installed at key locations of the tower crane, hoisted objects, and bridge components to collect location information, load, status, and weather condition data in real time. Environmental monitoring sensors are arranged at the construction site to obtain meteorological data and detect dynamic changes in the construction area, and the collected data is transmitted to the digital twin platform. After receiving the data, the digital twin platform builds a tower crane sensor database, a construction site sensor database, and a hoisted object sensor database according to the type of sensor data. The data in all databases will be used as input information to dynamically update the bridge construction digital twin model to display the real-time relationship between the tower crane and the construction site. The safety path planning module is connected to the bridge construction digital twin model module. The safety path planning module is configured to incorporate the construction progress data into the constructed bridge construction digital twin model, synchronously update the tower crane's operation tasks and lifting targets according to the construction progress data, adjust the tower crane's state in the bridge construction digital twin model according to the construction progress data, and calculate the tower crane's path according to the real-time sensor data combined with the tower crane path planning algorithm to obtain the optimal safety path of the tower crane in space and time; The optimization control module is connected to the safety path planning module. The optimization control module is configured to construct an optimization control system in combination with a tower crane path planning algorithm, and obtain changes in the surrounding environment of the tower crane in real time through the sensor real-time data collection bridge construction digital twin model, so that the bridge construction digital twin model can reflect the relative position between the tower crane and obstacles; The dynamic control module is connected to the optimization control module. The dynamic control module is configured to automatically adjust the movement direction of the tower crane or slow down the crane according to the relative position between the tower crane and the obstacle and the real-time feedback data from the sensor. If the tower crane is found to deviate from the predetermined path or there is a potential collision risk, the dynamic control module is configured to automatically adjust the movement direction of the tower crane or slow down the crane according to the relative position between the tower crane and the obstacle and the real-time feedback data from the sensor. When there are multiple tower cranes working together at the construction site, the collaborative control method of the digital twin platform is used to ensure mutual coordination and avoidance between the tower cranes to avoid conflicts. The safety path planning module includes: a tower crane dynamic motion subunit and a constraint subunit, wherein: The tower crane dynamic motion subunit is constructed by considering the three main motions of the tower crane, horizontal motion, vertical motion and the change of the boom angle, with x as the horizontal position of the tower crane in meters; y as the vertical position of the tower crane in meters; θ as the angle of the boom in degrees or radians, where The horizontal movement of the tower crane is expressed as: ， In the formula, is the horizontal force of the tower crane, and m is the mass of the tower crane. The horizontal acceleration of the tower crane is determined by the horizontal force applied to it. The horizontal position of the tower crane will change over time, and the magnitude and direction of the force will directly affect its motion state. The vertical movement of the tower crane is expressed as: ， In the formula, is the force of the tower crane in the vertical direction; The change of the tower crane's boom angle is expressed as: ， Where, I is the inertia moment of the boom; T is the control moment of the tower crane; τ wind is the disturbance torque caused by wind; t represents time. All variables with t in the above formula are functions of time. x(t) represents the change of the horizontal position of the tower crane over time, and y(t) represents the change of the vertical position of the tower crane over time. represents the horizontal force that changes with time, F y (t) represents the vertical force that changes with time, θ(t) represents the angle of the boom that changes with time, T(t) represents the control torque of the tower crane that changes with time, and τ wind (t) represents the variation of the disturbance torque caused by wind with time; The constraint subunits include: boom force constraint, boom angle constraint, motion restriction constraint and wind impact constraint, among which: The arm force constraint is used to indicate that the gravity of the load will affect the force of the arm, thereby indirectly affecting the vertical and horizontal acceleration of the tower crane, which is expressed by the following formula: ， In the formula, m load is the load mass, m load (t) is the change of load mass over time; g is the acceleration due to gravity; F load (t) is the force due to the weight of the load at time t, which affects the motion state of the tower crane; The boom angle constraint is used to indicate that the boom angle changes with the position of the tower crane, which is expressed by the following formula: ， Where x(t) is the horizontal position of the crane, in meters; y(t) is the vertical position of the crane, in meters; θ(t) represents the change of the boom angle over time; The motion limit constraint is used to describe the speed limit of the tower crane and is expressed by the following formula: ， In the formula, v max (m load (t)) is the maximum motion speed under load at time t; Wind impact constraints By taking into account the impact of wind, the control system can make more precise adjustments to ensure that the boom remains stable under the action of wind and prevent excessive swing or instability of the boom: ， In the formula, τ wind is the disturbance torque caused by wind, τ wind (t) represents the change of disturbance torque caused by wind over time, ρ is the air density, A wind is the windward surface area of ​​the tower crane boom, v wind represents wind speed, v wind (t) represents the change of wind speed over time; t represents time. All variables with t in the above formula are functions of time. The dynamic control module distinguishes the tower crane moving along the optimal path in water according to the dynamic optimization function, while avoiding collision and path deviation. The dynamic optimization function is: ， Wherein, u is the control input; the time interval [t, t+T] is the time window from the current time t to the future time t+T, which is used to indicate that the path should be optimized within this period of time; ， It is used to penalize the speed change of the path, so as to achieve path smoothness; where x(t) represents the change of the horizontal position of the tower crane over time, and y(t) represents the change of the vertical position of the tower crane over time; and are the speeds of the tower crane in the x and y directions at time t, respectively. The sum of the squares of the speeds reflects the magnitude of the speed change, which is used to penalize rapid changes in the path and encourage path smoothness. α is a weight coefficient used to adjust the degree of influence of speed smoothness. Used to penalize the effects of wind, is the disturbance torque caused by wind force at time t, which is used to reduce the impact of wind; β is the weight coefficient used to adjust the penalty degree of wind impact; Penalty for collision, is an indicator function used to detect whether the path enters the collision area. If a collision occurs, that is, the tower crane path enters the conflict area, then ; If there is no collision, that is, the crane path does not enter the conflict area, then , γ is the weight coefficient used to adjust the impact of collision penalty.

4. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, Implement the steps of the method for intelligent planning and dynamic control of tower crane paths in bridge construction as described in any one of claims 1 to 2.

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