Intelligent planning and dynamic control method and system for tower crane path in bridge construction and medium

Abstract

The invention discloses a tower crane path intelligent planning and dynamic control method and system in bridge construction and a medium, and belongs to the field of bridge construction.The method comprises the steps that a bridge construction digital twinborn model is constructed and used for describing the state and position of a tower crane; the construction progress data is incorporated into the constructed digital twinborn model, the operation task and the hoisting target of the tower crane are synchronously updated according to a construction progress plan, and the state of the tower crane is adjusted in the digital twinborn model according to the construction progress; an optimization control system is constructed in combination with a tower crane path planning algorithm, and the change of the surrounding environment of the tower crane is obtained in real time through a sensor real-time data set digital twin model, so that the digital twin model can reflect the relative position between the tower crane and an obstacle; according to the relative position between the tower crane and the obstacle and the data fed back by the sensor in real time, if the position of the tower crane deviates from a preset path or potential collision risks occur, the movement direction of the tower crane is automatically adjusted or the tower crane decelerates. The collision risk can be effectively avoided.

Description

Technical Field

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

[0002] Tower cranes are usually needed for heavy lifting in bridge construction, but traditional tower crane path planning methods have certain defects. When planning tower crane paths, existing technologies often fail to fully consider factors such as the dynamic changes in the construction environment and the impact of load conditions, resulting in insufficient accuracy and safety in path planning, and problems such as path deviation and collision risks.

[0003] Specifically, the traditional method lacks real-time perception and dynamic update of the construction site environment when planning the tower crane path, and cannot timely detect and avoid dynamic obstacles on the construction site, such as construction personnel, vehicles, and other mechanical equipment, which may cause collision risks. At the same time, the traditional method does not fully consider the impact of load status, such as load size, weight distribution, etc., when planning the path. These factors will directly affect the movement trajectory, speed, acceleration, etc. of the tower crane, and thus affect the accuracy of path planning. In addition, the traditional method cannot make dynamic adjustments based on real-time data after path planning. Once the construction environment or load status changes, the planned path may deviate and operational safety cannot be guaranteed.

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

[0005] One of the purposes of the present invention is to provide a method for intelligent planning and dynamic control of tower crane paths 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 implemented by the following technical scheme, a method for intelligent planning and dynamic control of tower crane path in bridge construction, comprising the following steps: S100, constructing a bridge construction digital twin model, the bridge construction digital twin model includes the environment and dynamic factors in the construction process, and can describe the state and position of the tower crane; S200, incorporating the construction progress data into the constructed bridge construction digital twin model, synchronously updating the operation tasks and hoisting targets of the tower crane according to the construction progress data, adjusting the state of the tower crane in the bridge construction digital twin model 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, 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 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 the obstacle; S400, according to the relative position between the tower crane and the obstacle and the real-time feedback data from the sensor, if it is found that the tower crane position deviates from the predetermined path or there is a potential collision risk, automatically adjust the movement direction of the tower crane or slow down,

[0007] Furthermore, constructing a digital twin model of bridge construction includes the following steps: S110, 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 based on the three-dimensional point cloud data obtained from the scan, 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 tower crane working models at different stages based on the tower crane installation position and lifting path; S130, modeling each stage of bridge construction, constructing a dynamic bridge construction digital twin model including the evolution of the construction stage, and comparing the dynamic bridge construction digital twin model including the evolution of the construction stage with different The digital twin platform is associated with the working model of the tower crane in the current stage; S140. After completing the construction of the detailed model of the tower crane, sensors are installed at key positions of the tower crane, hoisted objects, and bridge components to collect real-time data such as location information, load, status, and weather conditions. 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 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, the tower crane path is finely planned according to the actual use of the tower crane and the sensor data in the digital twin model of the bridge construction.

[0009] Furthermore, the dynamic motion model of the tower crane is constructed by considering the three main motions of the tower crane, namely 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; and θ being the angle of the boom in degrees or radians. The horizontal motion of the tower crane is expressed as:

[0010] , where 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 motion of the tower crane is expressed as:

[0011] , where is the vertical force of the tower crane; the change in the boom angle of the tower crane 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.

[0012] Furthermore, the constraint model includes: boom force constraint, boom angle constraint, motion restriction constraint and wind impact constraint, wherein the boom force constraint is used to indicate that the gravity of the load will affect the force of the boom, thereby indirectly affecting the vertical and horizontal acceleration of the tower crane, which is expressed by the following formula: , where m load ( t ) is the load mass; g is the acceleration due to gravity; F load ( t) is the force borne by the load due to the gravity 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; i ( t ) represents the variation of the boom angle with time; x ( t ) represents the change of the horizontal position of the tower crane over time, y ( t ) represents the change of the vertical position of the tower crane with time; 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 speed of motion under load at time t; Wind impact constraint By considering 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: , where t wind is the disturbance torque caused by wind, t wind ( t ) represents the variation of the disturbance torque caused by wind over time, r is the air density, A wind is the windward surface area of ​​the tower crane boom, v wind Indicates wind speed, v wind ( t ) represents the change of wind speed over time.

[0013] Furthermore, an optimization control system is constructed to dynamically adjust 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. At the same time, dynamic and precise control of the tower crane arm is achieved based on the control data calculated by the optimization control system.

[0014] Furthermore, the dynamic optimization function is:

[0015] , 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 indicate that the path should be optimized within this period of time;

[0016] , used to penalize the speed change of the path, thereby achieving 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 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.

[0017] On the other hand, the present invention provides an intelligent planning and dynamic control system for tower crane paths in bridge construction, the system comprising: 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 by the scan, and construct a fine model of the tower crane, wherein the construction of the fine model of the tower crane comprises drawing a lifting path according to 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; and performing high-precision scanning of each stage of the bridge construction. The digital twin model of the bridge construction that includes the evolution of the construction stages is constructed, and the dynamic digital twin model of the bridge construction that includes the evolution of the construction stages is associated with the tower crane working models at different stages; 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 position information, load, status, and weather condition data in real time, and 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 constructs a tower crane sensor database, a construction site sensor database, and a hoisted object sensor database according to the type of sensor data, and stores all the data The data in the database 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 safe path planning module is connected to the bridge construction digital twin model module, and the safe path planning module is configured to incorporate the construction progress data into the constructed bridge construction digital twin model, and synchronously update the tower crane's operating tasks and lifting targets according to the construction progress data, and adjust the tower crane's status in the bridge construction digital twin model according to the construction progress data, and calculate the tower crane's path based on the real-time sensor data combined with the tower crane path planning algorithm to obtain the tower crane's optimal safe path in space and time; the optimization control module is connected to the safe path planning module, and the optimization control module The block is configured to build an optimization control system in combination with the tower crane path planning algorithm, and obtain the 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 the obstacle; the dynamic control module is connected to the optimization control module, and the dynamic control module is configured to automatically adjust the movement direction of the tower crane or slow down if it is found that the tower crane position deviates from the predetermined path or there is a potential collision risk 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.

[0018] Furthermore, the safe 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 change of the boom angle, with x(t) being the horizontal position of the tower crane in meters; y(t) being the vertical position of the tower crane in meters; θ(t) being the angle of the boom in degrees or radians, wherein the horizontal motion of the tower crane is expressed as: , where F x (t) 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 directly affect its motion state. The vertical motion of the tower crane is expressed as: , where F y (t) is the vertical force of the tower crane; the change in the boom angle of the tower crane is expressed as: , where I is the inertia moment of the boom; T(t) is the control torque of the tower crane; τ wind (t) is the disturbance torque caused by wind; the constraint subunits include: boom force constraint, boom angle constraint, motion restriction constraint and wind impact constraint, among which the boom force constraint is used to indicate that the gravity of the load will affect the force of the boom, thereby indirectly affecting the vertical and horizontal acceleration of the tower crane, which is expressed by the following formula: F load (t) = m load (t)·gIn the formula, m load (t) is the load mass; g is the gravitational acceleration; 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: θ(t)=arctan ( ), where x(t) is the horizontal position of the crane in meters; y(t) is the vertical position of the crane in meters; the motion limit constraint is used to describe the speed limit of the crane, which is expressed by the following formula: , where v max (m load (t)) is the maximum speed of movement under load; Wind impact constraint By considering 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: , where τ wind (t) is the disturbance torque caused by wind, ρ is the air density, A wind is the windward surface area of ​​the tower crane boom.

[0019] On the other hand, the present invention provides a computer-readable storage medium having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, the steps of the method for intelligent planning and dynamic control of tower crane paths in bridge construction as described above can be implemented.

[0020] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0021] 1. The present invention constructs a digital twin model of bridge construction that includes a tower crane, construction environment, and hoisted objects, and uses multi-source sensors to collect real-time data such as the tower crane position, load status, and environmental data to dynamically update the model. It can accurately reflect the dynamic changes of the construction site, promptly discover and avoid dynamic obstacles, and effectively avoid collision risks.

[0022] 2. The present invention fully considers the influence of load status, such as load size, weight distribution, etc., during path planning, and incorporates it into the tower crane dynamics model, load influence model, etc., thereby improving the accuracy of path planning. The planned path is dynamically adjusted through a dynamic optimization function combined with real-time data. Once the construction environment or load status changes, the path can be optimized and adjusted in time to avoid path deviation, ensuring that the tower crane runs along the optimal path, thereby improving operational safety.

[0023] 3. The collaborative control method of the digital twin platform can achieve mutual 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

[0024] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0025] Figure 1 This is a flow chart of the method provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, 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 in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0027] Embodiment 1,

[0028] In this embodiment, a method for intelligent planning and dynamic control of tower crane paths in bridge construction is provided. Figure 1The flow chart of the path intelligent planning and dynamic control method in this embodiment is shown. It can be seen from the figure that this implementation includes the following steps:

[0029] Step 1: Construction and data collection of digital twin model of bridge construction. First, an accurate, real-time and synchronized digital twin model of bridge construction is created to reflect the dynamic information such as the working status of the tower crane, construction progress, environmental changes, etc. 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 function of the tower crane is to hoist various heavy objects, such as prefabricated bridge sections, reinforced concrete components, bridge steel structures, etc., to ensure that these materials can be moved to designated locations efficiently and safely. Therefore, in constructing the digital twin model of bridge construction of the construction bridge, it is necessary not only to accurately describe the status and position of the tower crane, but also to take into account the environmental and dynamic factors of the entire construction process.

[0030] Specifically, it includes the following:

[0031] First, LiDAR and unmanned aerial vehicles (UAVs) were used to perform high-precision scans of the bridge construction site to collect data on all static and dynamic elements, including the bridge structure, crane equipment, steel, precast beams, concrete structures, etc.

[0032] Based on the 3D point cloud data obtained by scanning, a 3D digital model of the construction site is generated through modeling software. Special attention should be paid to ensuring that the details of the model are accurate enough in key areas such as tower crane installation, lifting points, and construction roads.

[0033] In particular, the tower crane itself needs to be modeled in detail, including its structure (tower, boom, lifting and lowering mechanism, hook, etc.). And the lifting path needs to be drawn 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, the tower crane working model at different stages is created. For example, the position and lifting height of the tower crane will change at different stages of bridge construction, and these changes need to be gradually updated to the bridge construction digital twin model.

[0034] At the same time, the various stages of bridge construction must be modeled. Considering the structural changes in bridge construction, such as the installation of precast bridge segments, concrete pouring, bridge deck laying, etc., a dynamic bridge construction digital twin model that includes the evolution of construction stages is created. After the models of each stage in the bridge construction process are built, it is necessary to ensure that these stage models can be associated with the tower crane model. For example, when hoisting, the bridge position, the weight of the hoisted object, the shape of the hoisted object, the access point, etc. need to be considered.

[0035] After completing the tower crane model construction, sensors are installed at key locations such as the tower crane, hoisted objects, and various bridge components to collect data such as location information, load, status, and weather conditions in real time, and transmit them to the central control system through the Internet of Things (IoT) system.

[0036] Position sensors (such as GPS, IMU), load sensors (for monitoring hoisting weight), angle sensors (for monitoring boom angle), and vibration sensors (for detecting dynamic vibration during lifting) are installed at key locations of the tower crane to obtain real-time data on the position, load status, and operating speed of the tower crane, and transmit these data to the central control system through the Internet of Things (IoT) devices.

[0037] At the same time, environmental monitoring sensors are arranged at the construction site to obtain meteorological data (wind speed, temperature, humidity, etc.) and dynamic changes in the construction area (such as material stacking, construction road conditions, traffic conditions, etc.).

[0038] If the construction site is large, especially when the bridge spans a river or complex terrain, drones can be used with lidar to scan the surrounding environment in real time and update the obstacle information in the model.

[0039] Each bridge component being hoisted (such as precast bridge segments, steel beams, etc.) should be equipped with sensors to monitor its weight, hoisting position and dynamic response.

[0040] The data collected by the sensor data is transmitted to the digital twin platform in real time through the Internet of Things (IoT) system to provide real-time feedback on the hoisting operation. After receiving the data sent by the sensor, the digital twin platform builds a tower crane sensor database, a construction site sensor database, and a hoisting object sensor database according to the type of sensor data. The sensor data in all databases will be used as input information to dynamically update the tower crane position, hoisting object status, environmental conditions, etc. Through data fusion technology, data from multiple sources (tower crane sensors, environmental sensors, construction data, etc.) are integrated to achieve accurate synchronization and sharing of data, which is used to generate a visual interface on the digital twin platform to display the real-time relationship between the tower crane and the construction site.

[0041] Step 2: Incorporate construction progress data into the constructed bridge construction digital twin model. For example, at different construction stages, the corresponding bridge structure and tower crane positions in the model will change dynamically. Building information modeling can be used to combine the bridge construction plan and the bridge construction digital twin model to achieve full visualization of the construction process.

[0042] Based on the construction progress data, the tower crane's operation tasks and lifting targets are updated synchronously. For example, each task in the construction progress data (such as prefabricated bridge segment lifting, concrete pouring, etc.) is associated with the tower crane operation and integrated with environmental dynamic conditions (such as wind speed and temperature).

[0043] At the same time, as the construction progresses, the tower crane's path and load status will change. For example, at different stages, the tower crane's lifting radius may change, and the objects of the lifting task may also be different. The bridge construction digital twin model needs to automatically adjust the tower crane's working area, boom angle, lifting path, etc. according to the construction progress data.

[0044] When the tower crane is actually in operation, the bridge construction digital twin model will calculate the tower crane's path based on real-time data and the tower crane path planning algorithm, and plan and dynamically correct the tower crane path based on the calculated results. If there is an emergency during the hoisting process (such as excessive wind speed, abnormal load, etc.), the bridge construction digital twin model will adjust the hoisting path based on the real-time data of the sensor and reflect it to the construction site through the digital twin platform.

[0045] Specifically, the tower crane path planning algorithm fully considers the actual use of the tower crane and combines the mathematical model of the impact of sensor data (such as tower crane position, load status and environmental data) in the bridge construction digital twin model on the fine planning of the tower crane path.

[0046] The mathematical model includes the dynamic motion model of the tower crane (including changes in the tower crane position and boom angle); the impact of load status on the tower crane path (such as the restrictions of load size and position on the boom angle and movement speed); the impact of environmental factors on the tower crane movement (such as wind speed, temperature, humidity, etc.); and path planning optimization objectives (such as shortest path, safety optimization, load stability, etc.).

[0047] In this embodiment, a tower crane path planning mathematical model is constructed by combining partial differential equations, sensor data and load influence. The model takes into account the dynamic movement of the tower crane, the influence of load and environmental factors, and the optimization goals of path planning (such as shortest path, safety, and load stability). In practical applications, this algorithm is combined with digital twin technology to adjust the path planning in real time to ensure efficient and safe operation of the tower crane.

[0048] Specifically include:

[0049] 1) Constructing the position and velocity model: To construct the position and velocity model of the tower crane, it is necessary to consider the three main movements of the tower crane: horizontal movement, vertical movement, and change in the boom angle. Let: x is the horizontal position of the tower crane, in meters; y is the vertical position of the tower crane, in meters; θ is the angle of the boom, in degrees or radians. The dynamic movement of the tower crane can be described by the following motion equation:

[0050] The horizontal movement of the tower crane can be expressed as:

[0051] ,

[0052] in, 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 with time, and the size and direction of the force will directly affect its state of motion.

[0053] The vertical movement of the tower crane can be expressed as:

[0054] ,

[0055] F y is the vertical force of the tower crane.

[0056] Among them, the change of the tower crane's boom angle can be expressed as:

[0057] ,

[0058] Where I is the inertia moment of the boom; T is the control torque of the tower crane; τ wind is the disturbance torque caused by wind. Through this equation, the change of the boom angle can be described. The boom angle is not only affected by the tower crane control system, but may also be disturbed by external factors (such as wind).

[0059] It should be noted that in the above formula, 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.

[0060] 2) During the operation of the tower crane, considering that the tower crane is not just a simple motion system, it is also necessary to consider the impact of the load on the tower crane trajectory. Usually the weight and distribution of the load will affect the movement trajectory, speed, acceleration and other aspects of the tower crane, especially the angle of the boom and the movement limit of the tower crane.

[0061] Assume the mass of the load is m load (t) changes with time, the state of the load will affect the motion model of the tower crane. Specifically, the change of load will affect the mass m of the tower crane and the moment of inertia I of the boom, thereby changing the motion response of the tower crane under different working conditions.

[0062] It should be noted that, in general, the load mass m on the tower crane is load (t) is constant, especially in the following two cases: Fixed load: If there is a fixed weight on the tower crane and no loading or unloading operations are performed for a period of time, the load mass can be considered 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 load changes during the lifting process are not considered.

[0063] However, it is considered that the situation of lifting materials by the tower crane during the construction process is relatively complicated, and the load may change during the lifting process, for example: Unloading: The tower crane may unload part or all of the load at certain locations (for example, unloading a part of the cargo from the boom). Loading: The tower crane may also lift more materials at certain times, resulting in an increase in the load mass. Load unloading and loading rate: The rate of change of the load mass may be very small, and sometimes it can be regarded as a continuous change. However, in actual construction, the change of load is sometimes regarded as a discrete change (for example, loading or unloading an item of fixed mass at a time). Considering different loads at the same time, if the tower crane is lifting multiple independent items, the mass of these items may also be different, and the lifting time of each item is different, resulting in the load mass changing over time. Therefore, in this embodiment, by assuming that the tower crane load mass changes over time, the influence of the load state on the boom trajectory is more accurately described.

[0064] Specifically, the influence of the load state on the boom trajectory can be described by the following constraints:

[0065] 1. Force constraints on the boom:

[0066] ,

[0067] 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 gravity of the load at time t, which affects the motion 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 acceleration of the tower crane. This gravity 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 complicated. That is, F load (t) will affect the acceleration and angular acceleration of the tower crane, thus affecting the motion response of the tower crane.

[0068] 2.Boom angle constraint:

[0069] ,

[0070] 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 in the angle of the boom over time; this constraint is used to indicate that changes in the horizontal and vertical positions of the crane will affect the angle of the boom. The angle of the boom will affect how the crane carries the load, especially when the load is heavy, the boom angle may need to be further adjusted to remain stable. This is very important for path planning, because the trajectory of the crane must ensure that the boom angle remains within a safe range under the load. That is, θ(t) changes with the horizontal and vertical positions of the crane, and the boom angle is closely related to the stability of the load, affecting how the crane carries the load.

[0071] 3. Movement restrictions:

[0072] ,

[0073] In the formula, v max (m load (t)) is the maximum speed of movement under load 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 horizontal speed of the tower crane v max When the load is large, the speed of the tower crane must be limited to prevent excessive speed from causing the boom to become unstable or the load cannot be accurately controlled. max (m load (t)) is a load-related speed upper limit, whose value depends on the current load m load (t) The larger the load, the lower the upper speed limit of the crane. This is because larger loads make it more difficult to control and move the crane.

[0074] 4. Wind impact constraints:

[0075] ,

[0076] In the formula, τ windis 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 The windward surface area of ​​the tower crane boom, that is, the surface area of ​​the tower crane boom that the wind directly hits. Usually, this area is related to the length and structural shape of the tower crane boom. A larger windward area means a stronger impact of the wind. wind represents wind speed, v wind (t) represents the change of wind speed over time. This constraint indicates that the greater the wind speed, the greater the moment of the tower crane affected by the wind. The square relationship of wind speed means that the influence of wind speed on the boom is nonlinear, that is, the influence increases rapidly when the wind speed increases. By considering the influence of wind, the control system of the tower crane needs to be adjusted more accurately to ensure that the boom remains stable under the action of wind force and prevent the boom from swinging excessively or becoming unstable.

[0077] 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 constraints, a mathematical model for tower crane path planning is constructed. Through this model, the bridge construction digital twin model will take into account the influence of multiple variables when planning the tower crane path, thereby determining the speed, acceleration and boom angle of the movement. This makes path planning not only about the idle movement of the tower crane, but also must take into account the influence of the load to ensure the stability and efficiency of the tower crane under different conditions.

[0078] The tower crane path planning algorithm is constructed by combining the data from the tower crane sensor database, the construction site sensor database, and the hoisting object sensor database. The data is input into the tower crane path planning algorithm for real-time processing, and the processed data is fed back to the bridge construction digital twin model to realize the intelligent path planning of the tower crane. By combining real-time data with the tower crane path planning algorithm, dynamic adjustment of path planning can be achieved to ensure the safety and efficiency of tower crane movement. The specific control strategy can process the results calculated by the tower crane path planning algorithm in combination with methods such as PID controller or fuzzy control.

[0079] Step 3: After obtaining the optimal safe path of the tower crane in space and time through the tower crane path planning algorithm combined with sensor data, in order to achieve real-time dynamic adjustment of the tower crane during the construction process, it is necessary to combine the previous tower crane path planning algorithm and dynamic optimization function to build an optimization control system that can monitor, analyze and adjust the path in real time. Through real-time data feedback, combined with the dynamic optimization function, the speed, boom angle and other motion parameters of the tower crane can be dynamically adjusted to ensure that the tower crane always moves along the optimal path while avoiding possible collisions and path deviations.

[0080] In actual operation, the movement of the tower crane will be affected by many factors, such as wind speed, load size, tower crane position, etc. Therefore, it is necessary to combine the data in the sensor database and feed it back 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.

[0081] Specifically, the dynamic optimization function is:

[0082] ,

[0083] Here, u represents the control input, which usually refers to physical quantities such as the speed and acceleration of the tower crane, which affects the behavior and path of the system.

[0084] It should be noted that the design idea of ​​the dynamic optimization function is to optimize the control variable u so that the movement path of the tower crane reaches a certain optimal goal within a specified time interval [t, t+T]. Each term in the function corresponds to a different goal that needs to be optimized in path planning, such as path smoothness, wind impact, and collision avoidance.

[0085] 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 is to be optimized within this period of time. , which is used to penalize the speed change of the path, thereby achieving path smoothness. and They represent the speed of the 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. This setting can 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. The larger the value, the more the system tends to choose a smooth path.

[0086] Used to penalize the effect of wind, where τ wind (t) is the disturbance torque caused by the wind at time t. The impact of wind on tower cranes is usually not negligible, especially in outdoor environments. By optimizing the control path, the impact of wind can be minimized. β is a weight coefficient that determines the degree of penalty for wind impact. The larger the value, the greater the wind impact, and the path planning will tend to avoid areas with strong winds.

[0087] 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. It should be noted that The specific manifestation of can be defined by technical personnel in this field according to the actual construction situation, and the collision area can be calculated according to the construction situation to see whether the tower crane path enters these areas. For example, spatial judgment can be defined according to the specific construction situation. Common ones 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 tower crane path intersects with the bounding box of the obstacle. Alternatively, the distance threshold method can be used. 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 suitable for dynamic environments. When the tower crane approaches an obstacle, a collision may be triggered.

[0088] The dynamic optimization function combines real-time data with the bridge construction digital twin model to obtain real-time changes in the environment around the tower crane, especially dynamic obstacles (such as construction personnel, vehicles, other mechanical equipment, etc.). Through this dynamic update, the bridge construction digital twin model can accurately reflect the relative position between the tower crane and obstacles, helping to promptly detect potential collision risks.

[0089] Based on digital twin technology, the crane's motion model and the three-dimensional environment model of the construction site can be connected in real time, and the relative distances between the crane's components and obstacles in the environment can be accurately calculated through dynamic optimization functions. When these distances are less than a certain threshold, the model will immediately issue a collision alarm and feed back to the crane's path planning algorithm to adjust the crane's motion trajectory to avoid collisions.

[0090] Step 4: The digital twin platform uses the PID control algorithm to achieve dynamic and precise control of the tower crane arm based on the control data calculated by the optimization control system. Based on the real-time feedback data from the sensor, if the tower crane position deviates from the predetermined path or there is a potential risk of collision, the system will automatically adjust the movement direction of the tower crane or slow down. 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 mutual coordination and avoidance between the tower cranes to avoid conflicts. By adopting distributed control, each tower crane can make autonomous decisions through dynamic optimization functions based on its own local information data, but also maintain global coordination with other tower cranes.

[0091] If the construction site changes (such as the appearance of new obstacles, weather changes, etc.), the tower crane's path can be automatically corrected based on the sensor data. With real-time data updates, the path planning algorithm can recalculate the optimal path and instantly instruct the tower crane to perform corrective actions.

[0092] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection 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 a construction site, the collaborative control method of the digital twin platform can be used to ensure mutual coordination and avoidance between the tower cranes to avoid conflicts.

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. The method for intelligent planning and dynamic control of tower crane paths in bridge construction according to claim 1 is characterized in that: 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, 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.

4. The method for intelligent planning and dynamic control of tower crane paths in bridge construction according to claim 3 is characterized in that: 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.

5. The method for intelligent planning and dynamic control of tower crane paths in bridge construction according to claim 3 is characterized in that: 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 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 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.

6. The method for intelligent planning and dynamic control of tower crane paths in bridge construction according to claim 1 is characterized in that: The constructed 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. At the same time, based on the control data calculated by the optimization control system, dynamic and precise control of the tower crane arm is achieved.

7. The method for intelligent planning and dynamic control of tower crane paths in bridge construction according to claim 6 is characterized in that: 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.

8. 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 module will automatically adjust the movement direction of the tower crane or slow down the crane. 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.

9. The intelligent planning and dynamic control system for tower crane paths in bridge construction according to claim 8, characterized in that: 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.

10. 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 7.

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