Intelligent hoisting control method and system of bridge girder erection machine and computer program product

Abstract

The invention discloses an intelligent hoisting control method and system for a bridge girder erection machine and a computer program product. The intelligent hoisting control method comprises the following steps: firstly, monitoring wind speed distribution data around a girder body, dip angle data, position data and weight data of the girder body in real time; and then dynamically optimizing the hoisting path of the beam body by adopting a trajectory optimization algorithm based on the currently obtained wind speed distribution data, inclination angle data and position data. And then wind speed data and inclination angle data of the beam body at the next track point are predicted by optimizing the path. And calculating the tension required to be borne by each sling at the next track point by combining the predicted wind speed data, inclination angle data and weight data. And finally, respectively calculating length data corresponding to each sling in combination with the corresponding initial length and tension so as to adjust the length of each sling at the next track point. In this way, construction is globally optimized and dynamically adjusted in combination with real-time construction data, the method can adapt to constantly changing environmental conditions, and it is ensured that the beam body stably and efficiently moves according to the planned path.

Description

Technical Field

[0001] The present invention relates to the technical field of controlling the movement of suspended loads, and more particularly to an intelligent hoisting control method and system for a bridge erecting machine, and a computer program product. Background Art

[0002] Traditional bridge erecting machines usually rely on manual operation or semi-automatic control during construction, with a low degree of intelligence in the construction process. It is difficult to integrate real-time data at the construction site, such as the state of the beam body, environmental conditions, and operation progress, and it is impossible to globally optimize and adjust the construction according to the real-time data at the construction site. This results in low construction accuracy and speed, high construction costs, and high safety hazards. Summary of the Invention

[0003] In view of the deficiencies of the prior art, the present invention proposes an intelligent hoisting control method and system for a bridge erecting machine, and a computer program product, which can globally optimize and adjust the construction in real time. The specific technical solutions are as follows: In a first aspect, an intelligent hoisting control method for a bridge erecting machine is provided. In a first possible implementation manner of the first aspect, it includes: Obtain the weight data, inclination data, and position data of the beam body hoisted by the bridge erecting machine, as well as the wind speed distribution data around the beam body and the initial length of each suspension cable of the bridge erecting machine when there is no tension. Based on the wind speed distribution data, inclination data, and position data, use a trajectory optimization algorithm to dynamically optimize the hoisting path of the beam body. Determine the corresponding inclination data and wind speed data when the beam body is at the next trajectory point according to the hoisting path. Determine the tension that each suspension cable of the bridge erecting machine needs to bear when the beam body is at the next trajectory point according to the inclination data, wind speed data, and weight data. Combine the corresponding initial length and tension, and calculate the corresponding length data of each suspension cable at the next trajectory point respectively. When the beam body moves to the next trajectory point, adjust the length of each suspension cable according to the corresponding length data.

[0004] Combined with the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, using a trajectory optimization algorithm to dynamically optimize the hoisting path of the beam body includes: According to the wind speed distribution data, inclination data, and position data, use the A* algorithm to optimize the hoisting path of the beam body.

[0005] Combined with the second possible implementation manner of the first aspect, in a third possible implementation manner of the first aspect, the cost function corresponding to the A* algorithm is: ; Wherein, is the cumulative cost of the path length, is the node at the wind speed, is the inclination angle of the beam body at the node where, is the maximum allowable safe inclination angle of the beam body, 、 are the weight coefficients corresponding to the wind speed and the inclination angle respectively, is the heuristic function.

[0006] Combined with the third implementation manner of the first aspect, in the fourth implementation manner of the first aspect, the Euclidean distance is used as the heuristic function.

[0007] Combined with the first implementation manner of the first aspect, in the fifth implementation manner of the first aspect, when determining the tension that each sling needs to bear when the beam body is at the next trajectory point, it includes: Establish the force balance equation and the moment balance equation of the beam body; Based on the inclination angle data, the wind speed data and the weight data, use numerical methods to solve the force balance equation and the moment balance equation to obtain the tension that each sling needs to bear when the beam body is at the next trajectory point.

[0008] Combined with the first implementation manner of the first aspect, in the sixth implementation manner of the first aspect, the specific calculation formula of the length data corresponding to the sling at the next trajectory point is as follows: ; where, is the initial length of the sling, is the elastic coefficient of the sling, is the tension that the sling needs to bear.

[0009] Combined with the first implementation manner of the first aspect, in the seventh implementation manner of the first aspect, it further includes: obtaining the attitude monitoring data of the bridge erecting machine in real time, and sending an alarm signal when the attitude monitoring data is abnormal.

[0010] Second aspect, a smart hoisting control system for a bridge erecting machine is provided, including: An acquisition module configured to acquire the weight data, the inclination angle data and the position data of the beam body hoisted by the bridge erecting machine, as well as the wind speed distribution data around the beam body and the initial length of each sling of the bridge erecting machine when there is no tension; An optimization module configured to dynamically optimize the hoisting path of the beam body based on the wind speed distribution data, the inclination angle data and the position data by using a trajectory optimization algorithm; A determination module configured to determine the inclination angle data and the wind speed data corresponding to the beam body at the next trajectory point; A calculation module, configured to determine the tension that each sling of the bridge erecting machine needs to bear when the beam body is at the next trajectory point according to the inclination data, wind speed data, and weight data. An adjustment module, configured to calculate the length data corresponding to each sling at the next trajectory point by combining the corresponding initial length and tension, and when the beam body moves to the next trajectory point, adjust the length of each sling according to the corresponding length data.

[0011] In a third aspect, a computer program product is provided, including a computer program / instructions, which when executed by a processor, implement the steps of the intelligent hoisting control method of the bridge erecting machine according to any one of the first to seventh implementable ways in the first aspect.

[0012] Beneficial effects: By using the intelligent hoisting control method, system, and computer program product of the bridge erecting machine of the present invention, based on the inclination data, wind speed distribution data, and position data of the beam body obtained in real time, the hoisting path of the beam body can be dynamically optimized through a trajectory optimization algorithm. At the same time, according to the inclination data and wind speed data corresponding to the beam body at each trajectory point in the optimized hoisting path, the length of each sling of the bridge erecting machine can be dynamically adjusted. Thus, it can adapt to the continuously changing environmental conditions, ensure that the beam body moves smoothly along the planned path, and improve the safety, smoothness, and efficiency of the hoisting process. Description of the Drawings

[0013] In order to more clearly illustrate the specific implementation manners of the present invention, the drawings required for use in the specific implementation manners will be briefly introduced below. In all the drawings, the components or parts do not necessarily draw according to the actual ratio.

[0014] Figure 1 It is a flowchart of the intelligent hoisting control method of the bridge erecting machine provided by an embodiment of the present invention; Figure 2 It is a system block diagram of the intelligent hoisting control system of the bridge erecting machine provided by an embodiment of the present invention. Specific Embodiments

[0015] The embodiments of the technical solutions of the present invention will be described in detail below with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, so they are only examples and cannot be used to limit the protection scope of the present invention.

[0016] As Figure 1 shown in the flowchart of the intelligent hoisting control method of the bridge erecting machine, the control method includes: Step 1, obtain the weight data, inclination data, and position data of the beam body hoisted by the bridge erecting machine, as well as the wind speed distribution data around the beam body and the initial length of each sling of the bridge erecting machine without tension; Step 2: Based on the wind speed distribution data, inclination data, and position data, dynamically optimize the hoisting path of the beam using a trajectory optimization algorithm; Step 3: Determine the corresponding inclination data and wind speed data when the beam is at the next trajectory point according to the hoisting path; Step 4: Determine the tension that each sling of the girder bridge erection machine needs to bear when the beam is at the next trajectory point according to the inclination data, wind speed data, and weight data; Step 5: Combine the corresponding initial length and tension, and calculate the length data corresponding to each sling at the next trajectory point respectively. When the beam moves to the next trajectory point, adjust the length of each sling according to the corresponding length data.

[0017] Specifically, first, the wind speed distribution data, inclination data, position data, and weight data around the beam can be monitored in real time through the corresponding monitoring sensors set on the girder bridge erection machine, the beam, and around the girder bridge erection machine. At the same time, the initial length of each sling of the girder bridge erection machine without tension can be obtained according to the product manual of the girder bridge erection machine. Then, based on the currently obtained wind speed distribution data, inclination data, and position data, an existing trajectory optimization algorithm can be used to dynamically optimize the hoisting path of the beam. The trajectory optimization algorithm used can be the A* algorithm, Dijkstra algorithm, etc. After that, the position coordinates of the next trajectory point of the beam can be determined through the optimized hoisting path. Combining the current wind speed distribution data, inclination data, and the hoisting working condition data of the girder bridge erection machine, such as hoisting moving speed, acceleration, etc., the wind speed data and inclination data that the beam will bear when moving from the current position to the next trajectory point of the optimized path can be predicted.

[0018] Then, combining the predicted wind speed data, inclination data, and the weight data of the beam, the tension that each sling of the girder bridge erection machine needs to bear after the beam moves to the next trajectory point can be estimated. Finally, combining the corresponding initial length and tension, the length data corresponding to each sling at the next trajectory point can be calculated respectively, and the length of each sling can be adjusted when the beam moves to the next trajectory point. In this way, the construction can be globally optimized and dynamically adjusted in combination with real-time construction data, so as to adapt to the constantly changing environmental conditions, ensure the beam moves smoothly along the planned path, and improve the safety, smoothness, and efficiency of the hoisting process.

[0019] In this embodiment, optionally, in Step 2, dynamically optimizing the hoisting path of the beam using a trajectory optimization algorithm includes: According to the wind speed distribution data, inclination data, and position data, optimize the hoisting path of the beam using the A* algorithm.

[0020] Specifically, the A* algorithm can be used to optimize the hoisting path of the beam body. The A* algorithm introduces a heuristic function to guide the search for optimized trajectory points, which can improve the search efficiency of trajectory points and further enhance the efficiency during the hoisting process. Moreover, according to the actual situation of the construction site, a suitable heuristic function can be selected to adapt to different construction sites.

[0021] Specifically, first, create an open list and a closed list. The open list is used to store the wind speed data, inclination angle data, and position data corresponding to other nodes adjacent to the current position of the beam body. Then, based on the wind speed data, inclination angle data, and position data corresponding to other nodes in the open list, calculate the cost corresponding to each node respectively through a set cost function, and search for the node with the minimum cost as the current node. After that, determine whether the current node is the target node. If so, it indicates that the search is successful, and the movement path can be determined by backtracking through the position of the target node and the current position data of the beam body. On the contrary, put the current node into the closed list, update the open list according to the adjacent nodes of the current node, and conduct a new search until the target node is found or the open list is empty.

[0022] In this embodiment, the wind speed data and inclination angle data corresponding to other nodes adjacent to the current position of the beam body can be determined by methods such as interpolation algorithms and fluid mechanics models. Specifically, according to the wind speed distribution data, inclination angle data, and position data of the current node, use time series interpolation or spatial interpolation methods to predict the changing trends of the wind speed and inclination angle of adjacent nodes. Or, based on CFD (Computational Fluid Dynamics) simulation, combined with the historical data of the hoisting path, estimate the wind field changes in the adjacent area. Or, sensors can be directly arranged at other nodes adjacent to the current position of the construction beam body, and the wind speed data and inclination angle data of the adjacent other nodes can be directly measured through the sensors. Or, according to the wind speed data and inclination angle data of the current position, estimate the changing trends of the wind speed and inclination angle of adjacent nodes over time through a trained time series prediction model (such as LSTM), so as to determine the wind speed data and inclination angle data corresponding to other nodes.

[0023] In this embodiment, optionally, the cost function corresponding to the A* algorithm is: ; Wherein, is the cumulative cost of the path length, is the wind speed at node , is the inclination angle of the beam body at node , is the maximum allowable safety inclination angle of the beam body, , are the weight coefficients corresponding to the wind speed and inclination angle respectively, is a heuristic function.

[0024] Specifically, during the hoisting process, the wind speed and inclination angle have the greatest impact on the stability of the beam body. Therefore, the cost function comprehensively evaluates the cost of moving the beam body to the node by considering the wind speed and inclination angle to ensure that the beam body can move smoothly and safely to the target position.

[0025] In this embodiment, optionally, the Euclidean distance is used as the heuristic function.

[0026] Specifically, the Euclidean distance can directly measure the shortest straight-line distance between the current position and the target position of the beam body, thereby providing a simple, efficient, and low-cost path optimization criterion. Moreover, the calculation of the Euclidean distance is simple, which can reduce the amount of calculation. And the Euclidean distance represents the shortest path and is applicable to local optimization under the influence of dynamic factors such as wind speed and inclination angle.

[0027] In this embodiment, optionally, in step 4, when determining that the beam body is at the next trajectory point, the tension that each sling needs to bear includes: Establish the force balance equation and moment balance equation of the beam body; Based on the inclination angle data, wind speed data, and weight data, use numerical methods to solve the force balance equation and moment balance equation to obtain the tension that each sling needs to bear when the beam body is at the next trajectory point.

[0028] Specifically, first, the force balance equation and moment balance equation of the beam body can be established by combining the force balance condition of the beam body with the tension relationship.

[0029] Among them, the force balance equation is specifically as follows: ; The moment balance equation is as follows: ; Among them, is the tension borne by the sling, is the direction vector of the sling, is the gravity vector of the beam body, is the position vector from the suspension point to the centroid of the beam body, is the number of slings.

[0030] Due to the large number of slings of the bridge erecting machine, it is necessary to solve a system of equations with multiple unknowns to find the tension distribution that satisfies the force balance condition and the moment balance condition, and these equations may be non-linear equations. Therefore, based on the inclination data, wind speed data, and the weight data of the beam corresponding to the next trajectory point, numerical methods can be used to solve the above force balance equations and moment balance equations, and the tension that each sling needs to bear when the beam is at the next trajectory point can be obtained, so as to ensure that the beam remains stable after moving to the next trajectory point of the optimized path.

[0031] In this embodiment, optionally, in step 5, the specific calculation formula for the length data corresponding to the sling at the next trajectory point is as follows: ; Where is the initial length of the sling, is the elastic coefficient of the sling, is the tension that the sling needs to bear.

[0032] Specifically, when the tension that each sling of the bridge erecting machine needs to bear when the beam moves to the next trajectory point is calculated, according to the corresponding relationship between the tension and the length of the sling, the above calculation formula can be used to calculate the length data of each sling, and then the length of each sling can be adjusted according to the corresponding length data to ensure the force balance of the beam and thus maintain stability.

[0033] In this embodiment, optionally, it further includes: obtaining the attitude monitoring data of the bridge erecting machine in real time, and sending an alarm signal when the attitude monitoring data is abnormal.

[0034] Specifically, during the movement of the beam, the attitude of the bridge erecting machine can be monitored in real time through an attitude monitoring sensor, and it can be judged whether the attitude of the bridge erecting machine has changed excessively according to the attitude monitoring data. If so, an alarm signal can be sent in time to remind the staff to adjust the attitude of the bridge erecting machine to avoid construction accidents.

[0035] As Figure 2 shown in the system block diagram of the intelligent hoisting control system of the bridge erecting machine, this control system includes: An acquisition module configured to acquire the weight data, inclination data, and position data of the beam hoisted by the bridge erecting machine, as well as the wind speed distribution data around the beam and the initial length of each sling of the bridge erecting machine without tension; An optimization module configured to dynamically optimize the hoisting path of the beam based on the wind speed distribution data, inclination data, and position data by using a trajectory optimization algorithm; A determination module configured to determine the inclination data and wind speed data corresponding to the beam at the next trajectory point; A calculation module configured to determine the tension that each sling of the bridge erecting machine needs to bear when the beam body is at the next trajectory point according to the inclination data, wind speed data, and weight data. An adjustment module configured to calculate the length data corresponding to each sling at the next trajectory point by combining the corresponding initial length and tension, and adjust the length of each sling according to the corresponding length data when the beam body moves to the next trajectory point.

[0036] Specifically, the control system includes an acquisition module, an optimization module, a determination module, a calculation module, and an adjustment module. Among them, the acquisition module can real-time monitor the wind speed distribution data, inclination data, position data, and weight data around the beam body through the corresponding monitoring sensors arranged on the bridge erecting machine, the beam body, and around the bridge erecting machine. The optimization module can dynamically optimize the hoisting path of the beam body based on the currently acquired wind speed distribution data, inclination data, and position data by using existing trajectory optimization algorithms. The determination module can determine the position coordinates of the next trajectory point of the beam body through the optimized hoisting path, and combine the current wind speed distribution data, inclination data, and the hoisting working condition data of the bridge erecting machine to predict the wind speed data and inclination data that the beam body bears when moving from the current position to the next trajectory point of the optimized path.

[0037] The calculation module can combine the predicted wind speed data, inclination data, and the weight data of the beam body to estimate the tension that each sling of the bridge erecting machine needs to bear after the beam body moves to the next trajectory point. The adjustment module can calculate the length data corresponding to each sling at the next trajectory point by combining the corresponding initial length and tension, and adjust the length of each sling when the beam body moves to the next trajectory point.

[0038] In this way, the construction can be globally optimized and dynamically adjusted by combining real-time construction data, so as to adapt to the continuously changing environmental conditions, ensure that the beam body moves smoothly along the planned path, and improve the safety, smoothness, and efficiency of the hoisting process.

[0039] A computer program product includes a computer program / instructions, and when the computer program / instructions are executed by a processor, the steps of the above-mentioned intelligent hoisting control method of the bridge erecting machine are implemented.

[0040] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the various embodiments of the present invention, and they should all be covered by the scope of the claims and the description of the present invention.

Claims

1. An intelligent hoisting control method for a bridge erecting machine, characterized in that, Including: Obtaining the weight data, inclination data and position data of the girder lifted by the bridge girder erecting machine, as well as the wind speed distribution data around the girder and the initial length of each sling of the bridge girder erecting machine when there is no tension; Based on the wind speed distribution data, inclination data and position data, dynamically optimizing the lifting path of the girder by using a trajectory optimization algorithm; Determining the corresponding inclination data and wind speed data when the girder is at the next trajectory point according to the lifting path; Determining the tension that each sling of the bridge girder erecting machine needs to bear when the girder is at the next trajectory point according to the inclination data, wind speed data and weight data; Combining the corresponding initial length and tension, respectively calculating the length data corresponding to each sling at the next trajectory point, and when the girder moves to the next trajectory point, adjusting the length of each sling according to the corresponding length data.

2. The intelligent hoisting control method of the bridging machine according to claim 1, characterized in that, Dynamically optimizing the lifting path of the girder by using a trajectory optimization algorithm, including: According to the wind speed distribution data, inclination data and position data, optimizing the lifting path of the girder by using the A* algorithm.

3. The intelligent hoisting control method of the bridge erector according to claim 2, characterized in that, The cost function corresponding to the A* algorithm is: ； Among them, is the cumulative cost of the path length, is the wind speed at node ; is the inclination angle of the beam body at node ; is the maximum allowable safety inclination angle of the beam body, , are the weight coefficients corresponding to the wind speed and the inclination angle respectively, is the heuristic function.

4. The intelligent hoisting control method of the bridge erecting machine according to claim 3, characterized in that Using the Euclidean distance as the heuristic function.

5. The intelligent hoisting control method of the bridge erector according to claim 1, characterized in that Determining the tension that each sling needs to bear when the girder is at the next trajectory point, including: Establishing the force balance equation and moment balance equation of the girder; Based on the inclination data, wind speed data and weight data, using a numerical method to solve the force balance equation and moment balance equation, and obtaining the tension that each sling needs to bear when the girder is at the next trajectory point.

6. The intelligent hoisting control method of the bridge erector according to claim 1, characterized in that, The specific calculation formula of the length data corresponding to each sling at the next trajectory point is as follows: ； Among them, is the initial length of the sling, is the elastic coefficient of the sling, is the tension that the sling needs to bear.

7. The intelligent hoisting control method of the bridge erecting machine according to claim 1, characterized in that Also including: Real-time obtaining the attitude monitoring data of the bridge girder erecting machine, and sending an alarm signal when the attitude monitoring data is abnormal.

8. An intelligent hoisting control system for a bridge erecting machine, characterized in that, Including: An acquisition module configured to obtain the weight data, inclination data and position data of the girder lifted by the bridge girder erecting machine, as well as the wind speed distribution data around the girder and the initial length of each sling of the bridge girder erecting machine when there is no tension; An optimization module configured to dynamically optimize the lifting path of the girder by using a trajectory optimization algorithm based on the wind speed distribution data, inclination data and position data; A determination module configured to determine the corresponding inclination data and wind speed data when the girder is at the next trajectory point; A calculation module configured to determine the tension that each sling of the bridge girder erecting machine needs to bear when the girder is at the next trajectory point according to the inclination data, wind speed data and weight data; An adjustment module configured to combine the corresponding initial length and tension, respectively calculate the length data corresponding to each sling at the next trajectory point, and when the girder moves to the next trajectory point, adjust the length of each sling according to the corresponding length data.

9. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by a processor, the steps of the bridge girder erecting machine intelligent lifting control method as described in any one of claims 1-7 are implemented.

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