Hoisting moving device planning method, system and equipment

Abstract

The invention provides a hoisting moving device planning method, system and equipment, and belongs to the field of intelligent optimizing.By calculating an anti-tilting redundancy index of each hoisting moving device under an ideal standing distance, a moving cost coefficient is obtained from the anti-tilting redundancy index; selecting a hoisting moving device with the highest moving hoisting benefit by combining the anti-tilting redundancy index, the moving cost coefficient and the moving distance; for the selected hoisting moving device, calculating a unit vector between the coordinates of the hoisting point and the initial position of the hoisting moving device according to the direction of a connecting line between the coordinates of the hoisting point and the initial position of the hoisting moving device, and combining the working radius data of the hoisting moving device with the unit vector, and generating and outputting an ideal standing position for the selected hoisting and moving device. The bearing, the stability and the moving cost of the equipment are organically combined, a global optimal decision is realized, and the crane selected in a complex hoisting site is ensured to be safe and efficient.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent control optimization, and particularly relates to a planning method, system and device for a hoisting and moving device. Background Art

[0002] In traditional hoisting operation planning, the selection of cranes and the positioning strategy are usually determined by experienced engineers who choose a suitable crane based on past operation experience, on-site investigation and subjective judgment, and determine its position. This method relies on personal experience and lacks a quantitative scientific calculation basis, resulting in sub-optimal selection and even potential safety hazards or reduced construction efficiency. Some optimization methods may screen based on basic static parameters such as the maximum lifting capacity and working radius of the crane, but ignore key factors such as the anti-overturning ability, movement cost, and operating environment of the crane, making the selected equipment may have safety hazards or inconvenient operation in actual operation. Some intelligent optimization algorithms may select cranes and positions based on the principle of the shortest path, but such methods often only consider the shortest movement path or the lowest energy consumption, and fail to combine factors such as the stability, hoisting load, and anti-overturning ability of the crane, resulting in the selected crane may not meet the actual operation requirements.

[0003] Traditional methods generally only consider the rated load and working radius of the crane, and do not establish an accurate matching relationship between the anti-overturning moment of the crane and the hoisting task, which may lead to insufficient stability of the selected crane under extreme working conditions and a risk of overturning. In the patent document with the publication number CN113378455A, a smart optimization method for the hoisting process of prefabricated building components is recorded. Although the displacement value during the frame hoisting process and the frame speed at the end of hoisting are used as the objective function and the genetic algorithm is called for optimization and solution, there is a lack of scientific evaluation of the anti-overturning ability.

[0004] Existing technologies usually ignore the movement path of the crane from the initial position to the operation site and the resulting time and energy consumption. The selected crane may need to move long distances, resulting in reduced construction efficiency and increased fuel costs. For example, in a multi-crane lifting optimization method described in the patent document with the publication number CN110069882A, although wireless positioning tags are used to locate and monitor the lifted object to make the multi-crane lifting method more optimized, the equipment movement cost is not considered and there is a lack of a quantitative comprehensive evaluation system. Existing technical solutions lack a unified optimization goal and cannot comprehensively consider multiple factors such as safety, stability, and movement cost, resulting in the selected solution not being able to achieve global optimality. Summary of the Invention

[0005] The purpose of the present invention is to propose a planning method, system and device for a hoisting and moving device to solve one or more technical problems existing in the prior art, and at least provide a beneficial alternative or creative condition.

[0006] To achieve the above object, according to one aspect of the present invention, a method for planning a hoisting and moving device is provided. The method includes the following steps: In a hoisting site to be automatically planned, there are multiple hoisting and moving devices and multiple hoisting tasks. A unified plane coordinate system is established, and the initial position data, anti-overturning moment data, and maximum working radius data of each hoisting and moving device are input, and the weight of the hoisted object corresponding to each hoisting task and the coordinate data of its hoisting point are input; By obtaining the moving distance between the weight of the hoisted object, the coordinate of the hoisting point and the initial position of the hoisting and moving device, and the anti-overturning moment of the hoisting and moving device, calculate the anti-overturning redundancy index of each hoisting and moving device at the ideal standing distance, obtain the moving cost coefficient from the anti-overturning redundancy index, and select the hoisting and moving device with the highest moving hoisting efficiency in combination with the anti-overturning redundancy index, moving cost coefficient, and moving distance; For the selected hoisting and moving device, according to the connecting direction between the coordinate of the hoisting point and the initial position of the hoisting and moving device, calculate the unit vector between the coordinate of the hoisting point and the initial position of the hoisting and moving device, and combine the working radius data of the hoisting and moving device with the unit vector to generate the output ideal standing position for the selected hoisting and moving device.

[0007] Further, the hoisting and moving device is a device with hoisting and moving functions, specifically including a crane.

[0008] Further, the value of the anti-overturning moment of the hoisting and moving device is obtained by multiplying the value of the horizontal distance from the center of gravity of the hoisting and moving device to the tipping boundary by the value of the effective counterweight of the hoisting and moving device.

[0009] Further, the working radius data of each hoisting and moving device includes the value of its maximum working radius and the value of its minimum working radius.

[0010] Further, the method for selecting the hoisting and moving device with the highest moving hoisting efficiency in combination with the anti-overturning redundancy index, moving cost coefficient, and moving distance is as follows: For each hoisting point coordinate, obtain the moving distance between the initial position of each hoisting and moving device and the hoisting point coordinate; The ideal standing distance for the hoisting point coordinate is the maximum value among the minimum working radii of each hoisting and moving device; Divide the value of the anti-overturning moment of each hoisting and moving device by the product of the weight of the hoisted object of the hoisting task and the ideal standing distance, and the quotient obtained is the anti-overturning redundancy index of each hoisting and moving device; Normalize the values of the anti-tipping redundancy indices of each hoisting and moving device, and use the variance of the normalized values of the anti-tipping redundancy indices of each hoisting and moving device as the moving cost coefficient; Use the value of the anti-tipping redundancy index of each hoisting and moving device as the numerator, and use the sum of the product of the moving cost coefficient and the moving distance plus one as the denominator to calculate the moving hoisting efficiency of each hoisting and moving device, and select the hoisting and moving device with the highest moving hoisting efficiency value for this hoisting task.

[0011] Among them, the method of the present invention quantifies and matches the anti-tipping moment of the crane with the weight of the hoisted object and the working radius by calculating the anti-tipping redundancy index, so that the selected crane can not only meet the rated load requirements, but also provide sufficient anti-tipping redundancy to ensure the safety of the operation. The anti-tipping redundancy index can dynamically adapt to different hoisting tasks, avoiding misjudgments caused by traditional empirical rules and improving the reliability of hoisting operations.

[0012] Because the traditional method usually ignores the moving cost of the crane from the initial position to the working location, and this method is optimized through the moving cost coefficient, so that the finally selected crane not only has high safety, but also has a short moving path, low energy consumption and higher construction efficiency. This method can dynamically adjust the moving cost weight to adapt to different working conditions. In particular, in a complex construction site where the moving cost is high, the method will preferentially select a crane with a short moving distance; while in a flat construction site, the weight of the anti-tipping redundancy index can be appropriately increased to ensure the safety of the operation.

[0013] The traditional methods lack unity in the calculation methods of different crane parameters including anti-tipping moment, lifting radius, etc., which may lead to incomparable calculation results between different devices. However, through the normalization process of the anti-tipping redundancy index in the present invention, the mathematical distribution migration transformation of the anti-tipping redundancy index between different cranes to the mathematical characteristics of the moving cost has statistical comparability, making its mathematical statistical results more stable and reliable.

[0014] The present invention calculates the moving hoisting efficiency. This index comprehensively considers the safety represented by the anti-tipping redundancy index and the influence of the moving distance, ensuring that the selected crane achieves the best balance between safety and efficiency. By scoring all candidate cranes through this moving hoisting efficiency, the finally selected crane has the optimal comprehensive performance, avoiding suboptimal selections caused by only considering single factors such as the shortest path or the largest load-bearing capacity, etc.

[0015] The technical method of the present invention not only breaks through the problems in traditional hoisting operations, such as the selection and positioning decision of cranes relying on experience, lacking quantitative judgment, and insufficient real-time dynamic optimization ability, but also solves the technical problem that it is difficult to balance the safety and efficiency of hoisting operations. Under traditional working conditions, engineers often judge which crane is most suitable for a certain hoisting task based on past experience and simple rules, usually only considering the rated load and working radius of the equipment, while ignoring the anti-overturning ability of the crane, the cost required for the equipment to move from the initial position to the operation site, and the influence of complex on-site environmental factors. This not only easily leads to improper selection of cranes, thereby increasing the risk of overturning or equipment damage during hoisting operations, but also affects the construction efficiency and increases costs due to the long moving distance of the equipment.

[0016] However, the present invention constructs a mathematical model to calculate the ratio of the anti-overturning moment of the crane to the load moment generated by the hoisting task, obtaining the anti-overturning redundancy index described in the present invention, and introducing the moving cost by combining the actual moving distance of the crane from the initial position to the task point, calculating the moving hoisting benefit described in the present invention. This method can quantify the equipment safety redundancy and moving cost, and ensure the comparability between different equipment through normalization processing, so as to scientifically select the most suitable crane to perform the hoisting task and determine its optimal position.

[0017] Furthermore, the method for generating the ideal positioning position for the selected hoisting and moving device by combining the working radius data of the hoisting and moving device with the unit vector is as follows: For each selected hoisting and moving device, obtain the coordinates of its corresponding hoisting task, obtain the initial position of the selected hoisting and moving device, calculate the unit vector obtained by subtracting the initial position of the selected hoisting and moving device from the coordinates of its corresponding hoisting task, let the value of the ideal positioning distance be the value of the minimum working radius of the selected hoisting and moving device, and the coordinates of the ideal positioning position be the sum obtained by adding the coordinates of its corresponding hoisting task to the product of the value of its ideal positioning distance and the unit vector.

[0018] Furthermore, the coordinates of the ideal positioning position may also be the difference obtained by subtracting the product of the value of its ideal positioning distance and the unit vector from the coordinates of its corresponding hoisting task.

[0019] Furthermore, let the specific value of the moving cost coefficient be 0.1.

[0020] The present invention also provides a hoisting and moving device planning system, and the hoisting and moving device planning system includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the hoisting and moving device planning method are implemented. The hoisting and moving device planning system can run on computing devices such as desktop computers, laptop computers, palmtop computers, and cloud data centers. The operable system may include, but is not limited to, a processor, a memory, and a server cluster. The processor executes the computer program and runs in the units of the following system: An input unit for inputting the initial position data, anti-overturning moment data, and maximum working radius data of each hoisting and moving device, and inputting the weight of the hoisted object and the coordinate data of its hoisting point corresponding to each hoisting task; A calculation unit for calculating the anti-overturning redundancy index of each hoisting and moving device at the ideal standing position distance by obtaining the weight of the hoisted object, the moving distance between the hoisting point coordinates and the initial position of the hoisting and moving device, and the anti-overturning moment of the hoisting and moving device, obtaining the movement cost coefficient from the anti-overturning redundancy index, and selecting the hoisting and moving device with the highest moving hoisting benefit by combining the anti-overturning redundancy index, the movement cost coefficient, and the moving distance; An output unit for, for the selected hoisting and moving device, calculating the unit vector between the hoisting point coordinates and the initial position of the hoisting and moving device according to the connection direction between the hoisting point coordinates and the initial position of the hoisting and moving device, and combining the working radius data of the hoisting and moving device with the unit vector to generate the output ideal standing position for the selected hoisting and moving device.

[0021] Correspondingly, the present invention also provides an electronic device, a readable storage medium, and a computer program product: An electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the hoisting and moving device planning method and the methods of each step therein.

[0022] A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the hoisting and moving device planning method and the methods of each step therein.

[0023] A computer program product includes a computer program, and the computer program implements the hoisting and moving device planning method and the methods of each step therein when executed by a processor.

[0024] The beneficial effects of the present invention are as follows: The present invention provides a method, system and equipment for planning a hoisting and moving device. By calculating the anti-tipping redundancy index of each hoisting and moving device at the ideal standing position distance, the moving cost coefficient is obtained from the anti-tipping redundancy index. Combining the anti-tipping redundancy index, the moving cost coefficient and the moving distance, the hoisting and moving device with the highest moving hoisting benefit is selected. For the selected hoisting and moving device, according to the direction of the line connecting the hoisting point coordinates and the initial position of the hoisting and moving device, the unit vector between the hoisting point coordinates and the initial position of the hoisting and moving device is calculated. Combining the working radius data of the hoisting and moving device with the unit vector, the ideal standing position is generated for the selected hoisting and moving device. The load-bearing, stability and moving cost of the equipment are organically combined, realizing the global optimal decision-making and ensuring that the crane selected in the complex hoisting site is both safe and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] By elaborating on the embodiments shown in the accompanying drawings in detail, the above and other features of the present invention will become more obvious. The same reference numerals in the drawings of the present invention represent the same or similar elements. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. In the drawings: Figure 1 Shown is a flowchart of a method for planning a hoisting and moving device; Figure 2 Shown is a system structure diagram of a system for planning a hoisting and moving device. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] The following will clearly and completely describe the concept, specific structure and technical effects generated by the present invention in combination with the embodiments and the drawings, so as to fully understand the purpose, solution and effects of the present invention. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0027] In the description of the present invention, the meaning of several is one or more, the meaning of multiple is two or more, and understandings such as greater than, less than, exceeding, etc. do not include the present number, and understandings such as above, below, within, etc. include the present number. If there is a description of first and second, it is only for the purpose of distinguishing technical features and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0028] As Figure 1 Shown is a flowchart of a method for planning a hoisting and moving device according to the present invention. The following will elaborate on a method, system and equipment for planning a hoisting and moving device according to the embodiments of the present invention in combination with Figure 1 to illustrate.

[0029] The present invention provides a method for planning a hoisting and moving device, and the method specifically includes the following steps: Input the initial position data, anti-overturning moment data, and maximum working radius data of each hoisting and moving device, and input the weight of the hoisted object corresponding to each hoisting task and the coordinate data of its hoisting point; By obtaining the weight of the hoisted object, the moving distance between the hoisting point coordinates and the initial position of the hoisting and moving device, and the anti-overturning moment of the hoisting and moving device, calculate the anti-overturning redundancy index of each hoisting and moving device at the ideal standing position distance, obtain the moving cost coefficient from the anti-overturning redundancy index, and select the hoisting and moving device with the highest moving hoisting benefit by combining the anti-overturning redundancy index, the moving cost coefficient, and the moving distance; For the selected hoisting and moving device, calculate the unit vector between the hoisting point coordinates and the initial position of the hoisting and moving device according to the connection direction between the hoisting point coordinates and the initial position of the hoisting and moving device, and combine the working radius data of the hoisting and moving device with the unit vector to generate the output ideal standing position for the selected hoisting and moving device.

[0030] Further, the hoisting and moving device is a device with hoisting and moving functions, specifically including a crane.

[0031] Further, the value of the anti-overturning moment of the hoisting and moving device is obtained by multiplying the value of the horizontal distance from the center of gravity of the hoisting and moving device to the overturning boundary by the value of the effective counterweight of the hoisting and moving device.

[0032] Further, the working radius data of each hoisting and moving device includes the value of its maximum working radius and the value of its minimum working radius.

[0033] Further, the method for selecting the hoisting and moving device with the highest moving hoisting benefit by combining the anti-overturning redundancy index, the moving cost coefficient, and the moving distance is as follows: For each hoisting point coordinate, obtain the moving distance between the initial position of each hoisting and moving device and the hoisting point coordinate; The ideal standing position distance for the hoisting point coordinate is the maximum value among the minimum working radii of each hoisting and moving device; Divide the value of the anti-overturning moment of each hoisting and moving device by the product of the weight of the hoisted object of the hoisting task and the ideal standing position distance, and the quotient obtained is the anti-overturning redundancy index of each hoisting and moving device; Normalize the values of the anti-overturning redundancy indices of each hoisting and moving device, and use the variance of the normalized values of the anti-overturning redundancy indices of each hoisting and moving device as the moving cost coefficient; Taking the value of the anti-tipping redundancy index of each hoisting and moving device as the numerator and the sum of the product of the moving cost coefficient and the moving distance plus one as the denominator, calculate the moving and hoisting efficiency of each hoisting and moving device, and select the hoisting and moving device with the highest moving and hoisting efficiency value for this hoisting task.

[0034] In the traditional working conditions, engineers often judge which crane is most suitable for a certain hoisting task based on past experience and simple rules. They often only consider the rated load and working radius of the equipment, while ignoring the anti-overturning ability of the crane, the cost required for the equipment to move from the initial position to the operation site, and the influence of complex on-site environmental factors. This not only easily leads to improper selection of the crane, thereby increasing the risk of overturning or equipment damage during hoisting operations, but also affects the construction efficiency and increases the cost due to the long moving distance of the equipment.

[0035] However, the present invention calculates the anti-tipping redundancy index by constructing a mathematical model and calculating the ratio of the anti-overturning moment of the crane to the load moment generated by the hoisting task, and introduces the moving cost in combination with the actual moving distance of the crane from the initial position to the task point, and calculates the moving and hoisting efficiency described in the present invention. This method can quantify the equipment safety redundancy and moving cost, and ensure the comparability between different equipment through normalization processing, so as to scientifically select the crane most suitable for performing the hoisting task and determine its optimal standing position.

[0036] Further, the method for generating the ideal standing position for the selected hoisting and moving device by combining the working radius data of the hoisting and moving device with the unit vector is as follows: For each selected hoisting and moving device, obtain the coordinates of its corresponding hoisting task, obtain the initial position of the selected hoisting and moving device, calculate the unit vector obtained by subtracting the initial position of the selected hoisting and moving device from the coordinates of its corresponding hoisting task, let the value of the ideal standing distance be the value of the minimum working radius of the selected hoisting and moving device, and the coordinates of the ideal standing position be the sum of the coordinates of its corresponding hoisting task plus the product of the value of its ideal standing distance and the unit vector.

[0037] Further, the coordinates of the ideal standing position may also be the difference obtained by subtracting the product of the value of its ideal standing distance and the unit vector from the coordinates of its corresponding hoisting task.

[0038] Further, let the specific value of the moving cost coefficient be 0.1.

[0039] In the embodiments provided by the present invention, within a selected area to be automatically planned, such as within a hoisting construction site, there are several hoisting mobile devices. The hoisting mobile devices can include equipment with hoisting and moving functions such as cranes. The data of the hoisting mobile devices includes data such as the coordinates of their initial positions, the values of anti-overturning moments, and the values of their maximum working radii. Each crane has its maximum working radius R and minimum working radius r, that is, the maximum distance and minimum distance that the crane can reach when it is fixed in position for operation.

[0040] Within the hoisting construction site, there are also several hoisting tasks. The data of the hoisting tasks includes data such as the mass of the hoisted object and the coordinates of the hoisting point.

[0041] In such a complex hoisting site, according to the real-time physical quantity data, the most suitable crane for a certain hoisting task is accurately selected, and the best standing position of the crane on the site is calculated.

[0042] By obtaining the weight L of the hoisted object, the moving distance Dmove between the task point and the initial position of the crane, and the anti-overturning moment Mbase of the crane, calculate the anti-overturning redundancy index S of each crane at the ideal working distance R. Combining the anti-overturning redundancy index S, the moving cost coefficient k, and the moving distance Dmove, calculate the crane with the highest moving hoisting efficiency. For the selected crane, according to the direction of the line connecting the task point and the initial position of the crane, calculate the unit vector between the task point and the initial position of the crane. Calculate an ideal standing position, usually a position near the task point that satisfies the minimum safety distance R.

[0043] Among them, taking the coordinates of each hoisting task as the task point respectively, obtain the moving distance Dmove of each crane from the initial position to the task point. On the premise that each crane can stand around the task point, the ideal standing distance is taken as the maximum value among the minimum working radii of each crane, denoted as Rs. In some embodiments, the ideal standing distance is taken as Rs = 5m. Divide the value of the anti-overturning moment of each crane by the product of the weight L of the hoisted object of the hoisting task and the ideal standing distance Rs to calculate the anti-overturning redundancy index S of each crane. The anti-overturning redundancy index can be used to represent the anti-overturning ability provided by the crane, including but not limited to the ratio between the anti-overturning moment generated by the base and the overturning moment generated by the hoisting load at the safe distance. It can be used to measure the redundancy of the anti-overturning ability of the crane relative to the load requirement during the hoisting process. The higher its value, the greater the additional safety reserve of the crane, and thus it can execute the hoisting task more stably.

[0044] Normalize the values of the anti-tipping redundancy index S of each crane, and take the variance of the normalized values of the anti-tipping redundancy index S of each crane as the movement cost coefficient k. In some embodiments, preferably, the movement cost coefficient is taken as k = 0.1; Take the value of the anti-tipping redundancy index S of each crane as the numerator, and take the sum of 1 plus the product of the movement cost coefficient and the movement distance Dmove as the denominator, calculate the movement hoisting efficiency of each crane, and select the crane with the highest movement hoisting efficiency value for this hoisting task.

[0045] The movement hoisting efficiency is an index that reflects the matching degree between the crane and the current hoisting task by measuring and combining the bearing capacity, anti-tipping redundancy of the crane to represent the dynamic stability, and the cost of moving from the initial position to the work site. It not only reflects the matching degree between the crane and the hoisting task, but also emphasizes the overall efficiency brought by moving the crane from the initial position to the work site. The higher the value, the more it means that the equipment not only has a redundant safety margin in terms of bearing and stability, but also has lower costs and time required during the movement process, so it is more suitable for the current hoisting task.

[0046] Among them, for each selected crane, obtain the coordinates of its corresponding hoisting task as Ptask, obtain the coordinates of the initial position of the selected crane as Pcrane, calculate the unit vector of the vector Vec obtained by subtracting Pcrane from Ptask as v, and the calculation method of the ideal standing position Pstation is that the coordinate point of Pstation is equal to the coordinate point of Ptask plus the product of the value of r and the vector v, where r takes the minimum working distance of the selected crane. In some embodiments, the r can take the safe minimum distance, and here it takes 5m.

[0047] Among them, the calculation method of the ideal standing position Pstation may also be that the coordinate point of Pstation is equal to the coordinate point of Ptask minus the product of the value of r and the vector v.

[0048] Among them, the anti-tipping moment Mbase of the crane is generally determined by static calculation according to the structural diagram and load diagram of the crane. In some embodiments, respectively obtain the horizontal distance d (m) from the center of gravity of each crane to the tipping boundary, and obtain the effective counterweight of the crane as Wc (N), then the anti-tipping moment can be approximately calculated as Mbase = Wc × d. The horizontal distance d (m) from the center of gravity to the tipping boundary and the effective counterweight Wc (N) of the crane are usually determined by the design parameters of the crane, and come from calculating the self-weight and distribution of the crane body, the moment generated by the reaction force such as the counterweight block, and the friction and support area between the base and the ground. This value is generally provided by the manufacturer through detailed structural analysis.

[0049] In some embodiments, three mobile cranes A, B, and C at the site are monitored, and data on their initial positions, anti-tipping capabilities, and maximum working radii have been obtained; there are two lifting tasks, and the masses of the lifted objects and the coordinates of the lifting points for each task have been determined, and a rectangular coordinate system is established based on this data. To ensure safety, a horizontal distance of at least m meters must be maintained during the lifting process, that is, the minimum safety distance between the crane and the lifted object during the lifting operation. Taking this as a constraint condition for automatic planning, the calculation of the data begins. Precise measuring equipment is equipped on-site, which may include but is not limited to laser rangefinders, GPS, BIM models, etc., as well as necessary sensors for data acquisition, storage, and transmission, for real-time collection of crane positions, lifted object weights, and environmental data.

[0050] In addition to using laser rangefinders and GPS to determine the initial positions of each crane on-site, the BIM model data can also be used for auxiliary calibration. A wireless sensor network is used to collect the mass of the lifted object in real-time, including through load cells, environmental parameters such as wind speed, temperature, humidity, etc., and data on the current state of the crane, such as boom angle, equipment vibration, working current, etc., and the data is transmitted to the central control platform in real-time. At the same time, high-definition cameras and drones are set up on-site for monitoring, in order to record the actual obstacles and terrain conditions between the crane and the lifting task, and provide a more accurate environmental model for subsequent calculations.

[0051] Before the data enters the automatic planning system, data verification is required. For example, verify whether there is abnormal drift in the GPS data and whether the laser ranging data is consistent with the measured values in the BIM model. The data is unified into a standard rectangular coordinate system, and the unified BIM coordinate system can be used, and the abnormal data is filtered to ensure the accuracy and reliability of the data input into the model.

[0052] According to some embodiments, among multiple cranes, calculate the anti-tipping redundancy index of each device when lifting the same lifted object at the task site, and combine the moving cost of the crane from the initial position to the task site to determine the most suitable device for this lifting task.

[0053] In one of the provided embodiments, for lifting task 1, the mass of the lifted object at the site is known to be 2,000 kilograms. This value can be obtained on-site using a load cell or from the design documents. Multiply the mass of 2,000 kilograms by the acceleration due to gravity of 9.81 (in units of meters per second squared) to obtain the weight of the lifted object, which is approximately 19,620 (N) Newtons. The lifting point coordinates for our lifting task 1 are (5, 5); the lifting point for lifting task 2 is (18, -2). These data can be directly obtained from the BIM model or on-site survey data. For the three cranes, the on-site engineer obtained the data according to the equipment specifications: Crane A, initial position (0, 0), tipping moment resistance of 300,000 N·m, maximum working radius of 15 meters; Crane B, initial position (20, 0), tipping moment resistance of 250,000 N·m, maximum working radius of 12 meters; Crane C, initial position (10, 10), tipping moment resistance of 350,000 N·m, maximum working radius of 20 meters.

[0054] Preferably, when setting the lifting operation, a safety distance of at least 5 meters must be maintained between the crane and the lifting point. This value is determined based on the on-site safety regulations.

[0055] In one of the provided embodiments, the on-site uses a laser rangefinder or GPS system to calculate the straight-line distance from the initial position of each crane to the task point. For Crane A, the distance from (0, 0) to (5, 5) is measured to be approximately 7.07 meters; that is to say, for Crane B, the distance from (20, 0) to (5, 5) is approximately 15.81 meters; for Crane C, the distance from (10, 10) to (5, 5) is approximately 7.07 meters. These distances not only reflect the length that the crane needs to move but also relate to the preparation time before the operation and the energy consumption during the movement.

[0056] In some embodiments related to calculating the anti-tipping redundancy index, during lifting, it is assumed that the crane can reach an ideal standing position at the task site such that the horizontal distance from it to the lifting point is exactly 5 meters. At this time, the load moment generated by the lifted object at this distance can be calculated by multiplying the weight of the lifted object by 5 meters. Taking lifting task 1 as an example, the load moment generated by the lifted object is approximately, load moment = 19,620 (N) × 5 (M) = 98,100 (N·M). Next, for each crane, divide its anti-tipping moment by this load moment to obtain the anti-tipping redundancy index. For Crane A, 300,000 (N·m) divided by 98,100 (N·m), the result is approximately 3.06; for Crane B, 250,000 N·m divided by 98,100 N·m, the result is approximately 2.55; for Crane C: 350,000 N·m divided by 98,100 N·m, the result is approximately 3.57. These calculation results show that at the same working distance, Crane C has the highest anti-tipping redundancy index, followed by Crane A, and Crane B has the lowest.

[0057] In some embodiments, to reflect the additional cost of moving a crane from its initial position to the task site, the present invention introduces a mobile hoisting benefit. Using the variance of the normalized values of the anti-tipping redundancy index S of each crane as the mobile cost coefficient k, for convenience and directness, preferably, a k is set to 0.1, that is, the cost increases by 10% for every 1 meter of movement. When calculating the mobile hoisting benefit of each crane, the anti-tipping redundancy index is divided by the value of 1 plus k multiplied by the movement distance. For crane A, its movement distance is approximately 7.07 meters. Therefore, the mobile hoisting benefit is 3.06 divided by (1 + 0.1×7.07) ≈ 3.06 divided by 1.707, and the result is approximately 1.79; for crane B, its movement distance is approximately 15.81 meters, and the mobile hoisting benefit is 2.55 divided by (1 + 0.1×15.81) ≈ 2.55 divided by 2.581, and the result is approximately 0.99; for crane C, its movement distance is also approximately 7.07 meters, and the mobile hoisting benefit is 3.57 divided by 1.707, and the result is approximately 2.09. According to the numerical distribution of the mobile hoisting benefits, the mobile hoisting benefit value of crane C is the largest, indicating that for hoisting task 1, it is most suitable to select crane C to perform the hoisting task.

[0058] In some embodiments, after selecting the appropriate crane, determine the optimal standing position of the crane at the job site, which can not only ensure a safe distance from the hoisting point, such as at least about 5 meters, but also minimize the load moment during the hoisting process to ensure the smooth movement of the hoisted object.

[0059] In some specific embodiments of the standing position calculation method, the accurate coordinates of the task point and the initial position of the crane can be provided by on-site surveying and mapping or a BIM model. The vector from the initial position of the crane to the task point can be calculated and normalized to obtain the direction unit vector. For example, for hoisting task 1 and crane C, the task point coordinates are (5, 5), and the initial position of crane C is (10, 10). The difference vector between the two is (-5, -5); its length is approximately 7.07 meters, and the normalized unit vector is approximately (-0.707, -0.707). According to the safety requirements, the distance between the task point and the crane is fixed at 5 meters. The standing position can be selected in the direction of extending 5 meters along the unit vector from the task point. Since which side to specifically select needs to be judged in combination with the on-site environment, such as whether there are obstacles and the terrain flatness, the on-site engineer can decide whether to select the forward extension or the reverse extension according to the actual situation.

[0060] In a specific calculation example, for lifting task 1, when the task point is located at (5, 5) and the initial position of crane C is (10, 10). Calculate the difference vector between them (-5, -5), and the unit vector after normalization is approximately (-0.707, -0.707). If the position is selected in the direction of extending 5 meters forward from the task point, the position coordinates are (5, 5) plus (-0.707×5, -0.707×5), that is, (5 - 3.54, 5 - 3.54), approximately (1.46, 1.46). Another option is to select the position in the reverse extension direction of the task point, that is, (5, 5) plus (+3.54, +3.54), approximately (8.54, 8.54). The on-site engineer will judge which side is safer and has lower movement costs based on factors such as terrain, obstacle distribution, and road conditions, and finally determine the best position. Suppose after comprehensive evaluation, (1.46, 1.46) is selected as the best position.

[0061] For lifting task 2, the task point is located at (18, -2), and the suitable crane for this task is crane B, whose initial position is (20, 0). Calculate the difference vector (18 - 20, -2 - 0) = (-2, -2), and its length is approximately 2.83 meters. The unit vector after normalization is approximately (-0.707, -0.707). If a safety distance of 5 meters is used, extending 5 meters from the task point can obtain the position (18, -2) plus (-0.707×5, -0.707×5), approximately (18 - 3.54, -2 - 3.54), that is, (14.46, -5.54). However, similarly, the on-site situation determines whether to choose this side or the other side, and finally determines the best position coordinates.

[0062] For crane selection, the on-site measurement equipment can be used to determine the straight-line distance between the initial position of each crane and the task point; then calculate the weight of the lifted object according to the mass of the lifted object. For example, 2000 kilograms here corresponds to approximately 19,620 Newtons; assuming a working distance of m meters during lifting, calculate the load moment generated by the lifted object at this distance. The anti-overturning moment data of the crane can also be used. For example, the anti-overturning moment of crane C is 350,000 (Newton·meter), to calculate the anti-overturning redundancy index, that is, the anti-overturning moment divided by the load moment. Combining the movement distance of the crane from the initial position to the task site and the preset coefficient k, calculate the comprehensive score. Select the crane with the highest comprehensive score as the best equipment for this lifting task. For example, crane C is selected for lifting task 1.

[0063] Based on the coordinate difference between the task point and the initial position of the crane, the direction vector between the two can be calculated and normalized. Taking the safety distance of m meters as the benchmark, extend m meters along the positive or negative direction of the unit vector from the task point to calculate the candidate standing positions. Considering factors such as on-site obstacles, terrain conditions, and movement costs, the optimal standing position is finally determined. It should be noted here that since the initial position of the crane is (10, 10), if we want to reduce the movement distance and ensure that the lifted object is within the operation safety range, we can consider adjusting the standing position to the other side m meters away from the task point. Another option is to calculate the direction from the initial position of the crane C to the task point and select the point m meters away from the task point in the extended direction of the line connecting the task point and the initial position of the crane C. For example, for the lifting task 1 and the crane C here, according to the calculation, the candidate standing positions are (1.46, 1.46) or (8.54, 8.54), and the optimal solution is selected after on-site evaluation.

[0064] The above specific embodiments illustrate in detail how to select the most suitable crane and determine the optimal standing position based on the actual on-site physical data by calculating the weight of the lifted object, the movement distance, the load moment, and the anti-overturning ability of the crane. This data-driven optimization process not only considers static parameters but also combines movement costs and the actual on-site environment to ensure that the lifting operation reaches the optimal state in terms of safety and operation efficiency.

[0065] The described lifting and moving device planning system runs on any computing device such as a desktop computer, a laptop computer, a handheld computer, or a cloud data center. The computing device includes: a processor, a memory, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps in the described lifting and moving device planning method. The operable system may include, but is not limited to, a processor, a memory, and a server cluster.

[0066] An embodiment of the present invention provides a lifting and moving device planning system, as Figure 2 shown. The lifting and moving device planning system of this embodiment includes: a processor, a memory, and a computer program stored in the memory and operable on the processor. When the processor executes the computer program, it implements the steps in the above-described embodiment of the lifting and moving device planning method. The processor executes the computer program and runs in the following units of the system: An input unit for inputting the initial position data, anti-overturning moment data, and maximum working radius data of each lifting and moving device, and inputting the weight of the lifted object corresponding to each lifting task and its lifting point coordinate data; A calculation unit, configured to calculate the anti - tipping redundancy index of each hoisting mobile device at an ideal standing distance by obtaining the weight of the hoisted object, the moving distance between the hoisting point coordinates and the initial position of the hoisting mobile device, and the anti - tipping moment of the hoisting mobile device, obtain the moving cost coefficient from the anti - tipping redundancy index, and select the hoisting mobile device with the highest hoisting and moving efficiency by combining the anti - tipping redundancy index, the moving cost coefficient, and the moving distance; An output unit, configured to, for the selected hoisting mobile device, calculate the unit vector between the hoisting point coordinates and the initial position of the hoisting mobile device according to the connection direction between the hoisting point coordinates and the initial position of the hoisting mobile device, and combine the working radius data of the hoisting mobile device with the unit vector to generate the output ideal standing position for the selected hoisting mobile device.

[0067] Among them, in order to better unify the linear relationship and probability connection of the numerical values between physical quantities of different units, dimensionless processing can be performed on different physical quantities.

[0068] Among them, preferably, for all undefined variables in the present invention, if there is no clear definition, they can all be manually set thresholds.

[0069] The hoisting mobile device planning system can run on computing devices such as desktop computers, laptop computers, palm computers, and cloud data centers. The hoisting mobile device planning system includes, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above examples are only examples of a hoisting mobile device planning method, system, and device, and do not constitute a limitation on a hoisting mobile device planning method, system, and device. It may include more or fewer components than the examples, or combine certain components, or different components. For example, the hoisting mobile device planning system may also include input - output devices, network access devices, buses, etc.

[0070] The present invention also provides an electronic device, a readable storage medium, and a computer program product: An electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the hoisting mobile device planning method and the methods of each step therein.

[0071] A non - transitory computer - readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the hoisting mobile device planning method and the methods of each step therein.

[0072] A computer program product includes a computer program which, when executed by a processor, implements the method for planning a hoisting and moving device and the methods of the various steps therein.

[0073] Among them, the electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the invention described and / or claimed herein.

[0074] Various embodiments of the systems and techniques described above in this article can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a dedicated or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0075] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to the processor or controller of a general-purpose computer, a dedicated computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program codes can be executed entirely on the machine, partially on the machine, executed partially on the machine as an independent software package and partially on a remote machine, or executed entirely on a remote machine or server.

[0076] In the context of the present invention, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0077] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0078] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0079] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship to each other.

[0080] The so-called processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete component gate circuits, or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the hoisting mobile device planning system, and connects all sub-regions of the entire hoisting mobile device planning system through various interfaces and lines.

[0081] The memory can be used to store the computer programs and / or modules. The processor realizes various functions of the hoisting mobile device planning method, system, and equipment by running or executing the computer programs and / or modules stored in the memory, and by calling the data stored in the memory. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, at least one magnetic disk storage device, flash device, or other volatile solid-state storage devices.

[0082] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present invention can be achieved, and no limitations are imposed herein.

[0083] The present invention provides a method, system and device for planning a hoisting and moving device. By calculating the anti-tipping redundancy index of each hoisting and moving device at the ideal standing position distance, the moving cost coefficient is obtained from the anti-tipping redundancy index. The hoisting and moving device with the highest moving hoisting efficiency is selected by combining the anti-tipping redundancy index, the moving cost coefficient and the moving distance. For the selected hoisting and moving device, according to the direction of the line connecting the hoisting point coordinates and the initial position of the hoisting and moving device, the unit vector between the hoisting point coordinates and the initial position of the hoisting and moving device is calculated. Combining the working radius data of the hoisting and moving device with the unit vector, the ideal standing position is generated for the selected hoisting and moving device. The load-bearing, stability and moving cost of the equipment are organically combined, realizing the global optimal decision-making and ensuring that the crane selected in the complex hoisting site is both safe and efficient.

[0084] The above specific embodiments do not constitute a limitation to the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A planning method for a hoisting and moving device. In a hoisting site to be automatically planned, there are multiple hoisting and moving devices and multiple hoisting tasks, characterized in that, The method includes the following steps: Establish a unified planar coordinate system, input the initial position data, anti-overturning moment data, and maximum working radius data of each hoisting and moving device, and input the weight of the hoisted object corresponding to each hoisting task and the coordinate data of its hoisting point; By obtaining the weight of the hoisted object, the moving distance between the hoisting point coordinates and the initial position of the hoisting and moving device, and the anti-overturning moment of the hoisting and moving device, calculate the anti-overturning redundancy index of each hoisting and moving device at the ideal standing distance, obtain the moving cost coefficient from the anti-overturning redundancy index, and select the hoisting and moving device with the highest moving hoisting efficiency by combining the anti-overturning redundancy index, the moving cost coefficient, and the moving distance; For the selected hoisting and moving device, calculate the unit vector between the hoisting point coordinates and the initial position of the hoisting and moving device according to the connection direction between the hoisting point coordinates and the initial position of the hoisting and moving device, and combine the working radius data of the hoisting and moving device with the unit vector to generate the output ideal standing position for the selected hoisting and moving device.

2. The planning method of a hoisting and moving device according to claim 1, characterized in that Wherein, The hoisting and moving device is a device with hoisting and moving functions, specifically including a crane.

3. A method for planning a hoisting and moving device according to claim 1, characterized in that, Wherein, The value of the anti-overturning moment of the hoisting and moving device is obtained by multiplying the value of the horizontal distance from the center of gravity of the hoisting and moving device to the tipping boundary by the value of the effective counterweight of the hoisting and moving device.

4. A planning method for a hoisting and moving device according to claim 3, characterized in that, Wherein, The working radius data of each hoisting and moving device includes the value of its maximum working radius and the value of its minimum working radius.

5. A planning method for a hoisting and moving device according to claim 1, characterized in that Wherein, The method for selecting the hoisting and moving device with the highest moving hoisting efficiency by combining the anti-overturning redundancy index, the moving cost coefficient, and the moving distance is as follows: For each hoisting point coordinate, obtain the moving distance between the initial position of each hoisting and moving device and the hoisting point coordinate; The ideal standing distance for the hoisting point coordinate is the maximum value among the minimum working radii of each hoisting and moving device; Divide the value of the anti-overturning moment of each hoisting and moving device by the product of the weight of the hoisted object in this hoisting task and the ideal standing distance, and the quotient obtained is the anti-overturning redundancy index of each hoisting and moving device; Normalize the values of the anti-overturning redundancy indices of each hoisting and moving device, and use the variance of the normalized values of the anti-overturning redundancy indices of each hoisting and moving device as the moving cost coefficient; Use the value of the anti-overturning redundancy index of each hoisting and moving device as the numerator, and use the sum of the product of the moving cost coefficient and the moving distance plus one as the denominator to calculate the moving hoisting efficiency of each hoisting and moving device, and select the hoisting and moving device with the highest moving hoisting efficiency value for this hoisting task.

6. A method for planning a hoisting and moving device, according to claim 5, characterized in that Wherein, The method for combining the working radius data of the hoisting and moving device with the unit vector to generate the ideal standing position for the selected hoisting and moving device is as follows: For each selected hoisting and moving device, obtain the coordinates of its corresponding hoisting task, obtain the initial position of the selected hoisting and moving device, calculate the unit vector obtained by subtracting the initial position of the selected hoisting and moving device from the coordinates of its corresponding hoisting task, and let the value of the ideal standing position distance be the value of the minimum working radius of the selected hoisting and moving device. The coordinates of the ideal standing position are the sum obtained by adding the value of its ideal standing position distance multiplied by the unit vector to the coordinates of its corresponding hoisting task.

7. A method for planning a hoisting and moving device, according to claim 6, characterized in that, Wherein, the coordinates of the ideal standing position may also be the difference obtained by subtracting the value of its ideal standing position distance multiplied by the unit vector from the coordinates of its corresponding hoisting task.

8. A method for planning a hoisting and moving device, according to claim 6, wherein Wherein, let the specific value of the movement cost coefficient be 0.

1.

9. A hoisting and moving device planning system, characterized in that, The hoisting and moving device planning system runs on any computing device such as a desktop computer, a laptop computer or a cloud data center. The computing device includes: a processor, a memory, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps in the hoisting and moving device planning method according to any one of claims 1 to 8.

10. An electronic device, comprising: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor. The instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1 to 8.

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