Intelligent tower crane operation management method and system based on digital twinning

Abstract

The invention provides an intelligent tower crane operation management method and system based on digital twinning, and relates to the technical field of tower crane operation management.The method comprises the steps that an APF combination sequence is used for tracking the construction progress, obtaining production requirements, outputting operation requirements, selecting an optimal tower crane and an optimal hoisting control strategy, forming an operation instruction and distributing the operation instruction to a tower crane operation terminal; and the tower crane operation terminal is connected with the edge node, tracks the safety state of the tower crane corresponding to the operation instruction, and sends an on-way reminding instruction to inform operators on the way to carry out safety management. Through the method, the technical problem of low operation efficiency caused by difficulty in realizing optimal resource allocation due to limitation of a traditional method in the prior art can be solved, the construction progress is tracked through the APF combination sequence, the operation instruction is allocated in combination with the optimal hoisting algorithm, the safety state of the tower crane is monitored in real time, intelligent management of tower crane operation scheduling is realized, and the working efficiency is improved. The technical effect of improving the overall construction efficiency is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of tower crane operation management, and in particular to an intelligent management method and system for tower crane operations based on digital twins. Background Art

[0002] With the development of industrial technology, the demand for large-scale construction is increasing, especially in aerial work. Large-scale hoisting services are now widely used in many key areas, and tower crane operation management is gradually developing towards automation and intelligence.

[0003] At present, the existing tower crane operation management still has some defects in efficiency, safety and resource utilization.

[0004] In summary, the prior art has the technical problem that it is difficult to achieve optimal resource allocation due to the limitations of traditional methods, resulting in low operating efficiency. Summary of the invention

[0005] The purpose of this application is to provide an intelligent management method and system for tower crane operations based on digital twins, so as to solve the technical problem in the prior art that it is difficult to achieve optimal resource allocation due to the limitations of traditional methods, resulting in low operating efficiency.

[0006] In view of the above problems, the present application provides an intelligent management method and system for tower crane operations based on digital twins.

[0007] In the first aspect, the present application provides an intelligent management method for tower crane operations based on digital twins, and the method is implemented through an intelligent management system for tower crane operations based on digital twins, wherein the method includes: using an APF combination sequence to track the construction progress of tower crane operations to obtain the current construction progress; obtaining production requirements, and outputting operation requirements in combination with the current construction progress, wherein the operation requirements include lifting material requirements, current lifting position, unloading position, lifting time, and tower crane operation status within the lifting time window; based on the operation requirements, using the optimal lifting algorithm, selecting the optimal tower crane and the optimal lifting control strategy, forming operation instructions and assigning them to corresponding tower crane operation terminals; after receiving the operation instructions, the tower crane operation terminal connects to the tower crane safety management edge node, tracks the safety status of the tower crane during the lifting process corresponding to the operation instructions, and issues reminder instructions along the way; based on the reminder instructions along the way, notify the operators along the way to perform safety management.

[0008] In the second aspect, the present application also provides an intelligent management system for tower crane operations based on digital twins, which is used to execute the method described in the first aspect, wherein the system includes: a construction progress acquisition module, which is used to use the APF combination sequence to track the construction progress of the tower crane operation and obtain the current construction progress; a production demand acquisition module, which is used to obtain production demand, and output operation demand in combination with the current construction progress, and the operation demand includes hoisting material demand, current hoisting position, unloading position, hoisting time and tower crane operation status within the hoisting time window; an optimal hoisting algorithm module, which is used to select the optimal tower crane and the best lifting control strategy based on the operation demand using the optimal hoisting algorithm, and form operation instructions to assign to corresponding tower crane operation terminals; a reminder instruction issuance module, which is used for the tower crane operation terminal to connect to the tower crane safety management edge node after receiving the operation instruction, track the safety status of the tower crane during the hoisting process corresponding to the operation instruction, and issue reminder instructions along the way; a safety management notification module, which is used to notify the operators along the way to perform safety management based on the reminder instructions along the way.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages: The construction progress of the tower crane operation is tracked by using the APF combined sequence to obtain the current construction progress; the production demand is obtained, and the operation demand is output in combination with the current construction progress. The operation demand includes the lifting material demand, the current lifting position, the unloading position, the lifting time, and the tower crane operation status within the lifting time window; based on the operation demand, the optimal lifting algorithm is used to select the optimal tower crane and the best lifting control strategy, and the operation instructions are formed and assigned to the corresponding tower crane operation terminal; after receiving the operation instruction, the tower crane operation terminal connects to the tower crane safety management edge node, tracks the safety status of the tower crane during the lifting process corresponding to the operation instruction, and issues reminder instructions along the way; based on the reminder instructions along the way, the operators along the way are notified to perform safety management. The construction progress is tracked by using the APF combined sequence, the operation instructions are assigned in combination with the optimal lifting algorithm, the safety status of the tower crane is monitored in real time, and the intelligent management of the tower crane operation scheduling is realized, thereby achieving the technical effect of improving the overall construction efficiency.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0012] Figure 1 This is a flow chart of the intelligent management method for tower crane operations based on digital twins in this application; Figure 2 This is a structural diagram of the tower crane operation intelligent management system based on digital twins in this application.

[0013] Explanation of the reference numerals: construction progress acquisition module 11, production demand acquisition module 12, optimal lifting algorithm module 13, reminder instruction issuance module 14, safety management notification module 15. DETAILED DESCRIPTION

[0014] This application solves the technical problem in the prior art that it is difficult to achieve optimal resource allocation due to the limitations of traditional methods, resulting in low operating efficiency, by providing an intelligent tower crane operation management method and system based on digital twins. The construction progress is tracked through the APF combination sequence, the operation instructions are allocated in combination with the optimal lifting algorithm, the safety status of the tower crane is monitored in real time, and the intelligent management of tower crane operation scheduling is realized, thereby achieving the technical effect of improving the overall construction efficiency.

[0015] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0016] Embodiment 1 Please see attached Figure 1 The present application provides a tower crane operation intelligent management method based on digital twins, wherein the method is applied to a tower crane operation intelligent management system based on digital twins, and the method specifically comprises the following steps: Step 1: Use the APF combination sequence to track the construction progress of the tower crane operation and obtain the current construction progress.

[0017] Specifically, real-time data, including the position, motion state, load condition, etc. of the tower crane, is collected through sensors and monitoring systems installed on the tower crane. The collected data is used to establish a potential field model of the construction site to reflect the working environment and construction progress of the tower crane. The potential field model is analyzed to predict and calculate the current construction progress, including the amount of work completed and the remaining work. APF is an algorithm based on artificial intelligence and machine learning that is used to simulate and control robots or equipment in dynamic environments, such as tower cranes. In tower crane operations, APF can be used to simulate and analyze the working progress and environment of the tower crane, including its movement path, working area, and potential obstacles, in order to optimize the working process and improve efficiency. Combination sequence refers to combining multiple APF algorithms or models together to handle more complex working environments. In tower crane operations, this may involve considering multiple working points, different tower cranes, and various working restrictions at the same time. Through the combination sequence, the system can track the real-time position and status of the tower crane, thereby obtaining the current construction progress, and realizing real-time tracking and optimization management of the construction progress.

[0018] Step 2: Obtain production demand, combine the current construction progress, and output operation demand, the operation demand including lifting material demand, current lifting position, unloading position, lifting time, and tower crane operation status within the lifting time window.

[0019] Specifically, the system collects information on production requirements from the management system of the construction site and the managers of each flow section, including the type, quantity, and purpose of the hoisted materials, and combines the obtained production requirements with the current construction progress tracked through the APF combination sequence to ensure that the operation requirements match the actual situation of the construction site and avoid operation conflicts or delays caused by information asymmetry. Based on the combination of information from both, the system outputs specific operation requirements, including the type and quantity of hoisted materials, the starting and ending positions of hoisting, the specific time of hoisting, and the expected operating status of the tower crane during the hoisting period. By integrating real-time data and demand information, accurate operation instructions are provided to the construction site to reduce uncertainty in the operation process.

[0020] Step 3: Based on the operation requirements, use the optimal lifting algorithm to select the optimal tower crane and the best lifting control strategy, and form operation instructions to be allocated to the corresponding tower crane operation terminal.

[0021] Specifically, according to the output operation requirements, the optimal lifting algorithm is used to analyze the operation requirements by comprehensively considering factors such as the location, busyness, and performance of the tower crane. The system selects the most suitable tower crane to complete the task based on the operation requirements (weight of the lifting material, lifting position, etc.) and the performance parameters of the tower crane (such as lifting capacity, operating radius, etc.). The optimal lifting control strategy takes into account factors such as safety distance, operation path optimization, and obstacle avoidance, and determines the detailed steps to complete the lifting task, including lifting, moving, and unloading. According to the results of the optimal lifting algorithm, specific operation instructions are formed, including the operation sequence of the tower crane, lifting control parameters, etc. The generated operation instructions are assigned to the corresponding tower crane operation terminal, which can be the work equipment of the tower crane driver or the control panel fixed on the tower crane. The optimal lifting algorithm is a decision support tool based on digital models and algorithms, which is used to analyze different lifting schemes and select the optimal solution. The optimal lifting scheme and strategy provided by the system provide clear decision support for on-site managers and tower crane drivers, reducing the uncertainty of human judgment.

[0022] Step 4: After receiving the operation instruction, the tower crane operation terminal connects to the tower crane safety management edge node, tracks the safety status of the tower crane during the lifting process corresponding to the operation instruction, and issues reminder instructions along the way.

[0023] Specifically, the tower crane operation terminal receives the operation instructions of the system, which clarifies the operation content and requirements of the tower crane. Through wireless or wired means, a connection is established with the tower crane safety management edge node to monitor the key safety indicators of the tower crane, such as position, load, speed, etc., as well as the surrounding environment information in real time to ensure that the tower crane is always in a safe state during the operation. If there is a safety hazard in the operation state of the tower crane, the edge node will issue a reminder instruction along the way to the tower crane driver. The connection safety management edge node is an intelligent device installed on the tower crane, which is used to collect and analyze the operation data of the tower crane in real time, including the position, speed, load, tilt angle, etc. of the tower crane. The edge node is a computing device located near the tower crane, which is responsible for processing and analyzing real-time data to ensure the safety of the tower crane operation. The edge node analyzes the monitored data to determine whether the tower crane is within the safe operation range. If there are potential safety hazards, such as approaching overload, exceeding the operating range, and the risk of collision, the edge node will trigger an alarm and issue a reminder instruction along the way. These instructions can be sound, visual or tactile signals to remind the driver to pay attention to the current operation status and take corresponding safety measures to ensure that the tower crane works within a safe range. Reduce the occurrence of safety accidents at construction sites through real-time tracking and early warning.

[0024] Step 5: Based on the reminder instructions along the way, notify the workers along the way to perform safety management.

[0025] Specifically, when a potential safety risk is detected, the tower crane safety management edge node or central control system promptly notifies the relevant personnel at the construction site through effective communication means (such as radio, sound alarm, mobile device push, etc.), ensuring that the workers along the way take corresponding safety measures, including evacuating the dangerous area, stopping work, adjusting the working method or adding safety protection measures, etc. Timely and effective communication and response can help reduce accidents at the construction site.

[0026] Furthermore, step one of this application includes: The position data and motion data of the tower crane operation group towers at the tower crane construction site are collected in real time through the Beidou satellite navigation system; the position data and motion data of the tower crane operation group towers are processed using big data analysis technology to form an APF combination sequence; the APF combination sequence is pattern recognized through a machine learning algorithm to determine the current construction progress.

[0027] Specifically, at the construction site, the Beidou satellite navigation system collects the position, speed, acceleration and other information of each tower crane in real time, and transmits this data to the central processing system. By processing this data with big data analysis technology, valuable information can be extracted through data mining or analysis. Based on the structure of big data analysis, the system constructs an APF (adaptive potential field) combination sequence to form a sequence that can reflect the operating environment and dynamics of the tower crane. Furthermore, by using machine learning algorithms to perform pattern recognition on the APF combination sequence, it can automatically learn and identify the laws and patterns in the tower crane operation, understand the dynamic characteristics of the tower crane operation, and determine the current construction progress accordingly.

[0028] The BeiDou Navigation Satellite System is a global satellite navigation system independently developed by China that can provide high-precision position and velocity information for a variety of positioning and navigation applications, including tower crane operations at construction sites. Big data analysis technology is a method of processing and analyzing large amounts of data to extract valuable information. In tower crane operations, it involves cleaning, integrating, analyzing, and mining the collected position and motion data to understand the dynamics of the construction site. Machine learning algorithms are an artificial intelligence technology that allows computers to learn from data and make decisions or predictions. In tower crane operations, machine learning algorithms can use linear regression or time series analysis to predict construction progress.

[0029] In a specific example, there are 8 tower cranes working at the same time at a construction site. Each tower crane is equipped with a Beidou satellite navigation system to collect real-time location and motion data, including moving speed and direction. These data information are transmitted to the central processing system via a wireless network, and the data are cleaned, integrated, analyzed, and visualized through big data analysis technology. The system constructs an APF combination sequence to simulate the virtual potential field of the construction site and reflect the working environment and dynamics of these tower cranes. The linear regression algorithm is selected, and the machine learning model is trained using historical data. The APF combination sequence is pattern recognized by the model to discover potential patterns and laws. Based on the learning model, the system predicts that the hoisting operation in one of the areas will be completed in the next few hours, so as to plan the next stage of the operation tasks in advance, such as adjusting the operation plan or reallocating resources. Through real-time monitoring and prediction capabilities, it helps on-site managers to better coordinate operations and improve construction efficiency.

[0030] Further, step three of this application includes: According to the operation demand time in the operation demand, the tower crane operation group towers at the tower crane construction site are connected; based on the busyness of the tower crane operation group towers at the tower crane construction site, the tower crane construction busyness sequence is obtained; based on the transportation distance of the tower crane operation group towers at the tower crane construction site, the tower crane operation group towers are sorted from small to large to obtain the operation equipment transportation distance sequence; through the tower crane construction busyness sequence and the operation equipment transportation distance sequence, combined with the operation equipment performance, the optimal tower crane is selected.

[0031] Specifically, according to the operation demand time in the operation demand, all tower cranes at the tower crane construction site are connected in real time through the Beidou satellite navigation system, and the position and motion data of each tower crane are transmitted to the central control system in real time. The system analyzes the current operation volume and the amount of tasks waiting for each tower crane to obtain the busyness sequence of the tower crane. According to the distance from the current position of each tower crane to the operation target point, the tower cranes are sorted from small to large in terms of transportation distance to obtain a transportation distance sequence of operation equipment. Considering the busyness, transportation distance and performance parameters (such as lifting capacity, load capacity, moving speed, etc.) of the tower crane, the tower crane that best suits the current operation demand is selected. For example, the system at the construction site sorts the tower cranes according to their busyness and transportation distance. The analysis shows that tower crane 1 has better performance and is currently the busiest, tower crane 2 has the best performance and has three waiting tasks, tower crane 3 has medium performance, has one waiting task and is closest to the current operation point, and tower crane 4 has better performance, currently has no waiting tasks and is the second closest to the current operation point. Combining these factors, the system selects tower crane 4 to complete the current lifting task. By comprehensively considering multiple factors, the system can achieve optimal allocation of resources and reduce unnecessary waiting and movement time.

[0032] Furthermore, the present application also includes the following steps: Collect and analyze historical operation data of tower cranes, the historical operation data including lifting times, operation efficiency and safety accident records; use statistical methods to establish a tower crane operation safety prediction model; based on the tower crane operation safety prediction model, evaluate the expected performance of the tower crane operation group at the tower crane construction site under the operation requirements, and select the optimal tower crane.

[0033] Specifically, the operation data of the tower crane over the past period of time, including the number of hoisting times, operation efficiency and safety accident records, are collected from the log files, safety reports, operation records, etc. of the tower crane. The collected data are analyzed using statistical methods, such as regression analysis and time series analysis, to identify the key factors affecting the safety of tower crane operations. A prediction model is established to predict the safety risks of future operations. According to the current operation requirements, such as the type of hoisting materials, the weight of hoisting materials, and the hoisting height, the operation performance of each tower crane is predicted. Combined with historical data and prediction models, the expected performance of each tower crane under the current operation requirements is evaluated, and the tower crane that best suits the current operation requirements is selected. For example, if an operation requirement is to hoist a cargo weighing 50 tons, the system needs to evaluate the hoisting capacity, safety and operation efficiency of each tower crane. First, tower cranes with a hoisting capacity of less than or equal to 50 tons are excluded, and then the tower crane with the best performance and highest safety is selected to complete this operation requirement based on the performance and safety of the tower crane. By integrating the historical performance of the tower crane and the specific needs of the current operation, the safety of the tower crane can be evaluated through a predictive model, avoiding the use of tower cranes that are not suitable for the current operation needs, which helps reduce the risk of safety accidents.

[0034] Further, step 4 of this application includes: Connect to the on-site monitoring equipment to obtain environmental monitoring data, which includes wind speed data and wind direction data; based on the tower crane safety management edge node, receive and parse the operation instructions of multiple tower crane operation terminals corresponding to the tower crane operation group tower at the tower crane construction site, and perform wind deflection angle compensation in combination with the environmental monitoring data.

[0035] Specifically, various environmental monitoring devices are installed, such as anemometers, hygrothermometers, barometers, ultraviolet detectors, surveillance cameras, etc., to monitor the environmental data of the construction site and the operation of each tower crane in real time. These monitoring devices are connected by wire or wireless means to collect data monitored at the construction site, such as wind speed and wind direction, in real time. The tower crane safety management edge node receives operation instructions issued by multiple tower crane operation terminals connected to it, such as hoisting position, height, speed, etc. The environmental monitoring data is analyzed and the impact of these data on the tower crane operation is calculated, especially the wind speed and direction data, including the wind deflection angle. The system automatically adjusts the tower crane operation instructions and compensates for the wind deflection angle to ensure the safety of the operation. Wind deflection angle compensation means that in the tower crane operation, according to the influence of wind direction and wind speed, the deflection angle of the wind on the hoisted object is calculated, and the hoisting path and angle of the tower crane are automatically adjusted to maintain the stability of the hoisted object and avoid deviation or safety risks caused by wind force. Assume that the wind speed at the construction site is 15 meters per second and the wind direction is southeast. A tower crane needs to lift a heavy object from one point to another. Due to the influence of wind speed and direction, the lifting path may deviate from the target. With wind deflection angle compensation, the system will automatically adjust the tower crane's operating instructions to make the lifting path deviate to the northwest to offset the influence of southeast wind. Through real-time environmental monitoring and wind deflection angle compensation, the accuracy of the lifting path is ensured and the risk of safety accidents caused by wind is reduced.

[0036] Furthermore, the present application also includes the following steps: Based on the tower crane safety management edge node, sensor monitoring data is extracted, and the sensor monitoring data includes hoisting gravity, hoisting speed, and rotation speed; the sensor monitoring data is synchronized to the tower crane safety management edge node using edge computing technology; at the tower crane safety management edge node, the wind deflection angle is calculated by combining the environmental monitoring data and the sensor monitoring data, and the operating parameters of the tower crane are adjusted in real time.

[0037] Specifically, each tower crane is equipped with various sensors, such as the hoisting gravity sensor to monitor the size of the hoisting gravity in real time, the hoisting speed sensor to monitor the descent speed of the hoisted object, the rotation speed sensor to monitor the rotation speed of the tower crane, and the anemometer and wind vane to monitor the wind speed and wind direction in real time and collect key parameters. Data processing and analysis, such as filtering, compression and classification, are performed through edge computing devices. The processed data is synchronized to the tower crane safety management edge node, which is a small and efficient computing device installed near or on the tower crane. The system integrates data from environmental monitoring (such as wind speed and wind direction) and sensor monitoring data (such as hoisting gravity, hoisting speed, and rotation speed) to calculate the impact of wind on the tower crane operation, that is, the wind deflection angle. According to the calculated wind deflection angle, the operating parameters of the tower crane are adjusted in real time, including changing the hoisting path, adjusting the hoisting gravity, adjusting the rotation speed, etc., to offset the impact of the wind. Edge computing technology is a distributed computing model that transfers the task of data processing and analysis from the centralized cloud server to the edge of the network, that is, the source of data generation. The purpose of this technology is mainly to reduce data transmission delays, improve real-time processing capabilities, and reduce the burden on centralized data centers. Exemplarily, various sensors and an edge computing device are installed on the tower crane. When the tower crane is performing hoisting operations, the sensors collect data in real time, such as hoisting weight, hoisting speed, and rotation speed. The edge computing device performs preliminary processing on these data and calculates the real-time changes in hoisting weight and hoisting speed, as well as the wind deflection angle. Based on the calculated wind deflection angle, the edge computing device can adjust the operating parameters of the tower crane in real time, change the hoisting path or adjust the hoisting weight, and can also adjust the rotation speed of the tower crane to ensure that the hoisted object can be placed in the best position, compensate for the wind deflection angle, and reduce the swing and error caused by the wind. Through real-time monitoring and analysis, the system can automatically adjust the operating parameters of the tower crane to cope with environmental changes.

[0038] Furthermore, step five of this application includes: Based on the reminder instructions along the way, reminder instructions are sent to the workers along the way; and the sending and receiving of the reminder instructions and the responses of the workers along the way are recorded.

[0039] Specifically, when a potential safety risk is detected, the system automatically generates a reminder instruction along the way and sends it to the workers along the way. The system records the sending time, sending method and recipient of the reminder instruction, tracks the communication of the reminder instruction, and ensures that all staff have received the safety reminder. At the same time, the response of the workers along the way to the reminder instruction is recorded, such as whether safety measures have been taken or the dangerous area has been evacuated, based on which the effectiveness of the reminder system is evaluated and appropriate improvements are made. For example, when a tower crane is performing a hoisting operation, the system detects that the tower crane is close to the upper limit of the work and there is a risk of collision. The system immediately generates a reminder instruction along the way and pushes it to the workers along the way through the mobile device. After seeing the reminder, the personnel along the line immediately take measures to stop the operation. The system records the sending time, sending method, recipient, response, countermeasures, etc. of the reminder instruction. By automatically generating and sending reminders, and recording the actual situation, it helps to prevent danger and provide data support for subsequent safety management.

[0040] In summary, the tower crane operation intelligent management method based on digital twins provided in this application has the following technical effects: The construction progress of the tower crane operation is tracked by using the APF combined sequence to obtain the current construction progress; the production demand is obtained, and the operation demand is output in combination with the current construction progress. The operation demand includes the lifting material demand, the current lifting position, the unloading position, the lifting time, and the tower crane operation status within the lifting time window; based on the operation demand, the optimal lifting algorithm is used to select the optimal tower crane and the best lifting control strategy, and the operation instructions are formed and assigned to the corresponding tower crane operation terminal; after receiving the operation instruction, the tower crane operation terminal connects to the tower crane safety management edge node, tracks the safety status of the tower crane during the lifting process corresponding to the operation instruction, and issues reminder instructions along the way; based on the reminder instructions along the way, the operators along the way are notified to perform safety management. The construction progress is tracked by using the APF combined sequence, the operation instructions are assigned in combination with the optimal lifting algorithm, the safety status of the tower crane is monitored in real time, and the intelligent management of the tower crane operation scheduling is realized, thereby achieving the technical effect of improving the overall construction efficiency.

[0041] Embodiment 2 Based on the same inventive concept as the tower crane operation intelligent management method based on digital twin in the aforementioned embodiment, the present application also provides a tower crane operation intelligent management system based on digital twin, please refer to the attached Figure 2 , the system comprising: The construction progress acquisition module 11 is used to track the construction progress of the tower crane operation by using the APF combination sequence to acquire the current construction progress.

[0042] The production demand acquisition module 12 is used to acquire production demand and output operation demand in combination with the current construction progress. The operation demand includes lifting material demand, current lifting position, unloading position, lifting time and tower crane operation status within the lifting time window.

[0043] The optimal lifting algorithm module 13 is used to select the optimal tower crane and the best lifting control strategy based on the operation requirements using the optimal lifting algorithm, and form operation instructions to be allocated to the corresponding tower crane operation terminal.

[0044] The reminder instruction issuing module 14 is used for the tower crane operation terminal to connect to the tower crane safety management edge node after receiving the operation instruction, track the safety status of the tower crane during the lifting process corresponding to the operation instruction, and issue reminder instructions along the way.

[0045] The safety management notification module 15 is used to notify the operators along the way to perform safety management based on the reminder instructions along the way.

[0046] Furthermore, the construction progress obtaining module 11 in the system is also used for: The position data and motion data of the tower crane operation group towers at the tower crane construction site are collected in real time through the Beidou satellite navigation system; the position data and motion data of the tower crane operation group towers are processed using big data analysis technology to form an APF combination sequence; the APF combination sequence is pattern recognized through a machine learning algorithm to determine the current construction progress.

[0047] Furthermore, the optimal lifting algorithm module 13 in the system is also used for: According to the operation demand time in the operation demand, the tower crane operation group towers at the tower crane construction site are connected; based on the busyness of the tower crane operation group towers at the tower crane construction site, the tower crane construction busyness sequence is obtained; based on the transportation distance of the tower crane operation group towers at the tower crane construction site, the tower crane operation group towers are sorted from small to large to obtain the operation equipment transportation distance sequence; through the tower crane construction busyness sequence and the operation equipment transportation distance sequence, combined with the operation equipment performance, the optimal tower crane is selected.

[0048] Furthermore, the optimal lifting algorithm module 13 in the system is also used for: Collect and analyze historical operation data of tower cranes, the historical operation data including lifting times, operation efficiency and safety accident records; use statistical methods to establish a tower crane operation safety prediction model; based on the tower crane operation safety prediction model, evaluate the expected performance of the tower crane operation group at the tower crane construction site under the operation requirements, and select the optimal tower crane.

[0049] Furthermore, the reminder instruction issuing module 14 in the system is also used for: Connect to the on-site monitoring equipment to obtain environmental monitoring data, which includes wind speed data and wind direction data; based on the tower crane safety management edge node, receive and parse the operation instructions of multiple tower crane operation terminals corresponding to the tower crane operation group tower at the tower crane construction site, and perform wind deflection angle compensation in combination with the environmental monitoring data.

[0050] Furthermore, the reminder instruction issuing module 14 in the system is also used for: Based on the tower crane safety management edge node, sensor monitoring data is extracted, and the sensor monitoring data includes hoisting gravity, hoisting speed, and rotation speed; the sensor monitoring data is synchronized to the tower crane safety management edge node using edge computing technology; at the tower crane safety management edge node, the wind deflection angle is calculated by combining the environmental monitoring data and the sensor monitoring data, and the operating parameters of the tower crane are adjusted in real time.

[0051] Further, the security management notification module 15 in the system is also used for: Based on the reminder instructions along the way, reminder instructions are sent to the workers along the way; and the sending and receiving of the reminder instructions and the responses of the workers along the way are recorded.

[0052] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The tower crane operation intelligent management method based on digital twin and the specific examples in Example 1 are also applicable to the tower crane operation intelligent management system based on digital twin in this embodiment. Through the above detailed description of the tower crane operation intelligent management method based on digital twin, those skilled in the art can clearly know the tower crane operation intelligent management system based on digital twin in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0053] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0054] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. The intelligent management method of tower crane operation based on digital twin is characterized by: The method comprises: Use the APF combination sequence to track the construction progress of the tower crane operation and obtain the current construction progress; Obtain production demand, and output operation demand in combination with the current construction progress, wherein the operation demand includes hoisting material demand, current hoisting position, unloading position, hoisting time, and tower crane operation status within the hoisting time window; Based on the operation requirements, the optimal tower crane and the best lifting control strategy are selected using the optimal lifting algorithm to form operation instructions and allocate them to the corresponding tower crane operation terminals; After receiving the operation instruction, the tower crane operation terminal connects to the tower crane safety management edge node, tracks the safety status of the tower crane during the hoisting process corresponding to the operation instruction, and issues reminder instructions along the way; Based on the reminder instructions along the way, the operating personnel along the way are notified to perform safety management.

2. The method according to claim 1, characterized in that: Using the optimal hoisting algorithm, the optimal tower crane and the optimal hoisting control strategy are selected, and the method includes: Connecting the tower crane operation group towers at the tower crane construction site according to the operation demand time in the operation demand; Based on the busyness ranking of the tower crane operation groups at the tower crane construction site, a tower crane construction busyness sequence is obtained; Based on the tower crane operation group towers at the tower crane construction site, the transportation distances are sorted from small to large to obtain the operation equipment transportation distance sequence; The optimal tower crane is selected through the tower crane construction busyness sequence, the operating equipment transportation distance sequence, and the operating equipment performance.

3. The method according to claim 2, characterized in that: The optimal tower crane is selected in combination with the performance of the operating equipment. The method includes: Collect and analyze historical operation data of tower cranes, including the number of hoisting times, operation efficiency and safety accident records; Use statistical methods to establish a tower crane operation safety prediction model; According to the tower crane operation safety prediction model, the expected performance of the tower crane operation group at the tower crane construction site under the operation requirements is evaluated, and the optimal tower crane is selected.

4. The method according to claim 2, characterized in that: The construction progress of the tower crane operation is tracked by using the APF combination sequence to obtain the current construction progress. The method includes: The position data and movement data of the tower crane operation group towers at the tower crane construction site are collected in real time through the Beidou satellite navigation system; Using big data analysis technology to process the position data and motion data of the tower crane operation group towers to form an APF combination sequence; The APF combination sequence is subjected to pattern recognition through a machine learning algorithm to predict the current construction progress.

5. The method according to claim 4, characterized in that: Connecting to the tower crane safety management edge node, tracking the safety status of the tower crane during the hoisting process corresponding to the operation instruction, and issuing reminder instructions along the way, the method includes: Connecting to on-site monitoring equipment to obtain environmental monitoring data, the environmental monitoring data including wind speed data and wind direction data; Based on the tower crane safety management edge node, the operation instructions of multiple tower crane operation terminals corresponding to the tower crane operation group tower at the tower crane construction site are received and analyzed, and wind deflection angle compensation is performed in combination with the environmental monitoring data.

6. The method according to claim 5, characterized in that Receiving and parsing the operation instructions of multiple tower crane operation terminals corresponding to the tower crane operation group tower at the tower crane construction site, and performing wind deflection angle compensation in combination with the environmental monitoring data, the method includes: Based on the tower crane safety management edge node, extract sensor monitoring data, the sensor monitoring data includes hoisting gravity, hoisting speed, and rotation speed; Using edge computing technology, the sensor monitoring data is synchronized to the tower crane safety management edge node; At the tower crane safety management edge node, the wind deflection angle is calculated by combining the environmental monitoring data and the sensor monitoring data, and the operating parameters of the tower crane are adjusted in real time.

7. The method according to claim 1, characterized in that: Based on the reminder instruction along the way, notifying the operators along the way to perform safety management, the method includes: Based on the reminder instruction along the way, a reminder instruction is sent to the workers along the way; The sending and receiving of the reminder instructions and the responses of the workers along the way are recorded.

8. The tower crane operation intelligent management system based on digital twin is characterized by: For implementing the steps of the method according to any one of claims 1 to 7, the system comprises: A construction progress acquisition module is used to track the construction progress of the tower crane operation using the APF combination sequence to acquire the current construction progress; A production demand acquisition module, which is used to acquire production demand and output operation demand in combination with the current construction progress. The operation demand includes hoisting material demand, current hoisting position, unloading position, hoisting time, and tower crane operation status within the hoisting time window; An optimal hoisting algorithm module, which is used to select an optimal tower crane and an optimal hoisting control strategy based on the operation requirements using an optimal hoisting algorithm, and form an operation instruction to be allocated to a corresponding tower crane operation terminal; A reminder instruction issuing module, wherein the reminder instruction issuing module is used for the tower crane operation terminal to connect to the tower crane safety management edge node after receiving the operation instruction, track the safety status of the tower crane during the hoisting process corresponding to the operation instruction, and issue reminder instructions along the way; A safety management notification module is used to notify the operators along the way to perform safety management based on the reminder instructions along the way.

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