Full-process intelligent system for slow cooling of copper smelting slag ladle and working method

Abstract

The invention provides a full-process intelligent system for slow cooling of copper smelting slag ladles and a working method, and the system comprises a data management module which is used for collecting attributes, states and available resource data of equipment, smelting slag ladles and storage locations, and storing the attributes, states and available resource data in a database; the task generation module is used for generating a scheduling task based on the slag outlet state, the slag ladle cooling time, the equipment transport capacity and the storage space; the scheduling algorithm module is used for selecting the optimal equipment, smelting slag ladle and storage location from the database according to the specific requirements of the scheduling task; the communication protocol module is used for issuing an analyzable scheduling task instruction; the task execution and state feedback module is used for executing the task instruction by the equipment and feeding back an execution state to the system; the visual perception technology module is used for acquiring the geometrical shape and spatial position information of the target object and carrying out accurate positioning and information identification on the target object; and the manual processing module is used for transferring the abnormal condition to manual intervention auxiliary processing when the abnormal condition occurs in the system operation process.

Description

Technical Field

[0001] The present invention relates to the technical field of copper smelting process, and in particular to a full-process intelligent system and working method for slow cooling of a copper smelting slag ladle. Background Art

[0002] With the advancement of "carbon peak, carbon neutrality" and urbanization, the demand for copper in the fields of new domestic infrastructure, charging pile market, new energy vehicles and photovoltaic industry is continuing to grow. It is predicted that in the next three years, these fields will increase the demand for copper by at least 12.714 million tons. Against this backdrop, the copper industry is also constantly promoting technological innovation to adapt to market changes. The traditional copper smelting industry is transforming towards integration, intelligence and greening.

[0003] In the study and application of slag slow cooling automation control technology, the slag slow cooling automation control system was used to realize the cooling of the smelting slag bag and the automatic slag dumping of the slag bag, but it did not carry out systematic planning and coordinated scheduling of multiple machine models and multiple areas, and could not realize unmanned automated production.

[0004] Patent number CN201822081190.0, "A Scheduling System for Slow Cooling of Smelting Slag Ladles", realizes the cooling of smelting slag ladle through metallurgical gantry crane control subsystem, gantry sprinkler control subsystem, ground control station and ground scheduling subsystem. However, the patent does not have the function of automatic transportation, and cannot realize the automatic transportation and positioning of smelting slag ladle by using crane and electric flatbed car through intelligent control system.

[0005] Patent number CN202311725741.1, "An Intelligent Control Device and Method for Slow Cooling Process of Copper Smelting Slag", realizes the recycling of water in the process of water cooling of smelting slag ladle. At the same time, the automatic spray system combined with the scheduling system can intelligently control the slow cooling time of each slag ladle, reducing the error of manual timing. However, the water spraying device of this patent is fixed and cannot be freely scheduled.

[0006] Therefore, it is necessary to adopt new technologies and new equipment, and use modern information technologies such as big data and artificial intelligence to improve resource utilization, production efficiency and management level, reduce energy consumption and pollution, and achieve green and intelligent copper smelting. Summary of the invention

[0007] According to the technical problems raised above, a full-process intelligent system and working method for slow cooling of copper smelting slag ladle is provided. The present invention mainly utilizes data management module, task generation module, scheduling algorithm module, communication protocol module, task execution and state feedback module, visual perception technology module and manual processing module, combined with metallurgical gantry crane, automatic gantry sprinkler rail car, electric flatbed car, slag ladle pumping equipment and ladle turner to realize the intelligentization of slow cooling of copper smelting slag ladle.

[0008] The technical means adopted by the present invention are as follows:

[0009] A full-process intelligent system for slow cooling of copper smelting slag ladle, combining metallurgical gantry crane, automatic gantry sprinkler rail car, electric flatbed car, slag ladle pumping equipment and ladle turner, realizes intelligent slow cooling of copper smelting slag ladle, including: data management module, task generation module, scheduling algorithm module, communication protocol module, task execution and status feedback module, visual perception technology module and manual processing module, among which:

[0010] The data management module is used to collect the attributes, status and available resource data of equipment, smelting slag packages and storage locations, and save them in the database to provide data support;

[0011] The task generation module is used to generate scheduling tasks based on the slag outlet status, slag bag cooling time, equipment capacity and storage space;

[0012] The scheduling algorithm module is used to select the optimal equipment, smelting slag package and storage location from the database according to the specific requirements of the scheduling task;

[0013] The communication protocol module is used to issue parsable scheduling task instructions through the TCP communication protocol;

[0014] The task execution and status feedback module is used to receive the device task execution status and feed back the execution status to the system;

[0015] The visual perception technology module is used to obtain the geometric shape and spatial position information of the target object, and to accurately locate and identify the target object;

[0016] The manual processing module is used to transfer the abnormal situation that cannot be automatically resolved during the operation of the system to manual intervention for auxiliary processing.

[0017] The present invention also includes a working method of a full-process intelligent system for slow cooling of a copper smelting slag ladle, and the specific steps include:

[0018] S1. Generate a slag ladle slag receiving task according to the slag outlet status and smelting slag ladle information, and use an electric flatbed truck and a metallurgical gantry crane to transport the slag ladle to the slag outlet for slag receiving;

[0019] S2, transporting the smelting slag bag after slag connection to the air cooling area for standing;

[0020] S3, transporting the smelting slag bag that has been left to stand in the air cooling area to the water cooling area;

[0021] S4, using an automatic door-type watering rail car to spray water on the smelting slag ladle in the water cooling area to cool it down;

[0022] S5, transporting the cooled smelting slag bag to a bag turning machine for turning;

[0023] S6. The smelting slag bag after turning over is transported to the air cooling area to wait for slag receiving.

[0024] Furthermore, the step S1 specifically includes:

[0025] The task generation module generates the slag receiving task for the slag bag in combination with the slag outlet status and smelting slag bag information in the data management module; the scheduling algorithm module searches for the optimal empty smelting slag bag and the optimal metallurgical gantry crane in the site in combination with the available resource data in the data management module; the communication protocol module issues instructions to the metallurgical gantry crane and the electric flatbed truck to load the empty smelting slag bag on the electric flatbed truck. After the empty smelting slag bag is transported, it is transported to the designated location by the electric flatbed truck for pumping. After the pumping is completed, the electric flatbed truck loads the empty smelting slag bag to the slag receiving port for slag receiving; after the slag receiving is completed, the electric flatbed truck loads the smelting slag bag to the air cooling handover area.

[0026] Furthermore, the step S2 specifically includes:

[0027] The task generation module combines with the data management module to generate the task of placing the smelting slag bag in the air cooling area according to the smelting slag bag information and storage location information; the scheduling algorithm module combines with the data management module to find the optimal storage location and the optimal metallurgical gantry crane in the site; the communication protocol module issues instructions to the metallurgical gantry crane to transport the smelting slag bag with completed slag connection from the air cooling handover area to the air cooling area for static placement.

[0028] Furthermore, the step S3 specifically includes:

[0029] The task generation module combines with the data management module to generate the task of placing the smelting slag bag in the water cooling zone according to the smelting slag bag information and storage location information. The scheduling algorithm module combines with the data management module to find the optimal storage location, the optimal metallurgical gantry crane and the optimal electric flatbed truck in the site; the communication protocol module sends instructions to the metallurgical gantry crane and the electric flatbed truck to transfer the smelting slag bag that has been static; after the transfer is completed, the smelting slag bag is placed in the water cooling zone.

[0030] Furthermore, the step S4 specifically includes:

[0031] The task generation module combines with the data management module to generate watering tasks according to the smelting slag bag information. The scheduling algorithm module combines with the data management module to find the optimal automatic door-type watering rail car in the site; the communication protocol module sends instructions to the automatic door-type watering rail car to cool the smelting slag bag.

[0032] Furthermore, the step S5 specifically includes:

[0033] The task generation module combines with the data management module to generate the bag turning task according to the smelting slag bag information and storage location information; the scheduling algorithm module combines with the data management module to find the optimal gantry metallurgical crane, the optimal bag turning machine and the optimal storage location in the site; the communication protocol module issues instructions to the metallurgical gantry crane and the bag turning machine to transfer the cooled smelting slag bag to the bag turning machine, and the bag turning machine dumps the smelting slag bag according to the bag turning task, and after dumping, the smelting slag bag is placed in the designated location through the metallurgical gantry crane.

[0034] Furthermore, the step S6 specifically includes:

[0035] The task generation module combines the smelting slag bag information and storage location information in the data management module to generate the task of placing the smelting slag bag in the air cooling area; the scheduling algorithm module combines the data management module to find the optimal storage location, the optimal metallurgical gantry crane and the optimal electric flatbed truck in the site; the communication protocol module sends instructions to the metallurgical gantry crane and the electric flatbed truck to transport the dumped smelting slag bag and place it in the designated location in the air cooling area.

[0036] Furthermore, during the execution of S1-S6, the task execution and status feedback module monitors the execution process of each instruction and feeds back the execution status and completion status to the system. When an abnormal situation occurs during the execution process and the system cannot resolve it by itself, the operator takes over the system through the manual mode module to handle the abnormal situation.

[0037] Furthermore, when the metallurgical gantry crane performs the task of transporting the smelting slag ladle, the visual perception technology module is used to judge the standardization of the grabbing and releasing actions of the metallurgical gantry crane;

[0038] The visual perception technology module performs scanning and recognition through a laser radar, obtains point cloud data, analyzes the characteristics of the smelting slag ladle trunnion and the crane hook, and determines the standardization of the grabbing and releasing actions.

[0039] Compared with the prior art, the present invention has the following advantages:

[0040] The whole process intelligent system and working method of slow cooling of copper smelting slag provided by the present invention realizes the coordinated dispatch of multiple types of machines in multiple regions. Through the coordinated cooperation of multiple electric flatbed trucks, crane handling, sprinkler trucks, tippers and other equipment, the whole slow cooling field is basically unmanned through the independently developed multi-equipment collaborative algorithm and multi-objective optimization strategy. At the same time, scanning recognition technology and digital twin technology are added to better improve production efficiency and process transparency and intelligence. It can be applied to slow cooling of different types of smelting slag ladles, has strong versatility, and improves the intelligent production process chain of slow cooling of smelting slag ladles, making the production process more unmanned and the management process more standardized.

[0041] The full-process intelligent system and working method for slow cooling of copper smelting slag ladle provided by the present invention realize the automatic slag receiving function. The smelting slag ladle can be transported to the slag receiving port for slag receiving by using the intelligent control system, thereby improving the safety of the entire system. Then, the system realizes the automatic slag dumping function, and uses an automated device to accurately dump the smelting slag ladle, reducing the intensity of manual operation and safety risks. The entire system covers the full-process intelligent scheduling management of the smelting slag ladle from slag receiving to slow cooling and then to slag dumping, realizing automated, intelligent and refined operation. Through this system, production enterprises can more efficiently complete the processing of smelting slag ladle, improve production efficiency, reduce costs, and better ensure the safety of production personnel.

[0042] Based on the above reasons, the present invention can be widely promoted in the field of copper smelting process technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in 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 described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0044] Figure 1 The present invention is a flow chart of the whole process intelligent working method for slow cooling of copper smelting slag ladle.

[0045] Figure 2 This is the overall architecture diagram of the full-process intelligent system for slow cooling of copper smelting slag bags in the present invention. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0047] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0048] like Figure 1 As shown, the present invention provides a full-process intelligent system for slow cooling of copper smelting slag ladle, which combines metallurgical gantry crane, automatic gantry sprinkler rail car, electric flatbed car, slag ladle pumping equipment and ladle turner to realize intelligent slow cooling of copper smelting slag ladle, including: data management module, task generation module, scheduling algorithm module, communication protocol module, task execution and status feedback module, visual perception technology module and manual processing module, wherein:

[0049] The data management module is used to collect the attributes, status and available resource data of equipment, smelting slag packages and storage locations, and save them in the database to provide data support;

[0050] The task generation module is used to generate scheduling tasks based on the slag outlet status, slag bag cooling time, equipment capacity and storage space;

[0051] The scheduling algorithm module is used to select the optimal equipment, smelting slag package and storage location from the database according to the specific requirements of the scheduling task;

[0052] The communication protocol module is used to issue parsable scheduling task instructions through the TCP communication protocol;

[0053] The task execution and status feedback module is used to receive the device task execution status and feed back the execution status to the system;

[0054] The visual perception technology module is used to obtain the geometric shape and spatial position information of the target object, and to accurately locate and identify the target object;

[0055] The manual processing module is used to transfer the abnormal situation that cannot be automatically resolved during the operation of the system to manual intervention for auxiliary processing.

[0056] During implementation, the present invention uses a three-dimensional model to construct a plant area map, which can receive data on equipment management, smelting slag bag management, and storage location information management in real time, and clearly display the equipment operation status, storage area status, and smelting slag bag status, etc. At the same time, it supports three-dimensional visualization operations, can interact in a virtual environment, and conduct a deeper analysis and understanding of the data.

[0057] The present invention also includes a working method of a full-process intelligent system for slow cooling of a copper smelting slag ladle, and the specific steps include:

[0058] S1. Generate a slag ladle slag receiving task according to the slag outlet status and smelting slag ladle information, and use an electric flatbed truck and a metallurgical gantry crane to transport the slag ladle to the slag outlet for slag receiving;

[0059] In specific implementation, as a preferred embodiment of the present invention, the step S1 specifically includes:

[0060] The task generation module generates the slag receiving task for the slag bag in combination with the slag outlet status and smelting slag bag information in the data management module; the scheduling algorithm module searches for the optimal empty smelting slag bag and the optimal metallurgical gantry crane in the site in combination with the available resource data in the data management module; the communication protocol module issues instructions to the metallurgical gantry crane and the electric flatbed truck to load the empty smelting slag bag on the electric flatbed truck. After the empty smelting slag bag is transported, it is transported to the designated location by the electric flatbed truck for pumping. After the pumping is completed, the electric flatbed truck loads the empty smelting slag bag to the slag receiving port for slag receiving; after the slag receiving is completed, the electric flatbed truck loads the smelting slag bag to the air cooling handover area.

[0061] S2, transporting the smelting slag bag after slag connection to the air cooling area for standing;

[0062] In specific implementation, as a preferred embodiment of the present invention, step S2 specifically includes:

[0063] The task generation module combines with the data management module to generate the task of placing the smelting slag bag in the air cooling area according to the smelting slag bag information and storage location information; the scheduling algorithm module combines with the data management module to find the optimal storage location and the optimal metallurgical gantry crane in the site; the communication protocol module issues instructions to the metallurgical gantry crane to transport the smelting slag bag with completed slag connection from the air cooling handover area to the air cooling area for static placement.

[0064] S3, transporting the smelting slag bag that has been left to stand in the air cooling area to the water cooling area;

[0065] In specific implementation, as a preferred embodiment of the present invention, step S3 specifically includes:

[0066] The task generation module combines with the data management module to generate the task of placing the smelting slag bag in the water cooling zone according to the smelting slag bag information and storage location information. The scheduling algorithm module combines with the data management module to find the optimal storage location, the optimal metallurgical gantry crane and the optimal electric flatbed truck in the site; the communication protocol module sends instructions to the metallurgical gantry crane and the electric flatbed truck to transfer the smelting slag bag that has been static; after the transfer is completed, the smelting slag bag is placed in the water cooling zone.

[0067] S4, using an automatic door-type watering rail car to spray water on the smelting slag ladle in the water cooling area to cool it down;

[0068] In specific implementation, as a preferred embodiment of the present invention, step S4 specifically includes:

[0069] The task generation module combines with the data management module to generate watering tasks according to the smelting slag bag information. The scheduling algorithm module combines with the data management module to find the optimal automatic door-type watering rail car in the site; the communication protocol module sends instructions to the automatic door-type watering rail car to cool the smelting slag bag.

[0070] S5, transporting the cooled smelting slag bag to a bag turning machine for turning;

[0071] In specific implementation, as a preferred embodiment of the present invention, step S5 specifically includes:

[0072] The task generation module combines with the data management module to generate the bag turning task according to the smelting slag bag information and storage location information; the scheduling algorithm module combines with the data management module to find the optimal gantry metallurgical crane, the optimal bag turning machine and the optimal storage location in the site; the communication protocol module issues instructions to the metallurgical gantry crane and the bag turning machine to transfer the cooled smelting slag bag to the bag turning machine, and the bag turning machine dumps the smelting slag bag according to the bag turning task, and after dumping, the smelting slag bag is placed in the designated location through the metallurgical gantry crane.

[0073] S6. The smelting slag bag after turning over is transported to the air cooling area to wait for slag receiving.

[0074] In specific implementation, as a preferred embodiment of the present invention, step S6 specifically includes:

[0075] The task generation module combines the smelting slag bag information and storage location information in the data management module to generate the task of placing the smelting slag bag in the air cooling area; the scheduling algorithm module combines the data management module to find the optimal storage location, the optimal metallurgical gantry crane and the optimal electric flatbed truck in the site; the communication protocol module sends instructions to the metallurgical gantry crane and the electric flatbed truck to transport the dumped smelting slag bag and place it in the designated location in the air cooling area.

[0076] In specific implementation, as a preferred embodiment of the present invention, during the execution of S1-S6, the task execution and status feedback module monitors the execution process of each instruction, and feeds back the execution status and completion status to the system. When an abnormal situation occurs during the execution process and the system cannot resolve it by itself, the operator takes over the system through the manual mode module to handle the abnormal situation.

[0077] In specific implementation, as a preferred embodiment of the present invention, when the metallurgical gantry crane performs the task of transporting the smelting slag ladle, the visual perception technology module is used to judge the standard of the grabbing and releasing actions of the metallurgical gantry crane;

[0078] The visual perception technology module performs scanning and recognition through a laser radar, obtains point cloud data, analyzes the characteristics of the smelting slag ladle trunnion and the crane hook, and determines the standardization of the grabbing and releasing actions.

[0079] During implementation, laser scanning recognition includes two stages: automatic grabbing and automatic releasing.

[0080] In the automatic grabbing stage, the scanning process is subdivided into in-position confirmation, pre-hanging confirmation and suspension confirmation. For in-position confirmation: the algorithm input is the position of the smelting slag ladle that the crane hoist is about to go to; the algorithm output is whether the smelting slag ladle exists and the axis coordinates of the left and right ear shafts of the smelting slag ladle. For pre-hanging confirmation: the algorithm input is the position of the smelting slag ladle that the crane hoist is about to hang; the algorithm output is the entrance direction vector of the hooks on the left and right sides of the crane hoist, the hook center coordinates and the axis coordinates of the left and right ear shafts of the smelting slag ladle. For suspension confirmation: the algorithm input is the position of the smelting slag ladle that the crane hoist is about to hang; the algorithm output is the axis coordinates of the left and right ear shafts of the smelting slag ladle, the hook center coordinates of the left and right hooks of the crane hoist and the Boolean result of whether it is hung.

[0081] For the automatic release stage, the scanning process is divided into seat confirmation and unhooking confirmation. For seat confirmation: the algorithm input is the position of the smelting slag bag that the spreader is about to release; the algorithm output is whether the smelting slag bag has landed on the ground. For unhooking confirmation: the algorithm input is the position of the smelting slag bag that the spreader is about to release; the algorithm output is the coordinates of the hook center of the left and right sides of the crane spreader, the coordinates of the trunnion axis of the left and right sides of the smelting slag bag, and the Boolean result of whether it is unhooked.

[0082] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0083] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0084] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0085] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0086] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0087] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A full-process intelligent system for slow cooling of copper smelting slag ladle, which combines metallurgical gantry crane, automatic gantry sprinkler rail car, electric flatbed car, slag ladle pumping equipment and ladle turner to realize intelligent slow cooling of copper smelting slag ladle, characterized in that: include: Data management module, task generation module, scheduling algorithm module, communication protocol module, task execution and status feedback module, visual perception technology module and manual processing module, among which: The data management module is used to collect the attributes, status and available resource data of equipment, smelting slag packages and storage locations, and save them in the database to provide data support; The task generation module is used to generate scheduling tasks based on the slag outlet status, slag bag cooling time, equipment capacity and storage space; The scheduling algorithm module is used to select the optimal equipment, smelting slag package and storage location from the database according to the specific requirements of the scheduling task; The communication protocol module is used to issue parsable scheduling task instructions through the TCP communication protocol; The task execution and status feedback module is used to receive the device task execution status and feed back the execution status to the system; The visual perception technology module is used to obtain the geometric shape and spatial position information of the target object, and to accurately locate and identify the target object; The manual processing module is used to transfer the abnormal situation that cannot be automatically resolved during the operation of the system to manual intervention for auxiliary processing.

2. A working method of the full-process intelligent system for slow cooling of copper smelting slag ladle as claimed in claim 1, characterized in that: The specific steps include: S1. Generate a slag ladle slag receiving task according to the slag outlet status and smelting slag ladle information, and use an electric flatbed truck and a metallurgical gantry crane to transport the slag ladle to the slag outlet for slag receiving; S2, transporting the smelting slag bag after slag connection to the air cooling area for standing; S3, transporting the smelting slag bag that has been left to stand in the air cooling area to the water cooling area; S4, using an automatic door-type watering rail car to spray water on the smelting slag ladle in the water cooling area to cool it down; S5, transporting the cooled smelting slag bag to a bag turning machine for turning; S6. The smelting slag bag after turning over is transported to the air cooling area to wait for slag receiving.

3. The full-process intelligent working method for slow cooling of copper smelting slag ladle according to claim 2 is characterized in that: The step S1 specifically includes: The task generation module generates the slag receiving task for the slag bag in combination with the slag outlet status and smelting slag bag information in the data management module; the scheduling algorithm module searches for the optimal empty smelting slag bag and the optimal metallurgical gantry crane in the site in combination with the available resource data in the data management module; the communication protocol module issues instructions to the metallurgical gantry crane and the electric flatbed truck to load the empty smelting slag bag on the electric flatbed truck. After the empty smelting slag bag is transported, it is transported to the designated location by the electric flatbed truck for pumping. After the pumping is completed, the electric flatbed truck loads the empty smelting slag bag to the slag receiving port for slag receiving; after the slag receiving is completed, the electric flatbed truck loads the smelting slag bag to the air cooling handover area.

4. The full-process intelligent working method for slow cooling of copper smelting slag ladle according to claim 2 is characterized in that: The step S2 specifically includes: The task generation module combines with the data management module to generate the task of placing the smelting slag bag in the air cooling area according to the smelting slag bag information and storage location information; the scheduling algorithm module combines with the data management module to find the optimal storage location and the optimal metallurgical gantry crane in the site; the communication protocol module issues instructions to the metallurgical gantry crane to transport the smelting slag bag with completed slag connection from the air cooling handover area to the air cooling area for static placement.

5. The full-process intelligent working method for slow cooling of copper smelting slag ladle according to claim 2 is characterized in that: The step S3 specifically includes: The task generation module combines with the data management module to generate the task of placing the smelting slag bag in the water cooling zone according to the smelting slag bag information and storage location information. The scheduling algorithm module combines with the data management module to find the optimal storage location, the optimal metallurgical gantry crane and the optimal electric flatbed truck in the site; the communication protocol module sends instructions to the metallurgical gantry crane and the electric flatbed truck to transfer the smelting slag bag that has been static; after the transfer is completed, the smelting slag bag is placed in the water cooling zone.

6. The full-process intelligent working method for slow cooling of copper smelting slag ladle according to claim 2 is characterized in that: The step S4 specifically includes: The task generation module combines with the data management module to generate watering tasks according to the smelting slag bag information. The scheduling algorithm module combines with the data management module to find the optimal automatic door-type watering rail car in the site; the communication protocol module sends instructions to the automatic door-type watering rail car to cool the smelting slag bag.

7. The full-process intelligent working method for slow cooling of copper smelting slag ladle according to claim 2 is characterized in that: The step S5 specifically includes: The task generation module combines with the data management module to generate the bag turning task according to the smelting slag bag information and storage location information; the scheduling algorithm module combines with the data management module to find the optimal gantry metallurgical crane, the optimal bag turning machine and the optimal storage location in the site; the communication protocol module issues instructions to the metallurgical gantry crane and the bag turning machine to transfer the cooled smelting slag bag to the bag turning machine, and the bag turning machine dumps the smelting slag bag according to the bag turning task, and after dumping, the smelting slag bag is placed in the designated location through the metallurgical gantry crane.

8. The full-process intelligent working method for slow cooling of copper smelting slag ladle according to claim 2 is characterized in that: The step S6 specifically includes: The task generation module combines the smelting slag bag information and storage location information in the data management module to generate the task of placing the smelting slag bag in the air cooling area; the scheduling algorithm module combines the data management module to find the optimal storage location, the optimal metallurgical gantry crane and the optimal electric flatbed truck in the site; the communication protocol module sends instructions to the metallurgical gantry crane and the electric flatbed truck to transport the dumped smelting slag bag and place it in the designated location in the air cooling area.

9. The full-process intelligent working method for slow cooling of copper smelting slag ladle according to claim 2 is characterized in that: During the execution of S1-S6, the task execution and status feedback module monitors the execution process of each instruction and feeds back the execution status and completion status to the system. When an abnormal situation occurs during the execution process and the system cannot resolve it by itself, the operator takes over the system through the manual mode module to handle the abnormal situation.

10. The full-process intelligent working method for slow cooling of copper smelting slag ladle according to claim 2 is characterized in that: When the metallurgical gantry crane performs the task of transporting the smelting slag ladle, the visual perception technology module is used to judge the standard of the grabbing and releasing actions of the metallurgical gantry crane; The visual perception technology module obtains point cloud data through laser radar scanning and recognition, analyzes the characteristics of the smelting slag ladle trunnion and the crane hook, and determines the standardization of the grasping and releasing actions.

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