A hot coil storage crane intelligent scheduling system and method

Abstract

The application discloses a kind of hot coil library crane intelligent scheduling system and method, it is related to intelligent warehousing control technical field, including machine vision subsystem, OCR identification subsystem, steel coil tower type detection subsystem, temperature prediction subsystem, crane intelligent warehousing subsystem and crane automation control subsystem;The machine vision subsystem is used to obtain the spatial position data of hot steel coil, and the spatial position data is sent to the crane intelligent warehousing subsystem;The application obtains the multidimensional data of hot steel coil to dynamically schedule hot steel coil, can adjust the timing of steel coil hoisting operation according to the hot state of steel coil, improve the operation efficiency of steel coil scheduling, meet the job demand of intelligentization, while, can reduce the proportion of manual operation in hot steel coil library area, effectively reduce personnel operation deviation, prevent personnel from safety accident.

Description

Technical Field

[0001] This invention relates to the field of intelligent warehouse control technology, and in particular to an intelligent scheduling system and method for cranes in hot steel coil warehouses. Background Technology

[0002] In the steel metallurgical industry, hot-rolled steel coils are a key intermediate product produced in the rolling process. The temperature of the coils leaving the warehouse can reach 500-800℃, and a single coil can weigh tens of tons. The storage and transfer processes place high demands on the high-temperature resistance and automation level of the equipment. Hot-rolled steel coil storage areas undertake core functions such as temporary storage, cooling, and loading of steel coils. With the large-scale and refined development of the steel industry, the demand for unmanned and intelligent operations in high-temperature steel coil storage areas urgently needs to be increased.

[0003] At present, most steel mills still use manually operated cranes to complete the lifting operations in their hot-rolled coil storage areas. The automated lifting equipment deployed by a few companies is only suitable for normal temperature and light load storage scenarios. The equipment control architecture is independent and singular, only performing basic lifting and horizontal movement operations, and does not have the integrated control capability to adapt to high temperature and heavy load conditions.

[0004] However, manual on-site operation exposes workers to high-temperature and dusty conditions for extended periods, and fatigue-related errors can easily lead to safety accidents. In addition, the positioning of steel coils is often inaccurate and hoisting operations are prone to errors. Existing automated systems lack a multi-source data fusion architecture and a real-time monitoring mechanism for steel coil temperature, and cannot perform dynamic operations based on the thermal state of the steel coils. As a result, existing technologies cannot meet the requirements for unmanned and intelligent operation of hot steel coil warehouses. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent scheduling system and method for hot steel coil silos, which solves the technical problem that existing technologies cannot meet the requirements for unmanned and intelligent operation of hot steel coil silos.

[0006] The technical means employed in this invention are as follows: In a first aspect, embodiments of the present invention provide an intelligent scheduling system for hot steel coil warehouse cranes, comprising: a machine vision subsystem, an OCR recognition subsystem, a steel coil tower type detection subsystem, a temperature prediction subsystem, a crane intelligent warehousing subsystem, and a crane automated control subsystem; The machine vision subsystem is used to acquire spatial location data of hot steel coils and send the spatial location data to the crane intelligent warehousing subsystem. The OCR recognition subsystem is used to identify the hot steel coil number information and send the hot steel coil number information to the crane intelligent storage subsystem; The steel coil tower type detection subsystem is used to detect the status of the steel coil tower type and send the status of the steel coil tower type to the crane intelligent storage subsystem. The temperature prediction subsystem is used to predict the temperature change trend of hot steel coils and send the temperature change trend to the crane intelligent storage subsystem. The intelligent warehousing subsystem for cranes is used to generate target steel coil and storage location parameter information based on the received spatial location data, hot steel coil number information, steel coil tower type status and temperature change trend, generate hoisting task operation instructions based on the target steel coil and storage location parameter information, and send the hoisting task operation instructions to the crane automation control subsystem. The crane automation control subsystem is used to receive and execute the hoisting task operation instructions to dynamically schedule the hot steel coil.

[0007] Furthermore, the temperature prediction subsystem predicts the temperature change trend of the hot steel coil based on its current location, ambient temperature, and historical cooling data.

[0008] Furthermore, the target steel coil and storage location parameter information includes at least one of the following: steel coil number information, steel coil specification parameter information, steel coil real-time temperature information, steel coil spatial location information, steel coil tower type status information, storage location status information, and hoisting status information.

[0009] Furthermore, the intelligent warehousing subsystem for cranes includes an anomaly detection module and an alarm module. The anomaly detection module is used to send an alarm signal to the alarm module and send a hoisting task stop command to the crane automation control subsystem when it detects the existence of preset anomaly information. The alarm module is used to receive the alarm signal and issue an alarm prompt.

[0010] Furthermore, the preset abnormal information includes at least one of the following: steel coil identification abnormality, steel coil tower type abnormality, steel coil temperature abnormality, position identification abnormality, coil unwinding abnormality, unwinding abnormality, and communication abnormality.

[0011] Furthermore, the intelligent warehousing subsystem for cranes also includes an anomaly recording module, which is used to record at least one of the following when the preset anomaly information occurs: steel coil status data, equipment operating status data, and crane operating data.

[0012] Furthermore, the crane automation control subsystem includes a position control module, a clamp control module, and a core detection module; The position control module is used to control the movement of the crane's trolley, carriage, and hoisting mechanism. The clamp control module is used to control the opening and closing of the clamps; The core detection module is used to determine whether the clamp is located at the core of the steel coil.

[0013] Furthermore, the core detection module determines whether the clamp is at the core position of the steel coil by using a first set of laser beam sensors and a second set of laser beam sensors mounted on the clamp.

[0014] Furthermore, the crane automation control subsystem also includes an anti-sway control module, which is used to prevent the clamps from swinging during movement.

[0015] Secondly, embodiments of the present invention also provide an intelligent scheduling method for hot-rolled steel coil storage cranes, the method comprising: The spatial location data of the hot steel coil is acquired through the machine vision subsystem and then sent to the crane intelligent warehousing subsystem. The steel coil number information is identified by the OCR recognition subsystem and then sent to the crane intelligent storage subsystem. The status of the steel coil tower is detected by the steel coil tower type detection subsystem, and the status of the steel coil tower type is sent to the crane intelligent storage subsystem. The temperature prediction subsystem predicts the temperature change trend of hot steel coils and sends the temperature change trend to the crane intelligent storage subsystem. The crane intelligent warehousing subsystem generates target steel coil and storage location parameter information based on the received spatial location data, steel coil number information, steel coil tower type status and temperature change trend, generates hoisting task operation instructions based on the target steel coil and storage location parameter information, and sends the hoisting task operation instructions to the crane automation control subsystem. The crane automation control subsystem receives and executes the hoisting task operation instructions to dynamically schedule the hot steel coil.

[0016] Compared with the prior art, the present invention has the following advantages: This invention acquires multi-dimensional data of hot steel coils through a machine vision subsystem, an OCR recognition subsystem, a steel coil tower type detection subsystem, and a temperature prediction subsystem. The intelligent crane storage subsystem integrates and processes this multi-dimensional data to generate hoisting task operation instructions. The crane automation control subsystem receives and executes these hoisting task operation instructions. This invention can adjust the steel coil hoisting operation sequence in real time according to the thermal state of the steel coils, improving the efficiency of steel coil scheduling and meeting the needs of intelligent operation. At the same time, it can reduce the proportion of manual operations in the hot steel coil storage area, effectively reduce human operation errors, and prevent personnel safety accidents.

[0017] Based on the above reasons, this invention can be widely promoted in fields such as intelligent warehouse control. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a block diagram of the architecture of an intelligent scheduling system for a hot steel coil storage crane according to the present invention; Figure 2 This is a flowchart illustrating the process control for hot-rolled steel coil storage, including warehousing, unloading, and outbound operations. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0021] It should be noted that the terms "comprising" and "having" and any variations thereof in this invention are intended to cover non-exclusive inclusion. 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 explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0022] The embodiments of the present invention will now be described with reference to the accompanying drawings.

[0023] Please see Figure 1 , Figure 1 This is a block diagram of the architecture of an intelligent scheduling system for a hot steel coil storage crane according to the present invention.

[0024] This application provides an intelligent scheduling system for a hot-rolled steel coil warehouse crane, characterized in that it includes: a machine vision subsystem, an OCR recognition subsystem, a steel coil tower type detection subsystem, a temperature prediction subsystem, a crane intelligent storage subsystem, and a crane automated control subsystem.

[0025] The machine vision subsystem is used to acquire spatial location data of hot steel coils and send the spatial location data to the crane intelligent warehousing subsystem. By acquiring spatial location data of hot steel coils through the machine vision subsystem and transmitting it to the crane intelligent warehousing subsystem in real time, the storage location of each hot steel coil in the warehouse area can be effectively determined, reducing the workload of manual on-site inspection and positioning, and improving the continuity and accuracy of hot steel coil location information collection.

[0026] The OCR recognition subsystem is used to identify the hot-rolled steel coil number information and send it to the crane intelligent warehousing subsystem. By identifying the hot-rolled steel coil number information through the OCR recognition subsystem and sending it to the crane intelligent warehousing subsystem, the hot-rolled steel coil number information is matched with the preset basic information of steel coils in the crane intelligent warehousing subsystem. It can automatically match the order files corresponding to each hot-rolled steel coil in the warehouse area, reduce the workload of manually verifying the steel coil number information, and improve the efficiency of hot-rolled steel coil information verification.

[0027] The steel coil tower shape detection subsystem is used to detect the status of the steel coil tower shape and send the status to the crane intelligent storage subsystem; it can determine whether the target steel coil is a standard steel coil, so as to prevent the lifting of hot steel coils that do not meet the lifting standards and improve the effectiveness of lifting operations.

[0028] The temperature prediction subsystem is used to predict the temperature change trend of hot steel coils and send the temperature change trend to the crane intelligent warehousing subsystem; it can monitor the cooling progress of each hot steel coil in the warehouse in real time, adapt to the thermal state of the hot steel coils to adjust the transfer operation sequence, reduce the amount of manual on-site temperature measurement, and improve the autonomous adaptation level of hot steel coil scheduling.

[0029] In some implementations, the temperature prediction subsystem predicts the temperature change trend of the hot steel coil based on its current location, ambient temperature, and historical cooling data. By comprehensively deriving the temperature change trend from the current location, ambient temperature, and historical cooling data, the system can estimate the time when the temperature of the hot steel coil will drop to a preset temperature based on the actual working conditions in the warehouse area. This reduces the reliance on manual temperature measurement and prediction for each coil and improves the timing planning for steel coil transfer.

[0030] The intelligent warehousing subsystem for cranes generates target coil and storage location parameters based on received spatial location data, hot-rolled coil number information, coil tower status, and temperature change trends. It then generates hoisting operation instructions based on these parameters and sends them to the crane automation control subsystem. By fusing spatial location data, hot-rolled coil number information, coil tower status, and temperature change trends, the system integrates multi-dimensional operational information from various hot-rolled coils in the storage area. This generates target coil and storage location parameters, and based on the integrated information, generates hoisting operation instructions adapted to the hot-rolled coil's operating conditions. This reduces the workload of manual coil transfer within the storage area and improves the scheduling efficiency of hot-rolled coil hoisting operations.

[0031] In some implementations, the target steel coil and storage location parameter information includes at least one of the following: steel coil number information, steel coil specification parameters information, steel coil real-time temperature information, steel coil spatial location information, steel coil tower type status information, storage location status information, and hoisting status information. By integrating multiple data dimensions related to hot steel coils and storage areas into the target steel coil and storage location parameter information, dynamic scheduling of hot steel coils can be adapted to different storage area operation scenarios, mitigating scheduling judgment biases caused by single data dimensions and broadening the adaptability of hot steel coil hoisting and scheduling schemes.

[0032] In some implementations, the intelligent warehousing subsystem for cranes includes an anomaly detection module and an alarm module. The anomaly detection module sends an alarm signal to the alarm module and a stop command for the hoisting task to the crane automation control subsystem when it detects preset anomaly information. The alarm module receives the alarm signal and issues an alarm prompt. By identifying preset anomalies related to hot steel coils in the storage area through the anomaly detection module and simultaneously issuing stop and alarm commands, and cooperating with the alarm module to output prompt information, the hoisting operation of hot steel coils with potential risks can be terminated in a timely manner. This facilitates the rapid location of abnormal working conditions in the storage area by staff and reduces the risk of equipment and steel coil damage during the transfer of hot steel coils.

[0033] In some implementations, the preset anomaly information includes at least one of the following: coil identification anomaly, coil tower type anomaly, coil temperature anomaly, position identification anomaly, coil unwinding anomaly, unwinding anomaly, and communication anomaly. By categorizing various warehouse-related fault conditions related to hot steel coils into preset anomaly information, the types of risks that the anomaly detection module can identify are broadened, facilitating the identification of fault conditions during the hoisting of hot steel coils and ensuring efficient and safe hoisting operations.

[0034] In some implementations, the intelligent warehousing subsystem for cranes also includes an anomaly recording module. This module records at least one of the following when a preset anomaly occurs: steel coil status data, equipment operating status data, and crane operating data. By retaining relevant operating data of the steel coils, equipment, and crane during the anomaly occurrence phase through the anomaly recording module, the process information of abnormal hot steel coil hoisting conditions is preserved. This facilitates retrospective analysis by staff of the causes of anomalies in the warehouse area and reduces the difficulty of judgment due to missing information during fault diagnosis.

[0035] The crane automation control subsystem receives and executes hoisting operation commands to dynamically schedule hot steel coils. By receiving and executing hoisting operation commands through the crane automation control subsystem, dynamic scheduling operations can be performed automatically based on multi-dimensional steel coil information, reducing the need for manual on-site operation of the crane to transfer hot steel coils and improving the level of automation in warehouse hoisting operations.

[0036] In some implementations, the crane automation control subsystem includes a position control module, a clamp control module, and a core detection module. The position control module controls the movement of the crane's trolley, hoisting mechanism, and other components. The clamp control module controls the opening and closing of the clamps. The core detection module determines whether the clamps are positioned at the core of the steel coil. By controlling the crane movement, clamp opening and closing, and core alignment operations through the position control module, clamp control module, and core detection module, the automated actions of hot steel coil handling are completed in a coordinated manner. This reduces the need for manual crane operation for positioning and clamping the steel coils, and improves the accuracy of hot steel coil lifting and handling in the storage area.

[0037] In some implementations, the core detection module determines whether the clamp is at the core position of the steel coil by using a first set of laser beam sensors and a second set of laser beam sensors mounted on the clamp.

[0038] Specifically, the position control module controls the crane trolley and crane carriage to move according to the coordinates of the target storage location; during the movement of the trolley and carriage, the clamp control module pre-executes the clamp opening action according to the specification parameters corresponding to the target hot steel coil, and adjusts the clamp opening to the preset opening value that matches the specification, which can not only improve the efficiency of hot steel coil uncoiling operation, but also prevent the clamp from scratching and colliding with the outer surface of the hot steel coil during the descent stroke.

[0039] Once the crane trolley and crane carriage have traveled to the preset target position, the position control module drives the hoisting mechanism to lower the clamp at a high speed to the preset height value. After the clamp reaches the preset height, the position control module switches the hoisting mechanism to a low-speed descent gear and simultaneously starts the core detection module to execute the core position detection process.

[0040] The coil position detection process utilizes two sets of high-temperature resistant laser beam sensors mounted on the clamp body to acquire signals. When the first set of laser beam sensors switches from the on state to the off state, the system records the current lifting height of the hoisting mechanism in real time and marks it as Z1. When the first set of laser beam sensors returns from the off state to the on state, the system records the current lifting height of the hoisting mechanism again and marks it as Z2. The system calculates the actual coil thickness H of the hot steel coil based on the difference between the two height records, using the formula: H = Z1. Z2.

[0041] The basic parameters for hot-rolled steel coils issued by the intelligent warehousing subsystem of the crane include two types of parameters: the outer diameter D and the inner diameter R of the hot-rolled steel coil. The system calculates the theoretical coil thickness h based on these two parameters, and the calculation formula is: h = D R. The system compares the calculated actual coil thickness H with the theoretical coil thickness h. If the actual coil thickness H falls within the preset error threshold range, the system determines that the hot steel coil to be retrieved is the target object and executes the subsequent complete coil retrieval process. If the actual coil thickness H exceeds the preset error threshold range, the system determines that there is an abnormal coil retrieval condition on site, and the equipment performs an alarm prompt or restarts the warehouse location process.

[0042] When the second set of laser beam sensors switches from the on state to the off state and then back to the on state, the core detection module determines that the clamp has accurately reached the core position of the hot steel coil. At this time, the position control module controls the lifting mechanism to stop moving downward, and the clamp control module drives the clamp to complete the clamping action of the hot steel coil.

[0043] This invention integrates position control, clamp pre-action control, and core detection control logic, enabling precise positioning, efficient clamping, and automatic core identification in the fully automated hot steel coil unwinding process. This improves the efficiency of transfer operations in unmanned hot steel coil storage areas and the reliability of hot steel coil unwinding operations.

[0044] In some implementations, the crane automation control subsystem also includes an anti-sway control module, which is used to prevent the clamps from swinging during movement. By constraining the swing amplitude of the clamps during operation, the anti-sway control module reduces the probability of the clamps scraping or colliding with hot steel coils or warehouse equipment, stabilizes the clamping posture during the transfer of hot steel coils, and improves the operational stability and safety of the automatic transfer process for high-temperature hot steel coils.

[0045] Please see Figure 2 , Figure 2This is a control flowchart for the warehousing, unloading, and outbound processes of hot-rolled steel coils. The overall process comprises three parts: warehousing, unloading, and outbound. The crane-based intelligent warehousing subsystem acts as the data interaction hub, coordinating with the machine vision subsystem, OCR recognition subsystem, steel coil tower type detection subsystem, temperature prediction subsystem, and crane automation control subsystem. When the high-temperature hot-rolled steel coils arrive at the warehouse, the warehousing process begins. First, the crane-based intelligent warehousing subsystem acquires the basic specifications and temperature information of the high-temperature steel coils. Then, the machine vision subsystem performs position recognition to obtain the spatial location data of the hot-rolled steel coils. Subsequently, the OCR recognition subsystem identifies and matches the coil number. The coil number information obtained by the OCR recognition subsystem is fed back to the crane-based intelligent warehousing subsystem. The warehousing subsystem matches the corresponding steel coil information. After matching, it performs tower type detection. The steel coil tower type detection subsystem determines whether the current steel coil is a standard steel coil. If it is determined to be a non-standard steel coil, it enters the alarm handling process and requires manual intervention. If it is determined to be a standard steel coil, the crane intelligent warehousing subsystem performs data transmission operation, transmitting temperature information to the temperature prediction system to start the cooling completion time prediction, and transmitting the basic information and location information of the steel coil to the crane automation control system. After receiving the storage instruction, the crane automation control system controls the crane to complete the steel coil storage operation. The steel coil cooling-related data output by the temperature prediction system is synchronously supplied to the transfer process.

[0046] When there are order requirements or inventory transfer plans, the inventory transfer process is initiated. The temperature prediction subsystem calculates the cooling completion time of the steel coil based on factors such as the storage location of the steel coil, the season, and the real-time temperature of the workshop, and determines whether the steel coil has completed cooling. If cooling has not been completed, the cooling prediction step is continuously executed in a loop. If cooling has been completed, the crane intelligent warehousing subsystem determines the storage location of the cold coil by combining information such as the order and the empty space in the warehouse area and generates warehouse location status information. The crane intelligent warehousing subsystem sends the basic information and location information of the steel coil to the crane automation control system. After receiving the transfer instruction, the crane automation control subsystem controls the crane to transfer the steel coil to the target warehouse location.

[0047] When there are outbound requirements such as order requests and delivery plans, the outbound process is initiated. The crane intelligent warehousing subsystem first obtains the steel coil information to retrieve the basic information and storage location information of the steel coil to be outbound. The machine vision subsystem identifies the loading location information of the truck carrying the steel coil. The crane intelligent warehousing subsystem sends the basic information and location information of the steel coil to the crane automation control subsystem. After receiving the loading instruction, the crane automation control subsystem controls the crane to complete the steel coil outbound loading operation. Finally, a data update operation is performed to update the status of the corresponding steel coil to "outbound" and record the complete outbound information. The updated steel coil data is fed back to the crane intelligent warehousing subsystem, realizing closed-loop data management of the entire process of high-temperature hot steel coil warehousing, unloading, and outbound. At the same time, a manual intervention branch is set up for steel coil abnormalities to take into account both the needs of automated continuous operation and the safety handling of abnormal on-site conditions.

[0048] This invention also provides an intelligent scheduling method for cranes in hot-rolled coil storage facilities. The method includes: acquiring spatial location data of hot-rolled coils through a machine vision subsystem and sending the spatial location data to a crane intelligent storage subsystem; identifying coil number information through an OCR recognition subsystem and sending the coil number information to the crane intelligent storage subsystem; detecting the coil tower shape status through a coil tower shape detection subsystem and sending the coil tower shape status to the crane intelligent storage subsystem; predicting the temperature change trend of hot-rolled coils through a temperature prediction subsystem and sending the temperature change trend to the crane intelligent storage subsystem; the crane intelligent storage subsystem generating target coil and storage location parameter information based on the received spatial location data, coil number information, coil tower shape status, and temperature change trend; generating hoisting task operation instructions based on the target coil and storage location parameter information; and sending the hoisting task operation instructions to a crane automation control subsystem; and the crane automation control subsystem receiving and executing the hoisting task operation instructions to dynamically schedule the hot-rolled coils.

[0049] The same or similar parts among the various embodiments in this specification can be referred to mutually, and will not be repeated here.

[0050] This invention acquires multi-dimensional data of hot steel coils through a machine vision subsystem, an OCR recognition subsystem, a steel coil tower type detection subsystem, and a temperature prediction subsystem. The intelligent crane storage subsystem integrates and processes this multi-dimensional data to generate hoisting task operation instructions. The crane automation control subsystem receives and executes these hoisting task operation instructions. This invention can adjust the steel coil hoisting operation sequence in real time according to the thermal state of the steel coils, improving the efficiency of steel coil scheduling and meeting the needs of intelligent operation. At the same time, it can reduce the proportion of manual operations in the hot steel coil storage area, effectively reduce human operation errors, and prevent personnel safety accidents.

[0051] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions 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. An intelligent scheduling system for hot steel coil storage cranes, characterized in that, include: Machine vision subsystem, OCR recognition subsystem, steel coil tower type detection subsystem, temperature prediction subsystem, crane intelligent warehousing subsystem, and crane automated control subsystem; The machine vision subsystem is used to acquire spatial location data of hot steel coils and send the spatial location data to the crane intelligent warehousing subsystem. The OCR recognition subsystem is used to identify the hot steel coil number information and send the hot steel coil number information to the crane intelligent storage subsystem; The steel coil tower type detection subsystem is used to detect the status of the steel coil tower type and send the status of the steel coil tower type to the crane intelligent storage subsystem. The temperature prediction subsystem is used to predict the temperature change trend of hot steel coils and send the temperature change trend to the crane intelligent storage subsystem. The intelligent warehousing subsystem for cranes is used to generate target steel coil and storage location parameter information based on the received spatial location data, hot steel coil number information, steel coil tower type status and temperature change trend, generate hoisting task operation instructions based on the target steel coil and storage location parameter information, and send the hoisting task operation instructions to the crane automation control subsystem. The crane automation control subsystem is used to receive and execute the hoisting task operation instructions to dynamically schedule the hot steel coil.

2. The intelligent scheduling system for hot steel coil storage cranes according to claim 1, characterized in that, The temperature prediction subsystem predicts the temperature change trend of the hot steel coil based on its current location, ambient temperature, and historical cooling data.

3. The intelligent scheduling system for hot steel coil storage cranes according to claim 1, characterized in that, The target steel coil and storage location parameter information includes at least one of the following: steel coil number information, steel coil specification parameter information, steel coil real-time temperature information, steel coil spatial location information, steel coil tower type status information, storage location status information, and hoisting status information.

4. The intelligent scheduling system for hot steel coil storage cranes according to claim 1, characterized in that, The intelligent warehousing subsystem for cranes includes an anomaly detection module and an alarm module. The anomaly detection module is used to send an alarm signal to the alarm module and send a hoisting task stop command to the crane automation control subsystem when it detects the existence of preset anomaly information. The alarm module is used to receive the alarm signal and issue an alarm prompt.

5. The intelligent scheduling system for hot steel coil storage cranes according to claim 4, characterized in that, The preset abnormal information includes at least one of the following: coil identification abnormality, coil tower type abnormality, coil temperature abnormality, position identification abnormality, coil unwinding abnormality, unwinding abnormality, and communication abnormality.

6. The intelligent scheduling system for hot steel coil storage cranes according to claim 4, characterized in that, The intelligent warehousing subsystem for cranes also includes an anomaly recording module, which is used to record at least one of the following when the preset anomaly information occurs: steel coil status data, equipment operating status data, and crane operating data.

7. The intelligent scheduling system for hot steel coil storage cranes according to claim 1, characterized in that, The crane's automated control subsystem includes a position control module, a clamp control module, and a core detection module. The position control module is used to control the movement of the crane's trolley, carriage, and hoisting mechanism. The clamp control module is used to control the opening and closing of the clamps; The core detection module is used to determine whether the clamp is located at the core of the steel coil.

8. The intelligent scheduling system for hot steel coil storage cranes according to claim 7, characterized in that, The core detection module determines whether the clamp is at the core position of the steel coil by using a first set of laser beam sensors and a second set of laser beam sensors installed on the clamp.

9. The intelligent scheduling system for hot steel coil storage cranes according to claim 7, characterized in that, The crane automation control subsystem also includes an anti-sway control module, which is used to prevent the clamps from swinging during movement.

10. A method for intelligent scheduling of cranes in hot steel coil storage facilities, characterized in that, The method includes: The spatial location data of the hot steel coil is acquired through the machine vision subsystem and then sent to the crane intelligent warehousing subsystem. The steel coil number information is identified by the OCR recognition subsystem and then sent to the crane intelligent storage subsystem. The status of the steel coil tower is detected by the steel coil tower type detection subsystem, and the status of the steel coil tower type is sent to the crane intelligent storage subsystem. The temperature prediction subsystem predicts the temperature change trend of hot steel coils and sends the temperature change trend to the crane intelligent storage subsystem. The crane intelligent warehousing subsystem generates target steel coil and storage location parameter information based on the received spatial location data, steel coil number information, steel coil tower type status and temperature change trend, generates hoisting task operation instructions based on the target steel coil and storage location parameter information, and sends the hoisting task operation instructions to the crane automation control subsystem. The crane automation control subsystem receives and executes the hoisting task operation instructions to dynamically schedule the hot steel coil.

Images