Metallurgical crane operation path safety early warning method and system based on digital twinning

Abstract

The present application belongs to the technical field of metallurgical crane safety monitoring, and particularly relates to a kind of metallurgical crane operation path safety early warning method and system based on digital twinning, aiming at realizing the accurate monitoring and safety early warning of metallurgical crane operation path.The system presents the alarm rules and records of the position trajectory and operation behavior of crane car, main and auxiliary trolley, main and auxiliary hook through behavior control module; adopts a page structure of triangle type, the upper half part shows the trajectory, the left lower half part presents the operation procedure, state data and override alarm configuration, and the right lower half part displays the latest override alarm record; preset digital safety specifications such as starting tank procedure and running path, generate green corridor in digital twinning board, trigger sound and light prompt in cab when exceeding the corridor, and lock control system through intelligent instruction if necessary.The present application improves the intuitiveness, early warning timeliness and safety of crane operation monitoring.

Description

Technical Field

[0001] This invention belongs to the field of metallurgical overhead crane safety monitoring technology, specifically relating to a method and system for early warning of safety on the operation path of metallurgical overhead cranes based on digital twins. Background Technology

[0002] As metallurgical overhead cranes are key equipment in metallurgical production, the safety of their operating paths directly affects production safety and efficiency. Traditional overhead crane monitoring methods have the following shortcomings: 1. The lack of intuitive trajectory display makes it difficult to track the movement paths of the overhead crane, trolley, and hook in real time, and operators and managers cannot quickly determine whether the operation is compliant.

[0003] 2. Safety regulations (such as lifting angle, restricted areas, and iron pouring position limits) rely heavily on manual execution and supervision, lacking digital monitoring methods, making it difficult to detect violations in a timely manner.

[0004] 3. The early warning mechanism is lagging behind. When the vehicle approaches or exceeds the safety boundary, it cannot provide operators with intuitive warnings and relies solely on post-event records, which can easily lead to safety accidents.

[0005] 4. The alarm information has a weak correlation with the work process and equipment status, making it difficult for managers to quickly locate the cause of the violation and affecting the efficiency of handling.

[0006] Therefore, there is an urgent need for a monitoring method and system that combines digital twin technology to achieve visualization of overhead crane operation paths, digitalization of safety standards, and intelligent early warning, in order to solve the above problems. Summary of the Invention

[0007] To address the aforementioned technical issues, this invention proposes a method and system for safety early warning of metallurgical overhead crane operation paths based on digital twins. A laser rangefinder sensor is used to collect real-time position data of various components of the overhead crane, generating dynamic motion trajectories and associating and storing alarm rules. A triangular page structure is adopted, with the upper half displaying the trajectory, the lower left half presenting the operation procedures, status data, and over-control alarm configurations, and the lower right half displaying the latest over-control alarm records. Pre-set digital safety specifications such as lifting procedures and travel paths are used to generate a green corridor on the digital twin dashboard. When the crane exceeds the corridor, an audible and visual warning is triggered in the operator's cab, and if necessary, the control system is locked via intelligent commands.

[0008] The technical solution adopted by this invention is as follows: The first aspect of this invention provides a method for safety early warning of metallurgical overhead crane operation paths based on digital twins, comprising the following steps: S1: Collect position data of the overhead crane, main trolley, auxiliary trolley, main hook, and auxiliary hook, generate dynamic motion trajectory, and record alarm rules and historical alarm information during the operation process. S2: Information is displayed in a triangular structure. The upper half displays the crane's behavior trajectory in real time. The lower left half displays the current work process, crane status data, and over-control alarm configuration of the corresponding process. The lower right half displays the latest 5 over-control alarm records, including alarm time, involved parts, violation type, and related process information. It also supports clicking more tags to jump to the historical record database for detailed query. S3: Load the pre-set digital safety operation specifications and generate a green corridor in the digital twin dashboard as the safety path boundary for crane operations; S4: Real-time comparison of the actual trajectory of the crane with the position of the green corridor. When the crane component is detected to be outside the corridor range, an audible and visual warning is immediately sent to the driver's cab. If there is a serious safety risk, the control system is locked by intelligent command and can only be unlocked after manual confirmation of compliance.

[0009] Furthermore, S1 specifically refers to: S1.1: The X-axis plane coordinates of the trolley are collected by laser rangefinders deployed at both ends of the trolley track, the Y-axis plane coordinates of the main and auxiliary trolleys are collected by laser rangefinders deployed at the ends of the main and auxiliary trolley tracks, and the vertical height data of the Z-axis of the main and auxiliary hooks are collected by absolute encoders deployed at the shafts of the main and auxiliary hook winches. All sensor data are transmitted in real time to the edge computing unit of the trolley via the Profinet industrial bus. S1.2: The edge computing unit performs noise filtering, spatiotemporal alignment and outlier removal on the original location data, and splices the discrete coordinate points in time sequence to generate the continuous three-dimensional motion trajectory of the overhead crane, main and auxiliary trolleys and main and auxiliary hooks. S1.3: The processed trajectory data is cached in the edge local database on one hand, and uploaded to the cloud time series database on the other hand via industrial Ethernet; at the same time, the real-time trajectory data is synchronously pushed to the display module and the early warning and control module, and the preset over-control behavior alarm rules are associated and bound with the trajectory data, and all historical alarm information is recorded.

[0010] Furthermore, S2 specifically includes: S2.1: The display module simultaneously receives real-time 3D trajectory data from the behavior control module, green safety corridor boundary data from the specification and corridor module, current operation process signals and crane operation status data from the crane PLC control system; S2.2: Adopting a triangular page structure, the system uses a digital twin engine for synchronous rendering. The upper main view area restores the physical entity of the overhead crane in a 1:1 ratio, overlaying real-time motion trajectory and a green safety corridor to achieve synchronization of virtual and real actions. The lower left process status area synchronously displays the current work process, the real-time status parameters of the overhead crane, and the corresponding over-control alarm configuration. The lower right real-time alarm area receives and displays the latest 5 over-control alarm records. S2.3: Send temporary rule adjustment instructions to the Specifications and Corridor Module or manual unlock instructions to the Early Warning and Control Module via the touch interface of the display module.

[0011] Furthermore, S3 specifically includes: S3.1: The safety operation specifications for metallurgical overhead cranes are pre-converted into calculable digital parameters and stored in the cloud rule base. When the edge computing unit starts, the latest rules are automatically synchronized to the local machine. S3.2: Receive the current work process signal pushed by PLC in real time, call the safety parameters of the corresponding process, calculate the boundary coordinates of the safe work area in the digital twin three-dimensional coordinate system, and generate a semi-transparent green corridor model. S3.3: The generated green corridor boundary data is synchronized to the display module and the early warning and control module in real time. The corridor boundary is automatically updated and pushed when the operation process is switched.

[0012] Furthermore, S4 specifically includes: S4.1: The early warning and control module takes the edge computing unit as its core, periodically compares the real-time coordinates of each component of the crane with the boundary coordinates of the green corridor, and calculates the amount of boundary crossing and the duration of boundary crossing. S4.2: When a crane component is detected to be outside the corridor boundary, a command is immediately sent to the audible and visual alarm in the driver's cab to trigger a first-level audible and visual warning, and the alarm information is pushed to the display module and the central control room screen. S4.3: When the duration of the out-of-bounds violation exceeds the set threshold or constitutes a high-risk violation, the edge computing unit sends an intelligent locking command to the crane PLC control system via the Profinet bus to restrict the operation of the corresponding motion axis, and at the same time triggers a level two audible and visual alarm and generates a high-risk alarm work order. S4.4: After on-site verification and confirmation of compliance by management personnel, a manual unlocking command is sent through the display module. The command is forwarded to the PLC control system via the edge computing unit to unlock the system. The early warning and control module updates the alarm processing results and stores them synchronously in the cloud database.

[0013] Furthermore, the digital safety operation specifications include the range of hook angles when lifting the can, the restricted area boundaries of the travel path, and the position limits when dumping iron. Based on the specifications, a green corridor is generated in the three-dimensional scene of the digital twin dashboard, which is the digital boundary of the safe operation area. This serves as a dynamic safety benchmark for crane operations, and the green boundary automatically turns red when the crane exceeds the corridor.

[0014] Secondly, the present invention also provides a safety early warning system for the operation path of metallurgical overhead cranes based on digital twins, comprising: Behavior control module: used to collect and present the trajectories of the overhead crane's main trolley position, main trolley position, auxiliary trolley position, main hook position, and auxiliary hook position, as well as the alarm rules and alarm records of the overhead crane operation process; Display module: It adopts a triangular structure. The upper half displays the crane's control behavior trajectory, the lower left half displays the crane's operation procedures, status data, and corresponding over-control behavior alarm configurations, and the lower right half displays the latest 5 over-control alarm records. It also supports clicking more tabs to jump to the history list. Standards and Corridor Module: Pre-set digitization and generate green corridors in the digital twin dashboard; Early warning and control module: used to trigger audible and visual alerts in the cab when the crane operates outside the green corridor, and to lock the control system via intelligent commands if necessary.

[0015] Furthermore, the behavior control module includes a laser rangefinder and an encoder, and the data is transmitted to the edge computing unit via an industrial bus; the display module is deployed on the operator's cab console and the central control room screen, supporting a triangular interface operation; the early warning and control module is equipped with an audible and visual alarm with a decibel level of ≥85dB, red and green warning lights, and control commands communicate with the crane's main control system via a PLC.

[0016] Furthermore, it also includes a system architecture of multi-source perception – edge collaboration – cloud intelligence, the system architecture including: Data acquisition layer: integrates UWB positioning, laser ranging, weight sensor, encoder and camera; Edge computing layer: Enables protocol conversion, security protection, and remote management; Data center layer: performs data cleaning, multi-source data integration, and intelligent data analysis; Cloud server layer: Training fault diagnosis models based on hybrid algorithms, and performing model optimization and evaluation management; System application layer: Provides digital twin visualization, multi-dimensional alarms, and predictive maintenance.

[0017] Furthermore, in the specification and corridor module, the green corridor is generated based on parameters in the lifting procedure, such as the verticality of the hook to the tank opening being ≤5° and the travel path being at least 3m away from high-temperature areas; the early warning and control module triggers an audible and visual alarm when it detects that the overhead crane exceeds the corridor by 0.5m, and if it is not adjusted within 10 seconds, it automatically limits the crane's travel speed to 0.5m / s, and the central control room receives the early warning information simultaneously.

[0018] Furthermore, the behavior control module also includes a hook recognition submodule, which segments the hook shape using an instance segmentation model, calculates the relative position based on the key feature points of the hook and the ladle trunnion, and determines whether the hook is reliable.

[0019] The beneficial effects of this invention are: (1) High degree of visualization: Through digital twin model and triangular layout, the crane trajectory, process and alarm information are presented intuitively, improving monitoring efficiency.

[0020] (2) Standardize digital implementation: Transform safe operation standards into green corridors to achieve "visible safety boundaries" and reduce the cost of manual supervision.

[0021] (3) Timely and controllable early warning: The combination of sound and light prompts and intelligent locking transforms the response from "passive response" to "active prevention", reducing the risk of accidents.

[0022] (4) Strong traceability: Completely records alarm information (including time, component, violation type, current process, and processing status), with a storage period of ≥1 year, which facilitates post-event analysis and standardization optimization.

[0023] (5) Edge-cloud collaboration: meets the millisecond-level response requirements of high real-time scenarios, while realizing in-depth fault diagnosis and continuous model iteration. Attached Figure Description

[0024] 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 It is a system architecture diagram, showing a five-layer architecture of multi-source perception, edge collaboration, cloud intelligence, and scenario application; Figure 2 This is a flowchart for controlling the operation of overhead cranes; Figure 3 This is a flowchart of the overhead crane hook recognition process; Figure 4 This is a flowchart of the data access process of the present invention. Detailed Implementation

[0026] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to embodiments and accompanying drawings. The content mentioned in the embodiments is not intended to limit the present invention.

[0027] like Figure 4 As shown, this invention provides a method for safety early warning of metallurgical overhead crane operation paths based on digital twins, comprising the following steps: S1: Collect position data of the overhead crane, main trolley, auxiliary trolley, main hook, and auxiliary hook, generate dynamic motion trajectory, and record alarm rules and historical alarm information during the operation process. To further explain, the specific details include: S1.1: Laser rangefinders deployed at both ends of the overhead crane track collect the X-axis plane coordinates of the crane, laser rangefinders deployed at the ends of the main and auxiliary trolley tracks collect the Y-axis plane coordinates of the main and auxiliary trolleys, and absolute encoders deployed at the shafts of the main and auxiliary hook winches collect the vertical height data of the Z-axis of the main and auxiliary hooks. All sensor data are transmitted in real time to the local edge computing unit of the overhead crane via the Profinet industrial bus. S1.2: The edge computing unit performs noise filtering, spatiotemporal alignment and outlier removal on the original location data, and splices the discrete coordinate points in time sequence to generate the continuous three-dimensional motion trajectory of the overhead crane, main and auxiliary trolleys and main and auxiliary hooks. S1.3: The processed trajectory data is cached in the edge local database on one hand, and uploaded to the cloud time series database on the other hand via industrial Ethernet; at the same time, the real-time trajectory data is synchronously pushed to the display module and the early warning and control module, and the preset over-control behavior alarm rules are associated and bound with the trajectory data, and all historical alarm information is recorded.

[0028] S2: Information is displayed in a triangular structure. The upper half displays the crane's behavior trajectory in real time. The lower left half displays the current work process, crane status data, and corresponding over-control alarm configurations. The lower right half displays the latest 5 over-control alarm records, including alarm time, involved components, violation type, and related work process information. It also supports clicking more tags to jump to the historical record database for detailed queries.

[0029] To further explain, it specifically includes: S2.1: The display module simultaneously receives real-time three-dimensional trajectory data from the behavior control module, green safety corridor boundary data from the specification and corridor module, and current operation process signals and crane operation status data from the crane PLC control system; S2.2: Adopting a triangular page structure, the system uses a digital twin engine for synchronous rendering. The upper main view area restores the physical entity of the overhead crane in a 1:1 ratio, overlaying real-time motion trajectory and a green safety corridor to achieve synchronization of virtual and real actions. The lower left process status area synchronously displays the current work process, the real-time status parameters of the overhead crane, and the corresponding over-control alarm configuration. The lower right real-time alarm area receives and displays the latest 5 over-control alarm records. S2.3: Send temporary rule adjustment instructions to the Specifications and Corridor Module or manual unlock instructions to the Early Warning and Control Module via the touch interface of the display module.

[0030] S3: Load the pre-set digital safety operation specifications and generate a green corridor in the digital twin dashboard as the safety path boundary for crane operations; To further explain, this specifically includes: S3.1: The safety operation specifications for metallurgical overhead cranes are pre-converted into calculable digital parameters and stored in the cloud rule base. When the edge computing unit starts, the latest rules are automatically synchronized to the local machine. S3.2: Receive the current work process signal pushed by PLC in real time, call the safety parameters of the corresponding process, calculate the boundary coordinates of the safe work area in the digital twin three-dimensional coordinate system, and generate a semi-transparent green corridor model. S3.3: The generated green corridor boundary data is synchronized to the display module and the early warning and control module in real time. The corridor boundary is automatically updated and pushed when the operation process is switched.

[0031] S4: Real-time comparison of the actual trajectory of the crane with the position of the green corridor. When the crane component is detected to be outside the corridor range, an audible and visual warning is immediately sent to the driver's cab. If there is a serious safety risk, the control system is locked by intelligent command and can only be unlocked after manual confirmation of compliance.

[0032] To further explain, it specifically includes: S4.1: The early warning and control module uses the edge computing unit as the core to periodically compare the real-time coordinates of each component of the crane with the boundary coordinates of the green corridor, and calculate the amount of boundary crossing and the duration of boundary crossing; S4.2: When a crane component is detected to be outside the corridor boundary, a command is immediately sent to the audible and visual alarm in the driver's cab to trigger a first-level audible and visual warning, and the alarm information is pushed to the display module and the central control room screen. S4.3: When the duration of the out-of-bounds violation exceeds the set threshold or constitutes a high-risk violation, the edge computing unit sends an intelligent locking command to the crane PLC control system via the Profinet bus to restrict the operation of the corresponding motion axis, and at the same time triggers a level two audible and visual alarm and generates a high-risk alarm work order. S4.4: After on-site verification and confirmation of compliance by management personnel, a manual unlocking command is sent through the display module. The command is forwarded to the PLC control system via the edge computing unit to unlock the system. The early warning and control module updates the alarm processing results and stores them synchronously in the cloud database.

[0033] This invention also provides a digital twin-based safety early warning system for the operation path of metallurgical overhead cranes, comprising the following key modules: Behavior Control Module: This module connects the sensors and control system on the overhead crane, collecting real-time position data such as coordinates and height of the trolley, main and auxiliary trolleys, and main and auxiliary hooks, and generating continuous motion trajectories. Specifically, it uses laser rangefinders with an accuracy of ±1mm to collect the positions of the trolley and auxiliary trolleys, and encoders to collect the hook height. The data is transmitted to the edge computing unit via an industrial bus. Simultaneously, this module stores preset alarm rules, such as the criteria for determining over-control behavior, and historical alarm records, supporting the correlation query of trajectory and alarm information.

[0034] Display module: This module adopts a triangular page structure and is deployed on the driver's cab control panel (21.5-inch touch screen) and the central control room large screen (55-inch splicing screen), both of which support triangular interface touch operation.

[0035] It should be further explained that this module is divided into three parts. The upper part, based on a digital twin model, uses 3D visualization technology to display the real-time movement trajectory of each component of the overhead crane, keeping it synchronized with the physical crane's movements. The lower left part displays the current work process (e.g., lifting the ladle, adding iron, etc.), the crane's real-time status data (e.g., operating speed, load, etc.), and the corresponding over-control alarm configuration (e.g., allowed over-control time threshold, triggering conditions, etc.). The lower right part displays the latest 5 over-control alarm records in list form, including alarm time, involved components, violation type, related processes, etc., and supports clicking "More" to jump to the historical record database for detailed queries.

[0036] Standards and Corridor Module: This module pre-sets digital safety operation standards, including the hook angle range when lifting the can, restricted area boundaries of the travel path, and position limits when transferring iron. Specifically, it generates a green corridor in the digital twin model built in Unity3D. Corridor parameters include, for example, the perpendicularity of the hook to the can opening during lifting ≤5°, and the travel path being ≥3m away from high-temperature areas. Based on these standard parameters, a green corridor is generated in the 3D scene of the digital twin dashboard, which serves as the digital boundary of the safe operation area and a dynamic safety benchmark for overhead crane operations.

[0037] Early warning and control module: This module compares the actual trajectory of the overhead crane with the position of the green corridor in real time. When a crane component is detected to be outside the corridor's range, an audible and visual alert is immediately sent to the operator's cab, such as a buzzer alarm and flashing red warning lights. If the out-of-range behavior lasts for more than a set threshold or constitutes a high-risk violation, such as approaching a personnel area, an intelligent command is automatically triggered to lock the overhead crane control system, such as restricting movement or stopping lifting, until manual confirmation of compliance is received before unlocking.

[0038] It should be further explained that it also includes an audible and visual alarm with a decibel level of ≥85dB and red and green warning lights, which communicate with the crane's main control system via a PLC. When it detects that the crane has exceeded the corridor, such as when the crane approaches the edge of the material yard by 0.5m, an alarm is triggered; if it is not adjusted within 10 seconds, the crane's travel speed is automatically limited to 0.5m / s, and the central control room is notified simultaneously.

[0039] The present invention will be further described below with reference to specific embodiments and accompanying drawings.

[0040] like Figure 1As shown, the system of this invention adopts an industrial integrated monitoring architecture of "multi-source sensing - edge collaboration - cloud intelligence - scenario application," including a five-layer architecture of data acquisition, edge computing, data center, cloud server, and system application. It integrates overhead crane multimodal sensing and analysis technology to achieve closed-loop management from "data acquisition" to "intelligent decision-making." The technical logic and functional coordination of each layer are as follows: 1. Data Acquisition Layer: Comprehensive Sensing of Multiple Physical Quantities and High-Frequency Electrical Components This layer integrates the multi-source data acquisition capabilities of the overhead crane, constructing a dual-dimensional "mechanical-electrical" sensing network: Overhead crane multimodal sensing: spatial data such as the position of the trolley / cart and the height of the hook are collected through UWB positioning and laser rangefinder sensors; weight sensors monitor the load tension in real time; and cameras capture the hook posture and environmental visual information to achieve multi-dimensional dynamic perception of "position-load-vision".

[0041] 2. Edge Computing Layer: Device Collaboration and Edge Intelligent Analysis Edge station overhead crane equipment integrates edge computing capabilities to achieve lightweight intelligence through "real-time response + data preprocessing": Overhead crane equipment collaboration: The protocol conversion module is compatible with industrial bus protocols such as Modbus and Profinet, and the identity authentication and data encryption security protection mechanisms ensure reliable transmission of multi-source data; the remote management module supports remote configuration of equipment parameters and firmware upgrades.

[0042] 3. Data Center Layer: Central Hub for Multi-Source Data Integration and Analysis The data center serves as a central hub for overhead crane big data processing, enabling streamlined processes such as "data cleaning – feature extraction – anomaly detection." Data preprocessing: Denoising, spatiotemporal alignment, and cleaning of the crane position data; unifying the data format and timestamps. Data integration: Based on the data center, integrate crane location, load, and visual multimodal data, and achieve distributed data communication through Kafka; Data analysis: Machine learning algorithms are used to model historical data and extract the temporal features of the crane's over-control behavior and the visual features of the hook posture.

[0043] 4. Cloud Server Layer: Central Hub for Model Training and Intelligent Diagnosis Cloud servers, based on a "homogeneous and homogeneous model + big data hybrid algorithm," enable in-depth fault diagnosis of overhead cranes. Model training and optimization: Customized models are developed for scenarios such as crane overload control behavior and hook recognition. The diagnostic accuracy is improved by using a hybrid algorithm of "mechanism model (physical characteristics) + data-driven model (historical state statistics)".

[0044] Model inference and acceleration: Quantize and prune the model using tools such as TensorRT and ONNX Runtime to achieve real-time inference of 10KHz electrical data; improve throughput through batch inference and asynchronous processing to meet the high-frequency monitoring requirements of overhead cranes.

[0045] Model evaluation and version management: Validate model accuracy on the test set, such as fault identification accuracy and alarm response latency. Manage model versions using tools such as MLflow, record training parameters and evaluation metrics, and support rapid iteration.

[0046] 5. System Application Layer: Intelligent Monitoring and Decision Output for Overhead Cranes Across All Scenarios At the system application level, visualization and decision support are provided for the entire overhead crane operation process: Digital twin visualization: By mapping the physical entity of the overhead crane through digital twin technology, the trajectory of the trolley and the hook status and the temperature distribution of the equipment are dynamically displayed, realizing real-time synchronization between the virtual and real spaces; Multi-dimensional alarms and maintenance: Combined with the process analysis module, the overhead crane operation process is optimized, ultimately forming an integrated application loop of "data twin visualization - over-control / hook anomaly alarm - predictive maintenance - operating environment monitoring".

[0047] Example 1: System Hardware Configuration and Software Implementation Hardware configuration: Behavior control module: The system uses a laser rangefinder with an accuracy of ±1mm to collect the position of the trolley and the crane, and an encoder to collect the height of the hook. The data is transmitted to the edge computing unit, such as an industrial PC, via an industrial bus.

[0048] Display modules: A 21.5-inch touchscreen is deployed on the driver's cab console, and a 55-inch splicing screen is deployed on the central control room screen, both supporting a triangular interface touch operation.

[0049] Early warning and control module: Equipped with an audible and visual alarm with a decibel level of ≥85dB and red and green warning lights. Control commands are communicated with the crane's main control system via a PLC.

[0050] Software implementation: Digital twin model: built based on Unity3D, with a 1:1 scale to the physical crane size, and a refresh rate of ≥25Hz to ensure trajectory synchronization.

[0051] Green corridor generation: Based on the lifting procedure, parameters such as the verticality of the hook to the tank opening ≤5°, the travel path being ≥3m away from high-temperature areas, etc., a semi-transparent green boundary is generated in the model. When the boundary is exceeded, the boundary automatically turns red.

[0052] Alarm log format: Each log contains "time, accurate to the second, component, such as: main hook, violation type, such as: exceeding travel path, current process, such as: iron exchange, processing status, such as: warning issued, historical records, and storage period ≥ 1 year.

[0053] Example 2: Application Process like Figure 2 As shown, when the overhead crane performs the following processes: lifting the can → traveling → iron mixing, the behavior control module generates the main hook lifting trajectory and the trolley traveling trajectory in real time.

[0054] The upper part of the display module shows the trajectory and green corridor. During the lifting stage, the height of the hook in the corridor is limited to ≤10m, and during the travel stage, the corridor avoids the edge of the material yard.

[0055] If the trolley travels close to the edge of the material yard and exceeds the passageway by 0.5m, the early warning and control module will immediately trigger an audible and visual alarm in the driver's cab.

[0056] If the operator fails to make timely adjustments, the system will automatically limit the trolley's travel speed to 0.5 m / s after 10 seconds, and the central control room will receive a warning message simultaneously.

[0057] After a violation is handled, the alarm record is automatically updated to "handled" and stored in the database. The central control room can use the "More" tab to query statistics of similar violations over the past 3 months.

[0058] Example 3: Specific Process of Hook Identification like Figure 3 As shown, in order to reduce the dangers in the overhead crane steelmaking ladle hoisting process and improve work efficiency, the detection system is triggered to start working through multiple means such as positioning, weight and vision. The machine vision system uses a deep learning model to track the hook and ladle in real time and accurately. The hook shape is accurately segmented through an instance segmentation model. Based on multiple key feature points of the hook and ladle trunnion, the relevant positions are reliably calculated to accurately determine whether the overhead crane has reliably hooked the hook, thereby minimizing the false alarm rate and the missed alarm rate.

[0059] In summary, the technical solution of this invention improves the intuitiveness and timeliness of overhead crane operation monitoring, and achieves safe, manageable and controllable operation.

[0060] The above embodiments are preferred implementations of the present invention. In addition, the present invention can be implemented in other ways. Any obvious substitutions without departing from the concept of the present invention are within the protection scope of the present invention.

[0061] To facilitate understanding by those skilled in the art of the improvements of this invention over the prior art, some of the accompanying drawings and descriptions have been simplified, and for clarity, some other elements have been omitted from this application. Those skilled in the art should realize that these omitted elements may also constitute the content of this invention.

Claims

1. A method for safety early warning of metallurgical overhead crane operation path based on digital twin, characterized in that, Includes the following steps: S1: Collect position data of the overhead crane, main trolley, auxiliary trolley, main hook, and auxiliary hook, generate dynamic motion trajectory, and record alarm rules and historical alarm information during the operation process. S2: Information is displayed in a triangular structure. The upper half displays the crane's behavior trajectory in real time. The lower left half displays the current work process, crane status data, and over-control alarm configuration of the corresponding process. The lower right half displays the latest 5 over-control alarm records, including alarm time, involved parts, violation type, and related process information. It also supports clicking more tags to jump to the historical record database for detailed query. S3: Load the pre-set digital safety operation specifications and generate a green corridor in the digital twin dashboard as the safety path boundary for crane operations; S4: Real-time comparison of the actual trajectory of the crane with the position of the green corridor. When the crane component is detected to be outside the corridor range, an audible and visual warning is immediately sent to the driver's cab. If there is a serious safety risk, the control system is locked by intelligent command and can only be unlocked after manual confirmation of compliance.

2. The method for safety early warning of metallurgical overhead crane operation path based on digital twin as described in claim 1, characterized in that, Specifically, S1 is: S1.1: The X-axis plane coordinates of the trolley are collected by laser rangefinders deployed at both ends of the trolley track, the Y-axis plane coordinates of the main and auxiliary trolleys are collected by laser rangefinders deployed at the ends of the main and auxiliary trolley tracks, and the vertical height data of the Z-axis of the main and auxiliary hooks are collected by absolute encoders deployed at the shafts of the main and auxiliary hook winches. All sensor data are transmitted in real time to the edge computing unit of the trolley via the Profinet industrial bus. S1.2: The edge computing unit performs noise filtering, spatiotemporal alignment and outlier removal on the original location data, and splices the discrete coordinate points in time sequence to generate the continuous three-dimensional motion trajectory of the overhead crane, main and auxiliary trolleys and main and auxiliary hooks. S1.3: The processed trajectory data is cached in the edge local database on one hand, and uploaded to the cloud time series database on the other hand via industrial Ethernet; at the same time, the real-time trajectory data is synchronously pushed to the display module and the early warning and control module, and the preset over-control behavior alarm rules are associated and bound with the trajectory data, and all historical alarm information is recorded.

3. The method for safety early warning of metallurgical overhead crane operation path based on digital twin as described in claim 1, characterized in that, Specifically, S2 is: S2.1: Simultaneously receive real-time three-dimensional trajectory data, green safety corridor boundary data, current operation process signals from the crane PLC control system, and crane operation status data; S2.2: Adopting a triangular page structure, the system uses a digital twin engine for synchronous rendering. The upper main view area restores the physical entity of the overhead crane in a 1:1 ratio, overlaying real-time motion trajectory and a green safety corridor to achieve synchronization of virtual and real actions. The lower left process status area synchronously displays the current work process, the real-time status parameters of the overhead crane, and the corresponding over-control alarm configuration. The lower right real-time alarm area receives and displays the latest 5 over-control alarm records. S2.3: Send temporary rule adjustment commands or manual unlock commands via the touch interface.

4. The method for safety early warning of metallurgical overhead crane operation path based on digital twin as described in claim 1, characterized in that, Specifically, S3 is: S3.1: The safety operation specifications for metallurgical overhead cranes are pre-converted into calculable digital parameters and stored in the cloud rule base. When the edge computing unit starts, the latest rules are automatically synchronized to the local machine. S3.2: Receive the current work process signal pushed by PLC in real time, call the safety parameters of the corresponding process, calculate the boundary coordinates of the safe work area in the digital twin three-dimensional coordinate system, and generate a semi-transparent green corridor model. S3.3: Real-time synchronized green corridor boundary data, automatically updating and pushing corridor boundaries when switching work procedures.

5. The method for safety early warning of metallurgical overhead crane operation path based on digital twin as described in claim 1, characterized in that, Specifically, S4 is: S4.1: Using the edge computing unit as the core, periodically compare the real-time coordinates of each component of the overhead crane with the boundary coordinates of the green corridor to calculate the amount of boundary crossing and the duration of boundary crossing; S4.2: When a crane component is detected to be outside the corridor boundary, a command is immediately sent to the audible and visual alarm in the driver's cab to trigger a first-level audible and visual warning, and the alarm information is pushed to the display module and the central control room screen. S4.3: When the duration of the out-of-bounds violation exceeds the set threshold or constitutes a high-risk violation, the edge computing unit sends an intelligent locking command to the crane PLC control system via the Profinet bus to restrict the operation of the corresponding motion axis, and at the same time triggers a level two audible and visual alarm and generates a high-risk alarm work order. S4.4: After on-site verification and confirmation of compliance by management personnel, a manual unlocking command is sent through the display module. The command is forwarded to the PLC control system via the edge computing unit to unlock the system. The early warning and control module updates the alarm processing results and stores them synchronously in the cloud database.

6. The method for safety early warning of metallurgical overhead crane operation path based on digital twin as described in claim 4, characterized in that, The digital safety operation specifications include the range of hook angles when lifting the can, the restricted area boundaries of the travel path, and the position limits when dumping iron. Based on the specifications, a green corridor is generated in the three-dimensional scene of the digital twin dashboard, which is the digital boundary of the safe operation area. This serves as a dynamic safety benchmark for crane operations. When the crane exceeds the corridor, the green boundary automatically turns red.

7. A safety early warning system for metallurgical overhead crane operation paths based on digital twins, characterized in that, include: Behavior control module: used to collect and present the trajectories of the overhead crane's main trolley position, main trolley position, auxiliary trolley position, main hook position, and auxiliary hook position, as well as the alarm rules and alarm records of the overhead crane operation process; Display module: It adopts a triangular structure. The upper half displays the crane's control behavior trajectory, the lower left half displays the crane's operation procedures, status data, and corresponding over-control behavior alarm configurations, and the lower right half displays the latest 5 over-control alarm records. It also supports clicking more tabs to jump to the history list. Standards and Corridor Module: Pre-set digitization and generate green corridors in the digital twin dashboard; Early warning and control module: used to trigger audible and visual alerts in the cab when the crane operates outside the green corridor, and to lock the control system via intelligent commands if necessary.

8. The metallurgical overhead crane operation path safety early warning system based on digital twin as described in claim 7, characterized in that, The behavior control module includes a laser rangefinder and an encoder, and the data is transmitted to the edge computing unit via an industrial bus; the display module is deployed on the operator's cab console and the central control room screen, supporting a triangular interface operation; the early warning and control module is equipped with an audible and visual alarm with a decibel level of ≥85dB, red and green warning lights, and control commands communicate with the crane's main control system via a PLC.

9. The metallurgical overhead crane operation path safety early warning system based on digital twin as described in claim 7, characterized in that, It also includes a system architecture of multi-source perception-edge collaboration-cloud intelligence, which includes: Data acquisition layer: integrates UWB positioning, laser ranging, weight sensor, encoder and camera; Edge computing layer: Enables protocol conversion, security protection, and remote management; Data center layer: performs data cleaning, multi-source data integration, and intelligent data analysis; Cloud server layer: Training fault diagnosis models based on hybrid algorithms, and performing model optimization and evaluation management; System application layer: Provides digital twin visualization, multi-dimensional alarms, and predictive maintenance.

10. The metallurgical overhead crane operation path safety early warning system based on digital twin as described in claim 9, characterized in that, In the specification and corridor module, the green corridor is generated based on parameters in the lifting procedure, such as the verticality of the hook to the tank opening being ≤5° and the travel path being at least 3m away from high-temperature areas; the early warning and control module triggers an audible and visual alarm when it detects that the overhead crane exceeds the corridor by 0.5m, and if it is not adjusted within 10 seconds, it automatically limits the crane's travel speed to 0.5m / s, and the central control room receives the early warning information simultaneously.

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