Anti-collision method and system for multiple vehicles in span of bridge crane

Abstract

The application provides a bridge crane cross interval multi-vehicle cooperative anti-collision method and system, belongs to the technical field of metallurgical casting and molten metal, and is used for solving the problem of poor identification ability of the existing anti-collision system. The bridge crane cross interval multi-vehicle cooperative anti-collision method comprises the following steps: acquiring the real-time running speed, real-time load and real-time radar positioning of the vehicle; calculating the safe braking distance of the vehicle based on a preset dynamic braking distance model; acquiring the real-time running parameters and real-time positions of other vehicles in the cross interval through a cooperative communication module; determining a hierarchical safety protection threshold; executing corresponding hierarchical control strategies and introducing anti-shaking constraint logic in the control process; controlling the vehicle to complete the wrong car according to the preset peristaltic speed according to the conflict prediction result of the opposite meeting; and synchronously displaying the real-time positions of all vehicles in the cross interval on a man-machine interaction interface. The application can adapt to harsh environments, has dynamic risk assessment capability, and realizes multi-vehicle information sharing and cooperative control.

Description

Technical Field

[0001] This invention belongs to the field of metallurgical casting and molten metal technology, specifically relating to a method and system for multi-vehicle collaborative anti-collision between bridge cranes. Background Technology

[0002] In core operating areas such as the charging bay and molten steel bay of a steelmaking plant, at least two 260-ton or larger metallurgical casting overhead cranes (referred to as overhead cranes) are typically installed to undertake critical tasks such as hoisting molten iron ladles and molten steel ladles and feeding scrap steel. Molten metal is extremely dangerous; if a collision causes a ladle to fall or splash, it can easily trigger a catastrophic fire, explosion, or mass casualty accident. Currently, the laser ranging and collision avoidance systems mainly used in the industry have significant drawbacks: Firstly, the smoke, water vapor, and iron oxide dust in the steelmaking environment easily adhere to the laser mirror, causing signal attenuation or even interruption. Furthermore, the wear, settlement, and lateral bending caused by long-term heavy-load rolling of the track can cause the train's trajectory to deviate from a straight line, making it easy for the laser beam to deviate from the receiving target surface during long-distance transmission (over 30 meters), leading to false alarms or missed alarms. Secondly, existing systems mostly use fixed distance thresholds such as 10-meter alarm and 5-meter stop, which are difficult to match with the enormous inertia of a 260-ton crane fully loaded with molten steel ladles and the safety limitations of molten metal surface sloshing. This overly conservative approach can lead to frequent false stops, reducing production efficiency, or insufficient emergency braking distance, causing rear-end collision risks. Simultaneously, when multiple vehicles are operating, the driver's field of vision is limited, especially in scenarios where it is obstructed by adjacent vehicles, making it impossible to see hidden traffic conditions ahead. Existing systems lack cross-workshop information sharing and collaborative decision-making capabilities, relying on driver verbal coordination, which is inefficient and poses significant safety hazards. Summary of the Invention

[0003] Therefore, the technical problem to be solved by the present invention is to provide a method and system for multi-vehicle collaborative anti-collision between bridge cranes, which can adapt to harsh environments, have dynamic risk assessment capabilities, and realize multi-vehicle information sharing and collaborative control.

[0004] To address the aforementioned problems, this invention provides a multi-vehicle cooperative collision avoidance method for bridge cranes, comprising the following steps: Each vehicle in the span independently acquires its real-time operating speed, real-time load, and real-time radar positioning to obtain its real-time operating parameters and real-time position. Each vehicle is based on a preset dynamic braking distance model, which calculates the vehicle's safe braking distance according to its real-time operating speed and real-time load. Each vehicle obtains the real-time operating parameters and real-time position of other vehicles in the same section through the cooperative communication module, so as to obtain the real-time distance between the vehicle and other vehicles. Each vehicle determines its graded safety protection threshold based on its safe braking distance and the real-time distance between itself and other vehicles. Based on the comparison results of the real-time distance between this vehicle and other vehicles and the graded safety protection threshold, the corresponding graded control strategy is executed, and anti-sway constraint logic is introduced in the control process to limit the rate of speed change to meet the anti-sway requirements of molten metal hoisting. Each train controls itself to pass other trains at a preset creeping speed based on the conflict prediction results of oncoming trains; Based on the multi-vehicle data sharing mechanism, the real-time location of all vehicles in the span is displayed synchronously on the human-machine interface in the cab of each vehicle, as well as the virtual markers of vehicles obscured by neighboring vehicles.

[0005] The calculation formula for the dynamic braking distance model is as follows: (1) in, S safe For safe braking distance, v This is the real-time operating speed of the vehicle. t resp This is the inherent response time of the system. μ The equivalent friction coefficient is based on real-time load correction. g It is the acceleration due to gravity; Real-time load is collected in real time by the vehicle's on-board weight sensor; The graded safety protection threshold is dynamically adjusted according to the safe braking distance.

[0006] The hierarchical control strategy includes: When the real-time distance between this vehicle and other vehicles is greater than the first preset multiple of the safe braking distance, a level one warning is triggered, the audible and visual alarm in the driver's cab sounds intermittently, and the human-machine interface displays a yellow warning sign; When the real-time distance is less than or equal to the first preset multiple of the safe braking distance and greater than the second preset multiple of the safe braking distance, the second-level deceleration is triggered, forcibly limiting the vehicle's operating speed to the preset low gear and prohibiting the driver from manually accelerating; When the real-time distance is less than or equal to the second preset multiple of the safe braking distance, a level three emergency stop is triggered, the inverter of this vehicle is disconnected and the brakes of this vehicle are locked. Among them, the first preset multiple is greater than 1, and the second preset multiple is equal to 1; The anti-sway constraint logic is as follows: when performing deceleration control, the acceleration is limited to a preset threshold to ensure that the sway angle of the molten metal ladle does not exceed ±2°.

[0007] Each train, based on the conflict prediction result of oncoming traffic, controls itself to complete the passing maneuver at a preset creeping speed, including: Calculate in real time the overlapping area of ​​the vehicle's trajectory with that of oncoming vehicles and the estimated meeting time; If it is determined that the two vehicles cannot stop at a safe distance, the speed is reduced to the creeping speed; the creeping speed of each vehicle is determined dynamically based on the anti-sway requirements of the molten metal ladle and the load of each vehicle, and the value range is 5% to 10% of the rated operating speed; After the two vehicles have passed each other and the distance between them is greater than the safety threshold, the speed limit is lifted and normal operation control is restored.

[0008] The steps for generating the virtual identifier for a vehicle obscured by a neighboring vehicle include: Each vehicle obtains real-time operating parameters of neighboring vehicles and obstacle information within the neighboring vehicles' perception range through the collaborative communication module; If it is determined that there is a vehicle behind the adjacent vehicle that is not directly detected by the vehicle's radar, the vehicle that is not directly detected by the vehicle's radar will be marked with a red dashed box at the corresponding position on the human-machine interface in the driver's cab, and the real-time distance between the vehicle and the vehicle will be displayed simultaneously.

[0009] This invention also provides a multi-vehicle cooperative anti-collision system for bridge cranes, used to implement the above-mentioned multi-vehicle cooperative anti-collision method for bridge cranes; the system includes: The radar positioning module is used to collect real-time position data of each vehicle in the span; the radar positioning module includes a multipath suppression algorithm to filter out false positioning signals generated by reflections from the steel structure of the factory building; The data processing module is located at the on-board control terminal of each vehicle in the span; the data processing module is connected to the radar positioning module; the data processing module is used to run the dynamic braking distance model, calculate the safe braking distance based on the vehicle's real-time operating speed and real-time load, and determine the graded safety protection threshold. A graded control module is installed at the on-board control terminal of each crane in the span; the graded control module is electrically connected to the data processing module on the crane; the graded control module is used to output control signals to the frequency converter and brake of the crane based on the comparison result of the real-time distance between the crane and other cranes and the graded safety protection threshold, so as to execute the graded safety protection action; the graded control module includes anti-sway constraint logic to limit the rate of speed change; The collaborative communication module is used to realize real-time data interaction between the data processing modules of each train across the cross-section, as well as data interaction between the data processing modules of each train across the cross-section and the ground dispatch system; The human-machine interaction module is installed in the driver's cab of each vehicle; the human-machine interaction module is electrically connected to the data processing module of each vehicle in the span; the human-machine interaction module is used to display the real-time position of all vehicles in the span, as well as virtual markers of hidden obstacles obscured by adjacent vehicles.

[0010] The radar positioning module includes: multiple millimeter-wave radar base stations and radar reflection tags; Multiple millimeter-wave radar base stations are fixedly installed at both ends and the middle turning point of the span, and adopt the frequency-modulated continuous wave ranging system. The radar reflective tag includes a corner reflector array, which is fixedly installed in the middle of the main beam of each vehicle to avoid the high-temperature radiation area; The multipath suppression algorithm includes: pre-storing a priori map of the steel structure of the factory building, comparing the point cloud data detected by radar with the priori map, filtering out fixed false reflection points that match the coordinates of the steel structure of the factory building, and retaining only the moving point cloud data corresponding to the radar reflection labels.

[0011] This also includes a weight sensor; the weight sensor is installed on the vehicle and electrically connected to the vehicle's data processing module; the weight sensor is used to collect the vehicle's lifting load in real time and transmit it to the data processing module to correct the equivalent friction coefficient in the dynamic braking distance model; The collaborative communication module includes: multiple wireless access units arranged at intervals along the columns of the factory building; multiple wireless access units forming a wireless mesh network (MESH); the wireless mesh network communicating with the data processing module of each crane and the ground dispatch system; the data transmission delay of the wireless mesh network is no more than 50ms.

[0012] The hierarchical control module includes: The frequency converter control unit is electrically connected to the vehicle's data processing module and the vehicle's frequency converter. It is used to output frequency adjustment signals according to the hierarchical control strategy to limit the vehicle's operating speed. The brake control unit is electrically connected to the vehicle's data processing module and the vehicle's hydraulic push rod brake, and is used to output brake control signals according to the hierarchical control strategy. The audible and visual alarm unit is installed in the driver's cab of the vehicle and is electrically connected to the vehicle's data processing module. It is used to trigger corresponding warning sounds and lights according to the hierarchical control strategy.

[0013] The human-computer interaction module includes a touch screen display, which includes: The cross-section top-down planar schematic area includes the green solid icon of this vehicle, the yellow solid icons of other adjacent vehicles, the red dashed box icons of vehicles whose driving is obscured by adjacent vehicles, and the dynamic safety radius circle centered on this vehicle; The vehicle's real-time operating parameters display area includes real-time speed, real-time load, and real-time distance to the nearest vehicle. The alarm information display area is used to show the current warning level of this vehicle and the corresponding handling prompts.

[0014] Beneficial effects: The bridge crane multi-vehicle collaborative anti-collision method and system provided by this invention firstly calculates the safe braking distance by combining a dynamic braking distance model with the real-time operating speed and real-time load of the vehicle, breaking through the limitations of the fixed distance threshold of traditional anti-collision systems. This precisely matches the large inertia braking characteristics of a large-tonnage metallurgical casting crane fully loaded with molten steel ladles, avoiding both frequent false stops caused by overly strict thresholds and the risk of insufficient braking due to insufficient thresholds. Secondly, relying on a real-time data interaction mechanism between multiple vehicles in the span, the operating parameters and position information of all vehicles in the entire span can be accurately obtained, coordinating with human-machine interface... The virtual markers for vehicles obscured by adjacent vehicles in the interactive interface completely eliminate visual blind spots in traditional scheduling modes, effectively avoiding sudden collision hazards. Simultaneously, anti-sway constraint rules specifically for molten metal hoisting are embedded in the control logic, limiting the rate of speed change to prevent excessive swaying of the molten steel ladle caused by sudden acceleration or deceleration, thus meeting the safety specifications for metallurgical cranes from a process perspective. Furthermore, by predicting oncoming collisions and using a preset creeping speed passing mechanism, the sudden stop and start operations in traditional passing scenarios are replaced, ensuring absolute safety during passing while reducing equipment start-up and shutdown losses and operational interruptions. This invention achieves intelligent collaborative scheduling of multiple vehicles across a span, significantly improving operational efficiency in high-load operation scenarios such as the feeding span and molten steel span while strengthening the safety defenses for molten metal hoisting, fully adapting to the harsh environment and stringent safety requirements of metallurgical casting scenarios. Attached Figure Description

[0015] Figure 1 A flowchart of a multi-vehicle cooperative anti-collision method for a bridge crane span, according to an embodiment of the present invention, is provided. Figure 2 A schematic diagram of a multi-vehicle cooperative anti-collision system for a bridge crane span, according to an embodiment of the present invention; Figure 3 This is a schematic diagram of a touch display screen according to an embodiment of the present invention.

[0016] The reference numerals in the attached figures are as follows: 1. Radar positioning module; 2. Data processing module; 3. Hierarchical control module; 4. Cooperative communication module; 5. Human-machine interaction module; 6. Weight sensor; 7. Vehicle; 8. Driver's cab; 51. Touch screen display; 511. Spanning plan view area; 512. Real-time operating parameter display area for this vehicle; 513. Alarm information display area. Detailed Implementation

[0017] In this invention, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0018] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0019] This embodiment provides a method for multi-vehicle collaborative collision avoidance in the span of a bridge crane. Figure 1 This is a flowchart of a multi-vehicle collaborative anti-collision method for a bridge crane span provided in this embodiment.

[0020] like Figure 1 As shown, the multi-vehicle cooperative collision avoidance method for bridge cranes in this embodiment includes the following steps: S1. Each vehicle in the span independently acquires its real-time operating speed, real-time load, and real-time radar positioning to obtain its real-time operating parameters and real-time position. S2. Each vehicle 7 calculates its safe braking distance based on a preset dynamic braking distance model, according to its real-time operating speed and real-time load. S3. Each vehicle 7 obtains the real-time operating parameters and real-time position of other vehicles 7 in the span through the cooperative communication module 4, so as to obtain the real-time distance between the vehicle and other vehicles 7; S4. Each vehicle 7 determines its graded safety protection threshold based on its safe braking distance and the real-time distance between itself and other vehicles 7. S5. Based on the comparison results of the real-time distance between this vehicle and other vehicles 7 and the graded safety protection threshold, the corresponding graded control strategy is executed, and anti-sway constraint logic is introduced in the control process to limit the rate of change of speed to meet the anti-sway requirements of molten metal hoisting. S6. Each traveling crane 7, based on the conflict prediction result of oncoming vehicles, controls the traveling crane to complete the passing at a preset creeping speed; S7. Based on the multi-vehicle data sharing mechanism, the real-time positions of all vehicles 7 in the span are displayed synchronously on the human-machine interface of each vehicle's cab 8, as well as the virtual identifiers of vehicles 7 that are obscured by neighboring vehicles.

[0021] The multi-vehicle collaborative anti-collision method for bridge cranes in this embodiment firstly calculates the safe braking distance by combining a dynamic braking distance model with the real-time operating speed and load of each vehicle. This overcomes the limitations of fixed distance thresholds in traditional anti-collision systems and accurately matches the large inertia braking characteristics of a heavy-duty metallurgical casting crane fully loaded with molten steel ladles. This avoids frequent false stops caused by overly strict thresholds and eliminates the risk of insufficient braking due to inadequate thresholds. Secondly, relying on the real-time data interaction mechanism between the multi-vehicles in the span, the operating parameters and position information of all the cranes 7 in the entire span can be accurately obtained, in conjunction with the human-machine interface. The virtual identification of vehicles obscured by adjacent vehicles completely eliminates blind spots in traditional scheduling modes, effectively avoiding sudden collision hazards. Simultaneously, anti-sway constraint rules specifically for molten metal hoisting are embedded in the control logic, limiting the rate of speed change to prevent excessive swaying of the molten steel ladle caused by sudden acceleration or deceleration, thus meeting the safety specifications for metallurgical cranes from a process perspective. Furthermore, this embodiment replaces the emergency stop / start operation in traditional meeting scenarios with a pre-judgment of oncoming collisions and a preset creeping speed staggering mechanism, ensuring absolute safety during meeting while reducing equipment start-up and shutdown losses and operational interruptions. This embodiment achieves intelligent collaborative scheduling of multiple vehicles across a span, significantly improving operational efficiency in high-load operation scenarios such as the feeding and molten steel sections while strengthening the safety defenses for molten metal hoisting, fully adapting to the harsh environment and stringent safety requirements of metallurgical casting scenarios.

[0022] Among them, see Figure 1 The formula for calculating the dynamic braking distance model is: (1) in, S safe For safe braking distance, v This is the real-time operating speed of the vehicle. t resp This is the inherent response time of the system. μ The equivalent friction coefficient is based on real-time load correction. g It is the acceleration due to gravity; Real-time load is collected in real time by the vehicle's on-board weight sensor; The graded safety protection threshold is dynamically adjusted according to the safe braking distance.

[0023] This embodiment's dynamic braking distance model quantifies and adaptively adjusts the safety protection threshold in real time by incorporating the system's inherent response time, real-time operating speed, and load-corrected friction coefficient. Compared to traditional fixed threshold settings, this embodiment, through precise formulaic calculations, fully considers the nonlinear changes in the equivalent friction coefficient of large-tonnage casting cranes under different load conditions. This ensures that the calculated safe braking distance accurately reflects the physical braking capacity under the current operating conditions, resolving the issues of insufficient safety redundancy due to excessively large thresholds under light loads and frequent false stops caused by excessively small thresholds under heavy loads. Furthermore, the tiered safety protection thresholds in this embodiment dynamically adjust with the safe braking distance, ensuring that the triggering timing of warning, deceleration, and emergency stop commands precisely matches the actual braking requirements. This avoids collision risks caused by insufficient braking distance and minimizes unnecessary intervention. This embodiment significantly improves the efficiency of inter-span operations while ensuring absolute safety during molten metal hoisting.

[0024] Among them, see Figure 1 The hierarchical control strategy includes: When the real-time distance between this vehicle and other vehicles 7 is greater than the first preset multiple of the safe braking distance, a first-level warning is triggered, and the sound and light alarm in the cab 8 is controlled to sound intermittently, and a yellow warning sign is displayed on the human-machine interface. When the real-time distance is less than or equal to the first preset multiple of the safe braking distance and greater than the second preset multiple of the safe braking distance, the second-level deceleration is triggered, forcibly limiting the vehicle's operating speed to the preset low gear and prohibiting the driver from manually accelerating; When the real-time distance is less than or equal to the second preset multiple of the safe braking distance, a level three emergency stop is triggered, the inverter of this vehicle is disconnected and the brakes of this vehicle are locked. Among them, the first preset multiple is greater than 1, and the second preset multiple is equal to 1; The anti-sway constraint logic is as follows: when performing deceleration control, the acceleration is limited to a preset threshold to ensure that the sway angle of the molten metal ladle does not exceed ±2°.

[0025] This embodiment achieves dual protection of safety and process stability by constructing a hierarchical progressive control strategy of first-level early warning, second-level deceleration, and third-level emergency stop, combined with anti-sway constraint logic.

[0026] This embodiment divides the safe braking distance into intervals by setting a first preset multiple > 1 and a second preset multiple = 1, forming a buffer zone with sufficient safety redundancy. This allows the system to intervene before a collision occurs, completely changing the passive situation of traditional anti-collision devices that rely on critical alarms.

[0027] Furthermore, this embodiment deprives the driver of the manual acceleration authority during the secondary deceleration phase, forcibly limiting the speed to a safe level and effectively eliminating the risk of human error. Moreover, the deceleration control incorporates anti-sway constraint logic to limit jerk, strictly limiting the swing angle of the molten metal ladle within a safe range of ±2° by controlling the smoothness of speed changes. This perfectly meets the stability requirements for transporting liquid metal, fundamentally avoiding the significant safety hazard of molten steel splashing due to sudden deceleration and improving the inherent safety level of molten metal transport.

[0028] Among them, see Figure 1 Step S6 includes: S61. Calculate in real time the overlapping area of ​​the running trajectories of this vehicle and the oncoming vehicle 7 and the estimated meeting time; S62. If it is determined that the two vehicles cannot stop at a safe distance, then decelerate to the creeping speed; the creeping speed of each traveling vehicle 7 is determined dynamically based on the anti-sway requirements of the molten metal ladle and the load of each traveling vehicle, and the value range is 5% to 10% of the rated operating speed; S63. After the two trains 7 have completed passing and the distance between them is greater than the safety threshold, the speed limit is lifted and normal operation control is restored.

[0029] This embodiment calculates the overlapping area of ​​the two vehicles' trajectories and the estimated meeting time in real time, enabling precise decision-making before the critical point, thus avoiding the risk of violent swaying of the molten steel ladle caused by emergency braking. This embodiment dynamically limits the creeping speed to 5%~10% of the rated speed and adaptively matches it according to the real-time load and anti-sway requirements, retaining the necessary fine-tuning capability while ensuring the absolute stability of the molten metal surface using extremely low movement speed. This embodiment automatically removes the speed limit after the passing is completed and the distance meets the standard, eliminating the drawbacks of cumbersome reset of traditional safety systems and ensuring the continuity and smoothness of cross-regional logistics.

[0030] This embodiment effectively overcomes the traditional safety paradox of oncoming trains stopping immediately upon encountering danger in narrow spans by introducing an adaptive creeping passing mechanism based on conflict prediction, thereby improving the passage efficiency of the feeding span and the molten steel span under high-frequency production.

[0031] Among them, see Figure 1 The steps for generating the virtual identifier for vehicle 7, which is obscured by a neighboring vehicle, include: Each vehicle 7 obtains the real-time operating parameters of neighboring vehicles and obstacle information within the perception range of neighboring vehicles through the cooperative communication module 4; If it is determined that there is a vehicle 7 behind the adjacent vehicle that is not directly detected by the radar of this vehicle, then the vehicle 7 that is not directly detected by the radar of this vehicle is marked with a red dashed box at the corresponding position on the human-machine interface of the driver's cab 8, and the real-time distance between it and this vehicle is displayed simultaneously.

[0032] This embodiment accurately identifies vehicles behind neighboring vehicles that cannot be directly detected by the vehicle's radar by acquiring the real-time operating parameters of neighboring vehicles and obstacle information within the neighboring vehicles' perception range. This embodiment differentiates these hidden obstacles by marking them with red dotted boxes on the human-machine interface and simultaneously displays their real-time distance from the vehicle, allowing the driver to intuitively and comprehensively grasp the cross-sectional traffic situation in all dimensions, thus eliminating the cause of sudden collisions at the source.

[0033] This embodiment avoids the information delays and misjudgment risks caused by drivers relying on verbal coordination in the traditional model, and eliminates the need for frequent stops for verification to avoid blind spot risks. It ensures the continuity and efficiency of cross-operation and effectively overcomes the industry pain point that traditional collision avoidance systems can only detect obstacles within the direct radar range of the vehicle itself and hidden vehicles behind neighboring vehicles, forming dispatch blind spots.

[0034] This embodiment also provides a multi-vehicle collaborative anti-collision system for bridge cranes, used to implement the multi-vehicle collaborative anti-collision method for bridge cranes in the above embodiment. Figure 2 This is a schematic diagram of a multi-vehicle cooperative anti-collision system for a bridge crane span provided in this embodiment.

[0035] like Figure 2 As shown, the multi-vehicle cooperative anti-collision system for bridge cranes in this embodiment includes: Radar positioning module 1 is used to collect real-time position data of each crane 7 in the span; radar positioning module 1 includes a multipath suppression algorithm to filter out false positioning signals generated by reflections from the steel structure of the factory building; Data processing module 2 is installed on the vehicle control terminal of each vehicle 7 in the span; data processing module 2 is communicatively connected to radar positioning module 1; data processing module 2 is used to run dynamic braking distance model, calculate safe braking distance based on the real-time running speed and real-time load of the vehicle, and determine graded safety protection thresholds; The hierarchical control module 3 is installed on the on-board control terminal of each crane 7 in the span; the hierarchical control module 3 is electrically connected to the data processing module 2 on the crane 7; the hierarchical control module 3 is used to output control signals to the frequency converter and brake of the crane based on the comparison result of the real-time distance between the crane and other cranes and the hierarchical safety protection threshold, and to execute the hierarchical safety protection action; the hierarchical control module 3 includes anti-sway constraint logic to limit the rate of speed change; The collaborative communication module 4 is used to realize real-time data interaction between the data processing modules 2 of each train 7 in the cross-section, and data interaction between the data processing modules 2 of each train 7 in the cross-section and the ground dispatch system. The human-machine interaction module 5 is installed in the cab of each vehicle 7; the human-machine interaction module 5 is electrically connected to the data processing module 2 of each vehicle 7 in the span; the human-machine interaction module 5 is used to display the real-time position of all vehicles 7 in the span, as well as the virtual markers of hidden obstacles obscured by adjacent vehicles.

[0036] The bridge crane multi-vehicle collaborative anti-collision system of this embodiment includes a radar positioning module 1, a data processing module 2, a hierarchical control module 3, a collaborative communication module 4, and a human-machine interaction module 5. The radar positioning module 1's built-in multipath suppression algorithm effectively filters out false signals reflected from the steel structure of the factory building, solving the problem of accuracy drift in traditional positioning technology in environments with dense steel beams, and ensuring the accuracy of position data acquisition. The data processing module 2 calculates safety thresholds in real time based on a dynamic braking distance model, solidifying physical braking laws into control logic, thus avoiding inadequate protection caused by fixed thresholds from the source. The hierarchical control module 3 integrates anti-sway constraint logic, limiting the rate of speed change when outputting control commands, ensuring the stability of molten metal ladle hoisting from the execution end, and complying with the safety regulations for special equipment handling of liquid metal. The collaborative communication module 4 realizes real-time data interaction between the multi-vehicle system and the ground dispatching system, breaking down the information silos of individual cranes and providing a hardware foundation for multi-vehicle collaborative dispatching. The human-machine interaction module 5 synchronously displays the positions of all vehicles across the span and virtual markers of concealed vehicles through a visual interface, eliminating blind spots for the driver.

[0037] This embodiment achieves closed-loop protection from environmental perception, data processing, control execution to human-machine interaction through the coordinated operation of various modules. This ensures that the system can operate stably for a long time under extreme conditions such as dust, high temperature, and vibration, providing a highly reliable inherent safety guarantee for the hoisting of molten metal in the feeding span and molten steel span, and improving the efficiency of multi-vehicle collaborative operation.

[0038] Among them, see Figure 2 Radar positioning module 1 includes: multiple millimeter-wave radar base stations and radar reflection tags; Multiple millimeter-wave radar base stations are fixedly installed at both ends and the middle turning point of the span, and adopt the frequency-modulated continuous wave ranging system. The radar reflective tag includes a corner reflector array, which is fixedly installed in the middle of the main beam of each vehicle 7, avoiding the high-temperature radiation area; The multipath suppression algorithm includes: pre-storing a priori map of the steel structure of the factory building, comparing the point cloud data detected by radar with the priori map, filtering out fixed false reflection points that match the coordinates of the steel structure of the factory building, and retaining only the moving point cloud data corresponding to the radar reflection labels.

[0039] It should be noted that each vehicle 7 in this embodiment is also equipped with vehicle radar, which is used to directly detect vehicles and obstacles around the vehicle.

[0040] This embodiment employs a millimeter-wave radar base station with a frequency-modulated continuous wave ranging system, deployed at both ends and the intermediate turning point of the span. This achieves full-span coverage without blind spots and overcomes the shortcomings of traditional laser ranging, such as susceptibility to mirror contamination and beam alignment misalignment, thanks to the inherent characteristics of millimeter waves in penetrating dust and resisting ambient light interference. It is perfectly suited to the harsh working conditions of high dust and strong radiation in steelmaking spans. Furthermore, this embodiment uses a corner reflector array as radar reflection tags, fixed in the middle of the main beam of the crane to avoid high-temperature radiation areas. The corner reflectors have a high reflective cross-sectional area, maintaining signal transmission stability under high temperature and vibration environments. The optimized installation location avoids the heat of molten steel. Radiation-induced tag aging and failure significantly reduces the frequency of on-site maintenance. In addition, the multipath suppression algorithm in this embodiment compares the radar-detected point cloud data with the map coordinates one by one by pre-stored prior maps of the steel structure of the factory. It can accurately filter out false reflection signals generated by fixed structures such as steel beams and columns, and retain only the moving point cloud data of the corresponding corner reflector array. This completely solves the problem of positioning drift and false target misjudgment caused by radar multipath effect in dense steel structure scenarios. It provides high-precision position data support for subsequent dynamic braking distance calculation and hierarchical control strategy execution, and ensures the long-term stable operation of the anti-collision system under extreme conditions.

[0041] Among them, see Figure 2 The system in this embodiment also includes a weight sensor 6; the weight sensor 6 is mounted on the vehicle 7 and electrically connected to the vehicle's data processing module 2; the weight sensor 6 is used to collect the vehicle's lifting load in real time and transmit it to the data processing module 2 to correct the equivalent friction coefficient in the dynamic braking distance model. The collaborative communication module 4 includes: multiple wireless access units arranged at intervals along the columns of the factory building; multiple wireless access units forming a wireless mesh network (MESH); the wireless mesh network communicating with the data processing module 2 of each crane and the ground dispatch system; the data transmission delay of the wireless mesh network is no more than 50ms.

[0042] This embodiment adds a weight sensor 6 electrically connected to the data processing module 2, which can collect the load of the crane 7 in real time and feed it back to the dynamic braking distance model, so as to realize the online accurate correction of the equivalent friction coefficient, fully adapt to the actual braking performance under different working conditions such as no load, half load, and full load, and solve the problems of poor threshold adaptability, insufficient braking distance under heavy load, and frequent false stops under light load caused by the traditional anti-collision scheme ignoring the load variable.

[0043] Meanwhile, the collaborative communication module 4 in this embodiment constructs a wireless mesh network (MESH) using wireless access units spaced along the columns of the steel plant. This effectively overcomes the persistent communication problems caused by the dense steel components and severe signal obstruction in the steelmaking span, ensuring stable network coverage across the entire span at all times. Data transmission latency is strictly controlled to within 50ms, matching the control cycle at the maximum operating speed of the trolley (100m / min), ensuring real-time synchronization of position data and obstacle information for each trolley (7). This provides low-latency communication support for the reliable operation of core functions such as graded collision avoidance control, oncoming vehicle prediction, and visualization of hidden obstacles. Furthermore, the interconnection between the MESH network and the ground dispatch system facilitates dispatchers' overall understanding of the span's operational status, providing multi-dimensional physical protection for the safety of the entire molten metal hoisting process.

[0044] Among them, see Figure 2 The hierarchical control module 3 includes: The frequency converter control unit is electrically connected to the vehicle's data processing module 2 and the vehicle's frequency converter. It is used to output frequency adjustment signals according to the hierarchical control strategy to limit the vehicle's operating speed. The brake control unit is electrically connected to the vehicle's data processing module 2 and the vehicle's hydraulic push rod brake, and is used to output brake control signals according to the hierarchical control strategy. The audible and visual alarm unit is installed in the driver's cab 8 of this vehicle and is electrically connected to the data processing module 2 of this vehicle. It is used to trigger corresponding warning sounds and lights according to the hierarchical control strategy.

[0045] The hierarchical control module 3 in this embodiment includes a frequency converter control unit, a brake control unit, and an audible and visual alarm unit. The frequency converter control unit is linked with the data processing module 2 and the vehicle's frequency converter. It can precisely output frequency adjustment signals according to the hierarchical control strategy, flexibly limiting the operating speed and depriving the driver of manual acceleration authority when triggering secondary deceleration. This avoids the risk of speed loss due to human error and, through smooth speed adjustment, meets the anti-sway constraint requirements of the molten metal ladle, reducing the risk of molten steel splashing. The brake control unit connects to the vehicle's hydraulic push rod brake and can instantly output a brake control signal when the real-time distance reaches the emergency stop threshold. Combined with the calculation results of the dynamic braking distance model, it ensures that the braking distance fully covers the safety redundancy, preventing collisions caused by insufficient braking. The audible and visual alarm unit is installed in the cab 8 and can trigger differentiated sound and light prompts according to different warning levels. This allows the driver to quickly identify the risk level and respond without frequently checking the human-machine interface in high-dust, limited-visibility, and high-intensity steelmaking conditions, further reducing the probability of human error.

[0046] Figure 3 This is a schematic diagram of a touch display screen 51 provided in this embodiment. Wherein, as... Figure 3As shown, the human-computer interaction module 5 includes a touch screen display 51, and the touch screen display 51 includes: The cross-section top-down planar schematic diagram area 511 includes the green solid icon of this vehicle, the yellow solid icons of other adjacent vehicles, the red dashed frame icon of the vehicle 7 that is obscured by the adjacent vehicles, and the dynamic safety radius circle centered on this vehicle. The vehicle's real-time operating parameters display area 512 includes real-time speed, real-time load, and real-time distance to the nearest vehicle. Alarm information display area 513 is used to display the current warning level of this vehicle and the corresponding handling prompts.

[0047] The human-machine interaction module 5 in this embodiment includes a partitioned touch screen 51. The cross-span top-down planar schematic diagram area 511 uses solid green icons to mark the vehicle itself, solid yellow icons to distinguish neighboring vehicles, and red dashed boxes to indicate hidden obstacles behind neighboring vehicles. Combined with a dynamic safety radius circle centered on the vehicle itself, this allows the driver to fully grasp the distribution of vehicles across the entire cross-span, their own safety boundaries, and risk points in traditional blind spots within seconds without having to look up to observe the cross-span view, eliminating scheduling blind spots under high-density multi-vehicle operations. The real-time operating parameter display area 512 of the vehicle displays real-time speed, real-time load, and real-time distance to the nearest vehicle, eliminating the need for the driver to manually switch interfaces for querying. This allows the driver to intuitively verify the rationality of the safety threshold under the current working conditions. The alarm information prompt area 513 not only displays the current warning level but also provides corresponding handling prompts. For example, it prompts "Do not manually accelerate" during the second-level deceleration stage and "Brake will be engaged" during the third-level emergency stop stage, providing the driver with clear decision-making guidance and further reducing the risk of human error.

[0048] The partitioned design of the touch display screen 51 in this embodiment significantly improves the driver's risk response speed and operational accuracy, providing a user-friendly and reliable human-machine interaction support for the entire process of molten metal hoisting safety.

[0049] It will be readily understood by those skilled in the art that the aforementioned advantageous methods can be freely combined and superimposed without conflict.

[0050] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention. The above are merely preferred embodiments of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the protection scope of the present invention.

Claims

1. A method for multi-vehicle cooperative collision avoidance in a bridge crane span, characterized in that, The method includes the following steps: Each vehicle in the span independently acquires its real-time operating speed, real-time load, and real-time radar positioning to obtain its real-time operating parameters and real-time position. Each vehicle is based on a preset dynamic braking distance model, which calculates the vehicle's safe braking distance according to its real-time operating speed and real-time load. Each vehicle obtains the real-time operating parameters and real-time position of other vehicles in the same section through the cooperative communication module, so as to obtain the real-time distance between the vehicle and other vehicles. Each vehicle determines its graded safety protection threshold based on its safe braking distance and the real-time distance between itself and other vehicles. Based on the comparison between the real-time distance between this vehicle and other vehicles and the graded safety protection threshold, the corresponding graded control strategy is executed, and anti-sway constraint logic is introduced during the control process to limit the rate of speed change to meet the anti-sway requirements for molten metal hoisting. Each train controls itself to pass other trains at a preset creeping speed based on the conflict prediction results of oncoming trains; Based on the multi-vehicle data sharing mechanism, the real-time location of all vehicles in the span is displayed synchronously on the human-machine interface in the cab of each vehicle, as well as the virtual markers of vehicles obscured by neighboring vehicles.

2. The method for multi-vehicle cooperative collision avoidance between bridge cranes according to claim 1, characterized in that, The calculation formula for the dynamic braking distance model is as follows: （1） in, S safe For safe braking distance, v This is the real-time operating speed of the vehicle. t resp This is the inherent response time of the system. μ The equivalent friction coefficient is based on real-time load correction. g It is the acceleration due to gravity; The real-time load is collected in real time by the vehicle-mounted weight sensor; The graded safety protection threshold is dynamically adjusted according to the safe braking distance.

3. The method for multi-vehicle cooperative collision avoidance between bridge cranes according to claim 1, characterized in that, The hierarchical control strategy includes: When the real-time distance between this vehicle and other vehicles is greater than the first preset multiple of the safe braking distance, a level one warning is triggered, the audible and visual alarm in the driver's cab sounds intermittently, and the human-machine interface displays a yellow warning sign; When the real-time distance is less than or equal to the first preset multiple of the safe braking distance and greater than the second preset multiple of the safe braking distance, the second-level deceleration is triggered, forcibly limiting the vehicle's operating speed to the preset low gear and prohibiting the driver from manually accelerating; When the real-time distance is less than or equal to the second preset multiple of the safe braking distance, a level three emergency stop is triggered, the inverter of this vehicle is disconnected and the brakes of this vehicle are locked. Wherein, the first preset multiple is greater than 1, and the second preset multiple is equal to 1; The anti-sway constraint logic is as follows: when performing deceleration control, the acceleration is limited to a preset threshold to ensure that the sway angle of the molten metal ladle does not exceed ±2°.

4. The method for multi-vehicle cooperative collision avoidance between bridge cranes according to claim 1, characterized in that, Each traveling crane, based on the conflict prediction result of oncoming vehicles, controls itself to complete the passing maneuver at a preset creeping speed, including: Calculate in real time the overlapping area of ​​the vehicle's trajectory with that of oncoming vehicles and the estimated meeting time; If it is determined that the two vehicles cannot stop at a safe distance, the speed is reduced to the creeping speed; the creeping speed of each vehicle is determined dynamically based on the anti-sway requirements of the molten metal ladle and the load of each vehicle, and the value range is 5% to 10% of the rated operating speed; After the two vehicles have passed each other and the distance between them is greater than the safety threshold, the speed limit is lifted and normal operation control is restored.

5. The method for multi-vehicle cooperative collision avoidance between bridge cranes according to claim 1, characterized in that, The steps for generating the virtual identifier for a vehicle obscured by a neighboring vehicle include: Each vehicle obtains real-time operating parameters of neighboring vehicles and obstacle information within the neighboring vehicles' perception range through the collaborative communication module; If it is determined that there is a vehicle behind the adjacent vehicle that is not directly detected by the vehicle's radar, the vehicle that is not directly detected by the vehicle's radar will be marked with a red dashed box at the corresponding position on the human-machine interface in the driver's cab, and the real-time distance between the vehicle and the vehicle will be displayed simultaneously.

6. A multi-vehicle cooperative anti-collision system for bridge cranes, characterized in that, A system for implementing the multi-vehicle cooperative anti-collision method for bridge cranes as described in any one of claims 1 to 5; the system comprises: The radar positioning module is used to collect real-time position data of each vehicle in the span; the radar positioning module includes a multipath suppression algorithm to filter out false positioning signals generated by reflections from the steel structure of the factory building; A data processing module is installed on the vehicle control terminal of each vehicle in the span; the data processing module is communicatively connected to the radar positioning module; the data processing module is used to run the dynamic braking distance model, calculate the safe braking distance based on the real-time operating speed and real-time load of the vehicle, and determine the graded safety protection threshold. A hierarchical control module is installed on the on-board control terminal of each traveling vehicle in the span; the hierarchical control module is electrically connected to the data processing module on the traveling vehicle; the hierarchical control module is used to output control signals to the frequency converter and brake of the traveling vehicle based on the comparison result of the real-time distance between the traveling vehicle and other traveling vehicles and the hierarchical safety protection threshold, so as to execute the hierarchical safety protection action; the hierarchical control module includes anti-sway constraint logic to limit the rate of speed change; The collaborative communication module is used to realize real-time data interaction between the data processing modules of each train across the cross-section, and data interaction between the data processing modules of each train across the cross-section and the ground dispatch system. A human-machine interaction module is installed in the driver's cab of each vehicle; the human-machine interaction module is electrically connected to the data processing module of each vehicle in the span; the human-machine interaction module is used to display the real-time position of all vehicles in the span, as well as virtual markers of hidden obstacles obscured by adjacent vehicles.

7. The multi-vehicle cooperative anti-collision system for bridge cranes according to claim 6, characterized in that, The radar positioning module includes: multiple millimeter-wave radar base stations and radar reflection tags; Multiple millimeter-wave radar base stations are fixedly installed at both ends and the middle turning point of the span, and adopt a frequency-modulated continuous wave ranging system. The radar reflective tag includes a corner reflector array, which is fixedly installed in the middle of the main beam of each vehicle to avoid the high-temperature radiation area; The multipath suppression algorithm includes: pre-storing a priori map of the steel structure of the factory building, comparing the point cloud data detected by radar with the priori map, filtering out fixed false reflection points that match the coordinates of the steel structure of the factory building, and retaining only the moving point cloud data corresponding to the radar reflection labels.

8. The multi-vehicle cooperative anti-collision system for bridge cranes according to claim 6, characterized in that, It also includes a weight sensor; the weight sensor is installed on the vehicle and electrically connected to the data processing module of the vehicle; the weight sensor is used to collect the lifting load of the vehicle in real time and transmit it to the data processing module to correct the equivalent friction coefficient in the dynamic braking distance model; The collaborative communication module includes: multiple wireless access units arranged at intervals along the columns of the factory building; Multiple wireless access units form a wireless mesh network (MESH); the wireless mesh network is communicatively connected to the data processing module of each vehicle and the ground dispatch system; the data transmission delay of the wireless mesh network is no greater than 50ms.

9. The multi-vehicle cooperative anti-collision system for bridge cranes according to claim 6, characterized in that, The hierarchical control module includes: The frequency converter control unit is electrically connected to the data processing module and the frequency converter of the vehicle, and is used to output frequency adjustment signals according to the hierarchical control strategy to limit the running speed of the vehicle. The brake control unit is electrically connected to the data processing module and the hydraulic push rod brake of the vehicle, and is used to output the brake control signal according to the hierarchical control strategy. The audible and visual alarm unit is installed in the driver's cab of the vehicle and is electrically connected to the data processing module of the vehicle. It is used to trigger corresponding warning sounds and lights according to the hierarchical control strategy.

10. The multi-vehicle cooperative anti-collision system for bridge cranes according to claim 6, characterized in that, The human-computer interaction module includes a touch screen display, which includes: The cross-section top-down planar schematic area includes the green solid icon of this vehicle, the yellow solid icons of other adjacent vehicles, the red dashed box icons of vehicles whose driving is obscured by adjacent vehicles, and the dynamic safety radius circle centered on this vehicle; The vehicle's real-time operating parameters display area includes real-time speed, real-time load, and real-time distance to the nearest vehicle. The alarm information display area is used to show the current warning level of this vehicle and the corresponding handling prompts.

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