Safety control method and system for bridge crane

Abstract

The invention relates to the technical field of bridge crane work monitoring, in particular to a safety control method and system for a bridge crane, and the method specifically comprises the following steps: extracting real-time hoisting cargo state data of the bridge crane; importing the real-time hoisting cargo state data into a dynamic falling area evaluation strategy to obtain a dynamic falling area, and projecting the dynamic falling area to the ground; predicting a moving track of the violation person through a track state prediction model; fusing and evaluating the safety work threat coefficient of the bridge crane and adopting a safety control strategy. The problems that in the prior art, for a warning mode of drawing pedestrian path marking lines on the ground of an operation area, the situation that the working position of a bridge crane is not fixed, the marking lines cannot move dynamically, and the warning effect is not timely are not considered.

Description

Technical Field

[0001] The invention relates to the technical field of bridge crane operation monitoring, and relates to a bridge crane safety control method and system. Background Art

[0002] A bridge crane is a type of lifting equipment that is horizontally mounted above workshops, warehouses, and material yards to lift materials. The bridge of a bridge crane runs longitudinally along the tracks laid on the elevated platforms on both sides, and the lifting trolley runs transversely along the tracks laid on the bridge, forming a rectangular working range. This allows full use of the space under the bridge to lift materials, so that the lifted heavy objects can be lifted vertically or moved horizontally in space without being hindered by ground equipment. This type of crane is widely used in indoor and outdoor warehouses, factories, docks, and open-air storage yards. Since the objects lifted by bridge cranes during operation are heavy, ranging from hundreds of kilograms to tens of tons, accidental drops or collisions can lead to very serious consequences. Therefore, safety warnings and interlocks during the operation of bridge cranes are particularly important. In the prior art, monitoring is performed only by installing work alarms on bridge cranes and using manual supervision. These methods are not only easily affected by production noise in the operating area, but also make the operating safety entirely dependent on the real-time status of the caretaker, which results in large errors. In addition, the prior art also has a warning method of drawing pedestrian walkway markings on the ground in the operating area, which does not take into account the fact that the working position of the bridge crane is not fixed, the markings cannot be moved dynamically, and the warning effect is not timely. Summary of the invention

[0003] The technical problem to be solved by the present invention is that in the prior art, for the warning method of drawing pedestrian passage markings on the ground in the working area, it does not take into account the problem that the working position of the bridge crane is not fixed, the markings cannot be moved dynamically, and the warning effect is not timely. A safety control method and system for a bridge crane are proposed.

[0004] In order to achieve the above object, a technical solution for a bridge crane safety control method of the present invention comprises the following steps: S1: Start the bridge crane control background and initialize the boundary data of the operation area, and simultaneously extract the real-time lifting cargo status data of the bridge crane; S2: importing the real-time hoisting cargo status data into the dynamic falling area assessment strategy, obtaining the dynamic falling area, and projecting the dynamic falling area onto the ground; S3: Use high-definition cameras to capture the location data of violators and predict the movement trajectory of violators through trajectory state prediction models; S4: Based on S2-S3, integrate and evaluate the safety work threat factor of the bridge crane; S5: Adopt safety control strategies for bridge cranes based on the safety work threat factor.

[0005] Specifically, S1 includes the following specific steps: S11: Open the control software of the bridge crane, and perform a software self-check before each crane performs a work task, and perform a system self-check to ensure that the network connection and data transmission of each sensor, camera and execution device in the control software are normal; S12: Synchronously extracting real-time cargo hoisting status data of the bridge crane, wherein the real-time cargo hoisting status data includes: cargo hoisting weight data m of the bridge crane, hoisting height data h of the hoisting cargo, and hoisting speed data v of the bridge crane.

[0006] Specifically, in S2, the dynamic fall area assessment strategy is as follows: ; in, is the area of ​​the dynamic falling zone; , r is the radius of the falling area; It is the initial ground contact area of ​​the lifted cargo; Indicates the first horizontal scatter distance caused by the lifting speed; , t is the estimated falling time of the hoisted cargo, , g is the acceleration due to gravity; It indicates the second horizontal scattering distance caused by the acceleration of the hanging cargo falling; ; are respectively the proportional coefficients of the first horizontal scattering distance and the second horizontal scattering distance; the dynamic falling area is a circular area.

[0007] Specifically, S3 includes the following specific steps: S31: According to the dynamic falling area projected on the ground, a preliminary warning area and a trajectory prediction area are added in sequence around the dynamic falling area, and a high-definition camera is used to capture the location data and status data of the violators in the trajectory prediction area, wherein the preliminary warning area and the trajectory prediction area are two circular areas with a circle width of 30m, and the preliminary warning area, the trajectory prediction area and the dynamic falling area constitute concentric circle areas, wherein the concentric circle areas are the dynamic falling area, the preliminary warning area and the trajectory prediction area from the inside to the outside.

[0008] Specifically, S3 also includes the following specific steps: S32: Taking the bridge center of the bridge crane as the coordinate origin and the lateral running direction of the crane trolley on the track as the y-axis, a plane coordinate system is established, and the plane coordinate system is projected to the ground in equal proportion, wherein the position data of the violator in the trajectory prediction area includes: , are respectively the horizontal and vertical coordinates of the illegal person in the plane coordinate system projected on the ground; The status data of the offender in the trajectory prediction area includes: ; Respectively represent the moving speed of the offender in the horizontal and vertical directions; k is a subscript, which indicates the kth unit monitoring time step after the violator enters the trajectory prediction area. The duration of the unit monitoring time step is ; S33: A trajectory state prediction model is established to predict the movement trajectory of the violator, wherein the state transfer matrix F of the violator in the trajectory state prediction model is specifically: ; S34: Predict the movement trajectory of the violator according to the state transfer matrix F of the violator. ,in, is the k-th unit monitoring time step, the real-time state matrix of the violator, ; The real-time state matrix of the violator at the k+1th unit monitoring time step is predicted. S35: Extract the predicted real-time state matrix of the violator at the k+1th unit monitoring time step In the figure, the horizontal and vertical coordinates of the plane coordinate system projected on the ground by the violator constitute the predicted position coordinates output by the trajectory state prediction model.

[0009] Specifically, in S4, the fusion assessment of the safety work threat coefficient of the bridge crane specifically includes: ; Where w is the safety working threat factor of the bridge crane; It is the straight-line distance between the predicted position coordinates output by the trajectory state prediction model and the center of the dynamic falling area.

[0010] Specifically, S5 includes the following specific steps: S51: preset the safety working threat threshold W of the bridge crane; S52: Determine the working status of the bridge crane, including: when When the bridge crane is judged to be in general threat mode; when When the bridge crane is judged to be in a major threat mode; S53: Take safety control strategies according to the working status of the bridge crane.

[0011] Specifically, in S53, the safety control strategy includes: when the bridge crane is in a general threat mode, a warning message is sent to the monitoring terminal of the on-site guard, and the working alarm on the bridge crane is turned on; when the bridge crane is in a major threat mode, a stop work control prompt is sent to the crane work control console.

[0012] In addition, the present invention provides a safety control system for a bridge crane, comprising the following modules: Data acquisition module, fall area projection module, movement trajectory prediction module, safety work threat coefficient calculation module and safety control module; The data acquisition module is used to start the bridge crane control background and initialize the boundary data of the operation area, and synchronously extract the real-time lifting cargo status data of the bridge crane; The falling area projection module imports the real-time hoisting cargo status data into the dynamic falling area assessment strategy, obtains the dynamic falling area, and projects the dynamic falling area onto the ground; The movement trajectory prediction module is used to capture the location data of the violator using a high-definition camera and establish a machine learning model to predict the movement trajectory of the violator; The safety work threat coefficient calculation module is used to integrate and evaluate the safety work threat coefficient of the bridge crane; The safety control module adopts a safety control strategy for the bridge crane according to the safety work threat coefficient.

[0013] A storage medium stores instructions, and when a computer reads the instructions, the computer executes the safety control method for a bridge crane.

[0014] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned method for safety control of a bridge crane is implemented.

[0015] Compared with the prior art, the technical effects of the present invention are as follows: 1. The present invention solves the problem that during the lifting operation of a bridge crane, when the lifted cargo is suspended and translated in the air, if there are people passing below, the existing facilities cannot mark the cargo falling area, and cannot timely warn and shut down the equipment; 2. The present invention realizes dynamic marking of the operation area and the core area through the falling area projection module, the moving trajectory prediction module and the safety control module, thereby solving the problem of safety identification; through the moving trajectory prediction module, an early warning is issued for violators approaching the operation area, and through the safety control module, a whistle is sounded for violators approaching the core area, and the bridge crane is controlled to automatically slow down to prevent the occurrence of safety accidents during the lifting process. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them: Figure 1 A schematic diagram of a flow chart of a safety control method for a bridge crane according to the present invention; Figure 2 It is a structural schematic diagram of a safety control system for a bridge crane of the present invention; Figure 3 This is an example diagram of a safety control module for a bridge crane according to the present invention; Reference numerals: 1. Bridge; 2. Safety control module; 3. Movement trajectory prediction module; 4. Falling area projection module; 5. Preliminary warning area; 6. Dynamic falling area; 7. Lifting trolley. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0018] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0020] Embodiment 1: like Figure 1 As shown, a safety control method for a bridge crane according to an embodiment of the present invention is as follows: Figure 1 As shown, the specific steps are as follows: S1: Start the bridge crane control background and initialize the boundary data of the operation area, and simultaneously extract the real-time lifting cargo status data of the bridge crane; S1 includes the following specific steps: S11: Open the control software of the bridge crane, and perform a software self-check before each crane performs a work task, and perform a system self-check to ensure that the network connection and data transmission of each sensor, camera and execution device in the control software are normal; S12: Synchronously extracting real-time cargo hoisting status data of the bridge crane, wherein the real-time cargo hoisting status data includes: cargo hoisting weight data m of the bridge crane, hoisting height data h of the hoisting cargo, and hoisting speed data v of the bridge crane.

[0021] S2: importing the real-time hoisting cargo status data into the dynamic falling area assessment strategy, obtaining the dynamic falling area, and projecting the dynamic falling area onto the ground; In S2, the dynamic fall zone assessment strategy is as follows: ; in, is the area of ​​the dynamic falling zone; , r is the radius of the falling area; It is the initial ground contact area of ​​the lifted cargo; Indicates the first horizontal scatter distance caused by the lifting speed; , t is the estimated falling time of the hoisted cargo, , g is the acceleration due to gravity; It indicates the second horizontal scattering distance caused by the acceleration of the hanging cargo falling; ; are respectively the proportional coefficients of the first horizontal scattering distance and the second horizontal scattering distance; the dynamic falling area is a circular area.

[0022] S3: Use high-definition cameras to capture the location data of violators and predict the movement trajectory of violators through trajectory state prediction models; S3 includes the following specific steps: S31: According to the dynamic falling area projected on the ground, a preliminary warning area and a trajectory prediction area are added in sequence around the dynamic falling area, and a high-definition camera is used to capture the location data and status data of the violators in the trajectory prediction area, wherein the preliminary warning area and the trajectory prediction area are two circular areas with a circle width of 30m, and the preliminary warning area, the trajectory prediction area and the dynamic falling area constitute concentric circle areas, wherein the concentric circle areas are the dynamic falling area, the preliminary warning area and the trajectory prediction area from the inside to the outside.

[0023] S3 also includes the following specific steps: S32: Taking the bridge center of the bridge crane as the coordinate origin and the lateral running direction of the crane trolley on the track as the y-axis, a plane coordinate system is established, and the plane coordinate system is projected to the ground in equal proportion, wherein the position data of the violator in the trajectory prediction area includes: , are respectively the horizontal and vertical coordinates of the illegal person in the plane coordinate system projected on the ground; The status data of the offender in the trajectory prediction area includes: ; Respectively represent the moving speed of the offender in the horizontal and vertical directions; k is a subscript, which indicates the kth unit monitoring time step after the violator enters the trajectory prediction area. The duration of the unit monitoring time step is ; S33: A trajectory state prediction model is established to predict the movement trajectory of the violator, wherein the state transfer matrix F of the violator in the trajectory state prediction model is specifically: ; S34: Predict the movement trajectory of the violator according to the state transfer matrix F of the violator. ,in, is the k-th unit monitoring time step, the real-time state matrix of the violator, ; The real-time state matrix of the violator at the k+1th unit monitoring time step is predicted. S35: Extract the predicted real-time state matrix of the violator at the k+1th unit monitoring time step In the figure, the horizontal and vertical coordinates of the plane coordinate system projected on the ground by the violator constitute the predicted position coordinates output by the trajectory state prediction model.

[0024] S4: Based on S2-S3, integrate and evaluate the safety work threat factor of the bridge crane; In S4, the fusion assessment of the safety working threat factor of the bridge crane specifically includes: ; Where w is the safety working threat factor of the bridge crane; It is the straight-line distance between the predicted position coordinates output by the trajectory state prediction model and the center of the dynamic falling area.

[0025] S5: Adopt safety control strategies for bridge cranes based on the safety work threat factor.

[0026] S5 includes the following specific steps: S51: preset the safety working threat threshold W of the bridge crane; S52: Determine the working status of the bridge crane, including: when When the bridge crane is judged to be in general threat mode; when When the bridge crane is judged to be in a major threat mode; S53: Take safety control strategies according to the working status of the bridge crane.

[0027] In S53, the safety control strategy includes: when the bridge crane is in a general threat mode, a warning message is sent to the monitoring terminal of the on-site guard, and the working alarm on the bridge crane is turned on; when the bridge crane is in a major threat mode, a stop work control prompt is sent to the crane work control console.

[0028] Embodiment 2: like Figure 2 and Figure 3 As shown, a safety control system for a bridge crane according to an embodiment of the present invention includes the following modules: Data acquisition module, fall area projection module, movement trajectory prediction module, safety work threat coefficient calculation module and safety control module; The data acquisition module is used to start the bridge crane control background and initialize the boundary data of the operation area, and synchronously extract the real-time lifting cargo status data of the bridge crane; The falling area projection module imports the real-time hoisting cargo status data into the dynamic falling area assessment strategy, obtains the dynamic falling area, and projects the dynamic falling area onto the ground; The movement trajectory prediction module is used to capture the location data of the violator using a high-definition camera and establish a machine learning model to predict the movement trajectory of the violator; The safety work threat coefficient calculation module is used to integrate and evaluate the safety work threat coefficient of the bridge crane; The safety control module adopts a safety control strategy for the bridge crane according to the safety work threat coefficient.

[0029] Embodiment three: This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned safety control method for a bridge crane by calling a computer program stored in the memory.

[0030] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement a method for safety control of a bridge crane provided in the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input / output interface for data input and output. This embodiment will not be described in detail here.

[0031] Embodiment 4: This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon; When the computer program runs on a computer device, the computer device is caused to execute the above-mentioned method for safety control of a bridge crane.

[0032] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0033] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0034] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0035] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0036] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0037] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0038] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0039] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0040] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0041] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0042] In summary, compared with the prior art, the technical effects of the present invention are as follows: 1. The present invention solves the problem that during the lifting operation of a bridge crane, when the lifted cargo is suspended and translated in the air, if there are people passing below, the existing facilities cannot mark the cargo falling area, and cannot timely warn and shut down the equipment; 2. The present invention realizes dynamic marking of the operation area and the core area through the falling area projection module, the moving trajectory prediction module and the safety control module, thereby solving the problem of safety identification; through the moving trajectory prediction module, an early warning is issued for violators approaching the operation area, and through the safety control module, a whistle is sounded for violators approaching the core area, and the bridge crane is controlled to automatically slow down to prevent the occurrence of safety accidents during the lifting process.

[0043] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A safety control method for a bridge crane, characterized in that: The method comprises the following specific steps: S1: Start the bridge crane control background and initialize the boundary data of the operation area, and simultaneously extract the real-time lifting cargo status data of the bridge crane; S2: importing the real-time hoisting cargo status data into the dynamic falling area assessment strategy, obtaining the dynamic falling area, and projecting the dynamic falling area onto the ground; S3: Use high-definition cameras to capture the location data of violators and predict the movement trajectory of violators through trajectory state prediction models; S4: Based on S2-S3, integrate and evaluate the safety working threat factor of the bridge crane; S5: Adopt safety control strategies for bridge cranes based on the safety work threat factor.

2. A safety control method for a bridge crane according to claim 1, characterized in that: S1 includes the following specific steps: S11: Open the control software of the bridge crane, and perform a software self-check before each crane performs a work task, and perform a system self-check to ensure that the network connection and data transmission of each sensor, camera and execution device in the control software are normal; S12: Synchronously extracting real-time cargo hoisting status data of the bridge crane, wherein the real-time cargo hoisting status data includes: cargo hoisting weight data m of the bridge crane, hoisting height data h of the hoisting cargo, and hoisting speed data v of the bridge crane.

3. A safety control method for a bridge crane according to claim 2, characterized in that: In S2, the dynamic fall zone assessment strategy is as follows: ； in, is the area of ​​the dynamic falling zone; , r is the radius of the falling area; It is the initial ground contact area of ​​the lifted cargo; Indicates the first horizontal scatter distance caused by the lifting speed; , t is the estimated falling time of the hoisted cargo, , g is the acceleration due to gravity; It indicates the second horizontal scattering distance caused by the acceleration of the hanging cargo falling; ; are respectively the proportional coefficients of the first horizontal scattering distance and the second horizontal scattering distance; the dynamic falling area is a circular area.

4. A safety control method for a bridge crane according to claim 3, characterized in that: S3 includes the following specific steps: S31: According to the dynamic falling area projected on the ground, a preliminary warning area and a trajectory prediction area are added in sequence around the dynamic falling area, and a high-definition camera is used to capture the location data and status data of the violators in the trajectory prediction area, wherein the preliminary warning area and the trajectory prediction area are two circular areas with a circle width of 30m, and the preliminary warning area, the trajectory prediction area and the dynamic falling area constitute concentric circle areas, wherein the concentric circle areas are the dynamic falling area, the preliminary warning area and the trajectory prediction area from the inside to the outside.

5. A safety control method for a bridge crane according to claim 4, characterized in that: S3 also includes the following specific steps: S32: Taking the bridge center of the bridge crane as the coordinate origin and the lateral running direction of the crane trolley on the track as the y-axis, a plane coordinate system is established, and the plane coordinate system is projected to the ground in equal proportion, wherein the position data of the violator in the trajectory prediction area includes: , are respectively the horizontal and vertical coordinates of the illegal person in the plane coordinate system projected on the ground; The status data of the offender in the trajectory prediction area includes: ; Respectively represent the moving speed of the offender in the horizontal and vertical directions; k is a subscript, which indicates the kth unit monitoring time step after the violator enters the trajectory prediction area. The duration of the unit monitoring time step is ; S33: A trajectory state prediction model is established to predict the movement trajectory of the violator, wherein the state transfer matrix F of the violator in the trajectory state prediction model is specifically: ； S34: Predict the movement trajectory of the violator according to the state transfer matrix F of the violator. ,in, is the k-th unit monitoring time step, the real-time state matrix of the violator, ; The real-time state matrix of the violator at the k+1th unit monitoring time step is predicted. S35: Extract the predicted real-time state matrix of the violator at the k+1th unit monitoring time step In the figure, the horizontal and vertical coordinates of the plane coordinate system projected on the ground by the violator constitute the predicted position coordinates output by the trajectory state prediction model.

6. A safety control method for a bridge crane according to claim 5, characterized in that: In S4, the fusion assessment of the safety working threat factor of the bridge crane specifically includes: ； Wherein, w is the safety working threat factor of the bridge crane; It is the straight-line distance between the predicted position coordinates output by the trajectory state prediction model and the center of the dynamic falling area.

7. A safety control method for a bridge crane according to claim 6, characterized in that: S5 includes the following specific steps: S51: preset the safety working threat threshold W of the bridge crane; S52: Determine the working status of the bridge crane, including: when When the bridge crane is judged to be in general threat mode; when When the bridge crane is judged to be in a major threat mode; S53: Take safety control strategies according to the working status of the bridge crane.

8. A safety control method for a bridge crane according to claim 7, characterized in that: In S53, the safety control strategy includes: when the bridge crane is in a general threat mode, a warning message is sent to the monitoring terminal of the on-site guard, and the working alarm on the bridge crane is turned on; when the bridge crane is in a major threat mode, a stop work control prompt is sent to the crane work control console.

9. A safety control system for a bridge crane, which is implemented based on a safety control method for a bridge crane as claimed in any one of claims 1 to 8, characterized in that: The system includes the following modules: Data acquisition module, fall area projection module, movement trajectory prediction module, safety work threat coefficient calculation module and safety control module; The data acquisition module is used to start the bridge crane control background and initialize the boundary data of the operation area, and synchronously extract the real-time lifting cargo status data of the bridge crane; The falling area projection module imports the real-time hoisting cargo status data into the dynamic falling area assessment strategy, obtains the dynamic falling area, and projects the dynamic falling area onto the ground; The movement trajectory prediction module is used to capture the location data of the violator using a high-definition camera and establish a machine learning model to predict the movement trajectory of the violator; The safety work threat coefficient calculation module is used to integrate and evaluate the safety work threat coefficient of the bridge crane; The safety control module adopts a safety control strategy for the bridge crane according to the safety work threat coefficient.

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