A computer vision-based floating bridge linear automatic control system and control method

Abstract

The application discloses a kind of floating bridge linear automatic control system based on computer vision, including shore-based control end and several floating ship control ends, shore-based control end is set in river bank, shore-based control end includes camera, image acquisition card and industrial computer, floating ship control end is respectively set on each floating ship and is located in same side, floating ship control end includes target on floating ship, environmental data acquisition unit and drive unit for driving floating ship to move, camera is used to monitor and capture target image on several floating ships, and image is converted into digital signal by image acquisition card and transmitted to industrial computer, industrial computer is used to analyze image and judge whether floating bridge linear deviation exceeds preset threshold, and according to the judgment result, environmental data acquisition unit is controlled to collect information, and industrial computer is analyzed to control drive unit to drive floating ship to move adjustment.The application realizes the automatic monitoring and adjustment of floating bridge linear, improves the adjustment efficiency and accuracy, enhances the stability and safety of floating bridge.

Description

Technical Field

[0001] This invention relates to the field of water transportation facilities technology, specifically to an automatic control system and control method for the alignment of floating bridges based on computer vision. Background Technology

[0002] With the development of water transportation facilities, pontoon bridges, as an important means of transportation connecting the two sides of a waterway, are of paramount importance in terms of stability and safety. Currently, common pontoon bridges are constructed from several floating boats and their own decks. Their load-bearing capacity mainly comes from the buoyancy of the water. However, their lateral stiffness is relatively weak, making them susceptible to the effects of wind, currents, and waves, and it is difficult to ensure the straightness of the alignment between the floating boats.

[0003] Traditional pontoon bridges rely on manual operation for alignment adjustments between several floating pontoons, a cumbersome process with low precision and low efficiency.

[0004] Therefore, there is an urgent need for an automatic control system and method for the alignment of floating bridges based on computer vision to solve the problem of low efficiency in adjusting the alignment between several floating vessels when using traditional floating bridges. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an automatic control system and method for the alignment of floating bridges based on computer vision, thereby solving the problem of low efficiency in adjusting the alignment between multiple floating vessels during the use of traditional floating bridges.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] An automatic control system for the alignment of a floating bridge based on computer vision is characterized by comprising a shore-based control terminal and several floating vessel control terminals. The shore-based control terminal is located on the riverbank and includes a camera, an image acquisition card, and an industrial computer. The floating vessel control terminals are respectively located on each floating vessel on the same side. The several floating vessels are interconnected to form a floating bridge. Each floating vessel control terminal includes a target, an environmental data acquisition unit, and a drive unit for moving the floating vessels. The camera is used to monitor and capture images of the target on the several floating vessels, and the image acquisition card converts the images into digital signals and transmits them to the industrial computer. The industrial computer analyzes the images and determines whether the deviation of the floating bridge alignment exceeds a preset threshold. Based on the determination result, it controls the environmental data acquisition unit to collect information on wind speed and direction, current speed and direction, and draft. The industrial computer then analyzes the information collected by the environmental data acquisition unit and controls the drive unit to move the floating vessels until the deviation of the floating bridge alignment meets the threshold.

[0008] To optimize the above technical solution, the specific measures also include:

[0009] Furthermore, the industrial computer includes an image processing module, an image analysis module, a data processing module, an instruction generation module, and a wireless communication module. The image processing module is used to perform image processing. The image analysis module is used to analyze the processed image, identify the corresponding target offset and offset speed, and determine whether the deviation of the floating bridge line shape exceeds a preset threshold. The instruction generation module generates control instructions based on the analysis results and sends them to the environmental data acquisition unit through the wireless communication module. The data processing module is used to analyze the information data collected by the environmental data acquisition unit and perform calculations. Based on the calculation results, it controls the drive unit on the corresponding floating vessel to perform drive adjustment through the instruction generation module and the wireless communication module.

[0010] Furthermore, the floating vessel control unit also includes a wireless communication module, a control unit, and a power supply module. The environmental data acquisition unit includes an anemometer for collecting wind speed and direction, and a flow velocity, flow direction, and draft gauge for collecting flow velocity, flow direction, and draft. The drive unit includes a drive motor and a propeller. The wireless communication module is used to receive and transmit information. The control unit is used to control the output force and output direction of the propeller driven by the drive motor according to the received information. The power supply module is used to provide power.

[0011] Furthermore, the anemometer uses an RS485 integrated anemometer and wind direction sensor with model number XM8189B.

[0012] Furthermore, the flow velocity, flow direction, and draft gauges are AN-HWDF6 acoustic Doppler flow rate and velocity meters.

[0013] Furthermore, a control method for an automatic control system for the alignment of a floating bridge based on computer vision is characterized by comprising the following steps:

[0014] Cameras monitor and capture images of targets on several floating pontoons. The image acquisition card converts the images into digital signals and transmits them to an industrial computer. The industrial computer analyzes the images and determines whether the deviation of the pontoon's alignment exceeds a preset threshold. When the deviation exceeds the preset threshold, the industrial computer controls the environmental data acquisition unit to collect information on wind speed and direction, current speed and direction, and draft. Based on the collected information, the data processing module within the industrial computer performs calculations and analyses, and then controls the drive unit of the corresponding pontoon to output and move the pontoon until the deviation meets the threshold.

[0015] Furthermore, the environmental data acquisition unit collects the water flow velocity v. water Flow direction θ water Wind speed v wind Wind direction θ wind In addition to data on draft and depth, the camera also collects the lateral offset d and offset velocity of the floating vessel currently perpendicular to the baseline.

[0016] Furthermore, the camera, in conjunction with the target detection algorithm in the data processing module, collects the lateral offset d and offset velocity of the floating vessel perpendicular to the baseline.

[0017] Furthermore, the calculations performed by the data processing module include the following steps:

[0018] Preset system parameters: water density ρ water air density ρ air Water resistance coefficient air drag coefficient The cross-sectional area A of the underwater floating section water The cross-sectional area A of the floating part above water wind Maximum propeller thrust T max ;

[0019] The system inputs parameter data from the environmental data acquisition unit and the camera, calculates the forces exerted by water flow and wind on the floating vessel, and decomposes them to the normal direction θ of the baseline. base :

[0020] Water force:

[0021]

[0022] Wind force:

[0023]

[0024] Total environmental forces:

[0025] F env =F water +F wind

[0026] Wherein: the cross-sectional area A of the underwater floating section water The cross-sectional area A of the floating part above water wind The calculation is performed by combining the draft depth data with the pre-input floating vessel cross-sectional area;

[0027] Based on the calculated total environmental force, the opposing force used to counteract it is derived:

[0028] F feedforward =-F env

[0029] Based on the current state of the floating vessel, including the offset d and the offset speed. Calculate restoring force:

[0030]

[0031] Where: k p It is the proportional gain, which determines the intensity of the response to the offset; k d It is the differential gain, which determines the intensity of the response to the offset velocity;

[0032] Formula for calculating total restoring force:

[0033]

[0034] Combined with the maximum thrust T of the propeller max Calculate the thrust:

[0035]

[0036] Where: the sign function sign(F) restore ) used to extract F restore The direction of F, if F restore If > 0, then sign(F) restore ) = 1. If F restore If < 0, then sign(F) restore = -1, the direction of thrust T is the same as F restore In the same direction, the drive unit outputs according to the obtained thrust T and the direction of thrust T.

[0037] Furthermore, it also includes the following steps: the camera continuously monitors the adjusted pontoon bridge alignment, and the shore-based control terminal continuously receives and analyzes new images to form a closed-loop control.

[0038] The beneficial effects of this invention are:

[0039] This invention uses a shore-based control unit with cameras, image acquisition cards, and an industrial computer to collect and analyze target images on several floating vessels in real time. This allows the system to determine whether the alignment deviation of the floating bridge, composed of these vessels, exceeds a preset threshold. When the threshold is exceeded, the control environmental data acquisition unit collects information on wind speed and direction, current speed and direction, and draft. The industrial computer then analyzes this information and, based on the analysis results, controls the drive unit to move the floating vessels until the alignment deviation meets the threshold. This achieves automatic monitoring and adjustment of the floating bridge alignment, significantly improving adjustment efficiency and accuracy, enhancing the stability and safety of the floating bridge, and providing a new solution for the intelligent management of water transportation facilities.

[0040] This invention addresses the problems of poor lateral stability of floating bridges, their susceptibility to wind, water flow, and waves, and the difficulty in maintaining a straight alignment. By combining modern computer vision and wireless communication technologies, it achieves automatic monitoring and adjustment of the floating bridge alignment, thereby improving the stability and safety of the floating bridge and solving the problems of low efficiency and poor accuracy in manual adjustment of the floating bridge alignment in existing technologies. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of an automatic control system for the alignment of a floating bridge based on computer vision, as proposed in this invention.

[0042] Figure 2 This is a schematic diagram illustrating the implementation of a computer vision-based automatic control system for the alignment of a floating bridge proposed in this invention.

[0043] Attached reference numerals: 1-Camera, 2-Industrial computer, 3-Riverbank, 4-Bridge deck, 5-Floating vessel, 6-Target, 7-Propeller, 8-Anemometer, 9-Flow velocity, direction and draft gauge. Detailed Implementation

[0044] The invention will now be described in further detail with reference to the accompanying drawings.

[0045] As attached Figure 1 and attached Figure 2 As shown in the figure, an automatic control system for the alignment of a floating bridge based on computer vision according to an embodiment of the present invention includes a shore-based control terminal and several floating vessel control terminals. The shore-based control terminal is set on the riverbank 3 and includes a camera 1, an image acquisition card, and an industrial computer 2. The floating vessel control terminals are respectively set on each floating vessel 5 and located on the same side. Several floating vessels 5 are interconnected to form a floating bridge through bridge decks 4 on them. The floating vessel control terminal includes a target 6, an environmental data acquisition unit, and a drive unit for driving the floating vessels 5 to move, all located on the floating vessels 5. The camera 1 is used to monitor and capture images of the target 6 on the several floating vessels 5, and the image acquisition card converts the images into digital signals and transmits them to the industrial computer 2. The industrial computer 2 is used to analyze the images and determine whether the deviation of the floating bridge alignment exceeds a preset threshold. Based on the judgment result, it controls the environmental data acquisition unit to collect information on wind speed and direction, current speed and direction, and draft. The industrial computer 2 then analyzes the information collected by the environmental data acquisition unit and controls the drive unit to drive the floating vessels 5 to move until the deviation of the floating bridge alignment meets the threshold.

[0046] This invention uses a camera 1, an image acquisition card, and an industrial computer 2 at a shore-based control terminal to collect and analyze images of targets 6 on several floating vessels 5 in real time. This allows the system to determine whether the alignment deviation of the floating bridge composed of the floating vessels 5 exceeds a preset threshold. When the threshold is exceeded, the control environmental data acquisition unit collects information on wind speed and direction, current speed and direction, and draft. The industrial computer 2 then analyzes the information collected by the environmental data acquisition unit and, based on the analysis results, controls the drive unit to move the floating vessels 5 until the alignment deviation of the floating bridge meets the threshold. This achieves automatic monitoring and adjustment of the floating bridge alignment, significantly improving adjustment efficiency and accuracy, enhancing the stability and safety of the floating bridge, and providing a new solution for the intelligent management of water transportation facilities.

[0047] In a further specific embodiment based on the above, the industrial computer 2 includes an image processing module, an image analysis module, a data processing module, an instruction generation module, and a wireless communication module. The image processing module is used to perform image processing, including filtering, edge detection, and feature extraction. The image analysis module is used to analyze the processed image, identify the corresponding target 6 offset and offset speed, and determine whether the deviation of the floating bridge line shape exceeds a preset threshold. The instruction generation module generates control instructions based on the analysis results and sends them to the environmental data acquisition unit through the wireless communication module. The data processing module is used to analyze and calculate the information data collected by the environmental data acquisition unit, and then control the drive unit on the corresponding floating vessel 5 to perform drive adjustment based on the calculation results through the instruction generation module and the wireless communication module.

[0048] In a further specific embodiment based on the above, the floating vessel control terminal also includes a wireless communication module, a control unit, and a power supply module. The environmental data acquisition unit includes an anemometer 8 for collecting wind speed and direction and a flow velocity, flow direction, and draft gauge 9 for collecting flow velocity, flow direction, and draft. The drive unit includes a drive motor and a propeller 7. The wireless communication module is used to receive and send information. The control unit is used to control the output force and output direction of the drive motor and propeller 7 according to the received information. The propeller 7 pushes the floating vessel 5 to move according to the control command to adjust the pontoon's alignment. The power supply module is used to supply power.

[0049] Among them, the aforementioned anemometer 8 uses an RS485 integrated anemometer and wind direction sensor, model XM8189B. The aforementioned flow velocity, flow direction, and draft gauge 9 uses an acoustic Doppler flow meter, model AN-HWDF6.

[0050] A control method for an automatic control system for the alignment of a floating bridge based on computer vision includes the following steps:

[0051] Camera 1 monitors and captures images of targets 6 on several floating vessels 5. The image acquisition card converts the images into digital signals and transmits them to industrial computer 2. Industrial computer 2 analyzes the images and determines whether the deviation of the floating bridge's alignment exceeds a preset threshold. When the deviation exceeds the preset threshold, industrial computer 2 controls the environmental data acquisition unit to collect information on wind speed and direction, current speed and direction, and draft. Based on the collected information, the data processing module within industrial computer 2 performs calculations and analyses, and then controls the drive unit of the corresponding floating vessel 5 to output and move the floating bridge until the deviation meets the threshold.

[0052] Furthermore, the environmental data acquisition unit collects the water flow velocity v. water Flow direction θ water Wind speed ν wind Wind direction θ windWith data on draft and depth, camera 1 collects the lateral offset d and offset velocity of the floating vessel 5, which is currently perpendicular to the baseline. Among them, camera 1, in conjunction with the target detection algorithm in the data processing module, collects the current lateral offset d and offset velocity of the floating vessel 5 perpendicular to the baseline.

[0053] The calculations performed by the aforementioned data processing module include the following steps:

[0054] Preset system parameters: water density ρ water air density ρ air Water resistance coefficient air drag coefficient The cross-sectional area A of the underwater floating section water The cross-sectional area A of the floating part above water wind Maximum propeller thrust T max The thrust-power mapping relationship is P = f(T).

[0055] The system inputs parameter data collected by the environmental data acquisition unit and camera 1, calculates the forces exerted by water flow and wind on the floating vessel, and decomposes them to the normal direction θ of the baseline. base :

[0056] Water force:

[0057]

[0058] Wind force:

[0059]

[0060] Total environmental forces:

[0061] F env =F water +F wind

[0062] Wherein: the cross-sectional area A of the underwater floating section water The cross-sectional area A of the floating part above water wind The calculation is performed by combining the draft depth data with the pre-input cross-sectional area of ​​the floating vessel 5.

[0063] Based on the calculated total environmental force, the opposing force used to counteract it is derived:

[0064] F feedforward =-F env

[0065] Based on the current state of the floating vessel, including the offset d and the offset speed. Calculate restoring force:

[0066]

[0067] Where: k p It is the proportional gain, which determines the intensity of the response to the offset; k d It is the differential gain, which determines the intensity of the response to the offset velocity;

[0068] Formula for calculating total restoring force:

[0069]

[0070] Combined with the maximum thrust T of the propeller max Calculate the thrust:

[0071]

[0072] Where: the sign function sign(F) restore ) used to extract F restore The direction (positive or negative), if F restore If > 0, then sign(F) restore ) = 1. If F restore If < 0, then sign(F) restore = -1, the direction of thrust T is the same as F restore In the same direction, the drive unit outputs according to the obtained thrust T and the direction of thrust T. The output power of the drive unit can be obtained through the thrust-power mapping relationship P = f(T).

[0073] Furthermore, it also includes the following steps: camera 1 continuously monitors the adjusted pontoon bridge alignment, and the shore-based control terminal continuously receives and analyzes new images to form a closed-loop control.

[0074] This invention addresses the problems of poor lateral stability of floating bridges, their susceptibility to wind, water flow, and waves, and the difficulty in maintaining a straight alignment. By combining modern computer vision and wireless communication technologies, it achieves automatic monitoring and adjustment of the floating bridge alignment, thereby improving the stability and safety of the floating bridge. It solves the problems of low efficiency and poor accuracy in the manual adjustment of floating bridge alignment in existing technologies, and provides a new solution for the intelligent management of water transportation facilities.

[0075] One specific embodiment of the present invention is as follows:

[0076] 1. Camera 1 captures images of the target on the floating vessel 5;

[0077] 2. The image acquisition card converts the image into a digital signal and transmits it to the industrial computer 2;

[0078] 3. The image processing module of industrial computer 2 performs image processing, including filtering, edge detection, and feature extraction;

[0079] IV. The image analysis module analyzes the processed image, identifies the target offset and offset velocity, and obtains the current state of pontoon 5: the current lateral offset d perpendicular to the baseline and the offset velocity. Determine whether the deviation of the pontoon bridge's alignment exceeds a preset threshold;

[0080] 5. When the deviation of the floating bridge's alignment exceeds the preset threshold, the command generation module generates control commands based on the analysis results and sends them to the environmental data acquisition unit at the floating vessel control terminal via the wireless communication module.

[0081] VI. The environmental data acquisition unit collects wind speed and direction, current velocity and direction, and draft to obtain environmental data: water flow velocity v water Flow direction θ water Wind speed v wind Wind direction θ wind And the draft used to calculate the cross-sectional area of ​​the above-water and underwater parts of the floating vessel, and transmit the data to the data processing module.

[0082] VII. The data processing module calculates the propeller's output power and the floating vessel's direction of movement based on the built-in algorithm.

[0083] The specific algorithm is as follows:

[0084] 1. Input parameters

[0085] Preset system parameters: water resistance coefficient air drag coefficient Floating vessel cross-sectional area A water (Underwater section), A wind (Above water section), maximum propeller thrust T max The thrust-power mapping relationship is P = f(T). Input the parameters obtained above, including the lateral offset d and offset velocity of the floating vessel 5. water flow velocity v water Flow direction θ water Wind speed v wind Wind direction θ wind And draft.

[0086] 2. Calculate environmental forces

[0087] Calculate the forces exerted by the water flow and wind on the floating vessel, and decompose them to the normal direction of the baseline:

[0088] Water force:

[0089]

[0090] Wind force:

[0091]

[0092] Total environmental forces:

[0093] f env =F water +F wind

[0094] 3. Calculate control force (feedforward compensation + PD control)

[0095] Feedforward compensation: Calculate the total environmental force F env You can directly apply an opposite force to counteract it.

[0096] F feedforward =-F env

[0097] PD control: Based on the current state of the floating vessel (offset d and offset speed) Calculate the restoring force.

[0098] Proportional control (P): Calculates the restoring force based on the offset d, and quickly reduces the offset.

[0099] Differential control (D): based on offset speed Calculate the restoring force to suppress oscillations.

[0100]

[0101] Where: k p It is the proportional gain, which determines the intensity of the response to the offset; k d It is the differential gain, which determines the strength of the response to the offset velocity.

[0102] Calculate total resilience:

[0103]

[0104] 4. Propeller thrust constraint

[0105] By limiting the magnitude of the thrust T, it is ensured that it does not exceed the maximum thrust T of the propeller. max This is to avoid overloading the propeller while ensuring the physical feasibility of the control system.

[0106]

[0107] The sign function sign(F) restore ) used to extract F restore The direction (positive or negative).

[0108] If F restore If > 0, then sign(F) restore ) = 1. If F restore If < 0, then sign(F) restore ) = -1.

[0109] 5. Power and Direction Calculation

[0110] Thrust direction: with F restore Same direction.

[0111] Power mapping: P = f(T).

[0112] 8. The wireless communication module sends the calculated control commands to the floating ship control terminal;

[0113] 9. The wireless communication module at the floating vessel control terminal receives control signals;

[0114] 10. The control unit analyzes the signals and generates specific instructions to control propeller 7;

[0115] 11. The drive motor controls the output power and propulsion direction of propeller 7 according to the instructions of the control unit;

[0116] 12. Propeller 7 moves pontoon 5 to adjust the alignment of the pontoon bridge;

[0117] Thirteen, the power module provides power to the floating vessel control terminal;

[0118] Fourteen, Camera 1 continuously monitors the adjusted pontoon bridge alignment, while the shore-based control terminal continuously receives and analyzes new images to form a closed-loop control system.

[0119] It should be noted that the terms such as "upper", "lower", "left", "right", "front", and "back" used in the invention are only for clarity of description and are not intended to limit the scope of the invention. Changes or adjustments to their relative relationships, without substantially altering the technical content, should also be considered within the scope of the invention.

[0120] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that those skilled in the art will understand that various changes, modifications, substitutions, refinements, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and these variations should be considered within the scope of protection of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A computer vision-based automatic control system for the alignment of a floating bridge, characterized in that: The system includes a shore-based control terminal and several floating control terminals. The shore-based control terminal is located on the riverbank (3) and includes a camera (1), an image acquisition card, and an industrial computer (2). The floating control terminals are respectively located on each floating vessel (5) and on the same side. Several floating vessels (5) are interconnected to form a floating bridge. The floating control terminal includes a target (6) on the floating vessel (5), an environmental data acquisition unit, and a drive unit for moving the floating vessel (5). The camera (1) is used to monitor and capture images of the target (6) on several floating vessels (5), and the image acquisition card converts the images into digital signals and transmits them to the industrial computer (2). The industrial computer (2) is used to analyze the images and determine whether the deviation of the floating bridge line shape exceeds a preset threshold. Based on the judgment result, it controls the environmental data acquisition unit to collect information on wind speed and direction, current speed and direction, and draft. The industrial computer (2) then analyzes the information collected by the environmental data acquisition unit and controls the drive unit to move the floating vessel (5) until the deviation of the floating bridge line shape meets the threshold.

2. The automatic control system for the alignment of a floating bridge based on computer vision according to claim 1, characterized in that: The industrial computer (2) includes an image processing module, an image analysis module, a data processing module, an instruction generation module, and a wireless communication module. The image processing module is used to perform image processing. The image analysis module is used to analyze the processed image, identify the corresponding target (6) offset and offset speed, and determine whether the deviation of the floating bridge line shape exceeds a preset threshold. The instruction generation module generates control instructions based on the analysis results and sends them to the environmental data acquisition unit through the wireless communication module. The data processing module is used to analyze the information data collected by the environmental data acquisition unit and calculate it. Then, based on the calculation results, it controls the drive unit on the corresponding floating vessel (5) to perform drive adjustment through the instruction generation module and the wireless communication module.

3. The automatic control system for pontoon bridge alignment based on computer vision according to claim 1, characterized in that: The floating vessel control terminal also includes a wireless communication module, a control unit, and a power supply module. The environmental data acquisition unit includes an anemometer (8) for collecting wind speed and direction and a flow velocity, flow direction, and draft gauge (9) for collecting flow velocity, flow direction, and draft. The drive unit includes a drive motor and a propeller (7). The wireless communication module is used to receive and send information. The control unit is used to control the output force and output direction of the drive motor driving the propeller (7) according to the received information. The power supply module is used to supply power.

4. The automatic control system for the alignment of a floating bridge based on computer vision according to claim 3, characterized in that: The anemometer (8) uses an RS485 integrated anemometer and wind direction sensor with model number XM8189B.

5. The automatic control system for the alignment of a floating bridge based on computer vision according to claim 3, characterized in that: The flow velocity, flow direction and draft gauge (9) is an acoustic Doppler flow velocity meter of model AN-HWDF6.

6. The control method for an automatic control system for the alignment of a floating bridge based on computer vision according to any one of claims 1-5, characterized in that, Includes the following steps: The camera (1) monitors and captures images of targets (6) on several floating vessels (5). The image acquisition card converts the images into digital signals and transmits them to the industrial computer (2). The industrial computer (2) analyzes the images and determines whether the deviation of the floating bridge line exceeds the preset threshold. When the deviation of the floating bridge line exceeds the preset threshold, the industrial computer (2) controls the environmental data acquisition unit to collect information on wind speed and direction, flow speed and direction, and draft. Based on the collected information, the data processing module in the industrial computer (2) performs calculation and analysis. Based on the calculation results, the drive unit of the corresponding floating vessel (5) is controlled to output and move until the deviation of the floating bridge line meets the threshold.

7. The control method for an automatic control system for the alignment of a floating bridge based on computer vision according to claim 6, characterized in that: The environmental data acquisition unit collects the water flow velocity v. water Flow direction θ water Wind speed v wind Wind direction θ wind The camera (1) collects data on the draft and the lateral offset d and offset velocity of the floating vessel (5) perpendicular to the baseline.

8. The control method for an automatic control system for the alignment of a floating bridge based on computer vision according to claim 7, characterized in that: The camera (1), in conjunction with the target detection algorithm in the data processing module, collects the current lateral offset d and offset speed of the floating vessel (5) perpendicular to the baseline.

9. The control method for an automatic control system for the alignment of a floating bridge based on computer vision according to claim 7, characterized in that, The calculations performed by the data processing module include the following steps: Preset system parameters: water density ρ water air density ρ air Water resistance coefficient air drag coefficient The cross-sectional area A of the underwater floating section water The cross-sectional area A of the floating part above water wind Maximum propeller thrust T max ; The system inputs parameter data collected by the environmental data acquisition unit and the camera (1), calculates the forces exerted by water flow and wind on the floating vessel, and decomposes them into the normal direction θ of the baseline. base : Water force: Wind force: Total environmental forces: F env =F water +F wind Wherein: the cross-sectional area A of the underwater floating section water The cross-sectional area A of the floating part above water wind The calculation is performed by combining the draft depth data with the pre-input cross-sectional area of ​​the floating vessel (5); Based on the calculated total environmental force, the opposing force used to counteract it is derived: F feedforward =-F env Based on the current state of the floating vessel, including the offset d and the offset speed. Calculate restoring force: Where: k p It is the proportional gain, which determines the intensity of the response to the offset; k d It is the differential gain, which determines the intensity of the response to the offset velocity; Formula for calculating total restoring force: Combined with the maximum thrust T of the propeller max Calculate the thrust: Where: the sign function sign(F) restore ) used to extract F restore The direction of F, if F restore If > 0, then sign(F) restore ) = 1; if F restore <0, then sign(F) restore = -1, the direction of thrust T is the same as F restore In the same direction, the drive unit outputs according to the obtained thrust T and the direction of thrust T.

10. The control method for an automatic control system of a floating bridge alignment based on computer vision according to claim 6, characterized in that, It also includes the following steps: the camera (1) continuously monitors the adjusted pontoon bridge alignment, and the shore-based control terminal continuously receives new images and analyzes them to form a closed-loop control.

Images