Bridge ship collision prevention collaborative early warning method and system based on digital twinning

Abstract

The invention relates to a bridge ship collision prevention collaborative early warning method and system based on digital twinning. The method comprises the steps that a physical entity in a target area is acquired, and a simulation model is built based on the physical entity by means of the digital twinning technology; calculating the ship collision risk degree of the bridge and the ultimate strength of the bridge member; estimating bridge ship collision time based on the simulation data corresponding to the bridge ship collision risk degree, calculating various types of water and land traffic evacuation time, and judging whether the bridge ship collision risk degree is an early warning threshold value or not based on the bridge ship collision time and the various types of water and land traffic evacuation time; and generating an early warning scheme based on the early warning threshold. The system is used for implementing the method. Compared with the prior art, the influence of secondary accidents caused by bridge ship collision events can be effectively prevented or relieved.

Description

Technical Field

[0001] The present invention relates to the technical field of ship safety systems, and in particular to a bridge ship collision prevention collaborative early warning method and system based on digital twins. Background Art

[0002] With the comprehensive construction of the national transportation network, the number of bridges across navigable waters is increasing day by day, and the number of ships in water transportation is also growing rapidly. In addition, the trend of large-scale and specialized ships is obvious, and the contradiction between bridge safety and ship navigation safety has intensified, resulting in frequent ship-bridge collision accidents. As a hub of transportation, bridges play a key role in carrying road, rail and pipeline transportation. Once a severe bridge-ship collision occurs, serious secondary accidents such as bridge destruction, ship sinking, casualties and environmental pollution often occur.

[0003] The Chinese patent application "CN116150951A" discloses a verification device and method for an active collision avoidance system for a ship and bridge in a bridge area, wherein the device includes: a first data transmission module for receiving navigation data of ships in the bridge area; a digital twin simulation module for obtaining virtual ship motion parameters based on navigation data of ships in the bridge area and a preset ship motion situation; a second data transmission module for sending the virtual ship motion parameters to the active collision avoidance system for the ship and bridge, and receiving physical ship motion optimization data; a function evaluation module for determining that the active collision avoidance system for the ship and bridge is effective when it is determined based on the virtual ship motion parameters and the physical ship motion optimization data that there is no distortion in the physical ship motion optimization data and that the virtual ship will not collide with the bridge pier.

[0004] Chinese patent "CN113436468B" discloses a method for collaborative configuration of a bridge collision avoidance system. By coordinating the bridge collision avoidance structure with representative navigable ship types, coordinating the bridge's active ship collision prevention and warning system with navigable ships in the bridge area, and coordinating the bridge's design, construction and operation stages with the environment and navigable ships, an intelligent and information-based waterway key node in the bridge area is constructed to solve the problem of bridge-ship collision and maximize the safety of waterway bridges and navigable ships.

[0005] Although both methods have achieved the goal of reducing the probability of bridge collision, they cannot avoid the losses caused by secondary accidents. Therefore, providing an early warning method that can avoid losses caused by secondary accidents is a problem that needs to be solved. Summary of the invention

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a bridge anti-ship collision collaborative warning method and system based on digital twin.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] According to a first aspect of the present invention, a bridge anti-ship collision collaborative warning method based on digital twin is provided, characterized in that the method comprises:

[0009] Acquire physical entities in the target area and build a simulation model based on the physical entities using digital twin technology; the physical entities include environmental entities, traffic entities and bridge entities;

[0010] Running the simulation model, acquiring simulation data and calculating the bridge-ship collision risk based on the simulation data; the simulation data includes static data corresponding to physical entity information that does not change during the simulation model operation and dynamic data corresponding to physical entity information that changes; the bridge-ship collision risk includes the bridge-ship collision probability and the bridge-ship collision collapse probability;

[0011] The bridge-ship collision time is estimated based on the simulation data corresponding to the bridge-ship collision risk, and the evacuation time of various types of water and land transportation is calculated, and whether the bridge-ship collision risk is a warning threshold is determined based on the bridge-ship collision time and the evacuation time of various types of water and land transportation; the various types of water and land transportation evacuation time include highway-bridge evacuation time, railway-bridge evacuation time and pipeline-bridge evacuation time;

[0012] If the risk of bridge-ship collision is determined as the warning threshold and meets the first warning requirement, a corresponding coordinated warning plan is generated based on the evacuation time of various types of water and land transportation; if the risk of bridge-ship collision is determined as the warning threshold and meets the second warning requirement but does not meet the first warning requirement, a warning plan is only generated for water transportation.

[0013] As a preferred technical solution, the environmental entities include wind, rain, fog, water flow, river banks and river beds; the traffic entities include ships of different types and sizes, vehicles of different types and sizes and different types of freight pipelines; the bridge entities include pile foundations, foundations, piers, abutments, bridge decks and the superstructure of the bridge decks.

[0014] As a preferred technical solution, the static data includes the shape, size and assembly relationship of the physical entities; the dynamic data includes wind speed, rainfall, fog visibility, water flow velocity and direction, water level, and the position, speed and direction of various types of ships, vehicles and pipeline cargo.

[0015] As a preferred technical solution, the method for determining the warning threshold is:

[0016] Acquire simulation data corresponding to the bridge-ship collision risk, and extract the distance between the ship and the bridge pier and the ship speed from the simulation data;

[0017] The bridge-ship collision time is estimated using the distance between the ship and the bridge pier and the ship speed;

[0018] Based on the simulation data, the evacuation time of various types of water and land transportation is calculated and compared with the estimated bridge-ship collision time. If the difference between the evacuation time of various types of water and land transportation and the estimated bridge-ship collision time is within a preset range or the difference is zero, the bridge-ship collision risk is used as a warning threshold.

[0019] As a preferred technical solution, the method for calculating the highway-bridge evacuation time is:

[0020]

[0021] Among them, x 总 represents the clear span length of the bridge, v car represents the vehicle speed, v pedestrian Indicates slow traffic speed.

[0022] As a preferred technical solution, the method for calculating the railway-bridge evacuation time is:

[0023]

[0024] Among them, t SD represents the train braking time, x 总 represents the clear span length of the bridge, v train is the train speed, l SD is the train braking distance, l train Indicates the length of the train.

[0025] As a preferred technical solution, the method for calculating the pipeline-bridge evacuation time is:

[0026] t tube = l tube / v tube ,

[0027] Among them, l tube Indicates the distance between two adjacent control nodes of the pipeline, v tube Indicates the transportation speed of pipeline cargo.

[0028] As a preferred technical solution, the first warning requirement is that the probability of bridge collapse due to ship collision is greater than or equal to a preset value; the second warning requirement is that the probability of bridge collapse due to ship collision is less than a preset value.

[0029] As a preferred technical solution, the collaborative early warning solution includes:

[0030] Highway-bridge coordinated warning scheme: automatic guardrails, stop signs and / or sound and light warnings are used to evacuate or block road traffic, while VHF communications and / or directional tweeters are used to warn target ships;

[0031] Railway-bridge coordinated warning scheme: warn trains that have arrived at the bridge to accelerate and leave the bridge, and warn trains that have not arrived at the bridge to brake, while using VHF communication and / or directional tweeters to warn target ships;

[0032] Pipeline-bridge coordinated early warning plan: cut off pipeline transportation and use VHF communication and / or directional tweeters to warn target ships at the same time.

[0033] According to a second aspect of the present invention, a bridge anti-ship collision collaborative warning simulation system based on digital twin is provided. The system is used to implement the above method, including:

[0034] Physical entity system: including an environmental subsystem, a traffic subsystem and a bridge subsystem, wherein the environmental subsystem includes multiple environmental entities, the traffic subsystem includes multiple traffic entities, the bridge subsystem includes multiple bridge entities, a data acquisition terminal and an early warning terminal; the data acquisition terminal is used to observe the status of each subsystem in the physical entity system in real time to obtain digital twin data, and the early warning terminal is used to obtain and execute the early warning plan generated by the cloud platform control system;

[0035] Digital twin system: includes a digital twin data storage module and digital twin models corresponding to the subsystems of the physical entity system, including an environment module, a traffic module and a bridge module, and the error generated when the digital twin system and the physical entity system are running simultaneously is less than a preset value, wherein the digital twin data storage module is used to store the digital twin data generated when the digital twin system is running, and the digital twin data includes static data and dynamic data and various algorithm data involved in the operation process of the digital twin model;

[0036] Cloud platform control system: includes a data storage subsystem and a data analysis subsystem, wherein the data storage subsystem is used to store the physical entity data collected in real time by the physical entity system and the digital twin data in the digital twin system, and calculate and analyze the ship collision risk of a ship colliding with a bridge based on the digital twin data using the built-in bridge-ship collision hazard algorithm, and feed back the calculation and analysis results to the digital twin system and the physical entity system.

[0037] Compared with the prior art, the present invention calculates the bridge-ship collision time based on the estimated bridge-ship collision risk, determines the warning threshold in real time based on the bridge-ship collision time and the water and land traffic evacuation time, and when the bridge-ship collision risk is determined as the warning threshold, a waterway-landway coordinated warning or a waterway warning is performed in combination with the probability of bridge-ship collision collapse, which can effectively prevent or reduce the impact of secondary accidents such as ship sinking, bridge collapse, casualties and environmental pollution that may occur during the bridge-ship collision, and can protect the common safety of bridges and ships; and the present invention builds a digital twin model to simulate the actual physical situation, which efficiently and intuitively reflects the actual conditions of the water area in the bridge area. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a flow chart of the method of the present invention;

[0039] Figure 2 This is a schematic diagram of the highway bridge collaborative early warning of the present invention;

[0040] Figure 3 This is a schematic diagram of the railway bridge collaborative early warning of the present invention;

[0041] Figure 4 This is a schematic diagram of the pipeline-bridge collaborative early warning of the present invention;

[0042] Figure 5 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0044] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0045] Embodiment 1:

[0046] This embodiment provides a bridge anti-ship collision collaborative warning method based on digital twins. The digital twin technology is used to create a simulation model of the target object in the virtual space, and the simulation model is dynamically updated based on the real-time monitoring information of the physical object in the real world. The ship collision risk during navigation, that is, the bridge ship collision probability and the bridge ship collision collapse probability, is analyzed, and water-land transportation collaborative warning is performed for situations that meet the warning requirements. The process of this method is as follows: Figure 1 As shown, the detailed steps include:

[0047] S1. Simulation model construction:

[0048] The physical entities in the target area are acquired and a simulation model is built based on the physical entities using digital twin technology. The physical entities include environmental entities, traffic entities and bridge entities. Environmental entities include wind, rain, fog, water flow, river banks and riverbeds. Traffic entities include ships of different types and sizes, such as bulk carriers, general cargo ships, container ships, fishing boats and oil tankers, vehicles of different types and sizes, such as cars, trucks and high-speed trains, and different types of freight pipelines. Bridge entities include pile foundations, foundations, piers, abutments, bridge decks and the superstructure of the bridge decks.

[0049] S2. Calculation of bridge-ship collision risk:

[0050] Run the simulation model, obtain simulation data and calculate the bridge-ship collision hazard based on the simulation data, wherein the simulation data includes static data and dynamic data during the operation of the simulation model. Specifically, static data refers to data that does not change during the operation, such as the shapes, sizes, numbers and assembly relationships of ships, vehicles, pipelines, bridges and bridge ancillary facilities; dynamic data refers to data that changes during the operation, such as wind speed, rainfall, fog visibility, water flow velocity, water flow direction, water level, ship type, vehicle type, location of pipeline cargo, cargo transportation speed and transportation direction; the bridge-ship collision hazard includes the probability of bridge-ship collision and the probability of bridge-ship collision collapse.

[0051] S3. Determine the warning threshold:

[0052] S31. Estimate the bridge-ship collision time based on the simulation data corresponding to the bridge-ship collision risk.

[0053] S311, obtaining simulation data corresponding to the bridge-ship collision risk, and extracting the distance between the ship and the bridge pier and the ship speed from the simulation data.

[0054] S312. Divide the distance between the ship and the bridge pier by the ship's speed to obtain the bridge-ship collision time.

[0055] S32. Calculate the evacuation time of various types of water and land transportation, where the types of water and land transportation include highway-bridge, railway-bridge and pipeline-bridge.

[0056] The danger zone of collapse of the superstructure of the impacted bridge is related to the bridge deck connected to the piers, taking a single-span, double-navigation simply supported bridge as an example, and its clear span is set to 100m.

[0057] Specifically, Figure 2 The figure shows the water and land transportation form of highway bridges. The calculation method of evacuation time under this form is:

[0058]

[0059] Among them, x 总 represents the clear span length of the bridge, v car represents the vehicle speed, v pedestrian Indicates slow traffic speed.

[0060] like Figure 3 The figure shows the water and land transportation form of the railway bridge. The calculation method of evacuation time under this form is:

[0061]

[0062] Among them, t SD represents the train braking time, x 总 represents the clear span length of the bridge, vtrain is the train speed, l SD is the train braking distance, l train Indicates the length of the train.

[0063] like Figure 4 For the water and land transportation form of pipeline bridge, the evacuation time method under this form is:

[0064] t tube = l tube / v tube ,

[0065] Among them, l tube Indicates the distance between two adjacent control nodes of the pipeline, v tube Indicates the transportation speed of pipeline cargo.

[0066] S33. Determine whether the bridge-ship collision risk is a warning threshold based on the bridge-ship collision time and the evacuation times of various types of water and land transportation, and compare the calculated evacuation times of various types of water and land transportation with the estimated bridge-ship collision time. If the difference between the evacuation times of various types of water and land transportation and the estimated bridge-ship collision time is within a preset range or the difference is zero, then use the bridge-ship collision risk as the warning threshold.

[0067] S4. Early warning plan generation:

[0068] If the bridge-ship collision risk is determined as the warning threshold and the probability of bridge-ship collision collapse is greater than or equal to the preset value, the evacuation time of various types of water and land transportation is used as the limit time, and the corresponding coordinated warning plan is generated within the limit time. The detailed highway-bridge coordinated warning plan is to use automatic guardrails, stop signs and / or sound and light warning methods to evacuate or block road traffic, and use VHF communication and / or directional tweeters to warn target ships; the railway-bridge coordinated warning plan is to warn trains that have arrived at the bridge to accelerate and leave the bridge and warn trains that have not arrived at the bridge to take braking measures, and use VHF communication and / or directional tweeters to warn target ships; the pipeline-bridge coordinated warning plan is to cut off pipeline transportation, and use VHF communication and / or directional tweeters to warn target ships.

[0069] If the bridge-ship collision risk is determined as the warning threshold and the bridge-ship collision collapse probability is less than the preset value, a warning plan will be generated only for water traffic, that is, VHF communication and directional tweeters will be used to warn target ships.

[0070] Example 2

[0071] The above is an introduction to the method embodiment. The following is a further explanation of the solution of the present invention through a system embodiment.

[0072] like Figure 5As shown, the system includes a physical entity system, a digital twin system and a cloud platform control system.

[0073] Specifically, the physical entity system includes: an environmental subsystem, which is built based on environmental entities in the target area such as wind, rain, fog, water flow, river banks and riverbeds and their corresponding data; a transportation subsystem, which is built based on transportation entities in the target area such as bulk carriers, general cargo ships, container ships, fishing boats, oil tankers, etc., various types and sizes of vehicles such as cars, trucks, high-speed trains, and various types of freight pipelines and their corresponding data; a bridge subsystem, which includes the overall structure of the bridge, such as pile foundations, foundations, piers, abutments, bridge decks and bridge deck superstructures, and bridge ancillary facilities; among them, bridge ancillary facilities include acquisition terminals and early warning terminals for real-time observation of the status of each subsystem in the physical entity system to obtain digital twin data.

[0074] The data twin system includes digital twin data blocks and digital twin models, where the digital twin data blocks are used to store dynamic data, static data and algorithm data. Specifically, static data refers to data that does not change during the operation of the digital twin model, including: the shape, size, number and assembly relationship of ships, vehicles, pipelines, bridges, bridge ancillary facilities, etc.; dynamic data includes data on changes in the state of physical entities during the operation of the digital twin model, including: wind speed, rainfall, fog visibility, water flow velocity and direction, water level, location, transportation speed and direction of various types of ships, vehicles, and pipeline cargo; algorithm data includes various types of algorithm data involved in the operation of the digital twin model. The digital twin model includes submodules corresponding to each subsystem in the physical entity system, and in the process of building the digital twin model, the digital twin model needs to be accurately corrected to ensure that the consistency and synchronization rate of the physical entity system and the digital twin system are within a reasonable error threshold when they run together.

[0075] The cloud platform control system includes a data storage subsystem for storing the digital twin data generated by the digital twin system at each moment and a data analysis subsystem for data analysis. The data analysis subsystem is embedded with a bridge-ship collision risk prediction algorithm, which analyzes the ship collision risk of a ship colliding with a bridge through the dynamic data and static data obtained from the digital twin system, and calculates the bridge-ship collision duration and evacuation duration. The probability of bridge-ship collision and the probability of bridge-ship collision collapse, i.e., the bridge-ship collision risk, are determined based on the two durations, and the warning threshold and the parameters of the bridge-ship collision risk prediction algorithm are adjusted. Specifically, the steps for using the system for bridge-ship collision collaborative warning are as follows:

[0076] A1. The physical entity system and the digital twin system are operated synchronously, and the data acquisition terminal of the physical entity system observes the entity data of the physical entity system in real time to obtain the dynamic data and static data of the digital twin system.

[0077] A2. The data storage subsystem in the cloud platform control system receives and stores relevant data from the physical entity system and the digital twin system collected by the data acquisition terminal. The data analysis subsystem receives static data and dynamic data and uses built-in algorithms to perform real-time analysis and stores the results of the real-time analysis in the data storage subsystem. The real-time analysis includes calculating the risk of bridge-ship collision and the corresponding bridge-ship collision time and the evacuation time of various types of water and land transportation, determining the warning threshold, and generating the warning plan.

[0078] A3. The early warning terminal in the physical entity system receives the analysis results generated by the cloud platform control system, and issues coordinated early warning for water-land transportation or only for water transportation.

[0079] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A bridge ship collision prevention collaborative early warning method based on digital twin, characterized in that: The method includes: Acquire physical entities in the target area and build a simulation model based on the physical entities using digital twin technology; the physical entities include environmental entities, traffic entities and bridge entities; Running the simulation model, acquiring simulation data and calculating the bridge-ship collision risk based on the simulation data; the simulation data includes static data corresponding to physical entity information that does not change during the simulation model operation and dynamic data corresponding to physical entity information that changes; the bridge-ship collision risk includes the bridge-ship collision probability and the bridge-ship collision collapse probability; The bridge-ship collision time is estimated based on the simulation data corresponding to the bridge-ship collision risk, and the evacuation time of various types of water and land transportation is calculated, and whether the bridge-ship collision risk is a warning threshold is determined based on the bridge-ship collision time and the evacuation time of various types of water and land transportation; the various types of water and land transportation evacuation time include highway-bridge evacuation time, railway-bridge evacuation time and pipeline-bridge evacuation time; If the risk of bridge-ship collision is determined as the warning threshold and meets the first warning requirement, a corresponding coordinated warning plan is generated based on the evacuation time of various types of water and land transportation; if the risk of bridge-ship collision is determined as the warning threshold and meets the second warning requirement but does not meet the first warning requirement, a warning plan is only generated for water transportation.

2. According to the digital twin-based bridge anti-ship collision collaborative warning method of claim 1, it is characterized in that: The environmental entities include wind, rain, fog, water flow, river bank and riverbed; the traffic entities include ships of different types and sizes, vehicles of different types and sizes and different types of freight pipelines; the bridge entities include pile foundations, foundations, piers, abutments, bridge decks and the superstructure of the bridge decks.

3. According to the digital twin-based bridge anti-ship collision collaborative warning method of claim 1, it is characterized in that: The static data includes the shape, size and assembly relationship of the physical entities; the dynamic data includes wind speed, rainfall, fog visibility, water flow velocity and direction, water level, position, speed and direction of various types of ships, vehicles and pipeline cargo.

4. According to the digital twin-based bridge anti-ship collision collaborative warning method of claim 1, it is characterized in that: The method for determining the warning threshold is: Acquire simulation data corresponding to the bridge-ship collision risk, and extract the distance between the ship and the bridge pier and the ship speed from the simulation data; The bridge-ship collision time is estimated using the distance between the ship and the bridge pier and the ship speed; Based on the simulation data, the evacuation time of various types of water and land transportation is calculated and compared with the estimated bridge-ship collision time. If the difference between the evacuation time of various types of water and land transportation and the estimated bridge-ship collision time is within a preset range or the difference is zero, the bridge-ship collision risk is used as a warning threshold.

5. The bridge anti-ship collision collaborative warning method based on digital twin according to claim 1 is characterized in that: The method for calculating the highway-bridge evacuation time is: Among them, x 总 represents the clear span length of the bridge, v car represents the vehicle speed, v pedestrian Indicates slow traffic speed.

6. The bridge anti-ship collision collaborative warning method based on digital twin according to claim 1 is characterized in that: The method for calculating the railway-bridge evacuation time is: Among them, t SD represents the train braking time, x 总 represents the clear span length of the bridge, v train is the train speed, l SD is the train braking distance, l train Indicates the length of the train.

7. The bridge anti-ship collision collaborative warning method based on digital twin according to claim 1 is characterized in that: The method for calculating the pipeline-bridge evacuation time is: t tube =l tube / v tube , Among them, l tube Indicates the distance between two adjacent control nodes of the pipeline, v tube Indicates the transportation speed of pipeline cargo.

8. The bridge ship collision prevention collaborative warning method based on digital twin according to claim 1 is characterized in that: The first warning requirement is that the probability of bridge collapse due to ship collision is greater than or equal to a preset value; the second warning requirement is that the probability of bridge collapse due to ship collision is less than a preset value.

9. The bridge anti-ship collision collaborative warning method based on digital twin according to claim 1 is characterized in that: The collaborative early warning scheme includes: Highway-bridge coordinated warning scheme: automatic guardrails, stop signs and / or sound and light warnings are used to evacuate or block road traffic, while VHF communications and / or directional tweeters are used to warn target ships; Railway-bridge coordinated warning scheme: warn trains that have reached the bridge to accelerate and leave the bridge, and warn trains that have not reached the bridge to take braking measures, while using VHF communication and / or directional tweeters to warn target ships; Pipeline-bridge coordinated early warning plan: cut off pipeline transportation and use VHF communication and / or directional tweeters to warn target ships at the same time.

10. A bridge anti-ship collision collaborative warning simulation system based on digital twin, characterized in that: The system is used to implement the collaborative early warning method according to claims 1-9, including: Physical entity system: including an environmental subsystem, a traffic subsystem and a bridge subsystem, wherein the environmental subsystem includes multiple environmental entities, the traffic subsystem includes multiple traffic entities, the bridge subsystem includes multiple bridge entities, a data acquisition terminal and an early warning terminal; the data acquisition terminal is used to observe the status of each subsystem in the physical entity system in real time to obtain digital twin data, and the early warning terminal is used to obtain and execute the early warning plan generated by the cloud platform control system; Digital twin system: includes a digital twin data storage module and digital twin models corresponding to the subsystems of the physical entity system, including an environment module, a traffic module and a bridge module, and the error generated when the digital twin system and the physical entity system are running simultaneously is less than a preset value, wherein the digital twin data storage module is used to store the digital twin data generated when the digital twin system is running, and the digital twin data includes static data and dynamic data and various algorithm data involved in the operation process of the digital twin model; Cloud platform control system: includes a data storage subsystem and a data analysis subsystem, wherein the data storage subsystem is used to store the physical entity data collected in real time by the physical entity system and the digital twin data in the digital twin system, and calculate and analyze the ship collision risk of a ship colliding with a bridge based on the digital twin data using the built-in bridge-ship collision hazard algorithm, and feed back the calculation and analysis results to the digital twin system and the physical entity system.

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