Quantitative analysis method and system for risk of ship colliding with sea wind field

Abstract

The invention discloses a ship collision sea wind field risk quantitative analysis method and system, and the key points of the technical scheme are that the ship collision sea wind field risk quantitative analysis method comprises the following steps: S1, obtaining target data in real time, the target data comprising ship dynamic data, wind power field region data and environment data; s2, judging the area where the ship is located based on the real-time position of the ship and the wind power plant area data; s3, calculating a space-time risk accumulation value; s4, calculating a ship kinetic energy factor E; s5, calculating a ship risk attribute factor C; s6, calculating a real-time risk value R through a total risk formula based on results of the steps S2-S5; s7, introducing an environment correction coefficient to correct a risk level threshold value; and S8, according to the corrected risk grade threshold value, in combination with the area where the ship is located, risk grades are divided. According to the method, multi-dimensional risk factors are fused, risk assessment is upgraded from qualitative to quantitative, and misinformation and missing report caused by a single distance threshold value are eliminated.

Description

Technical Field

[0001] This invention relates to the field of maritime traffic safety, specifically to a method and system for quantitative analysis of ship collision risk in sea wind fields. Background Technology

[0002] With the large-scale construction of offshore wind farms, the risk of collisions between ships and wind farms has become a key issue restricting maritime traffic safety. Current technologies primarily rely on "virtual electronic fences" for warning of ship collisions with wind farms. These typically divide the area around a wind farm into a core no-navigation zone (the coordinates of the wind farm site) and three warning zones (500m, 1000m, and 1500m from the site, adjustable). An alarm is triggered when a ship's AIS position enters a warning zone or no-navigation zone.

[0003] However, existing technologies have significant drawbacks: The risk assessment method is too simplistic, resulting in a high false alarm rate or untimely alarms: The alarm threshold is based solely on the "relative distance between the ship and the wind farm," without considering key risk factors such as ship size, type, speed, and heading. If the electronic fence is set too small, large / high-speed ships will not have enough time to respond to the alarm due to insufficient braking distance; if it is set too large, a large number of ships without collision risk (such as small fishing boats and low-speed vessels) will trigger unnecessary alarms, interfering with the decision-making of monitoring personnel.

[0004] Risk assessment is "qualitative rather than quantitative": it can only determine "risk / no risk" and cannot quantify the degree of risk (such as the risk difference between "hazardous chemical ship sailing at high speed towards a restricted area" and "ordinary cargo ship approaching a warning area at low speed"), resulting in a lack of accuracy and priority distinction in early warning.

[0005] Lack of dynamic risk tracking capability: It does not track the risk changes of a vessel from "entering the monitoring range" to "leaving the monitoring range", and cannot capture the dynamic fluctuations of risk caused by changes in the vessel's course and speed (such as when a vessel changes from "heading towards the restricted area" to "moving away from the restricted area", the existing technology may still continue to issue warnings).

[0006] In summary, existing technologies, lacking a "multi-factor integrated risk quantification system," are insufficient to meet the needs of refined safety monitoring of offshore wind farms. There is an urgent need for a technical solution that can achieve "dynamic, quantitative, and accurate" risk assessment. Summary of the Invention

[0007] In view of the problems mentioned in the background art, the purpose of this invention is to provide a method and system for quantitative analysis of ship collision sea wind field risks, so as to solve the problems existing in the prior art.

[0008] The above-mentioned technical objective of the present invention is achieved through the following technical solution: A method for quantitative analysis of ship collision risk in offshore wind fields includes the following steps: S1: Real-time acquisition of target data, including ship dynamic data, wind farm area data, and environmental data; the ship dynamic data includes ship MMSI, ship name, ship type, ship size, speed, heading, and real-time location; the wind farm area data includes the wind farm ID, monitoring area, warning area, and restricted navigation area's geographical coordinates; the environmental data includes visibility, sea state, and typhoon information; S2: Based on the real-time location of the ship and the wind farm area data, determine the area where the ship is located: determine whether the area where the ship is located is a monitoring area, a warning area or a no-navigation area, and determine the value of the spatial correlation factor L: L=1 when the ship is in the monitoring area, L=3 when it is in the warning area, and L=5 when it is in the no-navigation area; S3: Calculate the spatiotemporal risk accumulation value, using the formula: G1 / T1 + G2 / T2 + G3 / T3, where: G1 is the cumulative / decreasing risk value of the vessel in the monitored area, and T1 is the time from the vessel entering the monitored area to entering the restricted area. If the vessel's track extension does not intersect the restricted area, G1 increases by 0 every N seconds; if it only intersects the restricted area, G1 increases by 3 every N seconds; if it intersects the restricted area, G1 increases by 5 every N seconds; if the vessel moves away from the restricted area, G1 decreases by 1 every N seconds; G1 = 0 when the vessel leaves the monitored area. G2 is the cumulative / decrease value of the risk of the vessel in the restricted area, and T2 is the time from the vessel entering the restricted area to entering the restricted area. If the vessel's track extension intersects with the restricted area, G2 increments by 100 for each position update. If they do not intersect or the vessel stops sailing, G2 increments by 0. G2=0 when the vessel leaves the restricted area. G3 is the cumulative risk value of a vessel in a restricted area, and T3 is the time from when the vessel enters the restricted area to when it leaves the restricted area; G3 increments by 150 each time the vessel's position is updated; G3=0 when the vessel leaves the restricted area; S4: Calculate the ship's kinetic energy factor E: E = Ship mass × Speed 2 The mass of the ship is calculated as: ship length × ship width × ship draft. If the draft is empty, the default draft is 2m. If the length or width is missing, it will not be included in the calculation of E. Furthermore, if the length is greater than 450m, it will not be included in the calculation of E. S5: Calculate the ship risk attribute factor C: C = Ship state coefficient × Ship type coefficient; The ship state coefficient includes: 1 for normal, 5 for deviation from normal course, and 8 for dragging anchor in typhoon conditions; The ship type coefficient includes: 10 for hazardous chemical ships, 10 for passenger ships, 8 for general cargo ships, and 1 for fishing vessels; S6: Based on the results of steps S2-S5, calculate the real-time risk value R using the total risk formula: R=L×(G1 / T1+G2 / T2+G3 / T3)×E×C; S7: Introduce an environmental correction factor to correct the risk level threshold: In environments with poor visibility, strong winds and waves, or typhoons, multiply the risk level threshold of the monitoring area, warning area, and no-navigation area by a preset correction factor, wherein the preset correction factor is 0.6-0.8. S8: Based on the revised risk level threshold and the area where the ship is located, the risk level is divided into four levels, and early warning information is generated based on the risk level to complete the quantitative analysis of the risk of ship collision with offshore wind farm.

[0009] In step S1, the ship dynamic data is acquired in real time through the AIS system, with a sampling frequency of once every 3 minutes; the environmental data is updated in real time through marine meteorological stations or satellite remote sensing data, with an update frequency of once every 15 minutes.

[0010] Preferably, in step S3, the criterion for determining the stoppage is that the ship's current speed is <1 knot; if the ship is in the monitoring area and stops, the risk event ends and G1 is cleared, where the monitoring area is a non-warning area or a restricted area.

[0011] Preferably, step S3 also includes signal loss handling rules: if the vessel is in a warning zone or a restricted area and its position is not updated for more than 16 minutes, it is determined to be a signal loss; if the vessel is in any area and its position is not updated for more than 4 hours, the current monitoring event is terminated and G1, G2, and G3 are reset.

[0012] Preferably, in step S8, the risk level threshold is configured separately for each wind farm, wherein: Monitoring area: Risk value < X1 is level 4, X1 ≤ risk value < Y1 is level 3, Y1 ≤ risk value < Z1 is level 2, and risk value ≥ Z1 is level 1; Warning Zone: Risk value < X2 is Level 4, X2 ≤ Risk value < Y2 is Level 3, Y2 ≤ Risk value < Z2 is Level 2, and Risk value ≥ Z2 is Level 1; No-navigation zone: Risk value < X3 is level 4, X3 ≤ risk value < Y3 is level 3, Y3 ≤ risk value < Z3 is level 2, and risk value ≥ Z3 is level 1; where X1, Y1, Z1, X2, Y2, Z2, X3, Y3, and Z3 are positive threshold values ​​preset by the wind farm based on the actual sea area vessel density and wind turbine layout.

[0013] Preferably, in step S8, the warning information includes the vessel's MMSI, vessel name, wind farm ID, current risk value, risk level, suggested warning text, and the vessel's real-time location; the suggested warning text is generated based on the vessel type and its location.

[0014] This invention also discloses a ship collision risk quantification analysis system for offshore wind fields, including: a data acquisition module: used to acquire ship dynamic data, wind farm area data and environmental data in real time, and to clean and convert the data format; The region determination and spatial factor calculation module is used to determine the region where the ship is located based on the ship's real-time location and wind farm area data, and output the spatial correlation factor L. Spatiotemporal risk accumulation calculation module: used to calculate G1, G2, G3 and corresponding T1, T2, T3 based on the intersection relationship between the ship's extended track and the region, the navigation status and the dwell time, and output (G1 / T1+G2 / T2+G3 / T3). Kinetic Energy and Risk Attribute Calculation Module: Used to calculate kinetic energy factor E based on ship size and speed, and risk attribute factor C based on ship status and type; Total risk calculation and classification module: used to execute the total risk formula as described in claim 1, combine the environmental correction coefficient to correct the risk level threshold, classify the risk level and generate early warning information; Early warning and handling module: used to display a list of vessels with risk level > level 4 that need to be handled, and provides functions such as vessel trajectory tracing, risk curve viewing, and manual broadcasting of alarm information; Storage module: Used to store the risk record form of the ship wind farm.

[0015] Preferably, the data acquisition module supports parallel data access, and can simultaneously acquire regional data of wind farms already built in Guangdong, Guangxi and Hainan and dynamic data of ships passing through the region, so as to realize real-time monitoring of at least 19 wind farms and 20,000 ships.

[0016] Preferably, the early warning and handling module also supports the visualization of risk curves. The risk curves are plotted with time on the horizontal axis and risk value on the vertical axis, and the ship speed curve is superimposed on them to intuitively present the trend of ship risk value changes over time. Preferably, the system also includes a parallel computing module: adopting a distributed computing architecture, it supports the simultaneous calculation of risk values ​​for at least 1,000 ships, with a calculation latency of ≤10 seconds, meeting the requirements for real-time early warning.

[0017] In summary, the present invention has the following main beneficial effects: This invention integrates multi-dimensional risk factors, upgrading risk assessment from "qualitative" to "quantitative," eliminating false alarms and missed alarms caused by single distance thresholds; this invention dynamically tracks risks throughout the entire event cycle of a vessel from entering the monitoring area to leaving, updating risk values ​​in real time; this invention introduces environmental adaptive correction to improve the accuracy of risk assessment under complex sea conditions; this invention provides visual early warning and response functions to assist monitoring personnel in making rapid decisions. Attached Figure Description

[0018] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1 refer to Figure 1 The method for quantitative analysis of ship collision risk in sea wind fields includes the following steps: S1: Real-time acquisition of target data, including vessel dynamic data, wind farm area data, and environmental data; vessel dynamic data includes vessel MMSI, vessel name, vessel type, vessel size, speed, heading, and real-time location; wind farm area data includes the wind farm ID, monitoring area, warning area, and geographical coordinates of the restricted area; environmental data includes visibility, sea state, and typhoon information. S2: Based on the real-time location of the ship and the wind farm area data, determine the area where the ship is located: determine whether the area where the ship is located is a monitoring area, a warning area or a no-navigation area, and determine the value of the spatial correlation factor L: L=1 when the ship is in the monitoring area, L=3 when it is in the warning area, and L=5 when it is in the no-navigation area; S3: Calculate the spatiotemporal risk accumulation value, using the formula: G1 / T1 + G2 / T2 + G3 / T3, where: G1 is the cumulative / decreasing risk value of the vessel in the monitored area, and T1 is the time from the vessel entering the monitored area to entering the restricted area. If the vessel's track extension does not intersect the restricted area, G1 increases by 0 every N seconds; if it only intersects the restricted area, G1 increases by 3 every N seconds; if it intersects the restricted area, G1 increases by 5 every N seconds; if the vessel moves away from the restricted area, G1 decreases by 1 every N seconds; G1 = 0 when the vessel leaves the monitored area. G2 is the cumulative / decrease value of the risk of the vessel in the restricted area, and T2 is the time from the vessel entering the restricted area to entering the restricted area. If the vessel's track extension intersects with the restricted area, G2 increments by 100 for each position update. If they do not intersect or the vessel stops sailing, G2 increments by 0. G2=0 when the vessel leaves the restricted area. G3 is the cumulative risk value of a vessel in a restricted area, and T3 is the time from when the vessel enters the restricted area to when it leaves the restricted area; G3 increments by 150 each time the vessel's position is updated; G3=0 when the vessel leaves the restricted area; S4: Calculate the ship's kinetic energy factor E: E = Ship mass × Speed 2 Ship mass = Ship length × Ship width × Ship draft. If the draft is empty, the default draft is 2m. If the length or width is missing, it will not be included in the calculation of E. If the length is greater than 450m, it will not be included in the calculation of E. S5: Calculate the ship risk attribute factor C: C = Ship condition coefficient × Ship type coefficient; Ship condition coefficient includes: 1 for normal, 5 for deviation from normal course, and 8 for dragging anchor in typhoon conditions; Ship type coefficient includes: 10 for hazardous materials ships, 10 for passenger ships, 8 for general cargo ships, and 1 for fishing vessels; S6: Based on the results of steps S2-S5, calculate the real-time risk value R using the total risk formula: R=L×(G1 / T1+G2 / T2+G3 / T3)×E×C; S7: Introduce an environmental correction factor to correct the risk level threshold: In environments with poor visibility, strong winds and waves, or typhoons, multiply the risk level threshold of the monitoring area, warning area, and no-navigation area by a preset correction factor, which is 0.6-0.8. S8: Based on the revised risk level threshold and the area where the ship is located, the risk level is divided into four levels, and early warning information is generated based on the risk level to complete the quantitative analysis of the risk of ship collision with offshore wind farm.

[0021] In step S1, ship dynamic data is acquired in real time through the AIS system, with a sampling frequency of once every 3 minutes; environmental data is updated in real time through marine meteorological stations or satellite remote sensing data, with an update frequency of once every 15 minutes.

[0022] In step S3, the criterion for stopping navigation is that the ship's current speed is less than 1 knot. If the ship is in the monitoring area and stops navigation, the risk event ends and G1 is cleared. The monitoring area is either a non-warning area or a restricted area.

[0023] Step S3 also includes signal loss handling rules: if a vessel is in a warning zone or a restricted area and its position is not updated for more than 16 minutes, it is determined to be a signal loss; if a vessel is in any area and its position is not updated for more than 4 hours, the current monitoring event is terminated and G1, G2, and G3 are reset.

[0024] In step S8, the risk level threshold is configured separately for each wind farm, wherein: Monitoring area: Risk value < X1 is level 4, X1 ≤ risk value < Y1 is level 3, Y1 ≤ risk value < Z1 is level 2, and risk value ≥ Z1 is level 1; Warning Zone: Risk value < X2 is Level 4, X2 ≤ Risk value < Y2 is Level 3, Y2 ≤ Risk value < Z2 is Level 2, and Risk value ≥ Z2 is Level 1; No-navigation zone: Risk value < X3 is level 4, X3 ≤ risk value < Y3 is level 3, Y3 ≤ risk value < Z3 is level 2, and risk value ≥ Z3 is level 1; where X1, Y1, Z1, X2, Y2, Z2, X3, Y3, and Z3 are positive threshold values ​​preset by the wind farm based on the actual sea area vessel density and wind turbine layout.

[0025] In step S8, the warning information includes the vessel's MMSI, vessel name, wind farm ID, current risk value, risk level, suggested warning text, and the vessel's real-time location; the suggested warning text is generated based on the vessel type and the area it is located in.

[0026] Example 2 refer to Figure 1 This embodiment also discloses a ship collision risk quantification analysis system for offshore wind fields, including: a data acquisition module: used to acquire ship dynamic data, wind farm area data and environmental data in real time, and to clean and convert the data format; The region determination and spatial factor calculation module is used to determine the region where the ship is located based on the ship's real-time location and wind farm area data, and output the spatial correlation factor L. Spatiotemporal risk accumulation calculation module: used to calculate G1, G2, G3 and corresponding T1, T2, T3 based on the intersection relationship between the ship's extended track and the region, the navigation status and the dwell time, and output (G1 / T1+G2 / T2+G3 / T3). Kinetic Energy and Risk Attribute Calculation Module: Used to calculate kinetic energy factor E based on ship size and speed, and risk attribute factor C based on ship status and type; Total Risk Calculation and Classification Module: This module is used to execute the total risk formula of claim 1, adjust the risk level threshold by combining the environmental correction factor, classify the risk level, and generate early warning information; Early warning and handling module: used to display a list of vessels with risk level > level 4 that need to be handled, and provides functions such as vessel trajectory tracing, risk curve viewing, and manual broadcasting of alarm information; Storage module: Used to store the risk record form of the ship wind farm.

[0027] The data acquisition module supports parallel data access, and can simultaneously acquire regional data of wind farms already built in Guangdong, Guangxi and Hainan and dynamic data of ships passing through the region, enabling real-time monitoring of at least 19 wind farms and 20,000 ships.

[0028] The early warning and response module also supports the visualization of risk curves. The risk curve has time as the horizontal axis and risk value as the vertical axis, and the ship speed curve is superimposed on it to intuitively show the trend of ship risk value changes over time. The system also includes a parallel computing module: it adopts a distributed computing architecture, supports the simultaneous calculation of risk values ​​for at least 1,000 ships, and has a calculation latency of ≤10 seconds, meeting the requirements for real-time early warning.

[0029] This invention integrates multi-dimensional risk factors, upgrading risk assessment from "qualitative" to "quantitative," eliminating false alarms and missed alarms caused by single distance thresholds; it dynamically tracks risks throughout the entire event cycle of a vessel from entering the monitoring area to leaving, updating risk values ​​in real time; it introduces environmental adaptive correction to improve the accuracy of risk assessment under complex sea conditions; and it provides visual early warning and response functions to assist monitoring personnel in making rapid decisions.

[0030] Example 3 The method of this invention realizes the quantitative calculation of the risk of ship collision with offshore wind farms, and completes the real-time quantification and visualization of the risk of ship collision with offshore wind farms, as well as the automatic alarm of the risk of ship collision with offshore wind farms through the application system of the invention.

[0031] The main principle of ship collision risk quantification and classification for offshore wind farms is as follows: The calculation begins when a ship enters the wind farm's monitoring area. As the ship moves from the outermost layer towards the restricted area, the risk value should increase from 0. Conversely, as the ship moves from the innermost layer away from the restricted area, the risk value should decrease until the ship leaves the wind farm, at which point the risk value returns to 0 or is considered zero. Key design parameters include: ship type, ship dimensions, spatial correlation factors such as speed, heading, and position, ship kinetic energy factors, and ship risk attribute factors.

[0032] Total risk calculation formula: R = L*(G1 / T1+G2 / T2+G3 / T3)*E*C G1 is the cumulative increase / decrease of the risk value in the monitoring area, and T1 is the time from when the vessel enters the monitoring area to when it enters the warning area.

[0033] G2 is the cumulative increase / decrease of the risk value in the warning zone, and T2 is the time from when the ship enters the warning zone to when the ship enters the restricted area.

[0034] G3 is the cumulative risk value of the restricted area, and T3 is the time from when the vessel enters the restricted area to when it leaves the restricted area.

[0035] 1. If a ship remains in a restricted or prohibited area for more than 16 minutes, it is considered a signal loss. If the ship's position is not updated for more than 4 hours, the monitoring event will be terminated.

[0036] 2. Only signal loss in warning zones and restricted navigation zones will be addressed; signal loss in monitored zones will be ignored. Monitoring events will also end if signal loss in a monitored zone exceeds 4 hours. Risk levels are assigned based on the vessel's location in the waters and the risk level; currently, there are four levels. Different wind farms can have their XYZ values ​​set separately to create different risk levels.

[0037] In situations with poor visibility, strong winds / waves / typhoons, etc., the risk level threshold is multiplied by an environmental correction factor to lower the risk level threshold. The risk record form for ship-based wind farms is designed as follows: Early warning and response 4.1 Vessels awaiting disposal According to the wind farm's query, vessels with a risk level greater than level four require early warning and handling. You can view the vessel's risk value, risk level, handling status, current location, and suggested warning text, among other information.

[0038] 4.2 Monitoring Event Details You can view the monitoring events generated after a ship enters the wind farm monitoring area, including the location of the monitoring events, the entry and exit times of other areas, and the corresponding risk values. You can also manually broadcast suggested warning information on this page.

[0039] This invention constructs a multidimensional spatiotemporal risk integral equation based on complex dynamic and static factors, realizing the digitization of multi-factor risks and transforming risk assessment from qualitative to quantitative visualization, thus providing accurate data support for early warning decisions. This invention enables continuous monitoring, treating risk events as a complete event from the occurrence to the disappearance of a risk. Through a risk integral equation, it achieves dynamic accumulation and subtraction of risks within the monitoring area, enabling full-stage tracking and monitoring and real-time calculation of risk values. The server of this invention has strong processing performance, scalable parallel computing capabilities, and high accuracy in early warning.

[0040] Using this invention, risk quantification monitoring can be carried out on all existing wind farms in Guangdong, Guangxi, and Hainan, real-time services can be provided for 19 wind farms, and real-time navigation assistance services can be provided for more than 20,000 ships passing through the waters of wind farms. It has strong application adaptability and promotion value.

[0041] This invention provides a significant lead time for accurate risk identification: the monitoring area covers risky vessels within a 12-nautical-mile radius of the wind turbine area, expanding the average monitoring range of each wind farm to 18-20 times the previous range, increasing the number of monitored vessels by 10 times, and improving risk identification accuracy by 30 times. It can identify the risk of a vessel colliding with a wind farm within a 20-30 minute voyage, providing sufficient time and space for emergency braking for medium and large vessels, effectively ensuring the safety of ship navigation and offshore structures.

[0042] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for quantitatively analyzing the risk of a ship collision with a sea wind field, characterized by, The method comprises the following steps: S1: real-time target data is acquired, the target data comprising ship dynamic data, wind farm area data and environmental data; the ship dynamic data comprising ship MMSI, ship name, ship type, ship size, speed, heading, real-time position; the wind farm area data comprising the geographical coordinate range of wind farm ID, monitoring area, warning area and no-go area; the environmental data comprising visibility, sea state and typhoon information; S2: based on the real-time position of the ship and the wind farm area data, the area where the ship is located is determined: the area where the ship is located is determined to be the monitoring area, the warning area or the no-go area, and the value of the spatial correlation factor L is determined: when the ship is in the monitoring area, L=1, when the ship is in the warning area, L=3, and when the ship is in the no-go area, L=5; S3: the time-space risk cumulative value is calculated, and the calculation formula is: G1 / T1+G2 / T2+G3 / T3, wherein: G1 is the risk accumulation / decrement value of the ship in the monitoring area, T1 is the time of the ship from entering the monitoring area to entering the warning area; if the extended line of the ship's track does not intersect with the warning area, the increment of G1 is 0 every N seconds; if it only intersects with the warning area, the increment of G1 is 3 every N seconds; if it intersects with the no-go area, the increment of G1 is 5 every N seconds; if the ship moves away from the no-go area, the decrement of G1 is 1 every N seconds; when the ship leaves the monitoring area, G1=0; G2 is the risk accumulation / decrement value of the ship in the warning area, T2 is the time of the ship from entering the warning area to entering the no-go area; if the extended line of the ship's track intersects with the no-go area, the increment of G2 is 100 every time the ship's position is updated; if it does not intersect or is at anchor, the increment of G2 is 0; when the ship leaves the warning area, G2=0; G3 is the risk accumulation value of the ship in the no-go area, T3 is the time of the ship from entering the no-go area to leaving the no-go area; the increment of G3 is 150 every time the ship's position is updated; when the ship leaves the no-go area, G3=0; S4: Calculate the ship kinetic factor E: E = ship mass x ship speed 2 , the ship mass = ship length x ship width x ship draft, if the draft is null then default draft = 2m, if the length or width is missing then it does not participate in the calculation of E, and if the length > 450m then it does not participate in the calculation of E; S5: the ship risk attribute factor C is calculated: C=ship state coefficient×ship type coefficient; the ship state coefficient comprises: 1 for normal, 5 for deviating from the normal channel, and 8 for anchoring in a typhoon state; the ship type coefficient comprises: 10 for a dangerous chemical ship, 10 for a passenger ship, 8 for a general cargo ship, and 1 for a fishing boat; S6: based on the results of steps S2-S5, the real-time risk value R is calculated through the total risk formula: R=L×(G1 / T1+G2 / T2+G3 / T3)×E×C; S7: the environmental correction coefficient is introduced to correct the risk level threshold: in poor visibility, strong wind and rough sea, or typhoon environment, the risk level threshold of the monitoring area, the warning area and the no-go area is multiplied by a preset correction coefficient, and the preset correction coefficient is 0.6-0.8; S8: according to the corrected risk level threshold, the risk level is divided in combination with the area where the ship is located, the risk level comprises the first to fourth levels, and the pre-warning information is generated based on the risk level, and the risk quantification analysis of the ship collision with the offshore wind farm is completed.

2. The method of claim 1, wherein: In the step S1, the ship dynamic data is acquired in real time through the AIS system, and the sampling frequency is 1 time / 3 minutes; the environmental data is updated in real time through the marine weather station or satellite remote sensing data, and the update frequency is 1 time / 15 minutes.

3. The method of claim 1, wherein: In the step S3, the stop sailing judgment standard is that the current sailing speed of the ship is less than 1 knot; if the ship is in the monitoring area and stops sailing, the risk event ends, and G1 is cleared.

4. The method of claim 3, wherein: In the step S3, the signal loss processing rule is also included: if the ship is in the alert area or the forbidden sailing area and the ship position is not updated for more than 16 minutes, it is judged as signal loss; if the ship is in any area and the ship position is not updated for more than 4 hours, the current monitoring event is ended, and G1, G2 and G3 are reset.

5. The method of claim 1, wherein: In the step S8, the risk level threshold is configured by the wind farm alone, wherein: monitoring area: risk valueX1 is the fourth level, X1risk valueY1 is the third level, Y1risk valueZ1 is the second level, and risk valueZ1 is the first level; alert area: risk valueX2 is the fourth level, X2risk valueY2 is the third level, Y2risk valueZ2 is the second level, and risk valueZ2 is the first level; forbidden sailing area: risk valueX3 is the fourth level, X3risk valueY3 is the third level, Y3risk valueZ3 is the second level, and risk valueZ3 is the first level; wherein X1, Y1, Z1, X2, Y2, Z2, X3, Y3 and Z3 are positive threshold values preset by the wind farm according to the actual sea area ship density and wind turbine layout.

6. The method of claim 1, wherein: In the step S8, the early warning information includes the ship MMSI, ship name, wind farm ID, current risk value, risk level, suggested alert text and real-time position of the ship; the suggested alert text is generated based on the ship type and the area where the ship is located.

7. A system for quantitatively analyzing the risk of a ship collision with a sea wind field, characterized by: It includes: a data acquisition module for acquiring ship dynamic data, wind farm area data and environmental data in real time, and cleaning and converting the data; a region determination and spatial factor calculation module for determining the region where the ship is located based on the real-time position of the ship and the wind farm area data, and outputting a spatial correlation factor L; a time-space risk accumulation calculation module for calculating G1, G2, G3 and corresponding T1, T2, T3 according to the intersection relationship of the ship track extension line and the region, the sailing state and the stay time, and outputting (G1 / T1+G2 / T2+G3 / T3); a kinetic energy and risk attribute calculation module for calculating a kinetic energy factor E based on the ship size and sailing speed, and calculating a risk attribute factor C based on the ship state and type; a total risk calculation and level division module for executing the total risk formula in claim 1, correcting the risk level threshold with the environmental correction coefficient, dividing the risk level and generating early warning information; an early warning disposal module for displaying a list of ships to be disposed of with a risk level greater than the fourth level, providing functions of ship trajectory backtracking, risk curve viewing and manual alert information broadcasting. A storage module is configured to store a ship wind farm risk record table.

8. The system for quantifying the risk of a ship collision with a wind farm according to claim 1, wherein: The data acquisition module supports parallel data access, and can simultaneously acquire regional data of wind farms built in Guangdong, Guangxi and Hainan regions and dynamic data of ships sailing through the regions, so as to realize real-time monitoring of at least 19 wind farms and 20000 ships.

9. The system for quantifying the risk of a ship collision with a wind farm according to claim 1, wherein: The early warning and treatment module also supports visualization display of a risk curve, the risk curve takes time as a horizontal axis and risk value as a vertical axis, and a ship speed curve is synchronously superimposed, so as to intuitively present a change trend of a ship risk value with time.

10. The ship collision with sea wind field risk quantification analysis system of claim 1, wherein, The system further comprises a parallel computing module: a distributed computing architecture is adopted, and the risk values of at least 1000 ships can be simultaneously calculated, the calculation delay is less than or equal to 10 seconds, and the real-time early warning requirement is met.

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