Navigation risk management method and system based on big data

Abstract

The invention relates to the technical field of shipping management, in particular to a shipping risk management method and system based on big data, and the method comprises the steps: obtaining ships in a target sea area, collecting the driving route and operation data of each target ship, and obtaining the operation abnormality evaluation index of each target ship through processing; obtaining the navigation speed of each target ship, dividing the driving route of each target ship, collecting the environment data of each navigation road section of each target ship, and obtaining the environment abnormal characteristic value of each target ship through processing; and carrying out risk assessment on the operation of each target ship according to the environment abnormity characteristic value and the operation abnormity assessment index of each target ship, obtaining an assessment result and carrying out feedback. According to the big data-based shipping risk management method and system provided by the invention, the environmental factors and the ship operation condition are comprehensively considered, and the composite factors possibly causing the risk can be more accurately identified, so that the accuracy of risk assessment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of shipping management, and in particular to a shipping risk management method and system based on big data. Background Art

[0002] As the main mode of transportation for international trade, the shipping industry undertakes more than 90% of the world's cargo trade transportation tasks. It plays a vital role in promoting the economic development of various countries and maintaining the stability of the global supply chain. There are many risks that may be faced in the shipping process, including natural disasters, technical failures, human errors, etc. These risks may lead to cargo losses and ship damage, posing a threat to the safety of shipping.

[0003] For example, the invention patent with announcement number: CN116562621B is a method, device and computing equipment for assessing shipping risks of sea ice disasters. The method includes: obtaining a historical daily-scale sea ice thickness data set in the monitoring area; assessing the hazard of sea ice disaster-causing factors, vulnerability and exposure of disaster-bearing bodies based on the historical daily-scale sea ice thickness data set; determining the disaster-bearing capacity and risk level of the disaster-bearing body in sea ice disasters based on the hazard of sea ice disaster-causing factors, vulnerability and exposure of the disaster-bearing body; assessing the shipping risks of different types of disaster-bearing bodies under different recurrence periods based on the disaster-bearing capacity and risk level of the disaster-bearing body in sea ice disasters. This application can provide risk references for different types of ships sailing in different ice-covered sea areas, and provide references and guidance for monitoring the risk avoidance of winter shipping in ice-covered sea areas.

[0004] For example, the invention patent with publication number: CN117474331A is a shipping industry operation risk warning method, which obtains the ship's schedule information, and obtains the ship's planned arrival time, planned departure time, actual arrival time and actual departure time from the schedule information; when the actual departure time is not a null value and the actual arrival time is a null value, it enters the planned schedule judgment logic to judge whether the ship deviates from the operating range during operating hours, and sends a corresponding warning signal; when both the actual arrival time and the actual departure time are not null values, it enters the historical trajectory judgment logic to judge whether the ship stays in the supervision area during non-operating hours, and sends a corresponding warning signal; the technical solution provided by this application can effectively overcome the defect of the prior art that it cannot provide effective risk warning for the dynamic navigation behavior of ships during shipping industry operations.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it was found that the above technology has at least the following technical problems: the existing risk assessment models are often constructed based on certain assumptions and simplified conditions, which are difficult to adapt to the complex and changeable marine environment, and therefore have certain assessment errors and limitations. Summary of the invention

[0006] In view of the deficiencies of the prior art, the present invention provides a shipping risk management method and system based on big data, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides a shipping risk management method based on big data, including: obtaining ships in the target sea area, marking them as target ships, and collecting the routes of each target ship and the operating data of each target ship.

[0008] According to the operation data of each target ship, the operation abnormality assessment index of each target ship is obtained after processing.

[0009] The navigation speed of each target ship is obtained, and the route of each target ship is divided according to the navigation speed of each target ship, and marked as each navigation section of each target ship. The environmental data of each navigation section of each target ship is collected, and the environmental abnormality characteristic value of each target ship is obtained after processing. According to the environmental abnormality characteristic value of each target ship and the operation abnormality assessment index of each target ship, the operation of each target ship is risk assessed, and the assessment results are obtained and fed back.

[0010] As a further method, the operation data of each target ship is processed to obtain the abnormal operation evaluation index of each target ship, and the specific process is: the operation data of each target ship includes the operation status data of each target ship and the system operation data of each target ship;

[0011] The operating status data of each target ship, including the draft, speed and inclination of each target ship at the current time point, is extracted from the shipping database to obtain the maximum restricted draft, reference standard speed, allowable deviation speed and maximum allowable inclination, and the operating status abnormal characteristic value of each target ship is obtained by comprehensive analysis;

[0012] Obtaining a preset system monitoring cycle, deploying several monitoring time points, the system operation data of each target ship, including the engine load and energy consumption of each target ship in the current system monitoring cycle, extracting reference engine load and reference energy consumption, allowable deviation engine load and allowable deviation energy consumption from the shipping database, and comprehensively analyzing to obtain the system operation abnormality characteristic value of each target ship;

[0013] The abnormal operation characteristic values ​​of the target ships and the abnormal system operation characteristic values ​​are comprehensively analyzed to obtain the abnormal operation evaluation index of each target ship. The abnormal operation evaluation index of each target ship is used to quantitatively evaluate the abnormal operation degree of each target ship and provide a basis for the evaluation of shipping risks.

[0014] As a further method, the route of each target ship is divided according to the navigation speed of each target ship. The specific division process is: presetting a navigation time period, obtaining the reference standard navigation speed of each target ship, and multiplying the reference standard navigation speed of each target ship by the preset navigation time period to obtain the route division length of each target ship;

[0015] The route of each target ship is divided according to the route division length of each target ship, and marked as each navigation section of each target ship.

[0016] As a further method, the environmental abnormality characteristic value of each target ship is obtained through processing, and the specific process is: the environmental data of each navigation section of each target ship includes the meteorological data of each navigation section of each target ship and the sea condition data of each navigation section of each target ship;

[0017] The meteorological data of each navigation section of each target ship, including wind speed, rainfall and temperature of each navigation section of each target ship, is extracted from the shipping database to obtain the maximum allowable wind speed, maximum allowable rainfall and minimum allowable temperature, and a comprehensive analysis is performed to obtain the characteristic value of abnormal weather conditions of each navigation section of each target ship;

[0018] The sea condition data of each navigation section of each target ship, including the wave height, sea ice density and marine life density of each navigation section of each target ship, extract the critical wave height, critical sea ice density and critical marine life density from the shipping database, and comprehensively analyze to obtain the abnormal sea condition characteristic value of each navigation section of each target ship;

[0019] Comprehensively analyze the abnormal weather condition characteristic values ​​of each navigation section of each target ship and the abnormal sea condition characteristic values ​​of each navigation section of each target ship to obtain the environmental abnormality characteristic values ​​of each target ship. The environmental abnormality characteristic values ​​of each target ship are used to quantitatively evaluate the degree of environmental abnormality of each target ship, providing a basis for evaluating shipping risks.

[0020] As a further method, the operation of each target ship is risk assessed according to the abnormal environmental characteristic value of each navigation section of each target ship and the abnormal operation assessment index of each target ship. The specific assessment process is: extracting the abnormal operation assessment index threshold of each target ship from the shipping database, and comparing the abnormal operation assessment index of each target ship with the abnormal operation assessment index threshold of each target ship;

[0021] Extracting the environmental anomaly characteristic threshold of each target ship from the shipping database, and comparing the environmental anomaly characteristic value of each target ship with the environmental anomaly characteristic threshold of each target ship;

[0022] If the operation abnormality assessment index of a target ship is lower than or equal to the target ship operation abnormality assessment index threshold, and the environmental abnormality characteristic value of the target ship is lower than or equal to the environmental abnormality characteristic threshold of the target ship, the operation abnormality risk assessment of the ship is qualified; if the operation abnormality assessment index of a target ship is higher than the target ship operation abnormality assessment index threshold or the environmental abnormality characteristic value of the target ship is higher than the environmental abnormality characteristic threshold of the target ship, the operation abnormality risk assessment of the ship is unqualified.

[0023] As a further method, the abnormal operating status characteristic value of each target ship is a quantitative evaluation data obtained by comprehensively analyzing the draft, speed and inclination of each target ship at the current time point, which is used to quantitatively evaluate the degree of abnormality in the operating status of each target ship and provide a basis for evaluating the operating abnormality of each target ship.

[0024] As a further method, the characteristic value of abnormal weather conditions in each navigation section of each target ship is quantitative evaluation data obtained by comprehensive analysis of wind speed, rainfall and temperature in each navigation section of each target ship, and is used to quantitatively evaluate the degree of abnormality of weather conditions in each navigation section of each target ship, providing a basis for evaluating the abnormal environment in each navigation section of each target ship.

[0025] As a further method, the specific numerical expression of the abnormal operation evaluation index of each target ship is:

[0026]

[0027] In the formula, represents the abnormal operation evaluation index of the i-th target ship, e represents a natural constant, represents the abnormal characteristic value of the operating status of the i-th target ship, represents the system operation abnormality characteristic value of the i-th target ship, θ1 represents the ship operation abnormality impact factor corresponding to the preset ship operation status abnormality characteristic value, and θ2 represents the ship operation abnormality impact factor corresponding to the preset ship system operation abnormality characteristic value.

[0028] As a further method, the specific numerical expression of the abnormal environmental characteristic value of each target ship is:

[0029]

[0030] In the formula, represents the abnormal environmental characteristic value of the i-th target ship, represents the characteristic value of abnormal weather conditions in the rth navigation section of the i-th target ship, r represents the number of each navigation section, r=1,2,3,...,h, h represents the total number of navigation sections, represents the abnormal sea condition characteristic value of the rth navigation section of the i-th target ship, ω1 represents the environmental abnormality characteristic influencing factor corresponding to the abnormal weather condition characteristic value of the preset navigation section, ω2 represents the environmental abnormality characteristic influencing factor corresponding to the abnormal sea condition characteristic value of the preset navigation section, Represents the weight factor of the abnormal environmental characteristics of the ship corresponding to the preset r-th navigation section.

[0031] The second aspect of the present invention provides a shipping risk management system based on big data, including: a shipping data collection module for acquiring ships in a target sea area, marking them as target ships, and collecting the routes and operating data of each target ship.

[0032] The ship operation abnormality assessment module is used to obtain the operation abnormality assessment index of each target ship through processing according to the operation data of each target ship.

[0033] The navigation section environment analysis module is used to obtain the navigation speed of each target ship, divide the route of each target ship according to the navigation speed of each target ship, mark it as each navigation section of each target ship, and collect the environmental data of each navigation section of each target ship, and obtain the environmental abnormality characteristic value of each target ship after processing.

[0034] The ship operation risk assessment feedback module is used to conduct risk assessment on the operation of each target ship according to the abnormal environmental characteristic value of each target ship and the abnormal operation assessment index of each target ship, obtain the assessment result and provide feedback.

[0035] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0036] (1) The present invention provides a shipping risk management method and system based on big data, which comprehensively considers environmental factors and ship operation conditions, and can more accurately identify the complex factors that may cause risks, thereby improving the accuracy of risk assessment. It can also reveal the interaction between environmental factors and ship operation conditions, so as to better understand the formation mechanism of risks, help accurately identify where risks are, and help to more reasonably allocate rescue resources, maintenance resources and human resources, thereby improving resource utilization efficiency.

[0037] (2) The present invention can better identify and manage high-risk areas in the route through the fine division of the navigation section, take corresponding risk control measures, and thus reduce the risk of accidents. Clear division of navigation sections helps to quickly locate the position of the ship in an emergency and improve the speed and efficiency of emergency response. For ships of different speeds, targeted emergency plans can be formulated to improve the pertinence of emergency treatment.

[0038] (3) The present invention helps to quickly find the cause of the fault and improve the accuracy of fault diagnosis by analyzing the abnormal characteristic values ​​of ship operation. Accurate fault diagnosis helps to reasonably arrange maintenance resources and improve maintenance efficiency. By analyzing the abnormal characteristic values ​​of operation, equipment failures, operating errors and other problems can be discovered in advance to avoid accidents. Early warning helps to reduce direct and indirect economic losses caused by accidents.

[0039] (4) By combining the abnormal characteristic values ​​of weather and sea conditions, the present invention can more comprehensively assess the risks of ships in specific environments, including potential threats such as storms, marine life, and floating ice. By real-time monitoring and evaluating the abnormal characteristic values ​​of the environment, it is possible to warn in advance of the bad weather and sea conditions that the ship may encounter, providing the ship with sufficient time to take evasive or safety measures. At the same time, the abnormal characteristic values ​​of the environment can also help ships plan safer routes, avoid high-risk areas, and reduce navigation risks caused by environmental factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0041] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0042] Figure 2 It is a schematic diagram of system module connection of the present invention.

[0043] Figure 3 It is a schematic diagram of the functional relationship between the abnormal weather condition characteristic value of the target ship's navigation section and the abnormal environment characteristic value of the target ship involved in an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0045] Reference Figure 1 As shown, the first aspect of the present invention provides a shipping risk management method based on big data, including: acquiring ships in a target sea area, marking them as target ships, and collecting the routes and operating data of each target ship.

[0046] It should be explained that in the target sea area, the ships that can obtain routes and be marked as target ships include commercial cargo ships, passenger ships, warships and law enforcement ships. Commercial cargo ships are the main force of maritime transportation, and they carry a large amount of goods for international trade. Such ships are usually equipped with advanced navigation and communication systems, which can report their position, speed, heading and other key information in real time. Commercial cargo ships need to sail according to the predetermined routes to ensure that the goods can be delivered to the destination safely and on time. Passenger ships are mainly used to carry passengers for sea travel. Similar to commercial cargo ships, passenger ships also have perfect navigation and communication systems to ensure the safety of passengers and the smooth sailing. Passenger ships usually sail along fixed routes to provide stable services for passengers. Warships and law enforcement ships are important forces for maritime security and national defense. They not only have strong navigation capabilities, but are also equipped with advanced detection and communication equipment, which can grasp the dynamic information in the sea area in real time. Although the routes of warships and law enforcement ships may be more flexible and changeable, they also need clear route planning when performing tasks to ensure the smooth completion of the mission.

[0047] In a specific embodiment, the above-mentioned target ships can be divided into three types according to their scale, including ultra-large ships, large ships and medium-sized ships, among which the deadweight tonnage of ultra-large ships is above 50,000 tons, the deadweight tonnage of large ships exceeds 10,000 tons, and the deadweight tonnage of medium-sized ships is between 3,000 tons and 10,000 tons.

[0048] According to the operation data of each target ship, the operation abnormality assessment index of each target ship is obtained after processing.

[0049] Specifically, according to the operation data of each target ship, the operation abnormality assessment index of each target ship is obtained through processing, and the specific process is as follows: the operation data of each target ship includes the operation status data of each target ship and the system operation data of each target ship;

[0050] The operating status data of each target ship, including the draft, speed and inclination of each target ship at the current time point, is extracted from the shipping database to obtain the maximum restricted draft, reference standard speed, allowable deviation speed and maximum allowable inclination, and a comprehensive analysis is performed to obtain the abnormal characteristic value of the operating status of each target ship.

[0051] The target ships in the same size range are divided into the same type of ships, and a mapping set of the same type of ships and their corresponding maximum restricted draft, reference standard speed, and maximum allowable inclination is constructed. The target ship is input to obtain the type of the target ship, and the maximum restricted draft, reference standard speed, and maximum allowable inclination of the target ship are obtained according to the mapping set.

[0052] It should be explained that professional ship design manuals usually contain design parameters and performance standards for various types of ships, such as the ship's displacement, speed, stability, structural strength, etc. The reference standard speed of the target ship refers to the average speed of various types of ships operating on the route within a preset historical period.

[0053] It should be understood that the abnormal operating status characteristic value of each target ship is a quantitative evaluation data obtained by comprehensively analyzing the draft, speed and inclination of each target ship at the current time point, which is used to quantitatively evaluate the degree of abnormality in the operating status of each target ship and provide a basis for evaluating the operating abnormality of each target ship.

[0054] In a specific embodiment, the numerical expression of the abnormal characteristic value of the operating status of each target ship is:

[0055]

[0056] In the formula, represents the abnormal characteristic value of the running state of the i-th target ship, i represents the number of each target ship, i=1,2,3,...,m, m represents the total number of target ships, C i represents the draft of the i-th target ship at the current time point, represents the maximum restricted draft depth of the i-th target ship, H i represents the speed of the i-th target ship at the current time point, represents the reference standard speed of the i-th target ship, ΔH represents the allowable deviation speed, Q i represents the inclination of the i-th target ship at the current time point, represents the maximum allowable inclination of the i-th target ship, σ1 represents the abnormal impact factor of the ship's operating state corresponding to the preset draft depth, σ2 represents the abnormal impact factor of the ship's operating state corresponding to the preset speed, and σ3 represents the abnormal impact factor of the ship's operating state corresponding to the preset inclination.

[0057] It should be understood that, from the above embodiments, it can be concluded that when the draft of the target ship is greater, the inclination of the target ship is greater, and the difference between the speed of the target ship at the current time point and the reference standard speed is greater, the corresponding abnormal characteristic value of the operating status of the target ship indicates that the degree of abnormality of the operating status of the target ship is greater.

[0058] It should be explained that, in the present embodiment, σ1 is the abnormal impact factor of the ship's operating state corresponding to the preset draft depth, which represents the numerical value of the degree of influence of the unit value of the draft depth on the ship's operating state. When used, the abnormal impact factor of the ship's operating state corresponding to the draft depth can be directly obtained from the shipping database, and the corresponding relationship can be a pre-set mapping relationship. For example, the draft of the target ship at the current time point and the abnormal impact factor of the ship's operating state corresponding to the draft depth preset in the shipping database form a mapping set, and the real-time draft is input into the mapping set to obtain the abnormal impact factor of the ship's operating state corresponding to the draft depth. The mapping relationship can be one-to-one or many-to-one.

[0059] It should be explained that in this embodiment, σ2 is the abnormal impact factor of the ship's operating state corresponding to the preset speed, which represents the numerical value of the influence degree of the speed unit value on the ship's operating state. When used, the abnormal impact factor of the ship's operating state corresponding to the speed can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the speed of the target ship at the current time point and the abnormal impact factor of the ship's operating state corresponding to the preset speed in the shipping database form a mapping set, and the real-time speed is input into the mapping set to obtain the abnormal impact factor of the ship's operating state corresponding to the speed. The mapping relationship can be one-to-one or many-to-one.

[0060] It should be explained that in the present embodiment, σ3 is the abnormal impact factor of the ship's operating state corresponding to the preset inclination, which represents the numerical value of the degree of influence of the unit value of the inclination on the ship's operating state. When used, the abnormal impact factor of the ship's operating state corresponding to the inclination can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the inclination of the target ship at the current time point and the abnormal impact factor of the ship's operating state corresponding to the preset inclination in the shipping database form a mapping set, and the real-time inclination is input into the mapping set to obtain the abnormal impact factor of the ship's operating state corresponding to the inclination, and the mapping relationship can be one-to-one or many-to-one.

[0061] It should be explained that the above-mentioned influencing factors are all extracted from the shipping database, and the value range is between 0 and 1.

[0062] It should be explained that the draft depth of the ship in this embodiment can be visually estimated by the draft mark (DraftMarks) of the ship. Some ships are equipped with an automatic identification system that can report the real-time draft depth. The draft depth can also be automatically measured by using an ultrasonic draft sensor. The speed of the ship can also obtain the real-time speed of the ship through the automatic identification system. For example, the ship's automatic identification system (Automatic Identification System) can provide a variety of information about the ship in real time, including but not limited to the name of the ship, heading, speed, and the position (latitude and longitude) of the ship. The speed can also be measured by the equipped speedometer. The inclination of the ship can be measured using an inclinometer (List Indicator). At the same time, modern ships may be equipped with a stability monitoring system that can measure the inclination in real time. The inclination can also be calculated by sensor data in the integrated control system of the onboard computer system.

[0063] It should be explained that, in general, the deeper the draft of a ship, the greater the resistance, and the speed may be reduced. The draft depth also affects the maneuverability of the ship. Too deep a draft may make the ship inflexible in turning. At the same time, the inclination of the ship affects the draft depth. Here, the inclination of the ship specifically refers to the longitudinal inclination of the ship. If the ship is tilted, the reading of the draft mark may be inaccurate. Improper loading of the ship or cargo movement may cause tilting, which in turn affects the draft depth. The inclination of the ship also affects the speed and stability of the ship. Excessive inclination may cause the speed of the ship to decrease and even affect the control of the ship. When sailing at high speed, the ship may tilt due to hydrodynamic effects, which needs to be controlled by adjusting the buoyancy of the ship. Specifically, the center of gravity of the ship can be kept within the design range and the buoyancy can be improved by optimizing the arrangement of cargo and equipment on board. This requires that balance be considered when loading cargo to avoid weight concentration on one side. It is also possible to use adjustable ballast or change the internal mass distribution of the hull to achieve dynamic adjustment of the center of gravity position to adapt to different sea conditions and loading conditions. The buoyancy and stability of the ship can also be adjusted through precise ballast water discharge and injection control. When sailing at high speed, the distribution of ballast water needs to be adjusted in time according to the inclination of the ship. Bilge keels or anti-roll fins can also be installed on both sides of the hull to reduce the roll amplitude of the ship and improve the buoyancy performance by generating lateral forces opposite to the waves. Alternatively, an anti-roll tank can be set in the hull to control the flow of water in the tank to generate a moment opposite to the roll of the ship to achieve the purpose of anti-roll. This embodiment can make the evaluation of the operating status of each target ship more comprehensive and accurate by comprehensively analyzing the draft, speed and inclination of the ship.

[0064] Obtaining a preset system monitoring cycle, deploying several monitoring time points, the system operation data of each target ship, including the engine load and energy consumption of each target ship in the current system monitoring cycle, extracting reference engine load and reference energy consumption, allowable deviation engine load and allowable deviation energy consumption from the shipping database, and comprehensively analyzing to obtain the system operation abnormality characteristic value of each target ship;

[0065] A mapping set of the same type of ships and their corresponding reference engine loads and reference energy consumption is constructed, a target ship is input, the type of the target ship is obtained, and the reference engine load and reference energy consumption of the target ship are obtained according to the mapping set.

[0066] It should be understood that the system operation abnormality characteristic value of each target ship is a quantitative evaluation data obtained by comprehensive analysis of the engine load and energy consumption of each target ship in the current system monitoring cycle, which is used to quantitatively evaluate the degree of system operation abnormality of each target ship and provide a basis for evaluating the operation abnormality of each target ship.

[0067] In a specific embodiment, the numerical expression of the system operation abnormality characteristic value of each target ship is:

[0068]

[0069] In the formula, represents the abnormal characteristic value of the system operation of the i-th target ship, F i represents the engine load of the i-th target ship in the current system monitoring cycle, N i represents the energy consumption of the i-th target ship in the current system monitoring cycle, F 0 represents the reference engine load of the i-th target ship, ΔF represents the allowable deviation engine load, N 0 represents the reference energy consumption of the i-th target ship, ΔN represents the allowable deviation energy consumption, ρ1 represents the abnormal operation impact factor of the ship system corresponding to the preset engine load, and ρ2 represents the abnormal operation impact factor of the ship system corresponding to the preset energy consumption.

[0070] It should be understood that, from the above embodiments, when the deviation value between the engine load of the current system monitoring cycle and the reference engine load is larger, and the deviation value between the energy consumption of the current system monitoring cycle and the reference energy consumption is also larger, the corresponding target ship's system operation abnormality characteristic value is larger, indicating that the greater the degree of abnormality in the ship's system operation, the greater the risk of system failure.

[0071] It should be understood that, in this embodiment, the engine load and energy consumption of the current system monitoring cycle refer to the engine load and energy consumption in the time period from the last time monitoring point to the current time monitoring point.

[0072] It should be explained that, in the present embodiment, ρ1 is the ship system operation abnormality impact factor corresponding to the preset engine load, which represents the numerical value of the influence degree of the unit value of the engine load on the ship system operation. When used, the ship system operation abnormality impact factor corresponding to the engine load can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the engine load of the target ship at the current time point and the ship system operation abnormality impact factor corresponding to the engine load preset in the shipping database form a mapping set, and the real-time engine load is input into the mapping set to obtain the ship system operation abnormality impact factor corresponding to the engine load, wherein the mapping relationship can be one-to-one or many-to-one.

[0073] It should be explained that in this embodiment, ρ2 is the abnormal operation impact factor of the ship system corresponding to the preset energy consumption, which represents the numerical value of the influence degree of the unit value of energy consumption on the operation of the ship system. When used, the abnormal operation impact factor of the ship system corresponding to the energy consumption can be directly obtained from the shipping database, and the corresponding relationship can be a pre-set mapping relationship. For example, the energy consumption of the target ship at the current time point and the abnormal operation impact factor of the ship system corresponding to the energy consumption preset in the shipping database form a mapping set, and the real-time energy consumption is input into the mapping set to obtain the abnormal operation impact factor of the ship system corresponding to the energy consumption. The mapping relationship can be one-to-one or many-to-one.

[0074] It should be explained that the above-mentioned influencing factors are all extracted from the shipping database, and the value range is between 0 and 1.

[0075] It should be explained that in this embodiment, the engine load can utilize the engine room monitoring system equipped by modern ships to monitor the engine load, temperature, vibration and other parameters in real time. The load can also be measured by sensors installed on the engine, such as pressure sensors and torque sensors. Ships include fuel-driven and electric-driven ships. The energy consumption of fuel-driven ships can be obtained by real-time monitoring of the fuel consumption monitoring system, and flow meters or other sensors can also be used to monitor the fuel consumption. For electric-driven ships, an electric energy meter can be used to monitor power consumption.

[0076] It needs to be explained that when the engine load increases, it usually means that the ship needs more power to maintain or increase the speed, which will lead to increased fuel consumption. Within a certain range, the engine load and fuel consumption are linearly related, that is, as the load increases, the fuel consumption also increases accordingly. The engine operates at different efficiencies under different loads. When operating within the optimal load range, the engine has the highest fuel efficiency. Too low or too high loads may reduce the efficiency of the engine and lead to increased fuel consumption. At the same time, long-term operation at excessive loads may accelerate engine wear, shorten its life, and may lead to increased maintenance costs. Comprehensive analysis of the engine load and energy consumption of each target ship can make the assessment of system operation abnormalities of each target ship more comprehensive and accurate. It can also help ship operators understand the performance of the ship, optimize the operating status of the engine, reduce unnecessary energy consumption, and extend the service life of the engine.

[0077] The abnormal operation characteristic values ​​of the target ships and the abnormal system operation characteristic values ​​are comprehensively analyzed to obtain the abnormal operation evaluation index of each target ship. The abnormal operation evaluation index of each target ship is used to quantitatively evaluate the abnormal operation degree of each target ship and provide a basis for the evaluation of shipping risks.

[0078] In a specific embodiment, the numerical expression of the abnormal operation evaluation index of each target ship is:

[0079]

[0080] In the formula, represents the abnormal operation evaluation index of the i-th target ship, e represents a natural constant, represents the abnormal characteristic value of the operating status of the i-th target ship, represents the system operation abnormality characteristic value of the i-th target ship, θ1 represents the ship operation abnormality impact factor corresponding to the preset ship operation status abnormality characteristic value, and θ2 represents the ship operation abnormality impact factor corresponding to the preset ship system operation abnormality characteristic value.

[0081] It should be understood that, from the above embodiments, when the abnormal characteristic value of the target ship's operating state is larger and the abnormal characteristic value of the target ship's system operation is also larger, the corresponding target ship operation abnormality assessment index is larger, indicating that the greater the degree of abnormal operation of the target ship, the greater the probability of risk occurrence.

[0082] Table 1 Example of target ship operation abnormality assessment index data

[0083]

[0084] It should be explained that, in this embodiment, the ship operation abnormality impact factor corresponding to the abnormal characteristic value of the ship's operating state is set to 0.5, and the ship operation abnormality impact factor corresponding to the abnormal characteristic value of the ship's system operation is set to 0.3.

[0085] It should be explained that in the present embodiment, θ1 is the ship operation abnormality impact factor corresponding to the preset ship operation status abnormal characteristic value, which represents the numerical value of the impact degree of the ship operation abnormality characteristic value on the ship operation. When used, the ship operation abnormality impact factor corresponding to the ship operation abnormal characteristic value can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the target ship's operation status abnormality characteristic value and the ship operation abnormality impact factor corresponding to the ship operation abnormality characteristic value preset in the shipping database form a mapping set, and the real-time ship operation status abnormality characteristic value is input into the mapping set to obtain the ship operation abnormality impact factor corresponding to the ship operation abnormality characteristic value, and the mapping relationship can be one-to-one or many-to-one.

[0086] It should be explained that, in the present embodiment, θ2 is a ship operation abnormality impact factor corresponding to a preset ship system operation abnormality characteristic value, which represents a numerical value of the degree of impact of the ship system operation abnormality characteristic value on the ship operation. When used, the ship operation abnormality impact factor corresponding to the ship system operation abnormality characteristic value can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the target ship system operation abnormality characteristic value and the ship operation abnormality impact factor corresponding to the ship system operation abnormality characteristic value preset in the shipping database form a mapping set, and the real-time ship system operation abnormality characteristic value is input into the mapping set to obtain the ship operation abnormality impact factor corresponding to the ship system operation abnormality characteristic value, wherein the mapping relationship can be one-to-one or many-to-one.

[0087] It should be explained that the above-mentioned influencing factors are all extracted from the shipping database, and the value range is between 0 and 1.

[0088] It should be explained that, in this embodiment, through real-time monitoring and abnormal evaluation of the ship's operating status, potential safety hazards can be discovered in time, corresponding preventive measures can be taken, and the risk of accidents can be reduced. The abnormal operation evaluation index in this embodiment helps ship managers understand the overall operating status of the ship, reasonably formulate maintenance plans, and improve the efficiency and economic benefits of the ship. By analyzing the abnormal operation characteristic values ​​of the ship, it is also helpful to find the links of energy waste and abnormal emissions, so as to take effective measures to reduce energy consumption and pollutant emissions. By analyzing the abnormal operation characteristic values, equipment failures, operating errors and other problems can be discovered in advance to avoid accidents. Early warning helps to reduce direct and indirect economic losses caused by accidents. By analyzing the abnormal characteristic values, the cause of the fault can also be quickly found to improve the accuracy of fault diagnosis. Accurate diagnosis of faults helps to reasonably arrange maintenance resources and improve maintenance efficiency. The abnormal operation evaluation index also helps to achieve the refinement of ship management and improve the management level. By analyzing the operation data, it can also promote the construction of ship management informatization and improve the management level.

[0089] The navigation speed of each target ship is obtained, and the route of each target ship is divided according to the navigation speed of each target ship, and marked as each navigation section of each target ship. The environmental data of each navigation section of each target ship is collected, and the environmental abnormality characteristic value of each target ship is obtained after processing. According to the environmental abnormality characteristic value of each target ship and the operation abnormality assessment index of each target ship, the operation of each target ship is risk assessed, and the assessment results are obtained and fed back.

[0090] Specifically, the route of each target ship is divided according to the sailing speed of each target ship. The specific division process is: preset a sailing time period, and obtain the reference standard speed of each target ship, multiply the reference standard speed of each target ship by the preset sailing time period, and obtain the route division length of each target ship.

[0091] The route of each target ship is divided according to the route division length of each target ship, and marked as each navigation section of each target ship.

[0092] It needs to be explained that it is difficult for the target ships sailing on the sea to reach the destination in a short time, so a sailing time period is preset, specifically 10 minutes, and the reference standard speed of each target ship is obtained. The reference standard speed of each target ship is multiplied by the preset sailing time period to obtain the route division length of each target ship.

[0093] It should be explained that the above process can better identify and manage high-risk areas in the route and take corresponding risk control measures through the fine division of the navigation sections. Clear division of navigation sections helps to quickly locate the position of the ship in an emergency and improve the speed and efficiency of emergency response. Reasonable route division helps ships choose the best route according to cargo demand, reduce unnecessary detours, and improve cargo efficiency. The clear division of navigation sections helps regulatory authorities to monitor and manage ships more effectively. By adjusting the navigation sections, it can ensure that the ship travels in suitable sea conditions and reduce navigation risks caused by bad weather or sea conditions. For goods that require special care, such as dangerous goods, their safe transportation can also be ensured by adjusting the navigation sections.

[0094] Furthermore, the environmental abnormality characteristic value of each target ship is obtained through processing, and the specific process is: the environmental data of each navigation section of each target ship includes the meteorological data of each navigation section of each target ship and the sea condition data of each navigation section of each target ship.

[0095] The meteorological data of each navigation section of each target ship, including the wind speed, rainfall and temperature of each navigation section of each target ship, is extracted from the shipping database to obtain the maximum allowable wind speed, maximum allowable rainfall and minimum allowable temperature, and a comprehensive analysis is performed to obtain the characteristic values ​​of abnormal weather conditions in each navigation section of each target ship.

[0096] A mapping set of the same type of ship and its corresponding maximum allowable wind speed, maximum allowable rainfall and minimum allowable temperature is constructed, and a target ship is input to obtain the type of the target ship. The maximum allowable wind speed, maximum allowable rainfall and minimum allowable temperature of the target ship are obtained according to the mapping set.

[0097] It should be understood that the characteristic value of abnormal weather conditions in each navigation section of each target ship is quantitative evaluation data obtained through comprehensive analysis of wind speed, rainfall and temperature in each navigation section of each target ship, and is used to quantitatively evaluate the degree of abnormality of weather conditions in each navigation section of each target ship, providing a basis for evaluating the abnormal environment in each navigation section of each target ship.

[0098] In a specific embodiment, the numerical expression of the abnormal weather condition characteristic value of each navigation section of each target ship is:

[0099]

[0100] In the formula, represents the characteristic value of abnormal weather conditions in the rth navigation section of the i-th target ship, r represents the number of each navigation section, r=1,2,3,...,h, h represents the total number of navigation sections, P irrepresents the wind speed of the rth navigation section of the i-th target ship, represents the maximum permissible wind speed of the i-th target ship, M ir represents the rainfall in the rth navigation section of the i-th target ship, represents the maximum allowable rainfall for the i-th target ship, W ir The temperature of the rth navigation section of the i-th target ship, represents the minimum allowable temperature of the i-th target ship, Indicates the impact factor of abnormal weather conditions on the navigation section corresponding to the preset wind speed. Indicates the impact factor of abnormal weather conditions on the navigation section corresponding to the preset rainfall. Indicates the impact factor of abnormal weather conditions on the navigation section corresponding to the preset temperature.

[0101] It should be understood that, from the above embodiments, it can be concluded that when the wind speed in each navigation section of the target ship is greater, the rainfall in each navigation section of the target ship is greater, and the temperature in each navigation section of the target ship is greater, the corresponding abnormal weather condition characteristic value of each navigation section of the target ship will be greater, indicating that the greater the degree of abnormality of the weather conditions in each navigation section of the target ship, the greater the impact on the ship's navigation.

[0102] It should be explained that in this embodiment It is the influence factor of abnormal weather conditions in the navigation section corresponding to the preset wind speed, which represents the numerical value of the influence degree of the unit value of wind speed on the abnormal weather conditions in the navigation section. When used, the influence factor of abnormal weather conditions in the navigation section corresponding to the wind speed can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the wind speed of the navigation section of the target ship and the influence factor of abnormal weather conditions in the navigation section corresponding to the preset wind speed in the shipping database form a mapping set, and the real-time wind speed is input into the mapping set to obtain the influence factor of abnormal weather conditions in the navigation section corresponding to the wind speed. The mapping relationship can be one-to-one or many-to-one.

[0103] It should be explained that in this embodiment It is the influence factor of abnormal weather conditions in the navigation section corresponding to the preset rainfall, which represents the numerical value of the influence degree of the unit value of rainfall on the abnormal weather conditions in the navigation section. When used, the influence factor of abnormal weather conditions in the navigation section corresponding to the rainfall can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the rainfall in the navigation section of the target ship and the influence factors of abnormal weather conditions in the navigation section corresponding to the preset rainfall in the shipping database form a mapping set, and the real-time rainfall is input into the mapping set to obtain the influence factor of abnormal weather conditions in the navigation section corresponding to the rainfall. The mapping relationship can be one-to-one or many-to-one.

[0104] It should be explained that in this embodiment It is the influence factor of abnormal weather conditions in the navigation section corresponding to the preset temperature, which represents the numerical value of the influence degree of the unit value of temperature on the abnormal weather conditions in the navigation section. When used, the influence factor of abnormal weather conditions in the navigation section corresponding to the temperature can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the temperature of the navigation section of the target ship and the influence factors of abnormal weather conditions in the navigation section corresponding to the temperature preset in the shipping database form a mapping set, and the real-time temperature is input into the mapping set to obtain the influence factor of abnormal weather conditions in the navigation section corresponding to the temperature. The mapping relationship can be one-to-one or many-to-one.

[0105] It should be explained that the above-mentioned influencing factors are all extracted from the shipping database, and the value range is between 0 and 1.

[0106] It should be explained that modern ships are usually equipped with weather fax machines, satellite communication equipment, etc., which can receive real-time weather data, including wind speed, rainfall and temperature. At the same time, the ship's radar and navigation system can also provide certain meteorological information. The size of the wind speed directly affects the speed and course of the ship. Side winds or headwinds will slow down the ship and increase the sailing time; tailwinds can speed up the ship. Strong winds may also cause the ship to lose control, especially when encountering storms at sea, the risk is greater. The amount of rainfall will affect visibility, especially in blizzards, where reduced visibility will increase the risk of navigation. Heavy rain and water accumulation may increase the load of the ship and affect the stability of the ship. When the temperature is low, the seawater may freeze, affecting the choice of route. Low temperature may also affect the operating efficiency of the ship's machinery and crew. The relationship between these three factors is mutually influential. For example, high wind speed may lead to lower temperature and accompanied by rainfall; while lower temperature may also lead to increased wind speed and rainfall. Comprehensive analysis can make the assessment of abnormal weather conditions in each navigation section more comprehensive.

[0107] The sea condition data of each navigation section of each target ship, including the wave height, sea ice density and marine life density of each navigation section of each target ship, extract the critical wave height, critical sea ice density and critical marine life density from the shipping database, and comprehensively analyze to obtain the abnormal sea condition characteristic value of each navigation section of each target ship;

[0108] A mapping set of the same type of ship and its corresponding critical wave height, critical sea ice density and critical marine life density is constructed, and a target ship is input to obtain the type of the target ship. The critical wave height, critical sea ice density and critical marine life density of the target ship are obtained according to the mapping set.

[0109] It should be understood that the abnormal sea condition characteristic value of each navigation section of each target ship is a quantitative evaluation data obtained by comprehensively analyzing the wave height, sea ice density and marine life density of each navigation section of each target ship, and is used to quantitatively evaluate the degree of abnormal sea condition in each navigation section of each target ship, providing a basis for evaluating the abnormal environment of each navigation section of each target ship.

[0110] In a specific expression, the numerical expression of the abnormal sea condition characteristic value of each navigation section of each target ship is:

[0111]

[0112] In the formula, represents the abnormal characteristic value of the sea condition in the rth navigation section of the i-th target ship, J ir represents the wave height of the rth navigation section of the i-th target ship, Z ir represents the sea ice density of the rth navigation section of the i-th target ship, S ir represents the density of marine organisms in the rth navigation section of the i-th target ship, represents the critical wave height of the i-th target ship, represents the critical sea ice density of the i-th target ship, represents the critical marine biological density of the i-th target ship, μ1 represents the abnormal sea condition impact factor of the navigation section corresponding to the preset wave height, μ2 represents the abnormal sea condition impact factor of the navigation section corresponding to the preset sea ice density, and μ3 represents the abnormal sea condition impact factor of the navigation section corresponding to the preset marine biological density.

[0113] It should be understood that, from the above embodiments, it can be concluded that when the wave height exceeds the limit value in each navigation section of the target ship, the sea ice density exceeds the limit value in each navigation section of the target ship, and the marine life density exceeds the limit value in each navigation section of the target ship, the corresponding abnormal sea condition characteristic value of each navigation section of the target ship will be greater, indicating that the greater the degree of abnormal sea condition in each navigation section of the target ship, the greater the impact on the ship's navigation.

[0114] It should be explained that, in the present embodiment, μ1 is the abnormal sea condition impact factor of the navigation section corresponding to the preset wave height, which represents the numerical value of the influence degree of the unit value of the wave height on the sea condition of the navigation section. When used, the abnormal sea condition impact factor of the navigation section corresponding to the wave height can be directly obtained from the shipping database, and the corresponding relationship can be a pre-set mapping relationship. For example, the wave height of the navigation section of the target ship and the abnormal sea condition impact factor of the navigation section corresponding to the wave height preset in the shipping database form a mapping set, and the real-time wave height is input into the mapping set to obtain the abnormal sea condition impact factor of the navigation section corresponding to the wave height, and the mapping relationship can be one-to-one or many-to-one.

[0115] It should be explained that in the present embodiment, μ2 is the abnormal sea condition impact factor of the navigation section corresponding to the preset sea ice density, which represents the numerical value of the influence degree of the unit value of the sea ice density on the sea condition of the navigation section. When used, the abnormal sea condition impact factor of the navigation section corresponding to the sea ice density can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the sea ice density of the navigation section of the target ship and the abnormal sea condition impact factor of the navigation section corresponding to the sea ice density preset in the shipping database form a mapping set, and the real-time sea ice density is input into the mapping set to obtain the abnormal sea condition impact factor of the navigation section corresponding to the sea ice density. The mapping relationship can be one-to-one or many-to-one.

[0116] It should be explained that in the present embodiment, μ3 is the abnormal sea condition impact factor of the navigation section corresponding to the preset marine biological density, which represents the numerical value of the influence degree of the unit value of the marine biological density on the sea condition of the navigation section. When used, the abnormal sea condition impact factor of the navigation section corresponding to the marine biological density can be directly obtained from the shipping database, and the corresponding relationship can be a pre-set mapping relationship. For example, the marine biological density of the navigation section of the target ship and the abnormal sea condition impact factor of the navigation section corresponding to the marine biological density preset in the shipping database form a mapping set, and the real-time marine biological density is input into the mapping set to obtain the abnormal sea condition impact factor of the navigation section corresponding to the marine biological density. The mapping relationship can be one-to-one or many-to-one.

[0117] It should be explained that the above-mentioned influencing factors are all extracted from the shipping database, and the value range is between 0 and 1.

[0118] It should be explained that the sea wave data can be obtained in real time through coastal buoys, wave riders and other observation equipment, and the sea ice density can be estimated by detecting microwave signals reflected by sea ice using satellites such as NOAA, RADARSAT and MODIS. It is also possible to use ship-based or work platform radars for observation, and extract sea ice information in combination with digital image processing technology. It is also possible to use unmanned aerial vehicles and other equipment for on-site observation to obtain more accurate sea ice density data. The density of marine organisms can be obtained by acoustically detecting marine organisms using equipment such as echosounders, and analyzing the number and distribution of organisms through echo signals. The wave height is the highest wave height within the first 5 minutes of 10 square meters around each navigation section on the route of each target ship, the sea ice density is the maximum sea ice density of 50 square meters around each navigation section on the route of each target ship, and the marine organism density is the maximum marine organism density of 50 square meters around each navigation section on the route of each target ship.

[0119] It should be explained that in this embodiment, the critical wave height refers to the maximum wave height that the ship can withstand. Waves exceeding the critical wave height will cause the ship to shake more severely, affect navigation stability, and increase the risk of capsizing. Extreme waves may also damage the ship structure and affect navigation safety. Large waves will increase the resistance of the ship during navigation, reduce the navigation speed, and increase fuel consumption. In order to maintain stability, the ship may need to adjust its course or slow down, further affecting the voyage and transportation efficiency. The ship may choose a safer route according to the wave forecast to avoid the large wave area, thereby changing the original navigation plan. The critical sea ice density refers to the maximum sea ice density that the ship can pass smoothly. When the critical sea ice density is exceeded, the ship is prone to sea ice collision, resulting in damage to the hull or stranding. Ice may also damage key components such as the propeller and rudder of the ship, affecting navigation safety. Severe sea ice may cause the channel to be blocked and the ship cannot pass. The critical marine organism density refers to the maximum marine organism density that the ship can pass smoothly. When the critical marine organism density is exceeded, the ship may be hit or entangled by marine organisms, resulting in damage to the hull or obstruction of navigation. Ships also need to avoid causing unnecessary harm to marine life during navigation, especially in ecologically sensitive areas. When the density of marine life is abnormal, ships may need to adjust their speed or route to reduce the impact on the marine ecology.

[0120] It needs to be explained that the height of waves is mainly affected by multiple factors such as wind, tide, and seabed topography. When sailing in ice areas, waves may impact sea ice, causing it to break, drift, or re-accumulate, thus affecting the density of sea ice. Generally speaking, large waves may aggravate the breakup and drift of sea ice, resulting in a decrease in the density of sea ice; while in relatively calm waters, sea ice may be more stable and have a higher density. The impact of wave height on the density of marine organisms is mainly reflected in the disturbance of the habitat of marine organisms. Large waves may destroy the habitat and breeding environment of marine organisms, resulting in a decrease in the density of organisms. At the same time, waves may also bring nutrients from the deep to the surface, promoting the growth of plankton, thereby indirectly affecting the density of marine organisms. However, this impact usually has regional and seasonal differences. Sea ice provides habitats and breeding places for many marine organisms, such as seals and penguins in polar regions. Changes in sea ice density will directly affect the living environment and number of these organisms. In addition, sea ice also indirectly affects the distribution and density of marine organisms by affecting ocean circulation and nutrient distribution. Comprehensive analysis can make the assessment of abnormal sea conditions in each navigation section more comprehensive.

[0121] Comprehensively analyze the abnormal weather condition characteristic values ​​of each navigation section of each target ship and the abnormal sea condition characteristic values ​​of each navigation section of each target ship to obtain the environmental abnormality characteristic values ​​of each target ship. The environmental abnormality characteristic values ​​of each target ship are used to quantitatively evaluate the degree of environmental abnormality of each target ship, providing a basis for evaluating shipping risks.

[0122] In a specific embodiment, the numerical expression of the environmental anomaly characteristic value of each target ship is:

[0123]

[0124] In the formula, represents the abnormal environmental characteristic value of the i-th target ship, represents the characteristic value of abnormal weather conditions in the rth navigation section of the i-th target ship, represents the abnormal sea condition characteristic value of the rth navigation section of the i-th target ship, ω1 represents the environmental abnormality characteristic influencing factor corresponding to the abnormal weather condition characteristic value of the preset navigation section, ω2 represents the environmental abnormality characteristic influencing factor corresponding to the abnormal sea condition characteristic value of the preset navigation section, Represents the weight factor of the abnormal environmental characteristics of the ship corresponding to the preset r-th navigation section.

[0125] It should be understood that, from the above embodiments, when the abnormal weather condition characteristic value of each navigation section of the target ship is larger, and the abnormal sea condition characteristic value of each navigation section of the target ship is larger, the corresponding abnormal environment characteristic value of the target ship is larger, indicating that the greater the degree of abnormality of the external environment, the greater the impact on shipping.

[0126] In a specific embodiment, taking a navigation section as an example, the environmental abnormality characteristic impact factor corresponding to the abnormal weather condition characteristic value of the navigation section is set to 0.5, the environmental abnormality characteristic impact factor corresponding to the abnormal sea condition characteristic value of the navigation section is set to 0.7, and the environmental abnormality characteristic weight factor of the ship corresponding to the navigation section is set to 1.0.

[0127] It should be understood that if Figure 3 As shown, curve a represents the relationship between the abnormal weather condition characteristic value of the target ship's navigation section and the abnormal environment characteristic value of the target ship when the abnormal sea condition characteristic value of the target ship's navigation section is 0.1, curve b represents the relationship between the abnormal weather condition characteristic value of the target ship's navigation section and the abnormal environment characteristic value of the target ship when the abnormal sea condition characteristic value of the target ship's navigation section is 0.3, and curve c represents the relationship between the abnormal weather condition characteristic value of the target ship's navigation section and the abnormal environment characteristic value of the target ship when the abnormal sea condition characteristic value of the target ship's navigation section is 0.5.

[0128] It should be explained that, in the present embodiment, ω1 is the environmental abnormality characteristic influencing factor corresponding to the preset abnormal weather condition characteristic value of the navigation section, which represents the numerical value of the influence degree of the abnormal weather condition characteristic value of the navigation section on the environment. When used, the environmental abnormality characteristic influencing factor corresponding to the abnormal weather condition characteristic value of the navigation section can be directly obtained from the shipping database, and the corresponding relationship can be a pre-set mapping relationship. For example, the abnormal weather condition characteristic value of the navigation section of the target ship and the environmental abnormality characteristic influencing factor corresponding to the abnormal weather condition characteristic value of the navigation section preset in the shipping database form a mapping set, and the real-time abnormal weather condition characteristic value of the navigation section is input into the mapping set to obtain the environmental abnormality characteristic influencing factor corresponding to the abnormal weather condition characteristic value of the navigation section, and the mapping relationship can be one-to-one or many-to-one.

[0129] It needs to be explained that, in the present embodiment, ω2 is the environmental abnormality characteristic influencing factor corresponding to the abnormal sea condition characteristic value of the preset navigation section, which represents the numerical value of the influence degree of the abnormal sea condition characteristic value of the navigation section on the environment. When used, the environmental abnormality characteristic influencing factor corresponding to the abnormal sea condition characteristic value of the navigation section can be directly obtained from the shipping database, and the corresponding relationship can be a pre-set mapping relationship. For example, the abnormal sea condition characteristic value of the navigation section of the target ship and the environmental abnormality characteristic influencing factor corresponding to the abnormal sea condition characteristic value of the navigation section preset in the shipping database form a mapping set, and the real-time abnormal sea condition characteristic value of the navigation section is input into the mapping set to obtain the environmental abnormality characteristic influencing factor corresponding to the abnormal sea condition characteristic value of the navigation section, and the mapping relationship can be one-to-one or many-to-one.

[0130] It should be explained that the above-mentioned influencing factors are all extracted from the shipping database, and the value range is between 0 and 1.

[0131] It should be explained that in this embodiment It is the environmental anomaly characteristic weight factor of the ship corresponding to the preset r-th navigation section, which represents the proportion of the environmental anomaly characteristic value of each navigation section to the environmental anomaly characteristic value of the ship. When used, the environmental anomaly characteristic weight factor of the ship corresponding to each navigation section can be directly obtained from the shipping database, and the corresponding relationship can be a preset mapping relationship. For example, the environmental anomaly characteristic weight factors of the ship corresponding to each navigation section preset in the shipping database form a mapping set, and the real-time navigation section is input into the mapping set to obtain the corresponding environmental anomaly characteristic weight factor of the ship, and the mapping relationship can be one-to-one.

[0132] It should be explained that the above embodiment can more comprehensively evaluate the risks of ships in specific environments, including potential threats such as storms, dense fog, and swells, by combining the abnormal characteristic values ​​of weather and sea conditions. By real-time monitoring and evaluating the abnormal characteristic values ​​of the environment, it is possible to warn in advance of the bad weather and sea conditions that the ship may encounter, and provide the ship with enough time to take evasive or safety measures. At the same time, the abnormal characteristic values ​​of the environment help ships plan safer routes, avoid high-risk areas, and reduce the navigation risks caused by environmental factors. Clear abnormal characteristic values ​​of the environment can also allow ships and shore support teams to quickly identify emergencies, initiate emergency plans in a timely manner, and improve the efficiency of emergency response. Furthermore, the abnormal characteristic values ​​of the environment provide quantitative risk assessment indicators, making risk assessment more scientific and objective, and helping decision makers make reasonable decisions. By analyzing the abnormal characteristic values ​​of the environment, ship accidents caused by bad weather and sea conditions can be prevented. In harsh environments, ships can take measures such as slowing down or changing routes to reduce possible damage. According to the abnormal characteristic values ​​of the environment, ships and cargo can be reasonably deployed to avoid unnecessary losses. By avoiding high-risk areas, fuel consumption and operating costs can be reduced. By effectively managing environmental risks, we can reduce sailing delays caused by weather and sea conditions, and ensure safe and on-time cargo transportation, which helps improve customer satisfaction and corporate reputation.

[0133] It should be explained that the present invention comprehensively considers environmental factors and ship operation conditions, and can more accurately identify complex factors that may cause risks, thereby improving the accuracy of risk assessment. The environmental abnormality characteristic value reflects the impact of the external environment on the ship, while the ship operation abnormality assessment index reflects the operation status of the ship itself. The combination of the two helps to fully identify potential risk points. When the environmental abnormality characteristic value and the ship operation abnormality assessment index simultaneously show high-risk signals, early warnings can be issued more effectively to remind crew members and managers to take preventive measures. In an emergency, the comprehensive analysis results can help the emergency response team understand the severity and urgency of the accident more quickly, so as to quickly take appropriate rescue measures. The ship operation abnormality assessment index can help identify problems in ship maintenance and management, and combined with the environmental abnormality characteristic value, it can more effectively plan maintenance work and improve management measures. Through comprehensive analysis, the present invention can reveal the interaction between environmental factors and ship operation conditions, so as to better understand the formation mechanism of risks. Based on comprehensive analysis, rescue resources, maintenance resources and human resources can be more reasonably deployed to improve resource utilization efficiency.

[0134] Specifically, the operation of each target ship is risk assessed based on the abnormal environmental characteristic value of each navigation section of each target ship and the abnormal operation assessment index of each target ship. The specific assessment process is: extracting the abnormal operation assessment index threshold of each target ship from the shipping database, and comparing the abnormal operation assessment index of each target ship with the abnormal operation assessment index threshold of each target ship.

[0135] A mapping set of ships of the same type and their corresponding operation abnormality assessment index thresholds is constructed, a target ship is input, the type of the target ship is obtained, and the operation abnormality assessment index threshold of the target ship is obtained according to the mapping set.

[0136] The abnormal environment characteristic threshold of each target ship is extracted from the shipping database, and the abnormal environment characteristic value of each target ship is compared with the abnormal environment characteristic threshold of each target ship.

[0137] If the operation abnormality assessment index of a target ship is lower than or equal to the target ship operation abnormality assessment index threshold, and the environmental abnormality characteristic value of the target ship is lower than or equal to the environmental abnormality characteristic threshold of the target ship, the operation abnormality risk assessment of the ship is qualified; if the operation abnormality assessment index of a target ship is higher than the target ship operation abnormality assessment index threshold or the environmental abnormality characteristic value of the target ship is higher than the environmental abnormality characteristic threshold of the target ship, the operation abnormality risk assessment of the ship is unqualified.

[0138] In a specific embodiment, the process of relevant early warning and control of unqualified ships is that once the target ship's operation risk assessment is found to be unqualified, the system immediately sends an early warning message to the ship's management personnel, the captain and relevant departments (such as the Maritime Safety Administration, port management agencies, etc.), notifying them that the abnormal operation risk assessment result of the ship is unqualified. The early warning information can be sent in a variety of ways such as SMS, e-mail, ship communication system or dedicated early warning platform to ensure the timeliness and effectiveness of the information. In addition to the immediate warning, the system should also generate a detailed risk assessment report, including but not limited to the specific value of the ship's operation abnormality assessment index, the specific value of the environmental abnormality characteristic value, the comparison with the threshold, possible risk factors and recommended countermeasures. This report helps managers and relevant departments to have a more comprehensive understanding of the ship's operating conditions and risk points. At the same time, a remote monitoring and tracking mechanism is activated for unqualified ships, and the position, speed, heading and other dynamic information of the ship are grasped in real time through technical means such as satellite positioning systems (such as global positioning systems) and ship automatic identification systems to ensure the safety of the ship during navigation. Furthermore, according to the risk assessment report and remote monitoring, if necessary, professional personnel will be dispatched to the ship site for on-site inspection to verify the risk situation and guide the ship management personnel and crew to take corresponding corrective measures to ensure that the ship's operation returns to normal. For ships with serious safety hazards, it may be necessary to take measures to restrict navigation, such as restricting their entry into specific waters, requiring them to slow down or change routes, etc., to reduce potential risks. At the same time, provide navigation guidance to help ships avoid high-risk areas or take safe navigation methods. Finally, follow up on unqualified ships and regularly evaluate their operating conditions and risk levels. If the ship returns to normal operation after rectification and the risk assessment results become qualified, the relevant restrictions and warning status will be lifted; if the problem still exists or worsens, it is necessary to continue to strengthen early warning and control efforts.

[0139] In a specific embodiment, ship risks have multiple impacts on the fluctuation of shipping freight rates. The existence and changes of these risks are directly related to the supply and demand relationship, operating costs and market expectations of the shipping market, which in turn have a significant impact on freight rates.

[0140] Specifically, ship risks, such as mechanical failures and maritime accidents, may cause some ships to temporarily or permanently withdraw from the market, thereby reducing the effective shipping capacity in the market. In the case of unchanged or increasing demand, the reduction in shipping capacity will drive up freight rates. Risks such as bad weather and marine life aggregation may cause ship delays or diversions, which in turn affect the implementation of transportation plans. Natural disasters such as bad weather, tsunamis, earthquakes and other natural disasters may lead to port closures, blocked waterways or damage to ships, which in turn affect the implementation of transportation plans and fluctuations in freight rates. Accidents such as grounding, reefing, collision and other accidents may cause damage to ships or loss of cargo, increase the operating costs and market risks of shipping companies, and thus drive up freight rates. Shipowners may need to re-arrange transportation and choose more expensive but more reliable modes of transportation, thereby increasing transportation costs and indirectly pushing up freight rates. Furthermore, ships need to be repaired after damage or accidents, and may face high insurance claims. These additional costs will increase the operating costs of shipping companies, and companies may pass on part of the costs to shippers in order to maintain profitability, resulting in higher freight rates.

[0141] Furthermore, although fuel prices are mainly affected by international oil prices, ship risks may also indirectly affect fuel costs. For example, ship delays may lead to longer sailing time and increased fuel consumption; while ship damage may require more fuel to maintain sailing speed or for emergency repairs.

[0142] Furthermore, ship risk may lead to a decline in investor confidence in the shipping market, which in turn affects capital inflows and shipbuilding plans. In the long run, this may lead to a slowdown in the growth of shipping market capacity, which will support freight rates. Furthermore, ship risk may also affect shippers' choice of transportation mode. In periods of higher risk, shippers may be more inclined to choose more reliable but more expensive transportation modes to ensure that their goods arrive at their destination safely and on time.

[0143] It should be explained that the shipping database described in the above embodiments is used to store relevant data in the shipping risk assessment process, including the maximum restricted draft, the reference standard speed, the allowable deviation speed and the maximum allowable inclination, the abnormal weather condition influencing factor of the navigation section corresponding to the wind speed, the abnormal weather condition influencing factor of the navigation section corresponding to the rainfall and the abnormal weather condition influencing factor of the navigation section corresponding to the temperature, etc. The data extracted from the shipping database in the above embodiments can be collected through the ship automatic identification system, the ship monitoring system and the sensors and Internet of Things devices installed on the ship to collect information such as ship performance, environmental conditions, cargo status, etc., and transmitted and collected through wireless networks or satellite communications, and included in the shipping database.

[0144] Reference Figure 2As shown, the second aspect of the present invention provides a shipping risk management system based on big data, characterized in that it includes: a shipping data acquisition module for acquiring ships in the target sea area, marking them as target ships, and collecting the routes of each target ship and the operating data of each target ship.

[0145] The ship operation abnormality assessment module is used to obtain the operation abnormality assessment index of each target ship through processing according to the operation data of each target ship.

[0146] The navigation section environment analysis module is used to obtain the navigation speed of each target ship, divide the route of each target ship according to the navigation speed of each target ship, mark it as each navigation section of each target ship, and collect the environmental data of each navigation section of each target ship, and obtain the environmental abnormality characteristic value of each target ship after processing.

[0147] The ship operation risk assessment feedback module is used to conduct risk assessment on the operation of each target ship according to the abnormal environmental characteristic value of each target ship and the abnormal operation assessment index of each target ship, obtain the assessment result and provide feedback.

[0148] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A shipping risk management method based on big data, characterized in that: include: Obtain the ships in the target sea area, mark them as target ships, and collect the routes and operation data of each target ship; According to the operation data of each target ship, the abnormal operation evaluation index of each target ship is obtained after processing; The navigation speed of each target ship is obtained, and the route of each target ship is divided according to the navigation speed of each target ship, and marked as each navigation section of each target ship. The environmental data of each navigation section of each target ship is collected, and the environmental abnormality characteristic value of each target ship is obtained after processing. According to the environmental abnormality characteristic value of each target ship and the operation abnormality assessment index of each target ship, the operation of each target ship is risk assessed, and the assessment results are obtained and fed back.

2. A shipping risk management method based on big data according to claim 1, characterized in that: According to the operation data of each target ship, the operation abnormality assessment index of each target ship is obtained through processing, and the specific process is as follows: The operation data of each target ship includes the operation status data of each target ship and the system operation data of each target ship; The operating status data of each target ship, including the draft, speed and inclination of each target ship at the current time point, is extracted from the shipping database to obtain the maximum restricted draft, reference standard speed, allowable deviation speed and maximum allowable inclination, and the operating status abnormal characteristic value of each target ship is obtained by comprehensive analysis; Obtaining a preset system monitoring cycle, deploying several monitoring time points, the system operation data of each target ship, including the engine load and energy consumption of each target ship in the current system monitoring cycle, extracting reference engine load and reference energy consumption, allowable deviation engine load and allowable deviation energy consumption from the shipping database, and comprehensively analyzing to obtain the system operation abnormality characteristic value of each target ship; The abnormal operation characteristic values ​​of the target ships and the abnormal system operation characteristic values ​​are comprehensively analyzed to obtain the abnormal operation evaluation index of each target ship. The abnormal operation evaluation index of each target ship is used to quantitatively evaluate the abnormal operation degree of each target ship and provide a basis for the evaluation of shipping risks.

3. The shipping risk management method based on big data according to claim 1 is characterized by: The routes of each target ship are divided according to the sailing speed of each target ship. The specific division process is as follows: A navigation time period is preset, and a reference standard speed of each target ship is obtained, and the reference standard speed of each target ship is multiplied by the preset navigation time period to obtain the route division length of each target ship; The route of each target ship is divided according to the route division length of each target ship, and marked as each navigation section of each target ship.

4. The shipping risk management method based on big data according to claim 1 is characterized by: The environmental abnormality characteristic value of each target ship is obtained through processing, and the specific process is as follows: The environmental data of each navigation section of each target ship includes meteorological data of each navigation section of each target ship and sea condition data of each navigation section of each target ship; The meteorological data of each navigation section of each target ship, including wind speed, rainfall and temperature of each navigation section of each target ship, is extracted from the shipping database to obtain the maximum allowable wind speed, maximum allowable rainfall and minimum allowable temperature, and a comprehensive analysis is performed to obtain the characteristic value of abnormal weather conditions of each navigation section of each target ship; The sea condition data of each navigation section of each target ship, including the wave height, sea ice density and marine life density of each navigation section of each target ship, extract the critical wave height, critical sea ice density and critical marine life density from the shipping database, and comprehensively analyze to obtain the abnormal sea condition characteristic value of each navigation section of each target ship; Comprehensively analyze the abnormal weather condition characteristic values ​​of each navigation section of each target ship and the abnormal sea condition characteristic values ​​of each navigation section of each target ship to obtain the environmental abnormality characteristic values ​​of each target ship. The environmental abnormality characteristic values ​​of each target ship are used to quantitatively evaluate the degree of environmental abnormality of each target ship, providing a basis for evaluating shipping risks.

5. The shipping risk management method based on big data according to claim 4 is characterized by: The operation of each target ship is risk assessed based on the abnormal environmental characteristic value of each navigation section of each target ship and the abnormal operation assessment index of each target ship. The specific assessment process is as follows: Extracting the threshold of each target ship operation abnormality assessment index from the shipping database, and comparing each target ship operation abnormality assessment index with the threshold of each target ship operation abnormality assessment index; Extracting the environmental anomaly characteristic threshold of each target ship from the shipping database, and comparing the environmental anomaly characteristic value of each target ship with the environmental anomaly characteristic threshold of each target ship; If the operation abnormality assessment index of a target ship is lower than or equal to the target ship operation abnormality assessment index threshold, and the environmental abnormality characteristic value of the target ship is lower than or equal to the environmental abnormality characteristic threshold of the target ship, the operation abnormality risk assessment of the ship is qualified; if the operation abnormality assessment index of a target ship is higher than the target ship operation abnormality assessment index threshold or the environmental abnormality characteristic value of the target ship is higher than the environmental abnormality characteristic threshold of the target ship, the operation abnormality risk assessment of the ship is unqualified.

6. The shipping risk management method based on big data according to claim 2 is characterized by: The abnormal operating status characteristic value of each target ship is a quantitative evaluation data obtained by comprehensively analyzing the draft, speed and inclination of each target ship at the current time point, which is used to quantitatively evaluate the abnormal degree of the operating status of each target ship and provide a basis for evaluating the operating abnormality of each target ship.

7. The shipping risk management method based on big data according to claim 4 is characterized by: The abnormal weather condition characteristic value of each navigation section of each target ship is quantitative evaluation data obtained by comprehensive analysis of wind speed, rainfall and temperature in each navigation section of each target ship, and is used to quantitatively evaluate the degree of abnormality of weather conditions in each navigation section of each target ship, providing a basis for evaluating the abnormal environment of each navigation section of each target ship.

8. The shipping risk management method based on big data according to claim 2 is characterized by: The specific numerical expression of the abnormal operation evaluation index of each target ship is: In the formula, represents the abnormal operation evaluation index of the i-th target ship, e represents a natural constant, represents the abnormal characteristic value of the operating status of the i-th target ship, represents the system operation abnormality characteristic value of the i-th target ship, θ1 represents the ship operation abnormality impact factor corresponding to the preset ship operation status abnormality characteristic value, and θ2 represents the ship operation abnormality impact factor corresponding to the preset ship system operation abnormality characteristic value.

9. The shipping risk management method based on big data according to claim 4 is characterized by: The specific numerical expression of the abnormal environmental characteristic value of each target ship is: In the formula, represents the abnormal environmental characteristic value of the i-th target ship, represents the characteristic value of abnormal weather conditions in the rth navigation section of the i-th target ship, r represents the number of each navigation section, r=1,2,3,...,h, h represents the total number of navigation sections, represents the abnormal sea condition characteristic value of the rth navigation section of the i-th target ship, ω1 represents the environmental abnormality characteristic influencing factor corresponding to the abnormal weather condition characteristic value of the preset navigation section, ω2 represents the environmental abnormality characteristic influencing factor corresponding to the abnormal sea condition characteristic value of the preset navigation section, Represents the weight factor of the abnormal environmental characteristics of the ship corresponding to the preset r-th navigation section.

10. A shipping risk management system using a shipping risk management method based on big data as claimed in any one of claims 1 to 9, characterized in that: include: The shipping data collection module is used to obtain ships in the target sea area, mark them as target ships, and collect the routes and operation data of each target ship; The ship operation abnormality assessment module is used to obtain the operation abnormality assessment index of each target ship through processing according to the operation data of each target ship; The navigation section environment analysis module is used to obtain the navigation speed of each target ship, divide the route of each target ship according to the navigation speed of each target ship, mark it as each navigation section of each target ship, and collect the environmental data of each navigation section of each target ship, and obtain the environmental abnormality characteristic value of each target ship after processing; The ship operation risk assessment feedback module is used to conduct risk assessment on the operation of each target ship according to the abnormal environmental characteristic value of each target ship and the abnormal operation assessment index of each target ship, obtain the assessment result and provide feedback.

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