CN-119622267-B - Regional ship risk analysis and decision system

CN119622267BCN 119622267 BCN119622267 BCN 119622267BCN-119622267-B

Abstract

The invention provides a regional ship risk analysis and decision-making system, which belongs to the technical field of ship safety and comprises a user interaction layer, a data processing layer and a data storage layer, and further comprises a current situation risk assessment module, a loss calculation module and a system data updating module, wherein the user interaction layer provides interfaces for interaction with crews for the three modules, the data processing layer provides support for construction, analysis and calculation of a Bayesian network model of the current situation risk assessment module, also provides data processing capacity for calculation of various charges in the loss calculation module, and realizes data conversion and storage in the system data updating module, and the data storage layer provides data storage and reading services for the three modules so as to ensure that the modules can acquire required data. The invention can evaluate the risk of ice trapping and ice damage possibly encountered by the ship, assist decision making and loss calculation, provide effective support and navigation advice for crews, and provide support for the actual regional ship risk management.

Inventors

LU YANG
ZHANG XINYUE
LIU YUEJUN
WANG YONGKUI
XUE YANZHUO
NI BAOYU
YUAN GUANGYU
DI SHAOCHENG

Assignees

哈尔滨工程大学

Dates

Publication Date: 20260508
Application Date: 20241211

Claims (4)

1. A regional ship risk analysis and decision system is characterized in that: the system comprises a user interaction layer, a data processing layer and a data storage layer; the user interaction layer is used for selecting the current risk node state, displaying an reasoning result and an auxiliary decision suggestion, and displaying an economic loss result; The data processing layer performs parameter learning and data reasoning through a Bayesian network model; The parameter transmission path of the data processing layer is specifically that a human-computer interface converts ice area and ship accident data into a computer engine, the input computer data is converted into Python type through Python software, and then a pgmpy library is utilized to construct a Bayesian network model and analyze and calculate; the Bayesian network returns the reasoning data to the Python engine, the Python engine converts the data into the original type data of the computer engine and transmits the data back to the computer engine, and the result is displayed on the human-computer interface, so that the functions of providing risk analysis and auxiliary decision are realized; The data storage layer is used for storing accident samples, and storing suggested measures and parameters; the system comprises a current situation risk assessment module, a loss calculation module and a system data updating module; the user interaction layer provides interfaces for interaction with crews for the three modules, and the crews operate the modules through the layer; the data processing layer provides support for the construction, analysis and calculation of a Bayesian network model of the current situation risk assessment module, also provides data processing capacity for each expense calculation in the loss calculation module, and simultaneously realizes the conversion and storage of data in the system data updating module; The data storage layer provides data storage and reading services for the three modules, so that the modules can acquire required data; the current situation risk assessment module display content comprises risk factor selection, bayesian network reasoning results and suggested measures, and has the functions of risk assessment and auxiliary decision making; The loss calculation module is used for briefly calculating economic loss of the ship after ice trapping and ice loss accidents, and the parameters comprise whether the ship approaches a port after the accidents occur, whether no-load sailing occurs, the accident occurs to the navigation section, the remaining mileage of the navigation section and the thrust loss after the accidents occur.
2. The system according to claim 1, wherein: The man-machine interface display content of the user interaction layer comprises current situation risk assessment, loss calculation, system data updating and exiting the system.
3. The system according to claim 2, wherein: the accident loss calculation considers maintenance cost F1, wherein the maintenance cost F1 comprises single maintenance cost such as annual maintenance and propeller, fuel oil increasing cost F2 caused by thrust reduction due to structural damage of the propeller, transshipment cost F3 and possible loss F4 caused by no-load return maintenance port, and the following formula is shown: wherein the maintenance fee F1 is calculated based on the annual maintenance rate of the ice-worthy vessel of 1.606%; The fuel increase cost F2 is dependent on the fuel consumption rate (F), the fuel price (bp) and the single voyage time (time), and the fuel cost is defined as: F2= Assuming a fuel price of 500USD/ton, the fuel consumption rate (f) can be calculated according to the propeller law by: SFOC represents specific fuel consumption rate (unit: g/kW.h), fixed value 185 g/kW.h, BHP is engine braking horsepower (unit: kW), m is a scale factor, vi is the speed of the container ship sailing in different sailing sections, BHPmax is the maximum output power of the host, and Vmax is the maximum ship speed; The transit port fee F3 mainly comprises (a) port service fee, (b) container loading and unloading fee, (c) port pilot fee and (d) ice breaking fee of a specific port, wherein each fee is generally calculated according to the ship NT or the box loading amount and related rate standards, and the following formula is shown: Wherein the icebreaking rate is obtained by russian north sea channel administration (Russia Northern Sea Route Administration); the loss F4 caused by no-load return to the maintenance port is calculated according to the freight rate index, and the freight rate of the container is assumed to be 900USD/TEU.
4. A system according to claim 3, characterized in that: The system data updating module is divided into an accident data updating part and an accident loss parameter updating part, a system user performs dispersion according to newly-generated ice-trapping and ice-loss accident reports and divided risk factors, inputs the dispersion into a corresponding frame of the accident data updating part, and then updates and adds a software accident database; Aiming at the problems of different ship types, such as ice trapping and different losses after ice loss accidents, the accident loss parameter updating module modifies corresponding parameters according to the specific type of the ship where the system user is located so as to obtain more accurate economic loss estimation.

Description

Regional ship risk analysis and decision system Technical Field The invention belongs to the technical field of ship safety, and particularly relates to a regional ship risk analysis and decision-making system. Background As global air temperature continues to rise, polar region glaciers continue to ablate, and commercial, normalized, and project-oriented operation of arctic waterway vessels will become a reality. But the harsh natural environment of arctic, special geographical location and complex navigation conditions pose a great threat and challenge to the navigation safety of the vessel. Ice trapping and ice damage are considered the most serious risks, which, once occurring, can lead to damage to vessels, property damage, environmental damage, and even casualties. At present, most of the risk assessment researches on the arctic ice region ships are theoretical, and the risk assessment researches can play a role in guiding actual production operation, but still cannot be directly applied to the ship navigation process. Therefore, it is necessary to design and implement a risk assessment and decision system for a ship in a arctic ice region, compile a bayesian network model by using a Python programming language to form a graphical interface interacted with a user, implement three system functions of risk assessment, auxiliary decision and loss calculation, and provide effective support and suggestion for shipman operation and navigation decision while assessing the ship risk in the current environment. Disclosure of Invention Aiming at two risk factors of ice trapping and ice damage of regional ships, the invention designs and establishes a regional ship risk analysis and decision system by using Python language. The regional ship risk analysis and decision system is realized by the following technical scheme: the system comprises a user interaction layer, a data processing layer and a data storage layer; the user interaction layer is used for selecting the current risk node state, displaying an reasoning result and an auxiliary decision suggestion, and displaying an economic loss result; The data processing layer performs parameter learning and data reasoning through a Bayesian network model; The data storage layer is used for storing accident samples, and storing suggested measures and parameters. Further, the human-computer interface display content of the user interaction layer comprises current situation risk assessment, loss calculation, system data updating and exiting the system. The data processing layer parameter transmission path is characterized in that a human-computer interface converts ice area and ship accident data into a computer engine, the input computer data are converted into Python types through Python software, and then a pgmpy library is utilized to construct a Bayesian network model and analyze and calculate; The Bayesian network returns the reasoning data to the Python engine, the Python engine converts the data into the original type data of the computer engine and transmits the data back to the computer engine, and the result is displayed on the human-computer interface, so that the functions of providing risk analysis and auxiliary decision making are realized. Further, the system comprises a current situation risk assessment module, a loss calculation module and a system data updating module; the user interaction layer provides interfaces for interaction with crews for the three modules, and the crews operate the modules through the layer; the data processing layer provides support for the construction, analysis and calculation of a Bayesian network model of the current situation risk assessment module, also provides data processing capacity for each expense calculation in the loss calculation module, and simultaneously realizes the conversion and storage of data in the system data updating module; the data storage layer provides data storage and reading services for the three modules, so that the modules can acquire required data. Further, the display content of the current situation risk assessment module comprises risk factor selection, bayesian network reasoning results and suggested measures, and has the functions of risk assessment and auxiliary decision making; The loss calculation module is used for briefly calculating economic loss of the ship after ice trapping and ice loss accidents, and the parameters comprise whether the ship approaches a port after the accidents occur, whether no-load sailing occurs, the accident occurs to the navigation section, the remaining mileage of the navigation section and the thrust loss after the accidents occur. Further, the accident loss calculation considers the maintenance cost F1, wherein the maintenance cost F1 comprises single maintenance cost such as annual maintenance and propeller, fuel increase cost F2 caused by thrust reduction due to structural damage of the propeller, port transfer cost F3 and possible loss F4 caused