Coastal LNG port operation tracking and evaluation method and system based on AIS data mining

Abstract

The present invention discloses a coastal LNG port operation tracking and evaluation method based on AIS data mining in the field of port planning technology, which obtains AIS data including first AIS historical big data and first AIS real-time big data; based on the ship type keyword information of LNG ships, cleans interference data, and builds a global LNG transport ship AIS big data resource pool; deduplicates and deletes duplicate data and abnormal data in the global LNG transport ship AIS big data resource pool; integrates spatial geographic information data including terminals and anchorages of international and domestic LNG ports, and analyzes the space-time motion trajectory of ships in international and domestic transportation of imported LNG ships; matches and calculates the LNG ship motion trajectory data and the international and domestic port regional geographic information data to obtain the space-time data information of each voyage of global LNG ships; based on the AIS storage data after cleaning, correlation and voyage analysis, the berth utilization rate of each domestic LNG terminal and the reasonable berth capacity can be calculated.

Description

Technical Field

[0001] The present invention relates to the technical field of port planning, and in particular to a coastal LNG port operation tracking and evaluation method and system based on AIS data mining. Background Art

[0002] Seaborne imported natural gas (liquefied natural gas / LNG) is an important component of my country's energy supply. It is crucial to track and evaluate the adaptability of coastal imported LNG transportation port facilities.

[0003] At present, in the tracking and adaptability assessment of the LNG (natural gas) transportation system in coastal ports, the relevant analysis work is mainly carried out based on the historical port and shipping statistical data. Through regular surveys and tracking, statistical data on coastal port throughput, terminal facility capacity of each port enterprise and terminal transportation volume are obtained, and the historical utilization rate of the terminal, the adaptability of the terminal capacity, etc. are analyzed and evaluated.

[0004] The current technical support for coastal LNG transportation system tracking and adaptability assessment research mainly has the following problems:

[0005] First, the data for tracking and evaluation work is collected mainly through regular surveys. The port and shipping big data collected through surveys are all historical data, which have problems such as long work cycle, lagging data information and lack of data timeliness.

[0006] Second, there are many LNG terminals in coastal ports across the country, with numerous operating entities, multiple data sources, different statistical standards and formats, and low data integration and analysis efficiency. Summary of the invention

[0007] The purpose of the present invention is to provide a coastal LNG port operation tracking and evaluation method and system based on AIS data mining, so as to solve the problems of long working cycle, data information lag and lack of data timeliness in the data collection method of the existing tracking and evaluation work in the prior art; and the technical problems that there are many distribution points of LNG terminals in coastal ports across the country, many operating entities, multiple sources of data, different statistical standards and formats, and low efficiency of data integration and analysis.

[0008] In order to solve the above technical problems, the present invention specifically provides a coastal LNG port operation tracking and evaluation method based on AIS data mining, comprising the following steps:

[0009] Data acquisition: Acquire AIS data including the first AIS (Automatic Identification System) historical big data and the first AIS real-time big data;

[0010] Data preprocessing: Based on the ship type keyword information of LNG ships, the non-LNG ship interference data in the first AIS historical big data and the first AIS real-time big data are cleaned, and a global LNG transport ship AIS big data resource pool is constructed;

[0011] Deduplication and deletion of duplicate data and abnormal data in the global LNG transport ship AIS big data resource pool;

[0012] Ship voyage correlation analysis: Based on the ArcGis platform, the spatial geographic information data including the docks and anchorages of international and domestic LNG ports are integrated to analyze the spatiotemporal movement trajectory of ships in international and domestic transportation of imported LNG ships;

[0013] The trajectory points with the shortest spatial distance and the closest sailing speed are associated to ensure that the ship trajectory data is the trajectory data of the same ship and the same voyage;

[0014] Based on the pre-processed LNG ship AIS big data and the spatial geographic information data of international and domestic LNG ports, the LNG ship movement trajectory data and the international-domestic port regional geographic information data are matched and calculated to obtain the spatiotemporal data information of each voyage of global LNG ships;

[0015] Calculate berth utilization rate and reasonable berth capacity: import the historical AIS data of global LNG ships after cleaning, correlation and voyage analysis into the MySQL (database management system) database. Based on the MySQL database, the berth utilization rate and reasonable berth capacity of each domestic LNG terminal can be calculated.

[0016] As a preferred solution of the present invention, the first AIS historical big data and the first AIS real-time big data are both derived from a multi-source AIS data source of "satellite network + shore-based network + ship-based network" to ensure data coverage density of key international and domestic waters.

[0017] As a preferred solution of the present invention, a method for processing the global LNG transport ship AIS big data resource pool includes data table association, table merging, row and column screening and data conversion.

[0018] As a preferred solution of the present invention, the method for matching the LNG ship motion trajectory data with the international-domestic port area geographic information data is as follows:

[0019] Identify the ship's entry and exit and berthing and unberthing times, analyze and calculate each ship's departure time, port departure time, first-leg transport arrival time, first-leg transport berthing time, domestic second-leg transshipment arrival time, and domestic second-leg transshipment berthing time. The above triggering times constitute a voyage of an LNG ship; thereby establish a 20-item indicator data set for each LNG ship's single voyage;

[0020] The 20 indicator data sets mainly include ship ID, MMSI number (marine mobile communication service identification code), ship type, navigation status, port ID, port arrival time, port departure time, port berthing terminal ID, port berthing time, port departure time, sailing time, and sailing mileage.

[0021] As a preferred solution of the present invention, the time-space-speed nearest neighbor method is used to associate the trajectory points with the closest spatial distance and the closest navigation speed;

[0022] The method of using the time-space-speed nearest neighbor method is: for two AIS ship tracks with the same MMSI number, the two tracks are track 1 and track 2;

[0023] If the associated trajectory point is closest to the extension line of trajectory 1 in vertical distance d1 and the speed v is relatively closer to the speed of the closest point (v1) of the trajectory, the associated trajectory point is associated to trajectory 1.

[0024] As a preferred solution of the present invention, a berth utilization calculation formula different from the general standard is proposed based on AIS data. The LNG berth utilization calculation formula is:

[0025]

[0026] The calculation formula can calculate the LNG berth utilization evaluation value in different regions and seasons;

[0027] The meanings of the symbols in the formula are as follows:

[0028] Api said: The berth utilization rate of LNG berths throughout the year or in a certain season can be divided into winter (November to February) and other seasons (March to October);

[0029] Si said: Based on the analysis of LNG ship AIS data, the number of any type of ship arriving at a certain LNG terminal along the coast of my country in a certain season was obtained;

[0030] The representative ship types are divided into: i=1 represents Q-max ship, i=2 represents Q-flex ship, i=3 represents 150,000-200,000 cubic meters ship, i=4 represents less than 150,000 cubic meters ship;

[0031] ti means: Based on the analysis of LNG ship AIS data, the berthing time of the corresponding berthing ship type at a certain LNG terminal along the coast of my country is obtained;

[0032] Tpi means: the number of effective working days throughout the year or in a certain season.

[0033] As a preferred solution of the present invention, the formula for calculating the reasonable performance capacity of the LNG berth is:

[0034] According to the seasonal characteristics of LNG transportation and the actual utilization rate of berths, the present invention further proposes a calculation formula for the reasonable throughput capacity of LNG berths based on seasonal imbalance on the basis of the calculation formula for the throughput capacity of LNG berths proposed in the specification. The calculation formula for the reasonable throughput capacity of LNG berths based on seasonal imbalance is as follows:

[0035]

[0036] The formula for calculating the reasonable available capacity of LNG berths can calculate the reasonable available capacity of LNG berths in different regions and seasons;

[0037] The meanings of the symbols in the formula are as follows:

[0038] Pt means: the reasonable capacity assessment value of the LNG berth for the whole year or a certain season, in 10,000 tons;

[0039] Api means: the berth utilization rate of LNG berths throughout the year or in a certain season, which is obtained based on the LNG berth utilization rate calculation formula;

[0040] Tpi means: the number of effective working days in a whole year or a certain season;

[0041] td means: day and night hours, 24 hours;

[0042] tz means: net unloading time for the corresponding ship type, in hours, obtained through research;

[0043] tf represents: auxiliary operation time of ship loading and unloading, in hours, obtained through investigation;

[0044] th represents: the additional time required for waiting for tides and currents or not entering and exiting the channel and berthing and leaving at night, in hours, obtained through surveys;

[0045] Gj represents: the actual load of the corresponding representative ship type, in 10,000 tons, obtained through research;

[0046] a j Indicates: The weight of the corresponding representative ship type, calculated based on AIS data.

[0047] Furthermore, according to the calculation formula of the reasonable throughput capacity of LNG berths, if the reasonable available capacity assessment value of the LNG berth to be tracked and evaluated is higher than or equal to the actual transportation volume of the whole country / a certain season, then the evaluation result of the capacity of the LNG port facility to be tracked and evaluated is that the plan is reasonable;

[0048] If the evaluation value of the reasonable LNG berth capacity function obtained by the evaluation function is lower than the actual transportation volume in the country / a certain season, the evaluation result of the LNG port facility capacity to be tracked and evaluated is that the plan is unreasonable.

[0049] Furthermore, based on the real-time big data of AIS of global LNG transport ships, the short-term forecast and evaluation method of LNG ship arrival and unloading volume is as follows:

[0050] According to the current position of the LNG transport ship on the international route provided by the real-time data, the 'destination' (estimated destination) field information of the ship's AIS static data is extracted, and the recent empirical routes of the LNG ships in operation are matched according to the probability analysis of the historical call routes of each LNG ship obtained by the above evaluation. The empirical routes are used to match the LNG ships expected to arrive at my country's coastal ports; in this way, the number of ships expected to arrive at various coastal LNG terminals in a short period of time is obtained by evaluation, and the empirical parameters of the actual load rate of LNG by ship type obtained by research experience can be combined to calculate the LNG unloading volume of ships expected to be unloaded in the short term at various coastal LNG terminals;

[0051] The short-term arrival LNG ship forecasting and unloading volume forecasting and evaluation method is used to forecast LNG ships at my country's coastal ports and assist in short-term supply situation assessment and decision-making.

[0052] Furthermore, the LNG unloading volume prediction formula is:

[0053]

[0054] The meanings of the symbols in the formula are as follows:

[0055] p p It means: the estimated LNG unloading volume of a coastal LNG terminal in the short term, 3 days, 5 days, 7 days, etc.;

[0056] S jp It means: Based on the analysis of AIS data of LNG ships arriving at coastal ports, the number of any type of ships arriving at a certain LNG terminal along the coast of my country in the next few days is obtained;

[0057] G j Indicates: the actual load of the corresponding ship type, in 10,000 tons.

[0058] The present invention constructs an evaluation function from three dimensions: history, real-time and short-term prediction, and quantitatively calculates the reasonable utilization rate and reasonable capacity evaluation value of LNG port terminals applicable to different coastal areas and seasons, and quantitatively evaluates the number of LNG ships arriving at my country's coastal ports and the loading and unloading volume in the short term.

[0059] It provides quantitative indicator support in the tracking and evaluation of the LNG transportation system and assists relevant departments in emergency management, improves the scientific nature of planning, and solves technical problems such as historical data, real-time data update and international-domestic port geographic information matching, analysis process and statistical effect visualization in the tracking and evaluation and analysis of the LNG transportation system, thereby improving work efficiency and quality.

[0060] The present invention further provides a coastal LNG port operation tracking and evaluation system based on AIS data mining, which is constructed based on the above-mentioned coastal LNG port operation tracking and evaluation method based on AIS data mining, so as to facilitate quantitative decision-making analysis by planners;

[0061] The coastal LNG port operation tracking and evaluation system includes a decision analysis subsystem based on historical AIS data and a decision analysis subsystem based on real-time AIS data;

[0062] The decision analysis subsystem based on historical AIS data includes a front-end visual layer for human-computer interaction, a business logic layer for processing data information, and a data support layer for storing data information;

[0063] The real-time AIS data-based decision analysis subsystem adopts the declarative HTTP client framework Feign technology, defines the interface description to call the service API, and then configures the request and response processing method through annotations to call the AIS real-time data online HTTP target service.

[0064] The construction method of the data support layer is as follows: import the historical AIS data resource pool of LNG ship transportation after cleaning and route analysis into the Mysql database; based on the GIS platform, obtain the spatial geographic information data resources of ports such as international and domestic LNG terminals required for system construction;

[0065] The construction method of the business logic layer is as follows: according to the business function requirements of the system, the Spring framework technology is used for business integration, the Spring application context initializer is loaded, the SpringApplication object is initialized, the project startup class is configured, and the event listener loading is set; based on the data support layer, data is encapsulated, the algorithm function logic business is encapsulated, each business module is packaged, divided into services and functions, and a context continuous operation mechanism is established to form a general service package of the system;

[0066] The construction method of the front-end visual layer is: it is built using Node.js and Vue-Cli systems, and rendered using the Element UI visualization framework adapted to Vue. It provides users with data display and management through the PC, such as traffic flow map display, ship spatiotemporal trajectory query, ship time statistics query at all stages of the port, map service operation, data record addition, deletion, modification and query, etc.; and integrates GIS platform data, and cooperates with the ArcGis service of the basic support layer to complete the overlay display of track maps, various data layers, remote sensing images and flow maps, attribute query and other operations.

[0067] Compared with the prior art, the present invention has the following beneficial effects:

[0068] The present invention acquires AIS historical big data and AIS real-time big data, builds a global LNG transport ship AIS big data resource pool, performs analysis of big data and correlation, imports global LNG ship historical AIS data into a MySQL database, and calculates the berth utilization rate and reasonable berth capacity of each domestic LNG terminal based on the MySQL database. The data collection cycle is short, the data is updated in real time, the timeliness is guaranteed, and the statistical standards and formats are unified, and the data integration and analysis efficiency is high. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0070] Figure 1 Schematic diagram of a data association method based on the time-space-speed nearest neighbor method in an embodiment of the present invention;

[0071] Figure 2 This is a block diagram of a global LNG transport ship AIS data cleaning and spatiotemporal data analysis system in an embodiment of the present invention;

[0072] Figure 3 This is a visualization block diagram of a decision analysis subsystem based on historical AIS data in an embodiment of the present invention. DETAILED DESCRIPTION

[0073] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0074] The present invention provides a coastal LNG port operation tracking and evaluation method based on AIS data mining, comprising the following steps:

[0075] The first AIS historical big data and the first AIS real-time big data are obtained. Both the first AIS historical big data and the first AIS real-time big data are derived from the multi-source AIS data source of "satellite-based network + shore-based network + ship-based network", ensuring the data coverage density of key international and domestic waters.

[0076] Based on the keyword information of static data fields such as "shiptype", the global LNG transport ship AIS big data resource pool is cleaned and constructed, which is applied to the LNG ports to be tracked and evaluated;

[0077] Based on the global LNG transport ship AIS big data resource pool, data processing components such as data table association, table merging, row and column screening, and data conversion are used to remove and delete duplicate data and abnormal data in the global LNG transport ship big data resource pool.

[0078] In the analysis system, based on the ArcGis platform, the spatial geographic information data of international and domestic LNG ports such as docks and anchorages are integrated to analyze the spatiotemporal movement trajectory of imported LNG ships during international and domestic transportation, forming the basis for identifying LNG dedicated routes, and forming the geographic information foundation support for the front-end display of the visualization system;

[0079] Based on the pre-processed LNG ship AIS big data and international and domestic LNG port geographic information data, all the track points of the area passed by the ship in the past historical period are obtained according to the ship's MMSI identification number;

[0080] like Figure 1 As shown, the present invention adopts the 'time-space-speed nearest neighbor method' to associate the trajectory points with the closest spatial distance and the closest sailing speed, ensuring that the ship trajectory data are the trajectory data of the same ship and the same voyage; the data association method based on the 'time-space-speed nearest neighbor method' is shown in FIG. Figure 1As shown, for two AIS ship tracks (track 1 and track 2) with the same MMSI number, if the associated track point is the closest to the vertical distance (d1) of the extension line of track 1 and the speed (v) is relatively closer to the speed of the closest point (v1) of the track, then the associated track point is associated with track 1.

[0081] like Figure 2 As shown, the LNG ship movement trajectory data and the international-domestic port area geographic information data are matched, the ship's entry and exit and berthing and unberthing times are identified, and the departure time, port departure time, one-leg transport arrival time, one-leg transport berthing time, domestic two-leg transshipment arrival time, and domestic two-leg transshipment berthing time of each ship are analyzed and calculated. The above-mentioned triggering times constitute one voyage for one ship.

[0082] In this way, a 20-item indicator data set for each LNG ship voyage is established, and the 20-item indicator data set mainly includes ship ID, MMSI number, ship type, navigation status, port ID, port arrival time, port departure time, port berthing terminal ID, port berthing time, port departure time, sailing time, sailing mileage, etc.;

[0083] The historical AIS data of global LNG ships that have been cleaned and route analyzed are imported into the MySQL database. Based on the MySQL database, the berth utilization rate and reasonable berth capacity of each domestic LNG terminal can be calculated.

[0084] Furthermore, there are seasonal imbalances in the transportation of LNG and crude oil, especially in winter when LNG transportation reaches its peak, so it is very important to pay attention to peak capacity. However, the current terminal design for the two types of cargo is calculated through capacity, and the industry specifications are mainly calculated based on the balance of transportation throughout the year. The calculation method of the standard system cannot meet the needs of calculating the peak terminal capacity.

[0085] The Bohai Rim and Yangtze River Delta are significantly affected by the winter LNG transportation peak, and the berth utilization rate has seasonal imbalance characteristics. The value of LNG berth utilization rate should be further refined in combination with regional consumption and transportation characteristics.

[0086] On the basis of the specification, the present invention further proposes a berth utilization calculation formula different from the general standard of the specification based on AIS data. The LNG berth utilization calculation formula is:

[0087]

[0088] The meanings of the symbols in the formula are as follows:

[0089] Api said: The berth utilization rate of LNG berths throughout the year or in a certain season can be divided into winter (November to February) and other seasons (March to October);

[0090] Si said: Based on the analysis of LNG ship AIS data, the number of any type of ship arriving at a certain LNG terminal along the coast of my country in a certain season was obtained;

[0091] The representative ship types are divided into: i=1 represents Q-max ship, i=2 represents Q-flex ship, i=3 represents 150,000-200,000 cubic meters ship, i=4 represents less than 150,000 cubic meters ship;

[0092] ti means: Based on the analysis of LNG ship AIS data, the berthing time of the corresponding berthing ship type at a certain LNG terminal along the coast of my country is obtained;

[0093] Tpi means: the number of effective working days throughout the year or in a certain season.

[0094] Furthermore, due to the different factors affecting the navigation environment of ships entering and leaving the ports, the configuration of terminal loading and unloading equipment, and the conditions of land-based collection and distribution in the rear, the designed throughput capacity of the LNG terminal cannot objectively reflect the actual throughput capacity of each port terminal. Only by using standardized and unified standards to evaluate the adaptability of the terminal capacity of the designed throughput capacity of the LNG terminal, the evaluation value deviates from the actual capacity of each port.

[0095] According to the seasonal characteristics of LNG transportation and the actual utilization rate of berths, the present invention further proposes a calculation formula for the reasonable throughput capacity of LNG berths based on seasonal imbalance on the basis of the calculation formula for the throughput capacity of LNG berths proposed in the specification. The calculation formula for the reasonable throughput capacity of LNG berths based on seasonal imbalance is as follows:

[0096]

[0097] The formula for calculating the reasonable available capacity of LNG berths can calculate the reasonable available capacity of LNG berths in different regions and seasons;

[0098] The meanings of the symbols in the formula are as follows:

[0099] Pt means: the reasonable capacity assessment value of the LNG berth for the whole year or a certain season, in 10,000 tons;

[0100] Api means: the berth utilization rate of LNG berths throughout the year or in a certain season, which is obtained based on the LNG berth utilization rate calculation formula;

[0101] Tpi means: the number of effective working days in a whole year or a certain season;

[0102] td means: day and night hours, 24 hours;

[0103] tz means: net unloading time for the corresponding ship type, in hours, obtained through research;

[0104] tf represents: auxiliary operation time of ship loading and unloading, in hours, obtained through investigation;

[0105] th represents: the additional time required for waiting for tides and currents or not entering and exiting the channel and berthing and leaving at night, in hours, obtained through surveys;

[0106] Gj represents: the actual load of the corresponding representative ship type, in 10,000 tons, obtained through research;

[0107] a j Indicates: The weight of the corresponding representative ship type, calculated based on AIS data.

[0108] The reasonable available capacity of the LNG berths is evaluated to reflect the reasonable system throughput capacity of LNG ships in a port.

[0109] If the reasonable available capacity assessment value of the LNG berth to be tracked and assessed is higher than or equal to the actual transportation volume of the whole country / a certain season, the evaluation result of the LNG port facility capacity to be tracked and assessed is that the plan is reasonable;

[0110] If the evaluation value of the reasonable LNG berth capacity function obtained by the evaluation function is lower than the actual transportation volume in the country / a certain season, it means that the port capacity is underutilized. Then the evaluation result of the LNG port facility capacity to be followed up will be that the plan is unreasonable and the plan needs to be adjusted.

[0111] Furthermore, under extreme weather and extreme conditions, the lack of technical means for short-term forecasting, early warning and analysis of seaborne imported oil and gas transportation makes it difficult to assist in emergency response work.

[0112] Based on the real-time big data of AIS of global LNG transport ships, the present invention provides a short-term forecasting and evaluation method for LNG ships arriving at the port and the unloading volume forecasting as follows:

[0113] According to the current position of the LNG transport ship on the international route provided by the real-time data, the 'destination' (estimated destination) field information of the ship's AIS static data is extracted, and the recent empirical routes of the LNG ships in operation are matched according to the probability analysis of the historical call routes of each LNG ship obtained by the above evaluation. The empirical routes are used to match the LNG ships expected to arrive at my country's coastal ports; in this way, the number of ships expected to arrive at various coastal LNG terminals in a short period of time is obtained by evaluation, and the empirical parameters of the actual load rate of LNG by ship type obtained by research experience can be combined to calculate the LNG unloading volume of ships expected to be unloaded in the short term at various coastal LNG terminals;

[0114] The short-term arrival LNG ship forecasting and unloading volume forecasting and evaluation method is used to forecast LNG ships at my country's coastal ports and assist in short-term supply situation assessment and decision-making.

[0115] Furthermore, the LNG unloading volume prediction formula is:

[0116]

[0117] The meanings of the symbols in the formula are as follows:

[0118] p p It means: the estimated LNG unloading volume of a coastal LNG terminal in the short term, 3 days, 5 days, 7 days, etc.;

[0119] S jp It means: Based on the analysis of AIS data of LNG ships arriving at coastal ports, the number of any type of ships arriving at a certain LNG terminal along the coast of my country in the next few days is obtained;

[0120] Gj represents: the actual load of the corresponding ship type, in 10,000 tons.

[0121] The present invention constructs an evaluation function from three dimensions: history, real-time and short-term prediction, and quantitatively calculates the reasonable utilization rate and reasonable capacity evaluation value of LNG port terminals applicable to different coastal areas and seasons, and quantitatively evaluates the number of LNG ships arriving at my country's coastal ports and the loading and unloading volume in the short term.

[0122] It provides quantitative indicator support in the tracking and evaluation of the LNG transportation system and assists relevant departments in emergency management, improves the scientific nature of planning, and solves technical problems such as historical data, real-time data update and international-domestic port geographic information matching, analysis process and statistical effect visualization in the tracking and evaluation and analysis of the LNG transportation system, thereby improving work efficiency and quality.

[0123] The present invention further provides a coastal LNG port operation tracking and evaluation system based on AIS data mining, which is constructed based on the above-mentioned coastal LNG port operation tracking and evaluation method based on AIS data mining, and is based on the aforementioned global LNG transport ship historical AIS database, the acquired global LNG transport ship real-time AIS data, and the coastal regional and seasonal LNG terminal capacity adaptability evaluation algorithms, so as to facilitate quantitative decision-making analysis by planners;

[0124] The coastal LNG port operation tracking and evaluation system includes a decision analysis subsystem based on historical AIS data, a decision analysis subsystem based on real-time AIS data, and a system development environment deployment.

[0125] The details are as follows:

[0126] The system development environment deployment mainly adopts Linux server, the operating system is CentOS, and the environment is built and used through command line.

[0127] The decision analysis subsystem based on historical AIS data adopts the current mainstream front-end and back-end separation technology to build a three-level architecture of data support layer, business logic layer, and front-end visual layer. Figure 3 shown.

[0128] The construction method of the data support layer is as follows: import the historical AIS data resource pool of LNG ship transportation after cleaning and route analysis into the Mysql database; based on the GIS platform, obtain the spatial geographic information data resources of ports such as international and domestic LNG terminals required for system construction;

[0129] The construction method of the business logic layer is as follows: according to the business function requirements of the system, the Spring framework technology is used for business integration, the Spring application context initializer is loaded, the SpringApplication object is initialized, the project startup class is configured, and the event listener loading is set; based on the data support layer, data is encapsulated, the algorithm function logic business is encapsulated, each business module is packaged, divided into services and functions, and a context continuous operation mechanism is established to form a general service package of the system;

[0130] The algorithm function is mainly based on the tracking and evaluation needs of the LNG transportation system, and the business module includes five major functions: analysis of the flow direction and flow of seaborne imported LNG ships by year and country; statistical analysis of the number of LNG ships calling at my country's coastal ports by year, season (with an emphasis on winter, the same below) and port; statistical analysis of the average berthing time of LNG ships by year, season and port; statistical analysis of berth utilization and terminal capacity of LNG ships berthing at terminals by year, season and port; query and analysis of the spatial and temporal trajectories and key node times of historical LNG ships berthing at my country's coastal ports.

[0131] In order to ensure system security and realize convenient remote services, the Security framework and the system unique identification MD5 string are further integrated for encryption processing. In addition, the entire system transaction management, remote access and other functions are implemented by using the aspect-oriented programming framework AOP technology under the Spring framework.

[0132] The construction method of the front-end visual layer is: it is built using Node.js and Vue-Cli systems, and rendered using the Element UI visualization framework adapted to Vue. It provides users with data display and management through the PC, such as traffic flow map display, ship spatiotemporal trajectory query, ship time statistics query at all stages of the port, map service operation, data record addition, deletion, modification and query, etc.; and integrates GIS platform data, and cooperates with the ArcGis service of the basic support layer to complete the overlay display of track maps, various data layers, remote sensing images and flow maps, attribute query and other operations.

[0133] The real-time AIS data-based decision analysis subsystem adopts the declarative HTTP client framework Feign technology, calls the AIS real-time data online HTTP target service by defining the interface description to call the service API, and then configures the request and response processing method through annotations. The real-time data service called by the present invention processes no less than 5,000 data records per second, and the activity target is greater than 100,000. The real-time AIS data resources required for system construction are obtained through step S8. When the user interface is called, the server accesses the Token obtained by the current logged-in user, thereby increasing the security and stability of the system data.

[0134] The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and protection scope of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present application.

[0135] The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and protection scope of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present application.

Claims

1. A coastal LNG port operation tracking and evaluation method based on AIS data mining, characterized in that: The following steps are involved: Data acquisition: Acquire AIS data including the first AIS historical big data and the first AIS real-time big data; Data preprocessing: Based on the ship type keyword information of LNG ships, the non-LNG ship interference data in the first AIS historical big data and the first AIS real-time big data are cleaned, and a global LNG transport ship AIS big data resource pool is constructed; Deduplication and deletion of duplicate data and abnormal data in the global LNG transport ship AIS big data resource pool; Ship voyage correlation analysis: Based on the ArcGis platform, the spatial geographic information data including the docks and anchorages of international and domestic LNG ports are integrated to analyze the spatiotemporal movement trajectory of ships in international and domestic transportation of imported LNG ships; The trajectory points with the shortest spatial distance and the closest sailing speed are associated to ensure that the ship trajectory data is the trajectory data of the same ship and the same voyage; Based on the pre-processed LNG ship AIS big data and the spatial geographic information data of international and domestic LNG ports, the LNG ship movement trajectory data and the international-domestic port regional geographic information data are matched and calculated to obtain the spatiotemporal data information of each voyage of global LNG ships; Calculate berth utilization rate and reasonable berth capacity: import the historical AIS data of global LNG ships after cleaning, correlation and voyage analysis into the MySQL database, and calculate the berth utilization rate and reasonable berth capacity of each domestic LNG terminal based on the MySQL database; The method for matching LNG ship movement trajectory data with international and domestic port area geographic information data is as follows: Identify the ship's entry and exit and berthing and unberthing times, analyze and calculate each ship's departure time, port departure time, first-leg transport arrival time, first-leg transport berthing time, domestic second-leg transshipment arrival time, and domestic second-leg transshipment berthing time. The above triggering times constitute a voyage of an LNG ship; thereby establish a 20-item indicator data set for each LNG ship's single voyage; The 20 indicator data sets mainly include ship ID, MMSI number, ship type, navigation status, port ID, port arrival time, port departure time, port berthing terminal ID, port berthing time, port departure time, navigation time, and navigation mileage; The space-time-speed nearest neighbor method is used to associate the trajectory points with the closest spatial distance and the closest navigation speed; The method of using the time-space-speed nearest neighbor method is: for two AIS ship tracks with the same MMSI number, the two tracks are track 1 and track 2; If the associated trajectory point is closest to the vertical distance d1 of the extension line of trajectory 1, and the speed v is relatively closer to the speed of the closest point (v1) of the trajectory, then the associated trajectory point is associated with trajectory 1; If the reasonable available capacity assessment value of the LNG berth to be tracked and assessed is higher than or equal to the actual transportation volume of the whole country / a certain season, the evaluation result of the LNG port facility capacity to be tracked and assessed is that the plan is reasonable; If the evaluation value of the reasonable LNG berth capacity function obtained by the evaluation function is lower than the actual transportation volume in the country / a certain season, the evaluation result of the LNG port facility capacity to be tracked and evaluated is that the plan is unreasonable, the port capacity is underutilized, and the plan needs to be adjusted.

2. According to claim 1, a coastal LNG port operation tracking and evaluation method based on AIS data mining is characterized in that: The first AIS historical big data and the first AIS real-time big data are both derived from multi-source AIS data sources including satellite-based networks, shore-based networks, and ship-based networks to ensure data coverage density in key international and domestic waters; The method for processing the global LNG transport ship AIS big data resource pool includes: data table association, table merging, row and column screening and data conversion.

3. According to claim 1, a coastal LNG port operation tracking and evaluation method based on AIS data mining is characterized in that: The calculation formula for LNG berth utilization is: ； The calculation formula can calculate the LNG berth utilization evaluation value in different regions and seasons; The meanings of the symbols in the formula are as follows: Api means: LNG berth utilization rate throughout the year or in a certain season; Si said: Based on the analysis of LNG ship AIS data, the number of any type of ship arriving at a certain LNG terminal along the coast of my country in a whole year or a certain season is obtained; The representative ship types are divided into: i=1 represents Q-max ship, i=2 represents Q-flex ship, i=3 represents 150,000-200,000 cubic meters ship, i=4 represents less than 150,000 cubic meters ship; ti means: Based on the analysis of LNG ship AIS data, the berthing time of the corresponding berthing ship type at a certain LNG terminal along the coast of my country is obtained; Tpi means: the number of effective working days throughout the year or in a certain season.

4. A coastal LNG port operation tracking and evaluation method based on AIS data mining according to claim 3, characterized in that: The calculation formula for the reasonable utilization capacity of LNG berths is: ； The formula for calculating the reasonable available capacity of LNG berths can calculate the reasonable available capacity of LNG berths in different regions and seasons; The meanings of the symbols in the formula are as follows: Pt means: the reasonable capacity assessment value of the LNG berth for the whole year or a certain season, in 10,000 tons; Api means: the berth utilization rate of LNG berths throughout the year or in a certain season, which is obtained based on the LNG berth utilization rate calculation formula; Tpi means: the number of effective working days in a whole year or a certain season; td means: day and night hours, 24 hours; tz means: net unloading time for the corresponding ship type, in hours, obtained through research; tf represents: auxiliary operation time of ship loading and unloading, in hours, obtained through investigation; th represents: the additional time required for waiting for tides and currents or not entering and exiting the channel and berthing and leaving at night, in hours, obtained through surveys; Gj represents: the actual load of the corresponding representative ship type, in 10,000 tons, obtained through research; Indicates: The weight of the corresponding representative ship type, calculated based on AIS data.

5. The method for tracking and evaluating coastal LNG port operations based on AIS data mining according to claim 1 is characterized in that: The method also includes predicting and evaluating the short-term arrival LNG ship forecast and unloading volume based on the real-time big data of AIS of global LNG transport ships. The specific evaluation method is: According to the current position of the LNG transport ship on the international route provided by the real-time data, the 'destination' field information of the ship's AIS static data is extracted, and the recent empirical routes of the LNG ships in operation are matched according to the probability analysis of the historical calling routes of each LNG ship obtained by the above evaluation. The empirical routes are used to match the LNG ships expected to arrive at my country's coastal ports; in this way, the number of ships by type expected to arrive at various coastal LNG terminals in a short period of time is evaluated, and the empirical parameters of the actual load rate of LNG by type obtained by the survey experience can be combined to calculate the LNG unloading volume of ships expected to be unloaded in the short term at various coastal LNG terminals; The short-term arrival LNG ship forecasting and unloading volume forecasting and evaluation method is used to forecast LNG ships at my country's coastal ports and assist in short-term supply situation assessment and decision-making.

6. A coastal LNG port operation tracking and evaluation method based on AIS data mining according to claim 5, characterized in that: The LNG unloading volume prediction formula is: The meanings of the symbols in the formula are as follows: p p It means: the estimated LNG unloading volume of a coastal LNG terminal in the next few days; S jp It means: Based on the analysis of AIS data of LNG ships arriving at coastal ports, the number of any type of ships arriving at a certain LNG terminal along the coast of my country in the next few days is obtained; G j Indicates: the actual load of the corresponding ship type, in 10,000 tons.

7. A coastal LNG port operation tracking and evaluation system based on AIS data mining, characterized in that: The coastal LNG port operation tracking and evaluation system is constructed based on a coastal LNG port operation tracking and evaluation method based on AIS data mining as described in claim 6, which facilitates quantitative decision-making analysis by planners; The coastal LNG port operation tracking and evaluation system includes a decision analysis subsystem based on historical AIS data and a decision analysis subsystem based on real-time AIS data; The decision analysis subsystem based on historical AIS data includes a front-end visual layer for human-computer interaction, a business logic layer for processing data information, and a data support layer for storing data information; The real-time AIS data-based decision analysis subsystem adopts the declarative HTTP client framework Feign technology, defines the interface description to call the service API, and then configures the request and response processing method through annotations to call the AIS real-time data online HTTP target service.

8. A coastal LNG port operation tracking and evaluation system based on AIS data mining according to claim 7, characterized in that: The construction method of the data support layer is as follows: import the historical AIS data resource pool of LNG ship transportation after cleaning and route analysis into the Mysql database; based on the GIS platform, obtain the spatial geographic information data resources of ports such as international and domestic LNG terminals required for system construction; The construction method of the business logic layer is as follows: according to the business function requirements of the system, the Spring framework technology is used for business integration, the Spring application context initializer is loaded, the SpringApplication object is initialized, the project startup class is configured, and the event listener loading is set; based on the data support layer, data is encapsulated, the algorithm function logic business is encapsulated, each business module is packaged, divided into services and functions, and a context continuous operation mechanism is established to form a general service package of the system; The construction method of the front-end visual layer is: it is built using Node.js and Vue-Cli systems, and rendered using the Element UI visualization framework adapted to Vue. It provides users with data presentation and management through the PC, integrates GIS platform data, and cooperates with the ArcGis service of the basic support layer to complete the overlay display of track maps, various data layers, remote sensing images and flow maps, and attribute query operations.

Images