CN110363369B - Ship shelving state judgment method, device, equipment and storage medium thereof - Google Patents

Ship shelving state judgment method, device, equipment and storage medium thereof Download PDF

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CN110363369B
CN110363369B CN201810323266.8A CN201810323266A CN110363369B CN 110363369 B CN110363369 B CN 110363369B CN 201810323266 A CN201810323266 A CN 201810323266A CN 110363369 B CN110363369 B CN 110363369B
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梁新
徐垚
温建新
赵利坡
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CETC Ocean Information Co Ltd
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Abstract

The application discloses a ship shelving state judging method, a ship shelving state judging device, equipment and a storage medium of the equipment. The method comprises the following steps: acquiring a ship real-time data set, wherein the ship real-time data set comprises at least one piece of real-time data at the same moment, and each piece of real-time data corresponds to each ship; judging whether the ship corresponding to the real-time data has an anchoring state and a ballast state simultaneously based on each real-time data in the real-time data set; if the vessel has both mooring and ballasting conditions, the vessel is in a stranded state. According to the technical scheme of the embodiment of the application, whether the ship is in the resting state or not is identified by identifying the anchoring state and the ballast state of the ship, the problem that the resting state of the ship cannot be identified in real time in the prior art is solved, the operation cost is reduced, and the reasonable planning of the ship stage is realized.

Description

Ship resting state judgment method, device, equipment and storage medium thereof
Technical Field
The present application relates generally to the field of marine transportation, and more particularly, to the field of data mining technology applied to marine transportation, and more particularly, to a method, an apparatus, a device, and a storage medium for determining a ship shelving status.
Background
Over 90% of goods trade in the world is completed by ship transportation, which causes the ship traffic in sea traffic main roads and port water areas to be increasingly congested. While the port and shipping industry is vigorously developed, the awareness of the risk of ship navigation needs to be improved. Therefore, acquiring the state data of the ship is an important basis for port construction, shipping policy, and maritime affair management.
At present, possible activity states of a ship include 4 states of putting aside, transporting, waiting at a port, loading and unloading at the port, and the states directly affect the work of port management, shipping arrangement and the like. The ship is placed, namely, the ship is selected to be temporarily stopped in the air when the shipping market is not in the air, and only a small number of crews are arranged on the ship to meet the requirements of fire fighting, damage management, security guard duty and other emergency operations of the ship. The ship shelving state can be divided into different situations such as hot car shelving, cold car shelving, long-term shelving and the like.
However, currently, there is no good criterion for determining whether a ship is in a resting state.
Disclosure of Invention
In view of the above-mentioned defects or shortcomings in the prior art, it is desirable to provide a solution for intelligently identifying whether a ship is in a resting state, which fills the gap in identifying the resting state of the ship.
In a first aspect, an embodiment of the present application provides a ship resting state determination method, including:
acquiring a ship real-time data set, wherein the ship real-time data set comprises at least one piece of real-time data at the same moment, and each piece of real-time data corresponds to each ship;
judging whether the ship corresponding to the real-time data has an anchoring state and a ballast state simultaneously based on each real-time data in the real-time data set;
if the vessel has both mooring and ballasting conditions, the vessel is in a stranded state.
In a second aspect, an embodiment of the present application provides a ship resting state determination device, including:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a ship real-time data set, and the ship real-time data set comprises at least one piece of real-time data at the same moment, and each piece of real-time data corresponds to each ship;
the first judgment unit is used for judging whether the ship corresponding to the real-time data has an anchoring state and a ballast state simultaneously or not based on each real-time data in the ship real-time data set; if the vessel has both mooring and ballasting conditions, the vessel is in a stranded state.
In a third aspect, embodiments of the present application provide a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the method as described in embodiments of the present application when executing the program.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, the computer program being configured to:
which when executed by a processor implements a method as described in embodiments of the present application.
According to the technical scheme provided by the embodiment of the application, whether the anchoring state and the ballast state exist in the ship or not is judged through analyzing the ship behavior data, and if the anchoring state and the ballast state exist in the ship, the ship is judged to be in the resting state. The technical scheme overcomes the problem that the shelve state of the ship cannot be identified in real time in the prior art, reduces the operation cost and realizes the reasonable planning of the shipping time.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
fig. 1 is a schematic flow chart illustrating a ship resting state determining method according to an embodiment of the present application;
fig. 2 is a schematic flow chart illustrating a ship resting state determining method according to still another embodiment of the present application;
fig. 3 is a block diagram showing an exemplary structure of a ship resting state determination apparatus according to an embodiment of the present application;
fig. 4 is a schematic structural diagram illustrating an exemplary ship resting state determining apparatus according to still another embodiment of the present application;
fig. 5 shows a schematic structural diagram of a computer system suitable for implementing the terminal device of the embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a ship resting state determining method according to an embodiment of the present application.
As shown in fig. 1, the method includes:
step 110, a ship real-time data set is obtained, wherein the ship real-time data set includes at least one real-time data at the same time, and each real-time data corresponds to each ship.
According to the ship state judging method and device, the state of the ship is judged by acquiring real-time data of the ship and analyzing the data. Wherein the real-time data of the ship is data related to a plurality of ships provided by the data source at each moment. The real-time data may be provided by one or more data sources simultaneously, for example. The data source may be, for example, a marine automatic identification system AIS, radar, beidou satellite navigation system, global positioning system GPS, or the like. The real-time data content provided by different data sources is different. For example, AIS telegraph data provided by the AIS system may include: the calling number of the ship, the type of the ship, the identification code MMSI (unique identification information of the ship), the speed of the ship, the heading direction, the track direction, the longitude, the latitude, the destination of the ship, the length and the width of the ship, the depth of draught of the ship and the like. For example, textual data provided by a radar system, which may include: radar ID number (unique identification information of the ship), ship orientation, ship speed, course and the like. Among them, the ship may be various cargo ships.
The ship real-time data set may be, for example, related data of a plurality of ships, and the data corresponding to each ship may be identified by unique identification information of the ship. For example,
at t 1 The AIS data sources provide real-time data that is received individually at a time,where each datum may be represented, for example, as (MMSI of the vessel, data, t) 1 ) The MMSI of a vessel is used to uniquely identify different vessels.
Or, at t 1 The real-time data provided by the radar data source are received individually at a time, each data being represented, for example, by (radar ID number, data, t) 1 ) Etc., the radar ID number is used to uniquely identify different vessels.
Or, at t 1 The real-time data of the same fusion batch number is obtained by a data fusion processing mode, for example, the real-time data can be expressed as (fusion batch number, data, t) 1 ) Wherein the fused lot number is used to uniquely identify the different vessels. The above method is only illustrative of real-time data, and the form and content of the real-time data are not particularly limited.
Step 120, judging whether the ship corresponding to the real-time data has an anchoring state and a ballast state simultaneously based on each real-time data in the real-time data set; the vessel is in a parked condition if both a moored condition and a ballasted condition exist with the vessel.
In the embodiment of the present application, after the real-time data of multiple ships at the same time are obtained in step 110, each real-time data is determined. Before the judgment, the acquired real-time data of a certain ship can be preprocessed correspondingly, and the preprocessing mode can be data fusion processing, repeated data cleaning, error data cleaning, data sorting, data interpolation processing and the like. And then judging each piece of real-time data after preprocessing.
For example, the behavior characteristic data for characterizing the ship in each real-time data is judged by using a specific judgment rule, so that the state of the ship is identified. The behavioral characteristic data for characterizing the ship may be, for example, data of speed, displacement, direction, draft, and the like of the ship. For example, the data of the ship such as speed, displacement and direction are judged with a certain rule base, so as to obtain whether the anchoring state of the ship exists. And further judging the draft depth value of the ship in the real-time data under the condition that the anchoring state exists, and if the draft depth value is compared with a certain preset value and meets the condition, determining that the ship is in a resting state.
The mooring state, also called a cast-off state, is mainly the behavior of safely mooring a ship by only using the mooring force of an anchor and an anchor chain. The ship needs to be anchored in order to load and unload goods, shelter from wind and wait for berthing. The ballast state refers to that a certain amount of seawater is pumped into the bottom of the ship tank to enhance the wind and wave resistance in order to keep the stability when the ship is unloaded. The unloaded state is a state in which the ship is not loaded. The ship-at-rest state means that the ship is not in maintenance but stops shipping.
Wherein the rule base is a set of thresholds corresponding to the ship parameters, and setting conditions. For example, the rule base may include a first threshold corresponding to the speed of the ship, a second threshold corresponding to the displacement of the ship, and if the set condition is, for example, less than the first threshold and less than the second threshold, and the sailing direction is continuous, it is determined that the anchoring state of the ship exists.
In the prior art, the judgment of the shelved state of the ship always lags behind the incident, so that the ship management platform cannot timely and effectively make a coping management strategy. Therefore, the embodiment of the present application provides a method capable of determining whether a ship is in a resting state in real time to overcome the foregoing problems.
For example, step 110 obtains t 1 Ship real-time data set { A) of time 1 ，A 2 ，A N In which A is 1 Denoted as vessel A at t 1 Data relating to time of day, A 2 Denoted as vessel B at t 1 Data relating to time of day, A N Indicates that the ship X is at t 1 Data relating to the time of day.
From A to A 1 And extracting behavioral characteristic data for representing the ship A, the navigational speed, the displacement, the direction and the draft of the ship.
And then comparing the speed of the ship A in the behavior characteristic data for representing the ship A with a first threshold value, if the speed of the ship A is smaller than the first threshold value, further comparing the displacement of the ship A with a second threshold value, if the displacement of the ship A is smaller than the second threshold value, further judging that the ship A has an anchoring state, and if the displacement of the ship A is smaller than the second threshold value, further judging that the sailing direction of the ship A is continuous, otherwise, judging that the anchoring state does not exist.
And when the ship A has an anchoring state, further judging the relation between the draft of the ship A and a third threshold value, and if the draft of the ship A is smaller than the third threshold value, judging that the ship A has a ballast state. When the anchoring state and the harbour pressing state exist in the ship A at the same time, the ship A can be determined to be in the resting state, so that the condition of the ship A is judged in real time and is sent to a ship management platform or other service platforms, and the management efficiency of the ship is improved.
According to the embodiment of the application, each piece of real-time data in the ship real-time data set is analyzed and judged to obtain that the ship has both an anchoring state and a ballast state, so that the corresponding ship is determined to be in a resting state.
In the embodiment of the application, the values of the preset first threshold, the second threshold and the third threshold can be determined in various ways. The values of the first threshold, the second threshold and the third threshold can be obtained according to the historical data of ship navigation or abnormal values in a normal navigation track can be selected. Preferably, the estimation can be obtained through a machine learning model, and the machine learning model is obtained through training and learning of a machine learning algorithm through a large amount of historical ship data. The state of the ship can be judged more accurately by estimating the threshold value through the machine learning model, and the judgment efficiency is improved.
According to the embodiment of the application, whether the ship is in the anchoring state and the ballasting state at the same time is obtained through analyzing the ship behavior data, so that whether the ship is in the resting state is judged. The shelving state of the ship is accurately identified, the management efficiency of the ship is improved, and the time and economic resources for ship management are saved.
On the basis of fig. 1, the embodiment of the present application further provides a ship resting state determination method, which further improves data processing efficiency. Referring to fig. 2, fig. 2 is a schematic flow chart illustrating a ship resting state determining method according to another embodiment of the present application.
As shown in fig. 2, the method includes:
optionally, step 210, operational parameters are obtained.
The operating parameters may include, for example: preset time range, ship type, etc.
The preset time range may be, for example, a time period of 30 minutes, 1 hour, etc., and the setting may be adjusted according to different requirements. The ship type may be a dry cargo ship, a liquid cargo ship, a refrigerated ship, a container ship, etc. The acquisition mode may read parameters from the corresponding functional area by a trigger event instruction. For example, parameters acquired in advance by the input device or parameters acquired in advance by the remote control apparatus are read.
Step 220, acquiring a ship real-time data set provided by the data source according to the operation parameters, wherein the ship real-time data set comprises at least one piece of real-time data at the same time, and each piece of real-time data corresponds to each ship.
The ship real-time data set may be, for example, data related to multiple ships provided by the data source at the same time, each piece of real-time data in the ship real-time data set corresponds to one ship, and the real-time data may be identified by unique identification information of the ship. E.g. at t 1 The real-time data provided by the AIS data sources are received individually at a time, where each data may be represented as (MMSI of the ship, data, t), for example 1 ) The MMSI of a ship is used to uniquely identify different ships. Or, at t 1 The real-time data provided by the radar data source are received individually at a time, each data being represented, for example, by (radar ID number, data, t) 1 ) Etc., the radar ID number is used to uniquely identify different vessels. Or, at t 1 The real-time data is received from a plurality of data sources at the same time, and the real-time data of the same fusion lot number is obtained through a data fusion processing mode, and can be represented as (fusion lot number, data, t 1), for example, wherein the fusion lot number is used for uniquely identifying different ships. The above method is merely illustrative of real-time data, and the form and content thereof are not particularly limited.
The ship real-time data set may be provided by at least one data source. The data source may be at least one of the following: the system comprises an automatic identification system AIS of the ship, a radar, a Beidou satellite navigation system and a global positioning system GPS.
An Automatic Identification System (AIS) for ships is a digital navigation aid System and equipment integrating network technology, modern communication technology, computer technology and electronic information display technology, which is connected with a GPS locator, a detector, an electric compass and the like on a ship through interfaces to acquire various ship navigation data and display the real-time navigation data provided by an operator on an electronic display screen. At the same time, the static and dynamic information of the ship is transmitted to a nearby onshore base station or satellite through the transmitting equipment of the system, and the data can be received by the surrounding ship and the traffic management center in the process.
An Automatic Radar plotter (APRA) is widely applied to ship monitoring and target positioning. The radar can only transmit signals in a single way, then receives and processes the returned information, but cannot receive the returned information of other radars, and the radar also has the problems of working blind areas, insufficient provided target information, low data reliability and the like.
Ocean boats and ships big dipper location navigation comprises satellite navigation operation center, bank end surveillance center and on-board big dipper terminal equipment, can realize omnidirectional ship position control through beidou system. For example, after receiving the AIS telegraph text and analyzing the AIS telegraph text to obtain the ship type, the MMSI code of the ship and relevant data of the ship corresponding to the MMSI code, such as data of speed, heading, draft, longitude, latitude, heading direction, track direction and the like corresponding to the MMSI, are further extracted. Or receiving radar telegraph text, and analyzing to obtain data such as ship speed, course and the like.
Step 230, preprocessing the ship real-time data set.
According to the embodiment of the application, after the ship real-time data set provided by the data source is obtained, corresponding preprocessing needs to be carried out on the real-time data.
The pretreatment may include one or more of the following methods:
data fusion processing, repeated data cleaning, error data cleaning, data sequencing and data interpolation processing.
In the embodiment of the present application, the acquired real-time data provided by the data source may be provided by a single data source alone, or provided by a plurality of different data sources simultaneously, for example. When a plurality of different data sources are provided simultaneously, a data fusion processing technology can be adopted, and real-time data provided by the different data sources are subjected to a series of processing such as coordinate transformation, time alignment, track association, track fusion and the like to obtain a data fusion processing result, so that the tracking precision is improved.
According to the embodiment of the application, the real-time data provided by each data source may have the problems of repetition, obvious errors, inconsistent time sequence and the like, and in order to more effectively utilize the data, for example, data processing modes such as repeated data cleaning, error data cleaning, data sorting, data interpolation processing and the like can be selected to correspondingly process the acquired real-time data, so that the data processing efficiency is improved. For example, the repeated data cleaning can clean the repeated and redundant data of the ship, so as to avoid reducing the calculation processing time and improve the timeliness of data processing. And error data cleaning can delete obvious data belonging to abnormal values or error values in the input data of the data source, so that the data processing quality is improved, and the reasonability of the data is ensured. The data sorting processing can sort the real-time position data of the ship according to time or other sequences, provides an optional interface for processing the ship behavior data, and is convenient for other terminal users to obtain data resources according to different requirements. The data interpolation processing is to supplement missing points in the data, and the commonly used data interpolation methods include Lagrange interpolation and the like, and the quality of the processed data is improved through data difference processing. The efficiency of the later data analysis and processing can be further improved through the preprocessing.
Optionally, step 240, determining whether a trigger condition is satisfied based on the statistical flag of each real-time data in the ship real-time data set, where the trigger condition is used to trigger execution of determining whether the anchoring state and the ballast state of the ship corresponding to the real-time data exist at the same time based on the real-time data.
According to the embodiment of the application, before judging whether the ship uniquely corresponding to each piece of real-time data simultaneously has the anchoring state and the ballast state based on the preprocessed ship real-time data set, whether the ship simultaneously has the anchoring state and the ballast state can be selectively triggered and judged by judging the statistical mark of the real-time data.
The statistical mark of the real-time data refers to the accumulated occurrence times of a certain ship within a preset time range. This may be in the form of, for example, a specific identification field in the data format, or an additional field, or a generated identification indicating accumulated information. The identification may be a cumulative number. E.g. at t 1 At a time, real-time data provided by the AIS data source is acquired, where each real-time data may be represented, for example, as (MMSI, data, t) 1 Statistical identification).
And when the value of the statistical identifier is greater than or equal to a preset threshold value, triggering and executing to judge whether the anchoring state and the ballast state exist in the ship at the same time. E.g. t 1 The method comprises the steps of obtaining a statistical identifier of 0 at a moment when the data are obtained, judging by using the statistical identifier and a preset threshold, directly judging the next data (item i + 1) without executing the step of judging whether the ship A has an anchoring state and a ballast state at the same time if the statistical identifier is smaller than the preset threshold, and determining whether the ship B has the anchoring state and the ballast state at the same time by adopting the same method for judging the statistical identifier.
At t 1+n The jth data in the real-time data at the moment belongs to data of a ship A, when the data are obtained, a statistical identifier at the moment is n-1, the statistical identifier and a preset threshold value are judged, and if the statistical identifier is larger than or equal to the preset threshold value, a step of judging whether the ship A has an anchoring state and a ballast state at the same time is triggered and executed.
By additionally arranging the triggering condition judging step, the data processing efficiency is further improved, and the data processing time is saved.
And step 250, judging whether the ship corresponding to the real-time data has an anchoring state or not based on each real-time data in the ship real-time data set.
In the embodiment of the present application, step 250 is optionally triggered by step 240. For example, the statistical identifier of the ith piece of data in the ship real-time data set is greater than or equal to a preset threshold, step 250 is executed.
And extracting the behavior characteristic data used for representing the ship in the ith data, comparing the behavior characteristic data with the mooring behavior rule base, and determining that the ship corresponding to the ith data has a mooring state if the setting conditions of the mooring behavior rule base are met.
The behavior characteristic data for characterizing the ship may include, for example: the sailing speed, sailing displacement and sailing direction of the ship are changed; the sailing displacement is the displacement generated by the current ship behavior relative to the initial ship behavior; the change in sailing direction is a change in direction of the sailing displacement.
By analyzing the ship behavior characteristic data or comparing the ship behavior characteristic data with a preset threshold value, the anchoring behavior of the ship can be identified, and therefore the efficiency of identifying the anchoring behavior is improved.
The method comprises the steps of establishing a corresponding anchoring behavior rule base based on ship behavior characteristic data, namely specifying option contents of the behavior characteristic data of the ship and setting conditions required to be met by each option content.
In the embodiment of the present invention, the mooring behavior rule base may be a set of determination rules for ship mooring behavior, and the set may define the mooring behavior through one or more rules, for example, perform qualitative comprehensive evaluation determination on data for characterizing ship behavior characteristics, or perform quantitative comprehensive evaluation determination based on the ship behavior characteristics. The anchor behavior rules library may include, for example: the navigation speed is less than a preset first threshold value; the navigation displacement is smaller than a preset second threshold value; the change of the sailing direction is a continuous change.
The values of the preset first threshold, the second threshold and the third threshold can be determined in various ways. The values of the first threshold, the second threshold and the third threshold can be obtained according to the analysis of the historical data of the ship navigation, or abnormal values in a normal navigation track can be selected. Preferably, the estimation can be obtained through a machine learning model, and the machine learning model is obtained through training and learning of a large amount of historical ship data by adopting a machine learning algorithm. The state of the ship can be accurately judged through the machine learning model prediction threshold, and the judgment efficiency is improved.
If the determination result in step 250 is yes, the process proceeds to step 260. If the determination result in the step 250 is negative, the process continues to return to the step 250, and the next real-time data in the ship real-time data set is determined.
And step 260, judging whether the ship corresponding to the real-time data has a ballast state or not based on the real-time data.
In the embodiment of the present application, after determining that the anchoring state exists in each real-time data in the ship real-time data set through step 250, the draft depth value of the ship is continuously extracted from the real-time data,
and then, comparing the draft depth value with a preset draft depth threshold value, and if a judgment condition is met, the ship corresponding to the real-time data has a ballast state.
The preset draft threshold may be, for example, an unloaded draft threshold, or a difference threshold set according to a difference between the unloaded draft and the loaded draft.
For example, if the draft value of the ship is smaller than the empty draft threshold value or the difference threshold value, it indicates that the judgment condition is satisfied, and it is determined that the ballast state of the ship exists.
The draft threshold value (which may be referred to as a third threshold value for the sake of distinction) may be set based on an empirical value or may be set based on an actual unloaded draft, and the draft in the ship ballast state may be determined by, for example, the ship type, the ship length, and the ship width indicated in the ship static information.
Preferably, the estimation can be further obtained through a machine learning model, and the machine learning model is obtained through training and learning of a large amount of historical ship data by adopting a machine learning algorithm.
The mooring behavior of the ship in the preset range is determined through the judgment of the mooring state of the ship, then whether the ship carries goods or not is judged through the draught of the ship, the mooring behavior and the ballast behavior of the ship are integrated, and finally the ship which is moored and does not carry goods can be judged to be in the mooring state, so that the ship management efficiency is improved.
If the determination result in step 260 is yes, it is determined that the ship uniquely corresponding to the real-time data is in the parked state. If the determination result in the step 260 is negative, the process continues to return to the step 260, and the next real-time data in the ship real-time data set is determined. And (4) until all real-time data in the ship real-time data set are judged to be finished.
After the ship is in the resting state, the state information of the ship is provided to a management organization such as a shipping company or a port administration in real time, and real-time service information is provided for the management organization, so that the shipping management efficiency is improved.
It should be noted that while the operations of the method of the present invention are depicted in the drawings in a particular order, this does not require or imply that the operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
The embodiment of the application also provides a device for judging the ship resting state. Referring to fig. 3, fig. 3 is a block diagram illustrating an exemplary structure of a ship resting state determining apparatus according to an embodiment of the present application.
The apparatus 300 comprises:
the first obtaining unit 310 is configured to obtain a ship real-time data set, where the ship real-time data set includes at least one real-time data at the same time, and each real-time data corresponds to each ship.
According to the ship state judging method and device, the state of the ship is judged by acquiring real-time data of the ship and analyzing the data. The real-time data of the ship is data related to a plurality of ships provided by a data source at each moment. The real-time data may be provided by one or more data sources simultaneously, for example. The data source may be, for example, a marine automatic identification system AIS, radar, beidou satellite navigation system, global positioning system GPS, or the like. The real-time data content provided by different data sources is different. For example, AIS telegraph data provided by the AIS system may include: the system comprises a calling number of a ship, a ship type, a water mobile communication service identification code MMSI (unique identification information of the ship), the speed of the ship, the heading direction, the track direction, the longitude, the latitude, the destination of the ship, the length and the width of the ship, the draft value of the ship and the like. For example, textual data provided by a radar system, which may include: radar ID number (unique identification information of the ship), ship orientation, ship speed, course and the like. Among them, the ship may be various cargo ships.
The ship real-time data set may be, for example, related data of a plurality of ships, and the data corresponding to each ship may be identified by unique identification information of the ship. E.g. at t 1 The real-time data provided by the AIS data sources are received individually at a time, where each data may be represented as (MMSI of the ship, data, t), for example 1 ) The MMSI of a vessel is used to uniquely identify different vessels. Or, at t 1 The real-time data provided by the radar data source are received individually at a time, each data being represented, for example, by (radar ID number, data, t) 1 ) Etc., the radar ID number is used to uniquely identify different vessels. Or, at t 1 The real-time data of the same fusion batch number is obtained by a data fusion processing mode, for example, the real-time data can be expressed as (fusion batch number, data, t) 1 ) Wherein the fused lot numbers are used to uniquely identify different vessels. The above method is merely illustrative of real-time data, and the form and content thereof are not particularly limited.
A first judging unit 320, configured to judge, based on each piece of real-time data in the real-time data set, whether a ship corresponding to the real-time data has both an anchoring state and a ballast state; if the vessel has both mooring and ballasting conditions, the vessel is in a stranded state.
In the embodiment of the present application, after the first obtaining unit 310 obtains the real-time data of multiple ships at the same time, each real-time data is determined. Before the judgment, the acquired real-time data of a certain ship can be preprocessed correspondingly, and the preprocessing mode can be data fusion processing, repeated data cleaning, error data cleaning, data sorting, data interpolation processing and the like. And then judging each piece of real-time data after preprocessing.
For example, the behavior characteristic data for characterizing the ship in each real-time data is judged by using a specific judgment rule, so that the state of the ship is identified. The behavioral characteristic data for characterizing the ship may be, for example, data of speed, displacement, direction, draft, and the like of the ship. For example, the data of the ship such as the speed, displacement and direction are judged with a certain rule base, so that whether the ship has the anchoring state or not can be obtained. And further judging the draft depth value of the ship in the real-time data under the condition that the anchoring state exists, and if the draft depth value is compared with a certain preset value and meets the condition, determining that the ship is in a resting state.
The mooring state, also called a cast-off state, is mainly the behavior of safely mooring a ship by only using the mooring force of an anchor and an anchor chain. Ships need anchoring and berthing for loading and unloading goods, avoiding wind and waiting berths. The ballast state refers to that a certain amount of seawater is pumped into the bottom of the ship tank to enhance the wind and wave resistance in order to keep the stability when the ship is unloaded. The unloaded state is a state in which the ship is not loaded. The ship-on-hold state means that the ship is not in maintenance but stops shipping.
Wherein the rule base is a set of thresholds corresponding to the ship parameters, and setting conditions. For example, the rule base may include a first threshold corresponding to the speed of the ship, a second threshold corresponding to the displacement of the ship, and if the set condition is, for example, less than the first threshold and less than the second threshold, and the sailing direction is continuous, it is determined that the anchoring state of the ship exists.
In the prior art, the judgment of the shelved state of the ship always lags behind the incident, so that the ship management platform cannot timely and effectively make a coping management strategy. Therefore, the embodiments of the present application provide a method capable of determining whether a ship is in a resting state in real time to overcome the foregoing problems.
For example, the first obtaining unit 310 obtains t 1 Ship real-time data set { A) of time 1 ，A 2 ，A N In which A is 1 Denoted as vessel A at t 1 Data relating to time of day, A 2 Denoted as vessel B at t 1 Data relating to time of day, A N Indicates that the ship X is at t 1 Time of day correlation data.
From A 1 And extracting behavioral characteristic data for representing the ship A, the navigational speed, the displacement, the direction and the draft of the ship.
And then comparing the speed of the ship A in the behavior characteristic data for representing the ship A with a first threshold value, if the speed of the ship A is smaller than the first threshold value, further comparing the displacement of the ship A with a second threshold value, if the displacement of the ship A is smaller than the second threshold value, further judging that the ship A has an anchoring state, and if the displacement of the ship A is smaller than the second threshold value, further judging that the sailing direction of the ship A is continuous, otherwise, judging that the anchoring state does not exist.
And when the ship A has an anchoring state, further judging the relation between the draft of the ship A and a third threshold value, and if the draft of the ship A is smaller than the third threshold value, judging that the ship A has a ballast state. When the anchoring state and the harbour pressing state exist in the ship A at the same time, the ship A can be determined to be in the resting state, so that the condition of the ship A is judged in real time and sent to a ship management platform or other service platforms, and the management efficiency of the ship is improved.
According to the embodiment of the application, each piece of real-time data in the ship real-time data set is analyzed and judged to obtain that the ship has both an anchoring state and a ballast state, so that the corresponding ship is determined to be in a resting state.
In the embodiment of the application, the values of the preset first threshold, the second threshold and the third threshold can be determined in various ways. The values of the first threshold, the second threshold and the third threshold can be obtained according to the analysis of the historical data of the ship navigation, or abnormal values in a normal navigation track can be selected. Preferably, the estimation can be obtained through a machine learning model, and the machine learning model is obtained through training and learning of a machine learning algorithm through a large amount of historical ship data. The state of the ship can be accurately judged through the machine learning model prediction threshold, and the judgment efficiency is improved.
According to the embodiment of the application, whether the ship is in the mooring state and the ballast state at the same time is obtained through analyzing the ship behavior data, so that whether the ship is in the resting state is judged. The shelving state of the ship is accurately identified, the management efficiency of the ship is improved, and the time and economic resources for ship management are saved.
On the basis of fig. 3, the embodiment of the present application further provides a ship resting state determination method, so as to further improve data processing efficiency. Referring to fig. 4, fig. 4 is a schematic structural diagram illustrating an exemplary ship resting state determining apparatus according to another embodiment of the present application.
As shown in fig. 4, the apparatus 400 includes:
optionally, a second obtaining unit 410 is configured to obtain the operation parameter.
The operating parameters may include, for example: preset time range, ship type, etc.
The preset time range may be, for example, a time period of 30 minutes, 1 hour, etc., and the setting may be adjusted according to different requirements. The ship type may be a dry cargo ship, a liquid cargo ship, a refrigerated ship, a container ship, etc. The acquisition mode may read parameters from the corresponding functional area by a trigger event instruction. For example, parameters acquired in advance by the input device or parameters acquired in advance by the remote control apparatus are read.
A first obtaining unit 420, configured to obtain a ship real-time data set provided by a data source according to the operation parameter.
The ship real-time data set may be, for example, data related to multiple ships provided by the data source at the same time, each piece of real-time data in the ship real-time data set corresponds to one ship, and the real-time data may be identified by unique identification information of the ship. E.g. at t 1 The real-time data provided by the AIS data sources are received individually at a time, where each data may be represented, for example, as (MMSI of the vessel, data,t 1 ) The MMSI of a vessel is used to uniquely identify different vessels. Or, at t 1 The real-time data provided by the radar data source are received individually at a time, each data being represented, for example, by (radar ID number, data, t) 1 ) Etc., the radar ID number is used to uniquely identify different vessels. Or, at t 1 The real-time data of the same fusion batch number is obtained by a data fusion processing mode, for example, the real-time data can be expressed as (fusion batch number, data, t) 1 ) Wherein the fused lot number is used to uniquely identify the different vessels. The above method is only illustrative of real-time data, and the form and content of the real-time data are not particularly limited.
The ship real-time data set may be provided by at least one data source. The data source may be at least one of the following: the system comprises an automatic identification system AIS of the ship, a radar, a Beidou satellite navigation system and a global positioning system GPS.
An Automatic Identification System (AIS) for ships is a digital navigation aid System and equipment integrating network technology, modern communication technology, computer technology and electronic information display technology, which is connected with a GPS locator, a detector, an electric compass and the like on a ship through interfaces to acquire various ship navigation data and display the real-time navigation data provided by an operator on an electronic display screen. At the same time, the static and dynamic information of the ship is transmitted to a nearby onshore base station or satellite through the transmitting equipment of the system, and the data can be received by the surrounding ship and the traffic management center in the process.
An Automatic Radar plotter (APRA) is widely applied to ship monitoring and target positioning. The radar can only transmit signals in a single way, then receives and processes the returned information, but cannot receive the returned information of other radars, and the radar also has the problems of working blind areas, insufficient provided target information, low data reliability and the like.
Ocean boats and ships big dipper location navigation comprises satellite navigation operation center, bank end surveillance center and on-board big dipper terminal equipment, can realize omnidirectional ship position control through big dipper system.
For example, after receiving the AIS telegraph text and analyzing the AIS telegraph text to obtain the ship type, further extracting the MMSI code of the ship and the relevant data of the ship corresponding to the MMSI code, such as the data of the speed, heading, draft, longitude, latitude, heading direction, track direction and the like corresponding to the MMSI code. Or receiving radar telegraph text, and analyzing to obtain data such as ship speed, course and the like.
And the preprocessing unit 430 is used for preprocessing the ship real-time data set.
According to the embodiment of the application, after the ship real-time data set provided by the data source is obtained, corresponding preprocessing needs to be carried out on the real-time data.
The pretreatment may include one or more of the following methods:
data fusion processing, repeated data cleaning, error data cleaning, data sequencing and data interpolation processing.
In the embodiment of the present application, the acquired real-time data provided by the data source may be provided by a single data source alone, or may be provided by a plurality of different data sources simultaneously. When a plurality of different data sources are provided simultaneously, a data fusion processing technology can be adopted, and real-time data provided by the different data sources are subjected to a series of processing such as coordinate transformation, time alignment, track association, track fusion and the like to obtain a data fusion processing result, so that the tracking precision is improved.
According to the embodiment of the application, the real-time data provided by each data source may have the problems of repetition, obvious errors, inconsistent time sequence and the like, and in order to more effectively utilize the data, for example, data processing modes such as repeated data cleaning, error data cleaning, data sorting, data interpolation processing and the like can be selected to correspondingly process the acquired real-time data, so that the data processing efficiency is improved. For example, the repeated data cleaning can clean the repeated redundant data of the ship, so as to avoid reducing the calculation processing time and improve the timeliness of data processing. And error data cleaning can delete obvious data belonging to abnormal values or error values in the input data of the data source, so that the data processing quality is improved, and the reasonability of the data is ensured. And the data sorting processing can sort the real-time position data of the ship according to time or other sequences, provide an optional interface for processing the ship behavior data, and facilitate other terminal users to acquire data resources according to different requirements. The data interpolation processing is to supplement missing points in the data, the commonly used data interpolation methods include Lagrange interpolation and the like, and the quality of the processed data is improved through data difference processing. The efficiency of the later data analysis and processing can be further improved through the preprocessing.
Optionally, the second determining unit 440 is configured to determine whether a triggering condition is met based on the statistical flag of each real-time data in the ship real-time data set, where the triggering condition is used to trigger execution of determination of whether the ship corresponding to the real-time data has the mooring state and the ballast state based on the real-time data.
According to the embodiment of the application, before judging whether the ship uniquely corresponding to each piece of real-time data simultaneously has the anchoring state and the ballast state based on the preprocessed ship real-time data set, whether the ship simultaneously has the anchoring state and the ballast state can be selectively triggered and judged by judging the statistical mark of the real-time data.
The statistical mark of the real-time data refers to the accumulated occurrence times of a certain ship within a preset time range. This may be in the form of, for example, a specific identification field in the data format, or an additional field, or a generated identification indicating accumulated information. The identification may be a cumulative number value. E.g. at t 1 At a time, real-time data provided by the AIS data source is acquired, where each real-time data may be represented, for example, as (MMSI, data, t) 1 Statistical identification).
And when the value of the statistical identifier is greater than or equal to a preset threshold value, triggering and executing to judge whether the anchoring state and the ballast state exist in the ship at the same time. E.g. t 1 The ith data in the real-time data of the moment belongs to the data of the ship A, when the data are obtained, the statistical identifier of the moment is obtained to be 0, the statistical identifier and a preset threshold value are used for judging, and if the statistical identifier is smaller than the preset threshold valueThe next data (item i + 1) can be directly judged without executing the step of judging whether the anchoring state and the ballast state exist in the ship A at the same time, and the next data can be the data belonging to the ship B, for example, and the step of judging whether the anchoring state and the ballast state exist in the ship B at the same time is triggered by adopting the same judging statistical identification mode.
At t 1+n The jth data in the real-time data at the moment belongs to the data of the ship A, when the data are obtained, the statistical identification at the moment is obtained to be n-1, the statistical identification is judged with a preset threshold value, and if the statistical identification is larger than or equal to the preset threshold value, the step of judging whether the ship A has an anchoring state and a ballast state at the same time is triggered and executed.
By additionally arranging the triggering condition judging step, the data processing efficiency is further improved, and the data processing time is saved.
And the anchoring judgment subunit 450 is configured to judge whether the ship corresponding to the real-time data has an anchoring state based on each real-time data in the ship real-time data set.
In the embodiment of the present application, step 250 is optionally triggered by step 240. For example, the statistical identifier of the ith piece of data in the ship real-time data set is greater than or equal to a preset threshold, step 250 is executed.
And extracting the behavior characteristic data used for representing the ship in the ith data, comparing the behavior characteristic data with the mooring behavior rule base, and determining that the ship corresponding to the ith data has a mooring state if the setting conditions of the mooring behavior rule base are met.
The behavior characteristic data for characterizing the ship may include, for example: the sailing speed, sailing displacement and sailing direction of the ship are changed; the sailing displacement is the displacement generated by the current ship behavior relative to the initial ship behavior; the change in sailing direction is a change in direction of the sailing displacement.
By analyzing the ship behavior characteristic data or comparing the ship behavior characteristic data with a preset threshold value, the anchoring behavior of the ship can be identified, and therefore the efficiency of identifying the anchoring behavior is improved.
The method comprises the steps of establishing a corresponding anchoring behavior rule base based on ship behavior characteristic data, namely specifying option contents of the behavior characteristic data of the ship and setting conditions required to be met by each option content.
In the embodiment of the present invention, the mooring behavior rule base may be a set of determination rules for ship anchoring behavior, and the set may define the mooring behavior through one or more rules, for example, perform qualitative comprehensive evaluation and determination on characteristic data for characterizing ship behavior, or perform quantitative comprehensive evaluation and determination based on the ship behavior characteristic data. The anchor behavior rules library may include, for example: the navigation speed is less than a preset first threshold value; the navigation displacement is smaller than a preset second threshold value; the change of the sailing direction is a continuous change.
The values of the preset first threshold, the second threshold and the third threshold can be determined in various ways. The values of the first threshold, the second threshold and the third threshold can be obtained according to the analysis of the historical data of the ship navigation, or abnormal values in a normal navigation track can be selected. Preferably, the estimation can be obtained through a machine learning model, and the machine learning model is obtained through training and learning of a large amount of historical ship data by adopting a machine learning algorithm. The state of the ship can be accurately judged through the machine learning model prediction threshold, and the judgment efficiency is improved.
Optionally, the anchoring determination subunit 450 includes:
a first extraction subunit 4501, configured to extract behavior feature data of the ship corresponding to real-time data from each piece of real-time data in the ship real-time data set;
a first determining subunit 4502, configured to compare the behavior feature data of the ship with the mooring behavior rule base, and determine that the ship corresponding to the real-time data has a mooring state if the setting condition of the mooring behavior rule base is satisfied.
In the case where the determination result of the mooring determination subunit 450 is yes, the ballast determination subunit 460 is entered. And under the condition that the judgment result of the anchoring judgment subunit 450 is negative, continuously returning to the anchoring judgment subunit 450 to judge the next real-time data in the ship real-time data set.
And a ballast judging subunit 460, configured to judge whether a ballast state exists in the ship corresponding to the real-time data based on the real-time data.
In the embodiment of the present application, after the existence of the anchoring state is determined by the anchoring determination subunit 450 for each piece of real-time data in the ship real-time data set, the draft depth value of the ship is continuously extracted from the real-time data,
and then, comparing the draft depth value with a preset draft depth threshold value, and if a judgment condition is met, the ship corresponding to the real-time data has a ballast state.
The preset draft threshold value may be, for example, an unloaded draft threshold value, or a difference threshold value set according to a difference between the unloaded draft and the loaded draft.
For example, if the draft value of the ship is smaller than the empty draft threshold value or the difference threshold value, it indicates that the judgment condition is satisfied, and it is determined that the ballast state of the ship exists.
The draft threshold value (which may be referred to as a third threshold value for the sake of distinction) may be set based on an empirical value or may be set based on an actual unloaded draft, and the draft in the ship ballast state may be determined by, for example, the ship type, the ship length, and the ship width indicated in the ship static information. Preferably, the estimation can be further obtained through a machine learning model, and the machine learning model is obtained through training and learning of a large amount of historical ship data by adopting a machine learning algorithm.
The anchoring behavior of the ship in a preset range is determined through the judgment of the anchoring state of the ship, then whether the ship carries goods or not is judged through the draught of the ship, the anchoring behavior and the ballast behavior of the ship are integrated, and finally the ship which is anchored and does not carry goods can be judged to be in the resting state, so that the efficiency of ship management is improved.
Optionally, the ballast judging subunit 460 may further include:
a second extraction subunit 4601, configured to continue to extract, from the real-time data, a draft value of the ship corresponding to the real-time data;
a second determining subunit 4602, configured to compare the draft depth value with a preset draft depth threshold value, and if a determination condition is met, determine that the ship corresponding to the real-time data has a ballast state.
In the case where the determination result of the ballast determining subunit 460 is yes, it is determined that the ship uniquely corresponding to the real-time data is in the parked state.
If the judgment result of the ballast judgment subunit 460 is negative, the process continues to return to the ballast judgment subunit 460 to judge the next real-time data in the ship real-time data set. And (4) until all real-time data in the ship real-time data set are judged to be finished.
After the ship is in the resting state, the state information of the ship is provided to a management organization such as a shipping company or a port administration in real time, and real-time service information is provided for the management organization, so that the shipping management efficiency is improved. It should be understood that the units or modules recited in the devices 300-400 correspond to various steps in the methods described with reference to fig. 1-2. Thus, the operations and features described above with respect to the methods are equally applicable to the apparatuses 300-400 and the units included therein and will not be described again here. The apparatus 400 may be implemented in a browser or other security applications of the electronic device in advance, or may be loaded into the browser or other security applications of the electronic device by downloading or the like. Corresponding elements in the apparatus 300-400 may cooperate with elements in the electronic device to implement aspects of embodiments of the present application.
Referring now to FIG. 5, shown is a block diagram of a computer system 500 suitable for use in implementing a terminal device or server of an embodiment of the present application.
As shown in fig. 5, the computer system 500 includes a Central Processing Unit (CPU) 501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
In particular, the processes described above with reference to fig. 1-2 may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the method of fig. 1-2. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present application may be implemented by software or hardware. The described units or modules may also be provided in a processor, and may be described as: a processor includes an acquisition unit and a determination unit. Where the names of these units or modules do not in some cases constitute a limitation of the unit or module itself, for example, the acquisition unit may also be described as a "unit for acquiring a set of real-time data of a vessel".
As another aspect, the present application also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the above-described embodiments; or it may be a separate computer readable storage medium not incorporated into the device. The computer-readable storage medium stores one or more programs for one or more processors to execute the ship's resting state determining method described in the present application.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of the invention as referred to in the present application is not limited to the embodiments with a specific combination of the above-mentioned features, but also covers other embodiments with any combination of the above-mentioned features or their equivalents without departing from the inventive concept. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.

Claims (17)

1. A ship resting state judgment method is characterized by comprising the following steps:
acquiring a ship real-time data set, wherein the ship real-time data set comprises at least one piece of real-time data at the same moment, and each piece of real-time data corresponds to each ship;
judging whether the ship corresponding to the real-time data has an anchoring state and a ballast state simultaneously or not based on each real-time data in the real-time data set, and the method comprises the following steps:
judging whether the ship corresponding to the real-time data has an anchoring state or not based on each real-time data in the real-time data set;
if the anchoring state exists, continuously judging whether the ship corresponding to the real-time data has a ballast state or not based on the real-time data, wherein the judging comprises the following steps:
extracting behavior characteristic data of the ship corresponding to the real-time data from each piece of real-time data in the real-time data set;
comparing the behavior characteristic data of the ship with an anchoring behavior rule base, and if the setting conditions of the anchoring behavior rule base are met, determining that the ship corresponding to the real-time data has an anchoring state;
if the vessel has both mooring and ballasting conditions, the vessel is in a stranded state.
2. The method of claim 1, wherein the behavior feature data comprises at least one of: navigation speed, ship displacement and navigation direction;
the mooring behavior rule base at least comprises: a threshold corresponding to the behavior feature data, and the setting condition.
3. The method of claim 2, wherein determining whether a ballast state exists for the vessel corresponding to the real-time data based on the real-time data comprises:
continuously extracting the draft value from the real-time data;
and comparing the draft depth value with a preset draft depth threshold value, and if the judgment condition is met, determining that the ship corresponding to the real-time data has a ballast state.
4. The method according to claim 3, characterized in that the threshold value corresponding to the behavioral characteristic data and/or the preset draft threshold value is estimated by a machine learning model.
5. The method of claim 1, wherein prior to determining whether a mooring state and a ballast state exist for a vessel corresponding to each real-time data in the set of real-time data based on the real-time data, the method further comprises:
and judging whether a triggering condition is met or not based on the statistical mark of each real-time data in the real-time data set, wherein the triggering condition is used for triggering and executing whether the anchoring state and the ballast state of the ship corresponding to the real-time data exist simultaneously or not based on the real-time data.
6. The method of claim 1, wherein after acquiring the set of real-time data for the vessel, the method further comprises:
preprocessing the ship real-time data set, wherein the preprocessing at least comprises one of the following steps: data fusion processing, repeated data cleaning, error data cleaning, data sequencing and data interpolation processing.
7. The method of claim 1, wherein prior to obtaining the set of real-time data for the vessel, the method further comprises:
obtaining operating parameters, wherein the operating parameters at least comprise one of the following: and presetting an acquisition time range and a ship type.
8. The method of claim 7, wherein said obtaining a set of real-time data for a vessel further comprises:
acquiring a ship real-time data set provided by a data source according to the operation parameters, wherein the data source at least comprises one of the following data: the system comprises an automatic identification system AIS of the ship, a radar, a Beidou satellite navigation system and a global positioning system GPS.
9. A ship resting state determination device, characterized by comprising:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a ship real-time data set, and the ship real-time data set comprises at least one piece of real-time data at the same moment, and each piece of real-time data corresponds to each ship;
the first judgment unit is used for judging whether the ship corresponding to the real-time data has an anchoring state and a ballast state simultaneously or not based on each real-time data in the ship real-time data set; if the anchoring state and the ballast state exist in the ship at the same time, the ship is in a resting state;
the first judgment unit includes:
the anchoring judgment subunit is used for judging whether the ship corresponding to the real-time data has an anchoring state or not based on each real-time data in the ship real-time data set; and
and the ballast judging subunit is used for continuously judging whether the ship corresponding to the real-time data has a ballast state or not based on the real-time data if the anchoring state exists.
10. The apparatus of claim 9, wherein the mooring determination subunit comprises:
the first extraction subunit is used for extracting the behavior characteristic data of the ship corresponding to the real-time data from each piece of real-time data in the real-time data set;
and the first determining subunit is used for comparing the behavior characteristic data of the ship with the anchoring behavior rule base, and determining that the ship corresponding to the real-time data has an anchoring state if the setting conditions of the anchoring behavior rule base are met.
11. The apparatus according to claim 9 or 10, wherein the ballast judging subunit includes:
a second extraction subunit, configured to continue to extract a draft value from the real-time data;
and the second determining subunit is used for comparing the draft depth value with a preset draft depth threshold value, and if the judgment condition is met, determining that the ship corresponding to the real-time data has a ballast state.
12. The apparatus of claim 9, wherein before the first determining unit, the apparatus further comprises:
and the second judging unit is used for judging whether a triggering condition is met or not based on the statistical mark of each real-time data in the ship real-time data set, and the triggering condition is used for triggering and executing the judgment of whether the ship corresponding to the real-time data has an anchoring state and a ballast state simultaneously or not based on the real-time data.
13. The apparatus of claim 9, wherein after the first obtaining unit, the apparatus further comprises:
the preprocessing unit is used for preprocessing the ship real-time data set, and the preprocessing comprises one or more of the following modes: data fusion processing, repeated data cleaning, error data cleaning, data sequencing and data interpolation processing.
14. The apparatus of claim 9, wherein prior to the first obtaining unit, the apparatus further comprises:
a second obtaining unit, configured to obtain an operating parameter, where the operating parameter at least includes one of: and presetting an acquisition time range and a ship type.
15. The apparatus of claim 14, wherein the first obtaining unit is further configured to obtain the set of real-time data of the vessel provided by a data source according to the operating parameter; the data source includes at least one of: the system comprises an automatic identification system AIS of the ship, a radar, a Beidou satellite navigation system and a global positioning system GPS.
16. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-8 when executing the program.
17. A computer-readable storage medium having stored thereon a computer program for:
the computer program, when executed by a processor, implements the method of any one of claims 1-8.
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