CN111814367A - Port ship emission monitoring and supervision cloud service system - Google Patents
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Abstract
The invention discloses a port ship emission monitoring and supervision cloud service system, which comprises: the ship data acquisition module is used for acquiring static information and dynamic information of a ship through the AIS; the regional ship emission calculation module is used for determining regional ship emission according to the ship traffic emission evaluation model; and the visualization module is used for finishing the space visualization of the ship emission by utilizing the GIS technology. The ship tail gas emission monitoring system can better solve the problem of data intensity in real-time calculation and analysis of ship tail gas emission through regional ship emission calculation, provides visual ship emission information of coastal water areas for managers, and has good influence on port ship tail gas emission monitoring.
Description
Technical Field
The invention relates to a cloud computing technology, in particular to a port ship emission monitoring and supervision cloud service system.
Background
The exhaust emission of ships becomes one of the main sources of air pollution in traffic flow dense areas such as coastal ports and main navigation channels, and influences the regional environment and the population health. The current methods for calculating the exhaust emission of ships mainly include a fuel method and a power method. The fuel method is based on ship fuel consumption statistics, and the power method is based on ship activity condition statistics. At present, coastal ports in China mostly adopt a dynamic method to calculate and analyze port discharge lists. However, with the increasing demand of maritime trade, the number of ships entering and leaving each port is increased sharply, so that the problem of data intensity in the calculation and analysis of ship dynamic discharge is caused, and the existing method and technical scheme are difficult to solve.
In addition, the ship emission has basic characteristics of dynamic emission, multi-source emission, strong flowability and the like. The massive integrated ship data and emission monitoring data can dynamically change along with the time-space change, are not easy to track, and need to be updated in real time in the monitoring process. Although the existing technical scheme performs space-time analysis and visualization on ship emission, the real-time and long-time visualization of port ship tail gas emission monitoring is not deeply and effectively researched only on the basis of research under a certain specific time period.
The port ship exhaust emission monitoring and supervising cloud service system based on the cloud computing and Geographic Information System (GIS) is designed and researched by adopting an improved ship exhaust emission measurement model to calculate the ship exhaust emission in the port area.
Disclosure of Invention
The invention aims to solve the technical problem of providing a port ship emission monitoring and supervision cloud service system aiming at the defects in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a port ship emission monitoring and supervision cloud service system comprises:
the ship data acquisition module is used for acquiring static information and dynamic information of a ship through the AIS; the static information comprises a ship mobile service identification code (MMSI), a ship name, a call sign, a ship type, a ship length and a ship width; the dynamic information comprises longitude and latitude position information of a ship, a timestamp, a ground Course (COG), a ground Speed (SOG) and a Heading (Heading);
the regional ship emission calculation module is used for determining regional ship emission according to the ship traffic emission evaluation model;
the ship emission in the determined area is as follows:
(1) selecting a calculation area: defining a region boundary, and screening ships in the region as calculation objects;
(2) correcting the ship speed of the ship: according to the real-time navigation environment information, the ground speed in the AIS data is corrected, and the interference of environmental factors such as wind, waves, currents and the like on the true value of the ship speed is eliminated;
the navigation environment information is obtained by searching an information platform in real time according to the longitude and latitude position information of the ship;
(3) identifying the state of the ship: according to the corrected ship speed and the ship name and navigation state information provided by the AIS, activity characteristics in the ship operation process in the region are researched and classified, wherein the activity characteristics comprise the classification of ship types, the classification of engine types and the classification of running modes;
the navigation state information comprises a navigation state and a parking state, and is determined according to the corrected ship speed;
(4) obtaining engine power: and inquiring a ship attribute database in the ship AIS information, and matching engine power data of the corresponding ship.
(5) Selecting a calculation factor: analyzing the operation characteristics, fuel consumption characteristics and various tail gases (including CO) of the energy consumption equipment including a main engine, an auxiliary engine and a boiler of the ship under different activity characteristics2CO, NOx, SOx, PM, etc.), selecting corresponding emission factors and load factors;
the emission factors include CO, CO2, PM, SO2, NOx, and the load factors include: CO, CO2, PM, SO2, NOx;
(6) calculating the discharge track of the single ship: calculating the single-ship exhaust emission by combining the ship motion state, the ship speed corrected by the environmental information, the ship engine power and various calculation factors through a ship exhaust emission calculation model;
the following model was used for the calculation:
if the ship is in an underway state, the main engine and the auxiliary engine are mainly in working states, and the calculation formula is as follows:
wherein, f (V)speed) Representing the original speed of the vessel corrected by environmental factors, where VspeedRepresenting speed of flight to ground, VmaxThe maximum design speed of the ship is shown, E represents the exhaust emission of the ship, P represents the power of the power equipment of the ship, and subscript i represents the exhaust emission type of the ship; subscripts m, a, b respectively represent the marine main engine, auxiliary engine and boiler; LF is a ship load factor, and EF is a ship emission factor;
if the ship is in a berthing state, the main engine stops working, the auxiliary engine and the boiler are in a working state, and the calculation formula is as follows:
Ei＝PaLFaTaEFi,a+PbTbEFi,b
wherein E represents the exhaust emission of the ship, P represents the power of the power equipment of the ship, and subscript i represents the exhaust emission type of the ship; subscripts m, a, b respectively represent the marine main engine, auxiliary engine and boiler; LF is a ship load factor, and EF is a ship emission factor;
(7) calculating the exhaust emission of all ships, and determining the total ship emission of a region according to the ship running track and the region boundary;
and the visualization module is used for finishing the space visualization of the ship emission by utilizing the GIS technology.
According to the scheme, in the regional ship emission calculation module, the single ship emission trajectory is obtained on the basis of online calculation of a Spark calculation engine.
According to the scheme, the single-ship emission track is calculated on line based on a Spark calculation engine, and the method specifically comprises the following steps:
the sparkStream component accesses an API (application program interface) by means of data provided by Kafka, the time interval is set to be 30s, and a DStream object is generated;
grouping the DStream objects, and dividing the AIS data with the same identification number into the same group according to the MMSI of the ship so as to carry out emission calculation;
if only one AIS data exists in the same group, taking out the nearest AIS point with the same identification number cached in the database according to the MMSI of the ship, and inserting the AIS point into the group;
according to the MMSI of the ship, the ship type, the host power and the auxiliary engine power static information of the ship corresponding to each AIS group are inquired in a static information table of a database;
determining the load factor and the ship navigation state of the ship by using the ship navigation speed information and combining the design navigation speed in the ship static information;
for each AIS array, combining various dynamic data and emission factor parameters in the AIS data, substituting the AIS data into a ship tail gas emission calculation model to calculate the ship emission;
calculating the discharge amount on each section of track according to the continuous AIS point pairs on the single ship track, and cumulatively adding to obtain the total discharge amount generated by the ship under the time window;
and traversing all ships to complete the calculation of the emission of all ships.
According to the scheme, the visualization module utilizes the GIS technology to complete the space visualization of ship emission, and the method specifically comprises the following steps:
(1) carrying out grid division on a research water area by utilizing a GIS technology;
(2) based on the single ship emission track data calculated in the dynamic exhaust emission calculation model, the single ship emission track data comprises starting point and ending point position information and is spatially equivalent to a line segment;
(3) performing superposition analysis on the obtained data and a sea area grid to obtain a part with an intersecting line segment;
(4) and then according to the length of the intersection, performing weight distribution on the emission value of the data according to the length of the intersection, and displaying diffusion results of the exhaust gas emitted by the regions at different moments in real time.
The invention has the following beneficial effects:
1. the system can better solve the problem of data intensity in real-time calculation and analysis of ship exhaust emission, and has functions of managing, inquiring and displaying marine data.
2. Multi-scale statistical information of ship exhaust emissions in space and time can be provided, as well as visual representations of various ship traffic flows and ship exhaust emissions. The method can be applied to relevant management departments of coastal ports or maritime management departments and the like, can provide visual coastal water area ship emission information for managers, and has good influence on port ship tail gas emission monitoring.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a schematic structural diagram of an embodiment of the present invention;
FIG. 2 is a schematic diagram of a model architecture of an embodiment of the present invention;
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, a port ship emission monitoring and supervision cloud service system includes:
the ship data acquisition module is used for acquiring static information and dynamic information of a ship through the AIS; the static information comprises a ship mobile service identification code (MMSI), a ship name, a call sign, a ship type, a ship length and a ship width; the dynamic information comprises longitude and latitude position information of a ship, a timestamp, a ground Course (COG), a ground Speed (SOG) and a Heading (Heading);
the regional ship emission calculation module is used for determining regional ship emission according to the ship traffic emission evaluation model;
the ship emission in the determined area is as follows:
(1) selecting a calculation area: defining a region boundary, and screening ships in the region as calculation objects;
(2) correcting the ship speed of the ship: according to the real-time navigation environment information, the ground speed in the AIS data is corrected, and the interference of environmental factors such as wind, waves, currents and the like on the true value of the ship speed is eliminated;
the navigation environment information is obtained by searching an information platform in real time according to the longitude and latitude position information of the ship;
(3) identifying the state of the ship: according to the corrected ship speed and the ship name and navigation state information provided by the AIS, activity characteristics in the ship operation process in the region are researched and classified, wherein the activity characteristics comprise the classification of ship types, the classification of engine types and the classification of running modes;
the navigation state information comprises a navigation state and a parking state, and is determined according to the corrected ship speed;
(4) obtaining engine power: and inquiring a ship attribute database in the ship AIS information, and matching engine power data of the corresponding ship.
(5) Selecting a calculation factor: analyzing the operation characteristics, fuel consumption characteristics and various tail gases (including CO) of the energy consumption equipment including a main engine, an auxiliary engine and a boiler of the ship under different activity characteristics2CO, NOx, SOx, PM, etc.), selecting corresponding emission factors and load factors;
(6) calculating the discharge track of the single ship: calculating the single-ship exhaust emission by combining the ship motion state, the ship speed corrected by the environmental information, the ship engine power and various calculation factors through a ship exhaust emission calculation model;
the following model was used for the calculation:
if the ship is in an underway state, the main engine and the auxiliary engine are mainly in working states, and the calculation formula is as follows:
wherein, f (V)speed) Representing the original speed of the vessel corrected by environmental factors, where VspeedRepresenting speed of flight to ground, VmaxThe maximum design speed of the ship is shown, E represents the exhaust emission of the ship, P represents the power of the power equipment of the ship, and subscript i represents the exhaust emission type of the ship; subscripts m, a, b respectively represent the marine main engine, auxiliary engine and boiler; LF is a ship load factor, and EF is a ship emission factor;
if the ship is in a berthing state, the main engine stops working, the auxiliary engine and the boiler are in a working state, and the calculation formula is as follows:
Ei＝PaLFaTaEFi,a+PbTbEFi,b
wherein E represents the exhaust emission of the ship, P represents the power of the power equipment of the ship, and subscript i represents the exhaust emission type of the ship; subscripts m, a, b respectively represent the marine main engine, auxiliary engine and boiler; LF is a ship load factor, and EF is a ship emission factor;
the single-ship emission track is obtained through online calculation based on a Spark calculation engine, and the method specifically comprises the following steps:
the sparkStream component accesses an API (application program interface) by means of data provided by Kafka, the time interval is set to be 30s, and a DStream object is generated;
grouping the DStream objects, and dividing the AIS data with the same identification number into the same group according to the MMSI of the ship so as to carry out emission calculation;
if only one AIS data exists in the same group, taking out the nearest AIS point with the same identification number cached in the database according to the MMSI of the ship, and inserting the AIS point into the group;
according to the MMSI of the ship, the ship type, the host power and the auxiliary engine power static information of the ship corresponding to each AIS group are inquired in a static information table of a database;
determining the load factor and the ship navigation state of the ship by using the ship navigation speed information and combining the design navigation speed in the ship static information;
for each AIS array, combining various dynamic data and emission factor parameters in the AIS data, substituting the AIS data into a ship tail gas emission calculation model to calculate the ship emission;
calculating the discharge amount on each section of track according to the continuous AIS point pairs on the single ship track, and cumulatively adding to obtain the total discharge amount generated by the ship under the time window;
and traversing all ships to complete the calculation of the emission of all ships.
(7) Determining the total ship emission amount of a region according to the calculated tail gas emission amount of all ships and the ship track and the region boundary;
the visualization module is used for completing the space visualization of ship emission by utilizing a GIS technology, and specifically comprises the following steps:
(1) carrying out grid division on a research water area by utilizing a GIS technology;
(2) based on the single ship emission track data calculated in the dynamic exhaust emission calculation model, the single ship emission track data comprises starting point and ending point position information and is spatially equivalent to a line segment;
(3) performing superposition analysis on the obtained data and a sea area grid to obtain a part with an intersecting line segment;
(4) and then according to the length of the intersection, performing weight distribution on the emission value of the data according to the length of the intersection, and displaying diffusion results of the exhaust gas emitted by the regions at different moments in real time.
Visualization of thematic maps:
the ship emission data visualization mode mainly comprises map visualization and statistical primitive expression, wherein statistical primitives and map components are divided into three types according to dimension requirements, and time distribution, space distribution and attribute association conditions of ship emission monitoring data are respectively counted. And adopting different types of statistical primitives according to different types of the geographic expression variables.
Visual statistical primitive and thematic map classification
Finally, various maritime data and subject data related to ship emission are packaged into standard web services issued by Tomcat, and the visualization of the electronic chart and the ship emission thematic data is realized by a display interface developed by a JavaScript technology.
It will be understood that modifications and variations can be made by persons skilled in the art in light of the above teachings and all such modifications and variations are intended to be included within the scope of the invention as defined in the appended claims.
Claims (5)
1. A port ship emission monitoring and supervision cloud service system is characterized by comprising:
the ship data acquisition module is used for acquiring static information and dynamic information of a ship through the AIS; the static information comprises a ship mobile service identification code MMSI, a ship name, a call sign, a ship type, a ship length and a ship width; the dynamic information comprises longitude and latitude position information of the ship, a timestamp, a ground course, a ground speed and a ship heading;
the regional ship emission calculation module is used for determining regional ship emission according to the ship traffic emission evaluation model;
the ship emission in the determined area is as follows:
(1) selecting a calculation area: defining a region boundary, and screening ships in the region as calculation objects;
(2) correcting the ship speed of the ship: correcting the ground speed in the AIS data according to the real-time navigation environment information, and eliminating the interference of environmental factors on the true value of the ship speed;
the navigation environment information is obtained by searching an information platform in real time according to the longitude and latitude position information of the ship;
(3) identifying the state of the ship: according to the corrected ship speed and the ship name and navigation state information provided by the AIS, activity characteristics in the ship operation process in the region are researched and classified, wherein the activity characteristics comprise the classification of ship types, the classification of engine types and the classification of running modes;
the navigation state information comprises a navigation state and a parking state, and is determined according to the corrected ship speed;
(4) obtaining engine power: inquiring a ship attribute database in the ship AIS information, and matching engine power data of a corresponding ship;
(5) selecting a calculation factor: analyzing the operation characteristics, the fuel consumption characteristics and the emission characteristics of various tail gases of energy consumption equipment including a ship main engine, an auxiliary engine and a boiler of the ship under different activity characteristics, and selecting corresponding emission factors and load factors;
the emission factors include CO, CO2, PM, SO2, NOx, and the load factors include: CO, CO2, PM, SO2, NOx;
(6) calculating the discharge track of the single ship: calculating the single-ship exhaust emission by combining the ship motion state, the ship speed corrected by the environmental information, the ship engine power and various calculation factors through a ship exhaust emission calculation model;
(7) calculating the exhaust emission of all ships, and determining the total ship emission of a region according to the ship running track and the region boundary;
and the visualization module is used for finishing the space visualization of the ship emission by utilizing the GIS technology.
2. The port ship emission monitoring and supervision cloud service system according to claim 1, wherein the following model is adopted in the regional ship emission calculation module for calculating the emission trajectory of a single ship:
if the ship is in an underway state, the main engine and the auxiliary engine are mainly in working states, and the calculation formula is as follows:
wherein, f (V)speed) Representing the original speed of the vessel corrected by environmental factors, where VspeedRepresenting speed of flight to ground, VmaxThe maximum design speed of the ship is shown, E represents the exhaust emission of the ship, P represents the power of the power equipment of the ship, and subscript i represents the exhaust emission type of the ship; subscripts m, a, b respectively represent the marine main engine, auxiliary engine and boiler; LF is a ship load factor, and EF is a ship emission factor;
if the ship is in a berthing state, the main engine stops working, the auxiliary engine and the boiler are in a working state, and the calculation formula is as follows:
Ei＝PaLFaTaEFi,a+PbTbEFi,b
wherein E represents the exhaust emission of the ship, P represents the power of the power equipment of the ship, and subscript i represents the exhaust emission type of the ship; subscripts m, a, b respectively represent the marine main engine, auxiliary engine and boiler; LF is the ship load factor, EF is the ship emission factor.
3. The port ship emission monitoring and supervision cloud service system according to claim 1, wherein in the regional ship emission calculation module, the single ship emission trajectory is obtained based on Spark calculation engine online calculation.
4. The port ship emission monitoring and supervision cloud service system according to claim 3, wherein the single ship emission trajectory is calculated online based on a Spark calculation engine, specifically as follows:
the sparkStream component accesses an API (application program interface) by means of data provided by Kafka, the time interval is set to be 30s, and a DStream object is generated;
grouping the DStream objects, and dividing the AIS data with the same identification number into the same group according to the MMSI of the ship so as to carry out emission calculation;
if only one AIS data exists in the same group, taking out the nearest AIS point with the same identification number cached in the database according to the MMSI of the ship, and inserting the AIS point into the group;
according to the MMSI of the ship, the ship type, the host power and the auxiliary engine power static information of the ship corresponding to each AIS group are inquired in a static information table of a database;
determining the load factor and the ship navigation state of the ship by using the ship navigation speed information and combining the design navigation speed in the ship static information;
for each AIS array, combining various dynamic data and emission factor parameters in the AIS data, substituting the AIS data into a ship tail gas emission calculation model to calculate the ship emission;
calculating the discharge amount on each section of track according to the continuous AIS point pairs on the single ship track, and cumulatively adding to obtain the total discharge amount generated by the ship under the time window;
and traversing all ships to complete the calculation of the emission of all ships.
5. The port ship emission monitoring and supervision cloud service system according to claim 1, wherein the visualization module performs space visualization of ship emission by using a GIS technology, and specifically comprises the following steps:
(1) carrying out grid division on a research water area by utilizing a GIS technology;
(2) based on the single ship emission track data calculated in the dynamic exhaust emission calculation model, the single ship emission track data comprises starting point and ending point position information and is spatially equivalent to a line segment;
(3) performing superposition analysis on the obtained data and a sea area grid to obtain a part with an intersecting line segment;
(4) and then according to the length of the intersection, performing weight distribution on the emission value of the data according to the length of the intersection, and displaying diffusion results of the exhaust gas emitted by the regions at different moments in real time.
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| CN112924622A (en) * | 2021-01-26 | 2021-06-08 | 武汉工程大学 | Unmanned aerial vehicle gas sensing and AIS information vector fusion ship tail gas tracking method |
| CN112924622B (en) * | 2021-01-26 | 2022-12-20 | 武汉工程大学 | Unmanned aerial vehicle gas sensing and AIS information vector fusion ship tail gas tracking method |
| CN113610370A (en) * | 2021-07-26 | 2021-11-05 | 武汉理工大学 | Inland ship domestic garbage supervision system and method |
| CN114239426A (en) * | 2021-10-20 | 2022-03-25 | 武汉理工大学 | Yangtze river trunk ship emission list generation method based on water flow data assimilation |
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| CN114550497A (en) * | 2022-02-14 | 2022-05-27 | 武汉理工大学 | Semantic calculation method and device for ship behaviors |
| CN114218231A (en) * | 2022-02-21 | 2022-03-22 | 杭州春来科技有限公司 | Ship tail gas monitoring data processing method and system and computer readable storage medium |
| CN114969014A (en) * | 2022-06-20 | 2022-08-30 | 交通运输部规划研究院 | AIS data-based port resource visual intelligent evaluation method and system |
| CN115290834A (en) * | 2022-10-09 | 2022-11-04 | 杭州泽天春来科技有限公司 | Ship carbon emission monitoring device and method |
| CN115290834B (en) * | 2022-10-09 | 2023-01-06 | 杭州泽天春来科技有限公司 | Ship carbon emission monitoring device and method |
| CN115905770A (en) * | 2022-10-28 | 2023-04-04 | 大连海事大学 | Ship pollution emission track measuring and calculating method based on AIS data |
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