CN115238918A - Offshore wind farm intelligent operation and maintenance method based on edge calculation - Google Patents
Offshore wind farm intelligent operation and maintenance method based on edge calculation Download PDFInfo
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- CN115238918A CN115238918A CN202210776782.2A CN202210776782A CN115238918A CN 115238918 A CN115238918 A CN 115238918A CN 202210776782 A CN202210776782 A CN 202210776782A CN 115238918 A CN115238918 A CN 115238918A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00004—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the power network being locally controlled
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
- H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
Abstract
The invention discloses an offshore wind farm intelligent operation and maintenance method based on edge calculation, which comprises the following steps: collecting offshore wind power plant data by the offshore edge computing node; carrying out intelligent identification on the offshore wind farm data, determining the core grade and the receiver of the data, and transmitting the core grade and the receiver to a corresponding data storage module; the data storage modules of the offshore edge computing node and the onshore cloud centralized control center process the collected information and store the processed information to the server; the offshore edge computing node and the onshore cloud centralized control center are combined with historical monitoring data stored in the server to perform analysis statistics, equipment health assessment and fault diagnosis and generate a real-time analysis data report; the offshore edge computing node and the onshore cloud centralized control center send corresponding control and adjustment instructions, and the offshore edge computing node intelligently responds; and the onshore cloud centralized control center intelligently outputs the operation and maintenance scheme and transmits the operation and maintenance scheme to the ship for carrying out the offshore operation and maintenance plan in real time. The invention can shorten the fault processing time of the fan and improve the operation and maintenance efficiency of offshore operation.
Description
Technical Field
The invention relates to the technical field of offshore wind power, in particular to an intelligent operation and maintenance method for an offshore wind farm based on edge calculation.
Background
At present, offshore wind power enters a fast and fast development period in China, but offshore wind power development still faces many challenges due to the special environment of an offshore wind power unit. Compared with land, offshore operation and maintenance are subject to many factors, such as meteorological conditions, marine conditions, shipping arrangements, and route arrangements, which result in high cost for offshore operation and maintenance. In terms of management and technology, offshore wind power has the risks of high offshore operation and maintenance risk, high equipment failure rate, large environmental influence, weak operation and maintenance management, low risk resistance, high operation and maintenance cost and the like. The current lagging operation and maintenance management state becomes an important bottleneck influencing the development of the offshore wind power market.
The edge calculation is a novel calculation model for executing calculation tasks at the edge of a network, and can more quickly and reliably respond to the data processing requirement of a terminal than a cloud calculation model; the intelligent operation and maintenance of the offshore wind farm is a problem which needs to be solved urgently by an intelligent operation and maintenance system by coordinating edge computing nodes and a cloud computing center to perform intelligent operation and maintenance information processing.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides an offshore wind farm intelligent operation and maintenance method based on edge calculation, and improves offshore operation and maintenance efficiency.
In order to realize the purpose, the technical scheme provided by the invention is as follows: an intelligent operation and maintenance method for an offshore wind farm based on edge calculation comprises the following steps:
step 1, collecting offshore wind farm data including offshore wind farm equipment data, marine hydrological meteorological data and unit maintenance data by an acquisition module of an offshore edge computing node;
step 2, intelligently identifying the collected offshore wind power plant data according to a preset data classification standard, determining the core grade of the data, determining a data receiver according to the core grade of the data, and transmitting the data receiver to a data storage module of the data receiver; wherein, the data receiver has: the system comprises offshore edge computing nodes, a land cloud centralized control center, offshore edge computing nodes and a land cloud centralized control center;
step 3, data processing is carried out on the collected offshore wind farm data by data storage modules of the offshore edge computing node and the onshore cloud centralized control center, and then the data are respectively stored in a wind farm localized data server of the offshore edge computing node and a cloud data server of the onshore cloud centralized control center, so that the monitoring of the running state of the offshore wind farm is further realized; the local data server of the wind power plant is used for storing historical data of the offshore wind power plant in a short term and supporting review and caching of the short-term data;
step 4, combining historical monitoring data stored in respective servers by the offshore edge computing node and the onshore cloud centralized control center, performing analysis statistics, equipment health assessment and fault diagnosis, and generating a real-time analysis data report;
step 5, according to the real-time analysis data reports obtained after processing and analysis, the offshore edge computing node and the onshore cloud centralized control center send corresponding control and regulation instructions to the intelligent response module of the offshore edge computing node, and the intelligent response module sends the control and regulation instructions to each device of the offshore wind farm;
and step 6, combining the unit maintenance data, the operation and maintenance records, the historical fault statistics and processing scheme stored in the cloud data server and the online acquired marine hydrological weather forecast data, intelligently outputting the operation and maintenance scheme by the onshore cloud centralized control center, transmitting the operation and maintenance scheme to a ship carrying out a marine operation and maintenance plan in real time through an intelligent response module of the marine edge computing node, and timely processing abnormal conditions occurring in operation.
Further, in step 1, the offshore wind farm equipment data comprises real-time running state data of a fan, a booster station and a submarine cable, the marine hydrographic meteorological data comprises sea wave height, wind speed, weather conditions, thunderstorm and fog conditions, and the unit maintenance data comprises a unit regular operation and maintenance plan, operation and maintenance personnel and scheduling, operation and maintenance ship data and spare part data; the offshore wind power plant equipment data, the marine hydrographic meteorological data and the unit maintenance data can be obtained from a wind power SCADA system, a booster station comprehensive automation system, a CMS vibration monitoring system, a marine meteorological and wind power prediction system, a submarine cable monitoring system, an AGC/AVC energy management system, an oil on-line monitoring system and an operation and maintenance ship GIS positioning management system.
Further, in step 2, if the data receiver is a marine edge computing node, the data receiver is sent to a data storage module of the marine edge computing node; if the data receiver is a land cloud centralized control center, the data receiver is sent to a data storage module of the land cloud centralized control center; and if the data receiver comprises the offshore edge computing node and the onshore cloud centralized control center, the data receiver simultaneously sends the data to the data storage modules of the offshore edge computing node and the onshore cloud centralized control center.
Further, in step 4, the specific steps of analyzing statistics, equipment health assessment and fault diagnosis and generating a real-time analysis data report are as follows:
401 The offshore edge computing node and the onshore cloud centralized control center call the marine hydrological meteorological data which are stored in the respective servers at the time t1 before the real-time, and obtain meteorological forecast and storm early warning data which are regularly issued by a marine weather forecasting department at the time t2 after the real-time node; judging whether a risk standard environment appears in marine hydrological meteorological data, meteorological forecasts and strong wind and big wave early warning data, if so, respectively counting the risk times and duration, determining the risk level, generating a risk record, and if not, not processing; judging whether the risk records exceed a threshold value, if so, respectively outputting a safety difference report, and if not, not processing;
402 The offshore edge computing node and the onshore cloud centralized control center call offshore wind farm equipment data which are stored in respective servers and are t3 times before the real-time, compare the real-time offshore wind farm equipment data, compare the state parameters of each fan, booster station and submarine cable of the same power generation farm, and respectively generate state difference reports;
403 The offshore edge computing node and the onshore cloud centralized control center respectively acquire the real-time offshore wind power plant equipment data, perform data cleaning by adopting a mutual comparison method and a least square method, establish a feature index library according to different equipment components, bring the data after feature extraction into a fault diagnosis model, perform fault classification and matching, and finally give out real-time fault diagnosis data; respectively comparing the real-time offshore wind farm equipment data with the offshore wind farm equipment prediction data obtained based on the artificial intelligence technology by the offshore edge computing node and the onshore cloud centralized control center to obtain potential fault early warning data of the offshore wind farm equipment;
404 The offshore edge computing node and the onshore cloud centralized control center respectively integrate the obtained safety difference value report, the state difference value report and the fault diagnosis data into respective real-time analysis data reports.
Further, in step 6, the intelligent output operation and maintenance scheme specifically comprises the following steps:
601 Whether a processing scheme matched with the current fault is stored in the historical fault statistics and processing schemes stored in the cloud data server or not is judged, if the corresponding processing scheme exists, the processing scheme is called, and if not, whether the equipment is in sea for maintenance or not is determined by comparing damage and maintenance cost of the fault to the equipment and on the premise of ensuring the safety of the equipment;
602 If the offshore maintenance is selected, combining the marine hydrological weather forecast data and the unit maintenance data to generate a processing scheme containing a ship navigation route with optimal operation and maintenance cost and optimal power generation loss; and if the offshore maintenance is not selected, generating a maintenance task packet, and overlapping for maintenance when the next equipment fails.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the method and the system can acquire offshore wind farm equipment data, marine hydrological meteorological data, unit maintenance data, fault data, historical operation and maintenance records and the like through real-time monitoring of the unattended equipment, facilitate operation and maintenance work of the offshore wind turbine power generation farm, quicken scheduling according to intelligent response, shorten the fault processing time of the wind turbine in the offshore wind farm, and improve operation and maintenance efficiency of offshore operation.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a flow chart of the intelligent output operation and maintenance scheme.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the embodiments of the present invention are not limited thereto.
As shown in fig. 1, the embodiment discloses an intelligent operation and maintenance method for an offshore wind farm based on edge calculation, which includes the following steps:
step 1, collecting offshore wind farm data including offshore wind farm equipment data, marine hydrological meteorological data and unit maintenance data by an acquisition module of an offshore edge computing node. Specifically, the method comprises the following steps:
the offshore wind power plant equipment data mainly comprises real-time running state data of a fan, a booster station and a submarine cable, the marine hydrographic meteorological data mainly comprises sea wave height, wind speed, weather conditions, thunderstorms and fog conditions, and the unit maintenance data mainly comprises unit regular operation and maintenance plans, operation and maintenance personnel, shift arrangement, operation and maintenance ship data and spare part data; the offshore wind power plant equipment data, the marine hydrographic meteorological data and the unit maintenance data can be obtained from a wind power SCADA system, a booster station integrated automation system, a CMS vibration monitoring system, a marine meteorological and wind power prediction system, a submarine cable monitoring system, an AGC/AVC energy management system, an oil on-line monitoring system and an operation and maintenance ship GIS positioning management system.
Step 2, intelligently identifying the collected offshore wind farm data according to a preset data classification standard, determining the core grade of the data, determining a data receiver according to the core grade of the data, and transmitting the data receiver to a data storage module of the data receiver, wherein the data receiver can be: the system comprises offshore edge computing nodes, a land cloud centralized control center, offshore edge computing nodes and a land cloud centralized control center. Specifically, the method comprises the following steps:
if the data receiver is the offshore edge computing node, sending the data to a data storage module of the offshore edge computing node; if the data receiver is a land cloud centralized control center, the data receiver is sent to a data storage module of the land cloud centralized control center; and if the data receiver comprises the offshore edge computing node and the onshore cloud centralized control center, the data receiver simultaneously sends the data to the data storage module of the onshore cloud centralized control center.
Step 3, the data storage modules of the offshore edge computing node and the onshore cloud centralized control center perform data processing on the collected offshore wind farm data, and then the data are respectively stored in a wind farm localized data server of the offshore edge computing node and a cloud data server of the onshore cloud centralized control center, so that the monitoring of the operation state of the offshore wind farm is further realized; the wind power plant localization data server is used for storing historical data of the offshore wind power plant in a short term and supporting review and caching of the short-term data.
And 4, combining historical monitoring data stored in respective servers by the offshore edge computing node and the onshore cloud centralized control center, performing analysis statistics, equipment health assessment and fault diagnosis, and generating a real-time analysis data report. The specific process is as follows:
401 The offshore edge computing node and the onshore cloud centralized control center call the marine hydrological meteorological data which are stored in the respective servers at the time t1 before the real-time, and obtain meteorological forecast and storm early warning data which are regularly issued by a marine weather forecasting department at the time t2 after the real-time node; judging whether a risk standard environment appears in marine hydrological meteorological data, meteorological forecasts and strong wind and big wave early warning data, if so, respectively counting the risk times and duration, determining the risk level, generating a risk record, and if not, not processing; and judging whether the risk records exceed a threshold value, if so, respectively outputting a safety difference value report, and if not, not processing.
402 The offshore edge computing node and the onshore cloud centralized control center call offshore wind farm equipment data which are stored in respective servers and are t3 times before the real-time, compare the real-time offshore wind farm equipment data, compare the state parameters of each fan, booster station and submarine cable of the same power generation farm, and respectively generate state difference reports.
403 The offshore edge computing node and the onshore cloud centralized control center respectively acquire the real-time offshore wind power plant equipment data, perform data cleaning by adopting a mutual comparison method and a least square method, establish a feature index library according to different equipment components, bring the data after feature extraction into a fault diagnosis model, perform fault classification and matching, and finally give out real-time fault diagnosis data; and respectively comparing the real-time offshore wind farm equipment data with the offshore wind farm equipment prediction data obtained based on the artificial intelligence technology by the offshore edge computing node and the onshore cloud centralized control center to obtain potential fault early warning data of the offshore wind farm equipment.
404 The offshore edge computing node and the onshore cloud centralized control center respectively integrate the obtained safety difference value report, the state difference value report and the fault diagnosis data into respective real-time analysis data reports.
And 5, according to the real-time analysis data reports obtained after the processing and the analysis, the offshore edge computing node and the onshore cloud centralized control center send corresponding control and regulation instructions to the intelligent response module of the offshore edge computing node, and the intelligent response module sends the control and regulation instructions to each device of the offshore wind power plant.
And step 6, combining the unit maintenance data, the operation and maintenance records, the historical fault statistics and processing scheme stored in the cloud data server and the online acquired marine hydrological weather forecast data, intelligently outputting the operation and maintenance scheme by the onshore cloud centralized control center, transmitting the operation and maintenance scheme to a ship carrying out a marine operation and maintenance plan in real time through an intelligent response module of the marine edge computing node, and timely processing abnormal conditions occurring in operation. Referring to fig. 2, the specific process of the intelligent output operation and maintenance scheme is as follows:
601 Whether a processing scheme matched with the current fault is stored in historical fault statistics and processing schemes stored in a cloud data server or not is judged, if the corresponding processing scheme exists, the processing scheme is called, and if not, whether the equipment is in sea for maintenance or not is determined by comparing damage and maintenance cost of the fault to the equipment and on the premise of ensuring the safety of the equipment.
602 If the offshore maintenance is selected, combining the marine hydrological weather forecast data and the unit maintenance data to generate a processing scheme which comprises a ship navigation route and has optimal operation and maintenance cost and optimal power generation loss; and if the offshore maintenance is not selected, generating a maintenance task packet, and overlapping for maintenance when the next equipment fails.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (5)
1. An offshore wind farm intelligent operation and maintenance method based on edge calculation is characterized by comprising the following steps:
step 1, collecting offshore wind farm data including offshore wind farm equipment data, marine hydrological meteorological data and unit maintenance data by an acquisition module of an offshore edge computing node;
step 2, intelligently identifying the collected offshore wind power plant data according to a preset data classification standard, determining the core grade of the data, determining a data receiver according to the core grade of the data, and transmitting the data receiver to a data storage module of the data receiver; wherein, the data receiver has: the system comprises offshore edge computing nodes, a land cloud centralized control center, offshore edge computing nodes and a land cloud centralized control center;
step 3, the data storage modules of the offshore edge computing node and the onshore cloud centralized control center perform data processing on the collected offshore wind farm data, and then the data are respectively stored in a wind farm localized data server of the offshore edge computing node and a cloud data server of the onshore cloud centralized control center, so that the monitoring of the operation state of the offshore wind farm is further realized; the wind power plant localization data server is used for storing historical data of the offshore wind power plant in a short term and supporting review and caching of the short-term data;
step 4, combining historical monitoring data stored in respective servers by the offshore edge computing node and the onshore cloud centralized control center, performing analysis statistics, equipment health assessment and fault diagnosis, and generating a real-time analysis data report;
step 5, according to the real-time analysis data reports obtained after processing and analysis, the offshore edge computing node and the onshore cloud centralized control center send corresponding control and regulation instructions to the intelligent response module of the offshore edge computing node, and the intelligent response module sends the control and regulation instructions to each device of the offshore wind farm;
and step 6, combining the unit maintenance data, the operation and maintenance records, the historical fault statistics and processing scheme stored in the cloud data server and the online acquired marine hydrological weather forecast data, intelligently outputting the operation and maintenance scheme by the onshore cloud centralized control center, transmitting the operation and maintenance scheme to a ship carrying out a marine operation and maintenance plan in real time through an intelligent response module of the marine edge computing node, and timely processing abnormal conditions occurring in operation.
2. The intelligent operation and maintenance method of the offshore wind farm based on the edge calculation is characterized in that in the step 1, the offshore wind farm equipment data comprise real-time operation state data of a fan, a booster station and a submarine cable, the marine hydrological meteorological data comprise sea wave height, wind speed, weather conditions, thunderstorm and fog conditions, and the unit maintenance data comprise a unit regular operation and maintenance plan, operation and maintenance personnel and scheduling, operation and maintenance ship data and spare part data; the offshore wind power plant equipment data, the marine hydrographic meteorological data and the unit maintenance data can be obtained from a wind power SCADA system, a booster station comprehensive automation system, a CMS vibration monitoring system, a marine meteorological and wind power prediction system, a submarine cable monitoring system, an AGC/AVC energy management system, an oil on-line monitoring system and an operation and maintenance ship GIS positioning management system.
3. The offshore wind farm intelligent operation and maintenance method based on edge computing according to claim 1, characterized in that in step 2, if the data receiver is an offshore edge computing node, the data receiver is sent to a data storage module of the offshore edge computing node; if the data receiver is a land cloud centralized control center, the data receiver is sent to a data storage module of the land cloud centralized control center; and if the data receiver comprises the offshore edge computing node and the onshore cloud centralized control center, the data receiver simultaneously sends the data to the data storage modules of the offshore edge computing node and the onshore cloud centralized control center.
4. The offshore wind farm intelligent operation and maintenance method based on edge calculation as claimed in claim 1, wherein in step 4, the specific steps of analyzing statistics, equipment health assessment and fault diagnosis and generating real-time analysis data report are as follows:
401 The offshore edge computing node and the onshore cloud centralized control center call the marine hydrological meteorological data which is stored in the respective server at the time t1 before the real-time, and obtain the meteorological forecast and the storm early warning data which are regularly issued by the marine weather forecasting department at the time t2 after the real-time node; judging whether a risk standard environment appears in marine hydrological meteorological data, meteorological forecasts and strong wind and big wave early warning data, if so, respectively counting the risk times and duration, determining the risk level, generating a risk record, and if not, not processing; judging whether the risk records exceed a threshold value, if so, respectively outputting a safety difference report, and if not, not processing;
402 The offshore edge computing node and the onshore cloud centralized control center call offshore wind farm equipment data which are stored in respective servers at a time t3 before the real-time, compare the real-time offshore wind farm equipment data, compare the state parameters of each fan, booster station and submarine cable of the same power generation farm, and respectively generate a state difference report;
403 The offshore edge computing node and the onshore cloud centralized control center respectively acquire the real-time offshore wind power plant equipment data, perform data cleaning by adopting a mutual comparison method and a least square method, establish a feature index library according to different equipment components, bring the data after feature extraction into a fault diagnosis model, perform fault classification and matching, and finally give out real-time fault diagnosis data; respectively comparing the real-time offshore wind farm equipment data with the offshore wind farm equipment prediction data obtained based on the artificial intelligence technology by the offshore edge computing node and the onshore cloud centralized control center to obtain potential fault early warning data of the offshore wind farm equipment;
404 The offshore edge computing node and the onshore cloud centralized control center respectively integrate the obtained safety difference value report, the state difference value report and the fault diagnosis data into respective real-time analysis data reports.
5. The offshore wind farm intelligent operation and maintenance method based on edge calculation as claimed in claim 1, wherein in step 6, the intelligent output operation and maintenance scheme comprises the specific steps of:
601 Whether a processing scheme matched with the current fault is stored in the historical fault statistics and processing schemes stored in the cloud data server or not is judged, if the corresponding processing scheme exists, the processing scheme is called, and if not, whether the equipment is in sea for maintenance or not is determined by comparing damage and maintenance cost of the fault to the equipment and on the premise of ensuring the safety of the equipment;
602 If the offshore maintenance is selected, combining the marine hydrological weather forecast data and the unit maintenance data to generate a processing scheme containing a ship navigation route with optimal operation and maintenance cost and optimal power generation loss; and if the offshore maintenance is not selected, generating a maintenance task packet, and overlapping for maintenance when the next equipment fails.
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| CN116760884A (en) * | 2023-08-14 | 2023-09-15 | 海南智慧海事科技有限公司 | Ocean big data cloud service system and application method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116760884A (en) * | 2023-08-14 | 2023-09-15 | 海南智慧海事科技有限公司 | Ocean big data cloud service system and application method |
| CN116760884B (en) * | 2023-08-14 | 2023-10-20 | 海南智慧海事科技有限公司 | Ocean big data cloud service system and application method |
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