CN105952588A - Wind driven generator monitoring method based on cloud computing and big data - Google Patents
Wind driven generator monitoring method based on cloud computing and big data Download PDFInfo
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- CN105952588A CN105952588A CN201610332195.9A CN201610332195A CN105952588A CN 105952588 A CN105952588 A CN 105952588A CN 201610332195 A CN201610332195 A CN 201610332195A CN 105952588 A CN105952588 A CN 105952588A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P70/00—Climate change mitigation technologies in the production process for final industrial or consumer products
- Y02P70/50—Manufacturing or production processes characterised by the final manufactured product
Abstract
The invention discloses a monitoring method of a wind driven generator based on cloud computing and big data. The monitoring method is characterized by comprising a power module, a cloud computing module, a data transmission module, an amount of precipitation monitoring module, an air pressure monitoring module, a temperature and humidity monitoring module, a wind direction and wind power detecting module, an image acquisition module, a switching value detecting module, a current monitoring module, a speed monitoring module, a voltage monitoring module, a positioning module, a display module and a control panel. According to the monitoring method, after the monitoring modules acquire various parameters of the wind driven generator, the parameters are sent to a cloud computing platform through the data transmission module, and the cloud computing platform extracts big data for analysis and calculation and proposes a solution for an emergent problem. The method can make up for defects of a traditional fan monitoring method and a problem solution; the stable operation of the wind driven generator is guaranteed better; the automatic control of the wind driven generator is achieved; and the monitoring method has relatively high practicability.
Description
Technical field
The invention belongs to wind power generation field, particularly to a kind of cloud computing and the monitoring method of big data wind energy conversion system.
Background technology
Along with becoming increasingly conspicuous of environmental problem and energy problem, wind energy, as a kind of green energy resource renewable, free of contamination, is increasingly paid close attention to by people.Wind-power electricity generation is one of principal mode utilizing wind energy.The position of blower fan, local environment, generated energy, fan operation is played vital effect by the parameters such as blade velocity of rotation, running environment humiture, these information are gathered and collect and through processing by this device respectively, cloud computing module will be passed to through the information of screening, through cloud computing module extract big data go forward side by side line program calculate and reasoning, pass on instruction by panel, effectively substitute manual operation, identify the most rapidly and solve the bursting problem in wind-driven generator running.
The present invention by after the various parameter acquisitions of blower fan by each monitoring modular, by the incoming cloud computing platform of data transmission module, is extracted big data by cloud computing platform and is analyzed calculating and proposing bursting problem solution.The present invention compensate for the deficiency of conventional fan detection method and issue-resolution, better assures that the stable operation of wind-driven generator, it is achieved that automatically controlling of wind-driven generator, has the strongest practicality.
Summary of the invention
The invention discloses a kind of cloud computing and the monitoring method of big data wind energy conversion system, it is characterised in that: include power module (1), cloud computing module (2), data transmission module (3), precipitation monitoring modular (4), Pressure monitoring module (5), temperature-humidity monitoring module (6), wind direction, wind-force monitoring modular (7), switching value monitoring modular (8), current monitoring module (9), speed monitoring module (10), voltage monitoring module (11), locating module (12), display module (13), panel (14).The present invention by after the various parameter acquisitions of blower fan by each monitoring modular, by the incoming cloud computing platform of data transmission module, is extracted big data by cloud computing platform and is analyzed calculating and proposing bursting problem solution.The present invention compensate for the deficiency of conventional fan detection method and issue-resolution, better assures that the stable operation of wind-driven generator, has the strongest practicality.
Described power module is cloud computing module, data transmission module, precipitation monitoring modular, Pressure monitoring module, temperature-humidity monitoring module, wind direction, wind-force monitoring modular, switching value monitoring modular, current monitoring module, speed monitoring module, voltage monitoring module, locating module, display module, panel provide electric energy.
Described cloud computing module is connected with data transmission module, is quickly identified by the information bank of internal system and calculation procedure and is proposed solution.
Described data transmission module and panel link uploads Monitoring Data to cloud computing module, and downloads the issue-resolution that cloud computing module proposes.
Described precipitation monitoring modular is connected with panel, the precipitation data that transmission of monitoring arrives.
Described Pressure monitoring module is connected with panel, the atmospheric pressure data that transmission of monitoring arrives.
Humiture is monitored and data for presentation to panel by described temperature-humidity monitoring module.
Described wind direction, wind-force monitoring modular are connected with panel, the wind direction that transmission of monitoring arrives, wind data.
Described switching value monitoring modular switch amount is monitored and data for presentation panel.
Detected current related data is passed to panel by described current monitoring module.
The velocity correlation data of gained are passed to panel by described speed monitoring module.
The voltage data monitored is sent to panel and processes by described voltage monitoring module.
Described locating module is then responsible for processing blower fan position data to panel.
Described display module receives information that panel processed and reflects on display.
The data that the described cloud computing module extraction big data in high in the clouds combination monitor carry out program calculating, and propose issue-resolution.
Described data transmission module uses wireless output transmission technology to upload and download data.
Described locating module uses GPS or Big Dipper location technology, it is also possible to be radio sector zone location
Described method by after the various parameter acquisitions of blower fan by each monitoring modular, by the incoming cloud computing platform of data transmission module, is extracted big data by cloud computing platform and is analyzed calculating and proposing bursting problem solution.The present invention compensate for the deficiency of conventional fan detection method and issue-resolution, better assures that the stable operation of wind-driven generator, it is achieved that automatically controlling of wind-driven generator has the strongest practicality.
Beneficial effects of the present invention include following some:
1., under wind-driven generator is operated in complex environment, each side data can be observed in time, fan operation situation is efficiently controlled.
2. simple in construction, easy to operate, control precisely；
3. low cost, cost performance is high.
Below by drawings and Examples, technical scheme is described in further detail.
Accompanying drawing explanation
Fig. 1 is a kind of cloud computing provided by the present invention and the monitoring method workflow schematic diagram of big data wind energy conversion system.
Detailed description of the invention
As shown in Figure 1, the present invention provides a kind of cloud computing and the monitoring method of big data wind energy conversion system, is made up of power module (1), cloud computing module (2), data transmission module (3), precipitation monitoring modular (4), Pressure monitoring module (5), temperature-humidity monitoring module (6), wind direction, wind-force monitoring modular (7), switching value monitoring modular (8), current monitoring module (9), speed monitoring module (10), voltage monitoring module (11), locating module (12), display module (13), panel (14).The present invention can real-time monitored blower fan operational data, and by cloud computing module combine big data solve bursting problem.
Panel (15) is connected with data transmission module (3), uploads Monitoring Data, and downloads solution.
Panel (15) is connected with locating module (13), it is achieved the location of blower fan physical location, and station-keeping mode is GPS or Big Dipper location..
Panel (15) is connected with switching value monitoring modular (9), current monitoring module (10), speed monitoring module (11), voltage monitoring module (12) simultaneously, the data such as the electric current of Real-time Collection blower fan, voltage, speed and control signal, the parameter that panel (15) is uploaded according to distance host, calculate in real time and Monitoring Data change, and extract big data by cloud computing system and carry out sequential operation proposition issue-resolution, realize the Autonomous control of wind-driven generator, substitute manual operation, solve bursting problem the most timely.
In sum, the monitoring method of a kind of cloud computing provided by the present invention and big data wind energy conversion system is simple and feasible.
It is last it is noted that above example is only limited in order to technical scheme to be described, although the present invention being described in detail with reference to preferred embodiment, it will be understood by those within the art that: technical scheme still can be modified or equivalent by it, and these amendments or equivalent also can not make amended technical scheme depart from the spirit and scope of technical solution of the present invention.
Claims (4)
1. the monitoring method of a cloud computing and big data wind energy conversion system is characterized in that the monitoring method of described a kind of cloud computing and big data wind energy conversion system is by power module (1), cloud computing module (2), data transmission module (3), precipitation monitoring modular (4), Pressure monitoring module (5), temperature-humidity monitoring module (6), wind direction, wind-force monitoring modular (7), switching value monitoring modular (8), current monitoring module (9), speed monitoring module (10), voltage monitoring module (11), locating module (12), display module (13), panel (14) forms.
A kind of cloud computing the most according to claim 1 and the monitoring method of big data wind energy conversion system, it is characterised in that the data that the described cloud computing module extraction big data in high in the clouds combination monitor carry out program calculating, and propose issue-resolution.
A kind of cloud computing the most according to claim 1 and the monitoring method of big data wind energy conversion system, it is characterized in that after the various parameter acquisitions of blower fan by each monitoring modular, by the incoming cloud computing platform of data transmission module, cloud computing platform extract big data and be analyzed calculating and proposing bursting problem solution.
4. the present invention compensate for the deficiency of conventional fan detection method and issue-resolution, better assures that the stable operation of wind-driven generator, it is achieved that automatically controlling of wind-driven generator, has the strongest practicality.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201610332195.9A CN105952588A (en) | 2016-05-19 | 2016-05-19 | Wind driven generator monitoring method based on cloud computing and big data |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201610332195.9A CN105952588A (en) | 2016-05-19 | 2016-05-19 | Wind driven generator monitoring method based on cloud computing and big data |
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| CN105952588A true CN105952588A (en) | 2016-09-21 |
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| CN201610332195.9A Pending CN105952588A (en) | 2016-05-19 | 2016-05-19 | Wind driven generator monitoring method based on cloud computing and big data |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110735764A (en) * | 2019-10-22 | 2020-01-31 | 杨长庆 | electric automobile wind power generation system |
Citations (4)
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| CN102541042A (en) * | 2012-03-20 | 2012-07-04 | 无锡职业技术学院 | Internet-of-things (IOT)-based monitoring system and monitoring method for off-grid small wind power plant |
| CN202817789U (en) * | 2012-08-28 | 2013-03-20 | 华锐风电科技(集团)股份有限公司 | Cloud monitor system for monitoring electric energy quality and electric power system |
| CN104915552A (en) * | 2015-05-27 | 2015-09-16 | 百度在线网络技术（北京）有限公司 | Method and device for predicting system faults |
| CN105510038A (en) * | 2015-12-31 | 2016-04-20 | 北京金风科创风电设备有限公司 | Wind turbine generator fault monitoring method and device |
-
2016
- 2016-05-19 CN CN201610332195.9A patent/CN105952588A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102541042A (en) * | 2012-03-20 | 2012-07-04 | 无锡职业技术学院 | Internet-of-things (IOT)-based monitoring system and monitoring method for off-grid small wind power plant |
| CN202817789U (en) * | 2012-08-28 | 2013-03-20 | 华锐风电科技(集团)股份有限公司 | Cloud monitor system for monitoring electric energy quality and electric power system |
| CN104915552A (en) * | 2015-05-27 | 2015-09-16 | 百度在线网络技术（北京）有限公司 | Method and device for predicting system faults |
| CN105510038A (en) * | 2015-12-31 | 2016-04-20 | 北京金风科创风电设备有限公司 | Wind turbine generator fault monitoring method and device |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110735764A (en) * | 2019-10-22 | 2020-01-31 | 杨长庆 | electric automobile wind power generation system |
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Application publication date: 20160921 |