CN202758087U - A reckoning system of characteristics of wind direction and wind speed - Google Patents
A reckoning system of characteristics of wind direction and wind speed Download PDFInfo
- Publication number
- CN202758087U CN202758087U CN201220467200.4U CN201220467200U CN202758087U CN 202758087 U CN202758087 U CN 202758087U CN 201220467200 U CN201220467200 U CN 201220467200U CN 202758087 U CN202758087 U CN 202758087U
- Authority
- CN
- China
- Prior art keywords
- wind
- wind direction
- terminal
- data
- cpu processor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Lifetime
Links
Images
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The utility model relates to a reckoning system of characteristics of wind direction and wind speed. The system comprises a group of aerovanes which are arranged at different observation positions and a PC terminal equipped with a memory unit and a CPU processor performing calculation according to inputted data. The IO end of the memory is connected with the IO end of the CPU processor. The data output ends of the aerovanes are connected with the input end of the memory unit. The PC terminal is also equipped with an input device connected with the input end of the CPU processor and an output device connected with the output end of the CPU processor. By using the structure of the reckoning system, characteristics of wind direction and wind speed can be reckoned according to existing observational data so as to provide basis for engineering application.
Description
Technical field
The utility model relates to a kind of wind direction and wind velocity feature Estimation System.
Background technology
County and town, China each province and city have built a lot of weather stations, the data informations such as simultaneously observational record temperature, air pressure, rainfall, wind speed, wind direction.Because China is vast in territory, landform, landforms change greatly, particularly coastal waters, Plain, the mutually nested topography and geomorphology in mountain area, on the impact variation difference of wind speed, wind direction greatly.Even set up a lot of meteorological wind speed, wind direction research station, still still can not reflect more accurately wind speed, the wind direction feature on this ground to local complicated terrain environment, these Local observations data are few, lack for many years continuous observation data.Because the impact of data shortage problem designs, follow-up normal operation produces a lot of risks to engineering when engineering is used.Therefore, how taking full advantage of existing observational data is that near the local complicated terrain environment zone foundation contact with adjoining weather station is an important research aspect.
The utility model content
The purpose of this utility model is: the problem for above-mentioned prior art exists, a kind of wind direction and wind velocity feature Estimation System is proposed, and can extrapolate the wind direction and wind velocity feature of impact point position according to existing observational data, using for engineering provides foundation.
Applicant's Research Thinking is: according to the continuity principle of hydromechanical physical quantity distribution, research station not far from one another is under the roughly the same Large-scale Circulation background, although their geographical environment has its different characteristics, but all be subject to common circumfluence background restriction, meteorological element changes the statistical correlation that more or less exists to a certain degree.Principle can adopt the simultaneous observation method accordingly, and the data information same period of weather station and impact point position is carried out correlation analysis, sets up the wind direction and wind velocity correlationship of weather station and two places, impact point position; Then, the long-term data of weather station is revised according to aforementioned correlationship, can be obtained the wind direction and wind velocity feature of impact point position.
In order to reach above purpose, the technical solution of the utility model is as follows:
A kind of wind direction and wind velocity feature Estimation System, comprise one group of anerovane that is in different observation positions, it is characterized in that, also comprise the PC terminal, the CPU processor that described PC terminal has storage unit and carries out computing according to the input data, the IO end of described storage unit is connected with CPU processor IO end, and the data output end of described each anerovane is connected with the input end of storage unit; Described PC terminal also has the input equipment that is connected with CPU processor input end and the output device that is connected with CPU processor output terminal.
After adopting structure of the present utility model, can extrapolate the wind direction and wind velocity feature of impact point position according to existing observational data, using for engineering provides foundation.
Description of drawings
Below in conjunction with accompanying drawing the utility model is further described.
Fig. 1 is the structural representation of the utility model embodiment.
Fig. 2 is the fitting result figure of Fig. 1 embodiment application case.
Embodiment
Embodiment
The wind direction and wind velocity feature Estimation System basic structure of the present embodiment as shown in Figure 1, comprise one group of anerovane that is in different observation positions (1-n), and PC terminal, the PC terminal has according to the input data carries out the CPU processor of computing and the storage unit that the IO end is connected with CPU processor IO end, and the data output end of each anerovane is connected with the input end of storage unit; The PC terminal also has the input equipment that is connected with CPU processor input end and the output device that is connected with CPU processor output terminal.
Anerovane comprises wind direction visualizer, Wind observation instrument and data transmission device, the wind direction visualizer is connected output terminal and is connected with the input end of data transmission device respectively with the Wind observation instrument, the output terminal of data transmission device overlaps with the data output end of anerovane.
The input equipment of PC terminal is keyboard, and output device is display screen.
Anerovane buyable (producer: Shanghai Meteorological Instrument Factory Co., Ltd., model: the EN2A anerovane); PC terminal buyable (commercially available any PC computing machine).
Concrete reckoning process is as follows:
1. in the impact point position anerovane is set, and gathers within a predetermined period of time the wind direction and wind velocity data of impact point position; Meanwhile, near the weather station the impact point position also gathers the wind direction and wind velocity data of this position, research station in identical predetermined amount of time.The storage unit that the wind direction and wind velocity data that impact point position, research station collect transfers to the PC terminal stores.
2. by the output device of PC terminal, the staff adds up each the observation position wind direction and wind velocity data that gathers in the aforementioned predetermined amount of time, then statistics is inputted the PC terminal through input equipment.
3.PC the CPU processor of terminal carries out match according to the statistics of input, draws the mutual relationship of impact point position and research station wind direction and wind velocity data.
4. the staff inputs the PC terminal with the long-term data of weather station through input equipment, PC terminal CPU processor carries out computing according to the 3rd step gained mutual relationship to the long-term data of inputting, and finally extrapolates the wind direction and wind velocity feature same period of impact point position.
Afterwards, can according to gained impact point position wind direction and wind velocity feature, the engineering application of impact point position be planned.
Application case:
Weather station A has and reaches the local wind direction and wind velocity data data in 31 years.Want now to extrapolate near B place, the impact point position wind direction and wind velocity same period feature of weather station A, but B place, impact point position has no precedent the wind direction and wind velocity data data.So the B place arranges anerovane in the impact point position, within 1 year, gather wind direction and wind velocity data herein; Meanwhile, weather station A also gathered its local wind direction and wind velocity data in this 1 year.
By statistics, in this 1 year, the annual mean wind speed of weather station A is 2.50m/s; The annual mean wind speed of impact point position B is 4.73m/s.Statistics is inputted the PC terminal carry out the correlativity match, the gained mutual relationship as shown in Figure 2.
With 31 years cumulative data data input PC terminals of weather station A, calculate the Kp value (as shown in table 1) of different directions; Then utilize above-mentioned mutual relationship, extrapolate the wind speed reproducible results (as shown in table 2) of B place, impact point position different directions.So namely draw the wind direction and wind velocity feature of impact point position B.
The Kp value of table 1 weather station A
The wind speed reproducible results (m/s) of table 2 impact point position B
| Reoccurrence period | N | NNE | NE | ENE | E | ESE | SE | SSE |
| 50 years | 24.7 | 20.4 | 23.7 | 22.7 | 26.5 | 28.8 | 25.3 | 27.4 |
| 10 years | 18.9 | 17.9 | 18.7 | 19.0 | 20.0 | 23.0 | 18.5 | 20.7 |
| 2 years | 12.1 | 14.1 | 12.8 | 13.5 | 12.2 | 15.1 | 11.5 | 13.0 |
| Reoccurrence period | S | SSW | SW | WSW | W | WNW | NW | NNW |
| 50 years | 19.2 | 19.0 | 12.6 | 21.4 | 21.7 | 24.7 | 24.2 | 29.5 |
| 10 years | 15.1 | 15.8 | 10.8 | 15.5 | 16.6 | 20.2 | 17.5 | 21.4 |
| 2 years | 10.7 | 11.2 | 8.1 | 8.8 | 10.7 | 14.1 | 9.5 | 12.7 |
In addition to the implementation, the utility model can also have other embodiments.All employings are equal to the technical scheme of replacement or equivalent transformation formation, all drop on the protection domain of the utility model requirement.
Claims (4)
1. wind direction and wind velocity feature Estimation System, comprise one group of anerovane that is in different observation positions, it is characterized in that, also comprise the PC terminal, the CPU processor that described PC terminal has storage unit and carries out computing according to the input data, the IO end of described storage unit is connected with CPU processor IO end, and the data output end of described each anerovane is connected with the input end of storage unit; Described PC terminal also has the input equipment that is connected with CPU processor input end and the output device that is connected with CPU processor output terminal.
2. wind direction and wind velocity feature Estimation System according to claim 1, it is characterized in that, described anerovane comprises wind direction visualizer, Wind observation instrument and data transmission device, described wind direction visualizer is connected output terminal and is connected with the input end of data transmission device respectively with the Wind observation instrument, the output terminal of described data transmission device overlaps with the data output end of anerovane.
3. wind direction and wind velocity feature Estimation System according to claim 2 is characterized in that, the input equipment of described PC terminal is that keyboard, output device are display screen.
4. wind direction and wind velocity feature Estimation System according to claim 3 is characterized in that, described anerovane model is the EN2A anerovane.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201220467200.4U CN202758087U (en) | 2012-09-13 | 2012-09-13 | A reckoning system of characteristics of wind direction and wind speed |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201220467200.4U CN202758087U (en) | 2012-09-13 | 2012-09-13 | A reckoning system of characteristics of wind direction and wind speed |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN202758087U true CN202758087U (en) | 2013-02-27 |
Family
ID=47737259
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201220467200.4U Expired - Lifetime CN202758087U (en) | 2012-09-13 | 2012-09-13 | A reckoning system of characteristics of wind direction and wind speed |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN202758087U (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103616732A (en) * | 2013-11-01 | 2014-03-05 | 南京大学 | Quality control method and quality monitoring device of upper-air wind data |
-
2012
- 2012-09-13 CN CN201220467200.4U patent/CN202758087U/en not_active Expired - Lifetime
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103616732A (en) * | 2013-11-01 | 2014-03-05 | 南京大学 | Quality control method and quality monitoring device of upper-air wind data |
| CN103616732B (en) * | 2013-11-01 | 2016-10-05 | 南京大学 | The quality inspection device of upper-level winds data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhang et al. | Spatial and temporal variability in the net primary production of alpine grassland on the Tibetan Plateau since 1982 | |
| Hasan et al. | Integrated hydrological-hydraulic model for flood simulation in tropical urban catchment | |
| CN104298841A (en) | Flood forecasting method and system based on historical data | |
| CN112685965B (en) | Method and system for monitoring risk of transmission tower in typhoon | |
| CN104182594A (en) | Method for drawing power system wind area graph | |
| CN104599069A (en) | Power transmission line route planning method based on environment factors and geographic features | |
| Chen et al. | The performance of global models in TC track forecasting over the western North Pacific from 2010 to 2012 | |
| Jiang et al. | Evaluating the TRMM multisatellite precipitation analysis for extreme precipitation and streamflow in Ganjiang River basin, China | |
| Sakti et al. | Spatial integration framework of solar, wind, and hydropower energy potential in Southeast Asia | |
| Qi et al. | Quantitative contribution of climate change and anthropological activities to vegetation carbon storage in the Dongting Lake basin in the last two decades | |
| CN104202817B (en) | The storage of the many focuses received signals fingerprint map in the large-scale interior space and matching process | |
| CN113358040B (en) | Method and device for acquiring icing thickness of power transmission line and computer equipment | |
| Lou et al. | Whether the enhanced terrestrial vegetation carbon sink affect the water resources in the middle-low latitude karst areas of China? | |
| Shen et al. | Analysis of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China from 1982 to 2010 | |
| CN202758087U (en) | A reckoning system of characteristics of wind direction and wind speed | |
| Cho et al. | Web-based agricultural infrastructure digital twin system integrated with GIS and BIM concepts | |
| CN105184041A (en) | Spline interpolation analysis method of power transmission line meteorological characteristics | |
| Subasinghe et al. | Neighborhood dynamics of urban expansion based on morphological spatial pattern analysis and geospatial techniques: a case study of the Colombo metropolitan area, Sri Lanka | |
| Lin et al. | Spatial-temporal dynamics of meteorological and soil moisture drought on the Tibetan Plateau: Trend, response, and propagation process | |
| Rahdari et al. | Monitoring sand drift potential and sand dune mobility over the last three decades (Khartouran Erg, Sabzevar, NE Iran). Sustainability, 2021, 13, 9050 | |
| CN112800697A (en) | Method, system and device for planning and site selection of wind measuring tower in early stage of wind power plant and storage medium | |
| Munar et al. | Modelling the climate change impacts on river discharge and inundation extent in the Magdalena River basin–Colombia | |
| Izeiroski et al. | Gis-based multi criteria analysis of site suitability for exploatation of renewable energy resources | |
| CN104134158A (en) | Interference analysis method of nuclear power plant landscape | |
| Wu et al. | Research and extraction of the hydrological characteristics based on GIS and DEM |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CX01 | Expiry of patent term |
Granted publication date: 20130227 |
|
| CX01 | Expiry of patent term |