CN107654341A - The vertical axis wind power generation monitoring device of survey is sentenced based on power observation and data exception - Google Patents
The vertical axis wind power generation monitoring device of survey is sentenced based on power observation and data exception Download PDFInfo
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- 238000010248 power generation Methods 0.000 title claims abstract description 25
- 238000012806 monitoring device Methods 0.000 title claims abstract description 13
- 238000012545 processing Methods 0.000 claims abstract description 73
- 238000005259 measurement Methods 0.000 claims abstract description 61
- 238000012544 monitoring process Methods 0.000 claims abstract description 55
- 230000006854 communication Effects 0.000 claims abstract description 52
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- 238000003860 storage Methods 0.000 claims abstract description 10
- 230000002159 abnormal effect Effects 0.000 claims abstract description 5
- 238000012360 testing method Methods 0.000 abstract description 10
- 238000000034 method Methods 0.000 abstract description 7
- 230000004927 fusion Effects 0.000 abstract description 6
- 238000009434 installation Methods 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 abstract description 3
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- 230000005540 biological transmission Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 230000007175 bidirectional communication Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
- F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
- F05B2260/00—Function
- F05B2260/80—Diagnostics
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
- F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
- F05B2270/00—Control
- F05B2270/70—Type of control algorithm
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Abstract
The invention discloses a kind of vertical axis wind power generation monitoring device that survey is sentenced based on power observation and data exception, mainly it is made up of in-site measurement and processing equipment and host computer intelligent display device.In-site measurement includes air force measurement module, generated output measurement module, vertical axis polarization measurement module, electromagnetism and noise measurement module, data monitoring processing module with processing equipment.In the microprocessor of data monitoring processing module there is data exception to sentence method of determining and calculating, can differentiate whether measurement data is abnormal.In-site measurement is powered with using Zigbee wireless telecommunications inside processing equipment, and using wind-light storage mode.In-site measurement uses WiFi wireless telecommunications with processing equipment with host computer intelligent display device.The present invention is by technologies such as FUSION WITH MULTISENSOR DETECTION, Wi-Fi communication, multimicroprocessor computings, with the features such as easy for installation, test is reliable, function modoularization, networking flexibility, friendly interface, easy care.
Description
The application is application number: 201510705075.4, application date: 2015.10.27, divisional application entitled "vertical axis wind power generation monitoring device based on multi-network fusion and distributed sensing".
Technical Field
The invention relates to the field of integrated monitoring of wind power generation systems, in particular to a vertical axis wind power generation monitoring device based on multi-network fusion and distributed sensing.
Background
"equipment is to be developed and test is to be preceded". The verification and the test of the small and medium-sized wind power generation equipment cannot be carried out from the design and the trial production to the production and maintenance processes. Due to the natural particularity of wind energy utilization, the data acquisition process of the equipment based on a manual mode and a wired transmission mode is very inconvenient no matter the equipment is used for wind tunnel test at the initial research and development stage or field operation monitoring of a prototype or a product.
The connection process of the distributed multi-sensor of the wind power generation system based on the wired transmission mode is extremely complicated and complicated, and the labor intensity of testers is high. The test in the narrow and small space of wind-tunnel still can cause the distortion of local wind field because of the difference of wire mode of walking, influences the measuring accuracy, even because of the wire drops and causes the winding of rotation axis, leads to serious accident. In a wind power generation operation site, due to the fact that geographical and meteorological conditions of unit site installation are severe, such as high terrain, roofs and the like in suburbs or urban areas, long-term large-amount manual data collection is extremely inconvenient, and too long leads can cause serious signal attenuation and interference.
Therefore, according to the actual application requirements of the fan power generation equipment, the intelligent test system platform based on the running state parameters of the wireless communication distributed sensor network is applied, so that the intelligent test system platform has important significance for the whole life cycle of a wind power generation product, and has good application and practical prospects.
Disclosure of Invention
The invention aims to provide a vertical axis wind power generation monitoring device based on multi-network fusion and distributed sensing, which is reasonable in structure, convenient to install, reliable in test and easy to maintain.
The technical solution of the invention is as follows:
a vertical axis wind power generation monitoring device based on multi-network fusion and distributed sensing is characterized in that: the intelligent display system comprises field measurement and processing equipment, wherein the field measurement and processing equipment is communicated with upper computer intelligent display equipment; the field measurement and processing equipment comprises an aerodynamic measurement module, a power generation power measurement module, a vertical axis polarization measurement module and an electromagnetic and noise measurement module, wherein the measurement modules are communicated with a data monitoring and processing module; the vertical axis polarization measurement module comprises 3 double-axis magnetic resistance sensors which are respectively arranged at the top end and the bottom end of a main shaft of the vertical axis wind turbine and an output shaft end of a rotor of the wind driven generator; each measuring module comprises a microprocessor and a Zigbee wireless communication interface; the data monitoring processing module comprises a microprocessor, a Zigbee wireless communication interface and a WiFi wireless communication interface; the measuring modules are communicated with the Zigbee wireless communication interface of the data monitoring processing module through the Zigbee wireless communication interfaces thereof; the WiFi wireless communication interface of the upper computer intelligent display equipment is communicated with the WiFi wireless communication interface of the data monitoring processing module;
the microprocessor of the data monitoring processing module adopts a data abnormity judgment algorithm; the data anomaly judgment algorithm comprises the following steps:
(1) Obtaining the generating power P of the generator e And real-time measurements of angular velocity ω;
(2) Calculating a mechanical power observation of a vertical axis wind turbine according to the following formula
Wherein J is the moment of inertia of the vertical axis wind turbine; z is a radical of formula 1 ，z 2 Is a state variable; beta is a beta 1 ，β 2 ，δ 1 ，δ 2 ，α 1 ，α 2 Is a normal coefficient, and 0<α 2 <α 1 <1；
(3) Obtaining mechanical power P of vertical axis wind turbine m Real-time measurements of (a);
(4) Observing the calculated mechanical powerAnd mechanical power P m The real-time measured values are compared, if the deviation between the two measured values is less than 15%, the measured data can be judged to be normal, otherwise, the measured data is judged to be abnormal.
Each measuring module and each data monitoring processing module in the field measuring and processing equipment adopt Zigbee wireless communication protocol for bidirectional communication; the data monitoring processing module and the upper computer intelligent display equipment adopt WiFi wireless communication protocol two-way communication.
The Zigbee wireless communication interfaces of the measurement modules in the field measurement and processing equipment are configured to be in a slave equipment mode, and the Zigbee wireless communication interfaces of the data monitoring and processing module are configured to be in a master coordinator mode; and a WiFi wireless communication interface of the data monitoring processing module is configured to be in a pure access point mode.
The aerodynamic force measurement module also comprises a wind speed sensor, an air temperature sensor, an air pressure sensor and a photovoltaic panel set; the field measurement and processing equipment adopts a wind-light storage mode to supply power.
The data monitoring and processing module calculates the mean square deviation, the kurtosis and the skewness values of the vertical axis wind turbine in the top end and the bottom end of a main shaft of the vertical axis wind turbine and the shaft outlet end of a rotor of a wind driven generator in real time according to the data of the double-axis magnetic resistance sensor, and the health degree of the vertical axis dynamic mechanical inclination is judged by comparing the mean square deviation, the kurtosis and the skewness values in the double-axis directions of 3 horizontal sections with a preset threshold value.
The invention has reasonable structure, convenient installation, reliable test and easy maintenance; its advantage still lies in:
(1) By adopting the distributed multi-microprocessor technology, all functional parts of the system are physically dispersed, the modularization degree and reliability of software and hardware are improved, and the maintenance, upgrading and overhaul are facilitated.
(2) The measured signal is digitized on site, so that the precision is improved, and the problems of attenuation, easy interference and the like of long-distance transmission of the traditional analog signal are avoided.
(3) By adopting a multi-wireless network communication technology, the problems of high cost, high power consumption, complex connection, inconvenient installation, mechanical strength and reliability and the like of wired transmission are avoided.
(4) And a method for comparing the estimated value with the measured value of the observer is adopted to judge whether the related data received by the data monitoring processing module is real and effective or not, so that the monitoring data of the test system is more reliable.
Drawings
The invention is further illustrated by the following figures and examples.
Fig. 1 is a general block diagram of one embodiment of the present invention.
Fig. 2 is a structural diagram of the aerodynamic force measurement module.
Fig. 3 is a mounting position distribution diagram of the biaxial magnetoresistive sensor.
FIG. 4 is a vertical viewStraight axis polarization curve (t, σ) i ,Kur i ,Sc i ) Examples are shown.
FIG. 5 is a wind wheel aerodynamic characteristics curve (λ, C) p ) Examples are shown.
FIG. 6 is a wind turbine performance curve (v) w ,n,P m ) Examples are shown.
FIG. 7 is a graph of electric power output characteristics (v) w ,P e ) Examples are shown.
FIG. 8 is a speed governing characteristic curve (v) w N) example graph.
FIG. 9 is a unit efficiency curve (v) w Eta) example graph.
FIG. 10 is a graph of electromagnetic intensity curves (t, E) m ) Examples are shown.
Fig. 11 is an exemplary graph of the noise curve (t, ANL).
Detailed Description
A vertical axis wind power generation monitoring device based on multi-network fusion and distributed sensing comprises an on-site measurement and processing device, wherein the on-site measurement and processing device is communicated with an upper computer intelligent display device; the field measurement and processing equipment comprises an aerodynamic measurement module, a power generation power measurement module, a vertical axis polarization measurement module and an electromagnetic and noise measurement module, wherein the measurement modules are communicated with a data monitoring and processing module; the vertical axis polarization measurement module comprises 3 double-axis magnetic resistance sensors which are respectively arranged at the top end and the bottom end of a main shaft of the vertical axis wind turbine and the shaft outlet end of a rotor of the wind driven generator; each measuring module comprises a microprocessor and a Zigbee wireless communication interface; the data monitoring processing module comprises a microprocessor, a Zigbee wireless communication interface and a WiFi wireless communication interface; the measuring modules are communicated with the Zigbee wireless communication interface of the data monitoring processing module through the Zigbee wireless communication interfaces thereof; and the WiFi wireless communication interface of the upper computer intelligent display equipment is communicated with the WiFi wireless communication interface of the data monitoring processing module.
The field measurement and processing equipment adopts a wind-light storage mode to supply power. The long-distance transmission of an external power supply line of the field measurement and processing equipment of the vertical axis wind power generation system is reduced on one hand, and the reliability of power supply of the field measurement and processing equipment can be increased on the other hand.
Further, referring to fig. 2, the aerodynamic force measurement module further includes a wind speed sensor, an air temperature sensor, an air pressure sensor and a photovoltaic panel assembly, and a microprocessor of the aerodynamic force measurement module transmits the wind speed v transmitted by the sensor w The temperature T and the air pressure P signals are converted into digital information, and then the digital information is transmitted to the data monitoring processing module through the Zigbee wireless communication interface. The photovoltaic panel group supplies power to the aerodynamic force measurement module so as to reduce long-distance transmission of an external power supply circuit.
The microprocessor converts the voltage V, current I and voltage frequency f signals transmitted by the sensors and the monitoring circuit into digital information, and then transmits the digital information to the data monitoring processing module through a Zigbee wireless communication interface.
The vertical axis polarization measurement module also comprises 3 double-axis magnetoresistive sensors, and a microprocessor of the vertical axis polarization measurement module converts deflection angle signals of the double axes in the horizontal direction of the vertical axis detected by each sensor into digital information, and then transmits the digital information to the data monitoring processing module through a Zigbee wireless communication interface. Referring to fig. 3, a mounting position distribution diagram of 3 biaxial magnetoresistive sensors is shown. In fig. 3, 101 is a vertical axis wind turbine, 102 is a vertical axis main shaft of the vertical axis wind turbine, and 3 biaxial magnetoresistive sensors are coaxially installed at the lower part of the vertical axis wind turbine, and are respectively installed at the top end, the bottom end and the shaft outlet end of a wind turbine rotor.
The electromagnetic and noise measuring module also comprises an electromagnetic intensity sensor and a noise sensor, and the microprocessor converts electromagnetic intensity and noise signals transmitted by the sensors into digital information and then transmits the digital information to the data monitoring and processing module through a Zigbee wireless communication interface.
And each measuring module and each data monitoring processing module in the field measuring and processing equipment adopt Zigbee wireless communication protocol bidirectional communication, wherein the Zigbee wireless communication interface of each measuring module is configured to be in a slave equipment mode, and the Zigbee wireless communication interface of the data monitoring processing module is configured to be in a master coordinator mode.
The data monitoring and processing module receives and stores data of the dual-axis magnetoresistive sensor. Then the microprocessor calculates the respective deflection mean square deviations sigma of the vertical axis wind turbine in the top end and the bottom end of the main shaft of the vertical axis wind turbine and the output shaft end of the rotor of the wind driven generator in real time and in the double-axis directions of 3 horizontal sections i Kur, kur i Inclination of S ci Values, where i =1,2,3, represent the numbers of 3 dual-axis magnetoresistive sensors.
With N sample point data (x) in a set of running data sets ik K =1, \ 8230;, N) is an example, the mean deviation σ thereof i Kur, kur i And the degree of skewness S ci Is calculated as follows:
and the data monitoring and processing module compares the calculation result of the formula with a preset threshold value stored in the data monitoring and processing module to form judgment on the vertical axis dynamic mechanical inclination health degree, such as indication of normal operation, small deflection angle, large deflection angle and the like.
Meanwhile, the data monitoring and processing module compares the current time t with 3 groups of mean square deviations sigma of the vertical axis wind turbine i Kur, kur i Inclination of S ci Formatted storage (t, sigma) as a pair of horizontal and vertical axis data, respectively i ,Kur i ,Sc i ) And obtaining the drawing data of the vertical axis principal axis polarization curve, as shown in figure 4.
The data monitoring and processing module receives and stores the wind speed v transmitted by the aerodynamic force measuring module w The air temperature T, the air pressure signal P, and the voltage V, the current I and the voltage frequency f signals transmitted by the power generation measuring module. The microprocessor calculates the air density rho according to the air temperature-air pressure-air density function stored in the microprocessor. Then the basic electromechanical parameters of the wind driven generator stored in the wind driven generator comprise a generating power coefficient K e N number of pole pairs of generator p The radius R of the vertical axis wind wheel, the wind sweeping sectional area A of the wind wheel and the like according to the calculation formula
P e ＝K e UI
Respectively calculating the rotating speed n, the angular speed omega, the tip speed ratio lambda and the relative moment coefficient C of the vertical axis wind turbine m And the power P generated by the generator e . Then according to the following calculation formula
C p ＝C m λ、P m ＝0.5ρAv w 3 C m λ、
Respectively calculating the wind energy utilization coefficient C of the vertical axis wind turbine p Mechanical power P m And unit efficiency η.
Further, the data monitoring processing module:
the tip speed ratio lambda and the wind energy utilization coefficient C p Formatted storage as a pair of horizontal and vertical axis data (lambda, C) p ) And obtaining the drawing data of the wind wheel aerodynamic characteristic curve, such as figure 5.
All the same wind speeds v w Interval vertical axis wind turbine speed n and mechanical power P m (v) formatted storage as a pair of horizontal and vertical axis data w ,n,P m ) And drawing data of the characteristic curve of the wind turbine can be obtained, such as figure 6.
The wind speed v w And the power P generated by the generator e (v) formatted storage as a pair of horizontal and vertical axis data w ,P e ) The plot data of the electric power output characteristic curve can be obtained, as shown in fig. 7.
Will wind speed v w And vertical axis wind turbine speed n as a pair of horizontal and vertical axis data for formatted storage (v) w N), the plot data of the speed regulation characteristic curve can be obtained, as shown in fig. 8.
Will wind speed v w Kneading machineThe group efficiency eta is stored in a format (v) as a pair of horizontal and vertical axis data w Eta), the mapping data of the unit efficiency curve can be obtained, as shown in fig. 9.
The data monitoring and processing module receives and stores the electromagnetic intensity and the noise value transmitted by the electromagnetic and noise measuring module, and receives the time t and the electromagnetic intensity E m Formatted storage as a pair of horizontal and vertical axis data (t, E) m ) Obtaining the drawing data of the electromagnetic intensity curve, such as fig. 10; the reception time t and the noise ANL are stored in a format (t, ANL) as a pair of horizontal and vertical axis data, and the plot data of the noise curve can be obtained, as shown in fig. 11.
In order to determine whether the relevant data received by the data monitoring and processing module is real and effective, a method of comparing the observer estimation value with the measured value can be adopted to determine. The principle comprises the following steps:
the electromechanical coupling kinematic equation of the vertical axis wind power generation system can be expressed as
In the formula, J is the rotational inertia of the vertical axis wind turbine, and B is the friction coefficient of the vertical axis wind power generation main shaft system.
The above formula shows that the generator generates power P e Angular velocity omega and vertical axis wind turbine mechanical power P m Are associated. Therefore, if a vertical axis wind turbine mechanical power P is assumed m Being unknown, the power P can be generated by a known generator e And angular velocity omega, calculating a mechanical power observation of the vertical axis wind turbine using the following equation
Wherein J is the moment of inertia of the vertical axis wind turbine; z is a radical of formula 1 ，z 2 Is a state variable; beta is a beta 1 ，β 2 ，δ 1 ，δ 2 ，α 1 ，α 2 Is a normal coefficient, and 0<α 2 <α 1 <, 1; fal () is a nonlinear combined power function expressed as
Wherein δ and α are normal coefficients, and 0< α <1.
Observing the calculated mechanical powerAnd mechanical power P m The real-time measured values are compared, if the deviation between the two measured values is less than 15%, the measured data can be judged to be normal, otherwise, the measured data is judged to be abnormal.
The data anomaly judgment algorithm can be realized by a microprocessor and software programming in the data monitoring processing module.
The data monitoring processing module and the upper computer intelligent display equipment adopt WiFi wireless communication protocol bidirectional communication, wherein a WiFi wireless communication interface of the data monitoring processing module is configured to be a pure Access Point (AP) mode. The upper computer intelligent display equipment can be intelligent portable equipment such as a PC (personal computer), a tablet personal computer or a mobile phone, and the upper computer intelligent display equipment can be used as a WiFi (wireless fidelity) wireless communication Station (STA) and can be accessed to a data monitoring processing module for data exchange and access, so that the intellectualization, the portability and the friendliness of the monitoring device are greatly improved.
The upper computer intelligent display equipment runs corresponding programs inside, receives various drawing data from the data monitoring and processing module, and comprises wind wheel aerodynamic characteristic curve data (lambda, C) p ) And the wind wheel mechanical characteristic curve data (v) w ,n,P m ) Electric power output characteristic curve data (v) w ,P e ) Speed control characteristic curve data (v) w N) unit efficiency curve data (v) w Eta), electromagnetic intensityCurve data (t, E) m ) Noise curve data (t, ANL), vertical axis polarization curve data (t, σ) i ,Kur i ,Sc i ) And drawing by using a dot drawing method, and displaying on a display device. Meanwhile, the 'measured data normal' or 'measured data abnormal' given by the data abnormity judgment algorithm and the judgment result of the vertical axis dynamic mechanical inclination health degree are displayed for the observation and judgment of users and monitoring personnel.
Other suitable embodiments of the invention are also possible, for example: the Zigbee wireless communication interfaces of the measurement modules in the field measurement and processing equipment are configured to be in a slave equipment mode, and the Zigbee wireless communication interfaces of the data monitoring and processing module are configured to be in a master coordinator mode; and a WiFi wireless communication interface of the data monitoring processing module is configured to be in a pure access point mode.
Claims (4)
1. A vertical axis wind power generation monitoring device based on power observation and data anomaly judgment is characterized in that: the intelligent display system comprises field measurement and processing equipment, wherein the field measurement and processing equipment is communicated with upper computer intelligent display equipment; the field measurement and processing equipment comprises an aerodynamic measurement module, a power generation power measurement module, a vertical axis polarization measurement module and an electromagnetic and noise measurement module, wherein the measurement modules are communicated with a data monitoring and processing module; the vertical axis polarization measurement module comprises 3 double-axis magnetic resistance sensors which are respectively arranged at the top end and the bottom end of a main shaft of the vertical axis wind turbine and the shaft outlet end of a rotor of the wind driven generator; each measuring module comprises a microprocessor and a Zigbee wireless communication interface; the data monitoring processing module comprises a microprocessor, a Zigbee wireless communication interface and a WiFi wireless communication interface; the measuring modules are communicated with the Zigbee wireless communication interface of the data monitoring processing module through the Zigbee wireless communication interfaces thereof; the WiFi wireless communication interface of the upper computer intelligent display equipment is communicated with the WiFi wireless communication interface of the data monitoring processing module;
the microprocessor of the data monitoring processing module adopts a data abnormity judgment algorithm; the data anomaly determination algorithm comprises the following steps:
(1) Obtaining the generating power P of the generator e And real-time measurements of angular velocity ω;
(2) Calculating a mechanical power observation of a vertical axis wind turbine according to the following formula
Wherein J is the moment of inertia of the vertical axis wind turbine; z is a radical of 1 ，z 2 Is a state variable; beta is a beta 1 ，β 2 ，δ 1 ，δ 2 ，α 1 ，α 2 Is a normal coefficient, and 0<α 2 <α 1 <1；
(3) Obtaining mechanical power P of vertical axis wind turbine m Real-time measurements of;
(4) Observing the calculated mechanical powerAnd mechanical power P m Comparing the real-time measured values, if the deviation between the two measured values is less than 15%, judging that the measured data is normal, otherwise, judging that the measured data is abnormal;
the microprocessor converts the voltage V, current I and voltage frequency f signals transmitted by the sensors and the monitoring circuit into digital information, and then transmits the digital information to the data monitoring processing module through a Zigbee wireless communication interface;
the vertical axis polarization measurement module also comprises 3 double-axis magnetic resistance sensors, and a microprocessor of the vertical axis polarization measurement module converts deflection angle signals of the double axes in the horizontal direction of the vertical axis, which are detected by each sensor, into digital information and then transmits the digital information to the data monitoring processing module through a Zigbee wireless communication interface.
2. The vertical axis wind power generation monitoring device based on power observation and data anomaly determination as claimed in claim 1, wherein: each measuring module and each data monitoring processing module in the field measuring and processing equipment adopt Zigbee wireless communication protocol to carry out two-way communication; the data monitoring processing module and the upper computer intelligent display equipment adopt WiFi wireless communication protocol two-way communication.
3. The vertical axis wind power generation monitoring device based on power observation and data anomaly determination as claimed in claim 1, wherein: the Zigbee wireless communication interfaces of the measurement modules in the field measurement and processing equipment are configured to be in a slave equipment mode, and the Zigbee wireless communication interfaces of the data monitoring and processing module are configured to be in a master coordinator mode; and a WiFi wireless communication interface of the data monitoring processing module is configured to be in a pure access point mode.
4. The vertical axis wind power generation monitoring device based on power observation and data anomaly determination as claimed in claim 1, wherein: the aerodynamic force measurement module further comprises a wind speed sensor, an air temperature sensor, an air pressure sensor and a photovoltaic panel set; the field measurement and processing equipment adopts a wind-light storage mode to supply power.
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| CN201710770200.9A CN107654341B (en) | 2015-10-27 | 2015-10-27 | The vertical axis wind power generation monitoring device of survey is sentenced based on power observation and data exception |
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| CN201710770200.9A CN107654341B (en) | 2015-10-27 | 2015-10-27 | The vertical axis wind power generation monitoring device of survey is sentenced based on power observation and data exception |
| CN201510705075.4A CN105221337B (en) | 2015-10-27 | 2015-10-27 | Vertical axis wind power generation monitoring device based on multiple networks fusion and distributed sensing |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201489125U (en) * | 2009-08-14 | 2010-05-26 | 北京中能联创风电技术有限公司 | Energy measuring system for wind power stations |
| US20100138060A1 (en) * | 2009-09-18 | 2010-06-03 | General Electric Company | Systems, methods, and apparatus for monitoring and controlling a wind driven machine |
| CN103670921A (en) * | 2013-11-11 | 2014-03-26 | 北京能高自动化技术股份有限公司 | Wind generating set intelligent condition monitoring system |
| CN104200628A (en) * | 2014-09-01 | 2014-12-10 | 中国东方电气集团有限公司 | Industrial GPRS monitoring terminal |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8043048B2 (en) * | 2010-04-08 | 2011-10-25 | General Electric Company | Systems and methods for monitoring a structural health of a wind turbine |
| CN202483794U (en) * | 2012-02-29 | 2012-10-10 | 南通大学 | Electro-mechanical coordination restraining device for chattering of rotary spindle of vertical axis wind turbine |
| DE102013002927A1 (en) * | 2013-02-21 | 2014-08-21 | Robert Bosch Gmbh | Sensor system for monitoring of rotor blade of wind power plant, has communication device providing monitoring signal, and autonomous power supply arranged for providing electrical energy for operating sensor and communication device |
| CN203463234U (en) * | 2013-08-29 | 2014-03-05 | 苏州科技学院 | Complementary power supply monitoring system based on wind energy and solar energy |
| CN204099123U (en) * | 2014-03-20 | 2015-01-14 | 上海电机学院 | Blade of wind-driven generator vibration monitoring and protective gear |
| CN204086906U (en) * | 2014-07-28 | 2015-01-07 | 龙源（北京）风电工程设计咨询有限公司 | A kind of marine wind field video monitoring system based on zigbee radio sensing network |
| CN204331438U (en) * | 2014-12-13 | 2015-05-13 | 西安扩力机电科技有限公司 | A kind of offshore wind farm set remote monitoring system |
-
2015
- 2015-10-27 CN CN201710770187.7A patent/CN107664099B/en active Active
- 2015-10-27 CN CN201510705075.4A patent/CN105221337B/en active Active
- 2015-10-27 CN CN201710770200.9A patent/CN107654341B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201489125U (en) * | 2009-08-14 | 2010-05-26 | 北京中能联创风电技术有限公司 | Energy measuring system for wind power stations |
| US20100138060A1 (en) * | 2009-09-18 | 2010-06-03 | General Electric Company | Systems, methods, and apparatus for monitoring and controlling a wind driven machine |
| CN103670921A (en) * | 2013-11-11 | 2014-03-26 | 北京能高自动化技术股份有限公司 | Wind generating set intelligent condition monitoring system |
| CN104200628A (en) * | 2014-09-01 | 2014-12-10 | 中国东方电气集团有限公司 | Industrial GPRS monitoring terminal |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| USD922126S1 (en) | 2019-06-06 | 2021-06-15 | Sharkninja Operating Llc | User interface for a food preparation device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105221337A (en) | 2016-01-06 |
| CN105221337B (en) | 2017-11-07 |
| CN107664099A (en) | 2018-02-06 |
| CN107664099B (en) | 2019-03-05 |
| CN107654341B (en) | 2019-06-14 |
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