CN111594391A - Wind power generation tower inclination online monitoring method - Google Patents
Wind power generation tower inclination online monitoring method Download PDFInfo
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- CN111594391A CN111594391A CN202010245431.XA CN202010245431A CN111594391A CN 111594391 A CN111594391 A CN 111594391A CN 202010245431 A CN202010245431 A CN 202010245431A CN 111594391 A CN111594391 A CN 111594391A
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- tower
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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
- F03D13/00—Assembly, mounting or commissioning of wind motors; Arrangements specially adapted for transporting wind motor components
- F03D13/20—Arrangements for mounting or supporting wind motors; Masts or towers for wind motors
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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
- 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
- F03D80/00—Details, components or accessories not provided for in groups F03D1/00 - F03D17/00
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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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/72—Wind turbines with rotation axis in wind direction
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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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/728—Onshore wind turbines
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- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Wind Motors (AREA)
Abstract
The invention discloses an online monitoring method for the gradient of a wind power generation tower, belongs to the technical field of wind power generation, can realize the function of monitoring the gradient of the tower, and can display monitoring data and analysis results in real time. In the method, firstly, a single-shaft tilt angle sensor is arranged on the inner wall of the top of a tower cylinder to acquire tilt angle data in real time; by collecting sample data, calculating the mean value mu and the standard deviation sigma of the sample data, tracking the trends of mu and sigma, and setting mu +/-3 sigma as an abnormal value detection threshold value as an early warning reference value. By utilizing the method provided by the invention, the health monitoring of the tower barrel of the wind turbine generator can be realized under the condition of no prior information and domain knowledge.
Description
Technical Field
The invention belongs to the technical field of wind power generation, and particularly relates to an online monitoring method for the inclination of a wind power generation tower barrel, which can realize the inclination monitoring function of the tower barrel and display monitoring data and analysis results in real time.
Background
In recent years, China has become the market with the largest and fastest growth of global wind power generation scale.
The tower barrel plays an important role as a supporting component of the wind generating set, and can be partially inclined due to various reasons in the processes of installation, debugging, operation, maintenance and the like. In the using process, the inclination of the tower barrel of the wind turbine generator set is an important monitoring parameter, if the inclination is too large, the normal operation of the wind turbine generator set can be influenced, serious safety accidents can be caused seriously, and even the life can be possibly damaged. Therefore, in order to ensure the safe production of the wind power plant, the inclination angle of the tower cylinder needs to be monitored on line.
At present, no unified standard or method exists for detecting the inclination of the wind turbine generator tower at home and abroad. Therefore, the wind turbine generator tower inclination detection method with strong operability and high precision has a guiding effect on the operation and maintenance work of the wind turbine generator tower and provides reference for the standard compilation of wind turbine generator tower inclination detection in the future.
Disclosure of Invention
In order to realize real-time monitoring of the inclination of the wind turbine tower, the invention provides an online monitoring method of the inclination of the wind turbine tower based on inclination angle sensor information. By utilizing the method provided by the invention, the health monitoring of the tower barrel of the wind turbine generator can be realized under the condition of no prior information and domain knowledge.
The technical scheme adopted by the invention for solving the problems is as follows: an on-line monitoring method for the gradient of a wind power generation tower cylinder is characterized by comprising the following steps:
firstly, mounting a sensor in a fan tower drum, wherein the mounting position is the inner wall of the top of the fan tower drum, and a vertical mounting mode is adopted; acquisition by sensorSample data a α1,α2…αn；
Secondly, calculating a sample data mean value mu and a standard deviation sigma according to the following formula;
wherein αiRepresenting sample inclination data, mu is a sample data mean value, and sigma is a sample data standard deviation;
thirdly, monitoring the inclination trend of the tower drum of the fan by drawing a mu and sigma time chart;
and fourthly, taking the dynamic mu +/-3 sigma as an abnormal value monitoring threshold value, and early warning in real time.
Compared with the prior art, the invention has the following advantages and effects:
a) the wind power generation tower cylinder inclination on-line monitoring method provided by the invention takes data information as drive, and introduces a Gaussian distribution numerical value statistical method, thereby constructing a self-adaptive abnormal value detection tool.
b) Compared with other tower inclination monitoring methods, the self-adaptive tower inclination health assessment index is constructed based on the Gaussian distribution numerical value statistical method, and the method is insensitive to noise and interference, simple to operate, economical and effective.
Drawings
Fig. 1 is a schematic view of a mounting structure of a tilt sensor in an embodiment of the present invention.
FIG. 2 is a sample graph of data in an embodiment of the invention.
FIG. 3 is a graph of a data sample distribution according to an embodiment of the present invention.
FIG. 4 is a graph of mean and standard deviation of data samples according to an embodiment of the present invention.
FIG. 5 is a schematic view of a data sample tower real-time monitoring system according to an embodiment of the invention.
In the figure: the wind power generation system comprises a wind power cabin 1, a sensor 2, a fan tower 3 and a tower footing ground plane 4.
Detailed Description
The present invention will be described in further detail below by way of examples with reference to the accompanying drawings, which are illustrative of the present invention and are not to be construed as limiting the present invention.
Examples are given.
The sensor 2 that this embodiment relates to is high accuracy unipolar tilt angle sensor, and for the data accuracy that ensures sensor 2 to gather, installs sensor 2 in the sensor collector, fixes sensor 2 in the top inner wall department of the fan tower section of thick bamboo 3 of wind-powered electricity generation cabin 1 lower part through the bolt, adopts the mode of perpendicular installation to install (as fig. 1). Data collected by the sensor 2 are transmitted to a database through an optical fiber interface reserved in the cabin control cabinet by using a fan ring network, are stored, and are processed and displayed in real time by establishing a remote application system through an informatization means.
The wind power generation tower inclination online monitoring method comprises the following steps:
firstly, a tower dynamic measuring device, namely a single-shaft inclination angle sensor, is arranged in a fan tower 3, the installation position is the top inner wall of the fan tower 3, a vertical installation mode is adopted, and sample data A obtained by a sensor 2 is α1,α2…αn(see FIG. 2);
secondly, calculating a sample data mean value mu and a standard deviation sigma according to the following formula;
wherein αiRepresenting sample inclination data, mu is a sample data mean value, and sigma is a sample data standard deviation;
thirdly, monitoring the inclination trend of the tower 3 of the wind turbine by using a mu and sigma time chart (as shown in figure 4);
and fourthly, taking the dynamic mu +/-3 sigma as an abnormal value monitoring threshold value, and carrying out real-time early warning (as shown in figure 5).
Those not described in detail in this specification are well within the skill of the art.
Although the present invention has been described with reference to the above embodiments, it should be understood that the scope of the present invention is not limited thereto, and that various changes and modifications can be made by those skilled in the art without departing from the spirit and scope of the present invention.
Claims (1)
1. An on-line monitoring method for the gradient of a wind power generation tower cylinder is characterized by comprising the following steps:
firstly, a sensor (2) is installed in a fan tower drum (3), the installation position is the top inner wall of the fan tower drum (3), a vertical installation mode is adopted, and sample data A which is α are obtained through the sensor (2)1,α2…αn；
Secondly, calculating a sample data mean value mu and a standard deviation sigma according to the following formula;
wherein αiRepresenting sample inclination data, mu is a sample data mean value, and sigma is a sample data standard deviation;
thirdly, monitoring the inclination trend of the tower drum (3) of the fan by drawing mu and sigma time;
and fourthly, taking the dynamic mu +/-3 sigma as an abnormal value monitoring threshold value, and early warning in real time.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010245431.XA CN111594391A (en) | 2020-03-31 | 2020-03-31 | Wind power generation tower inclination online monitoring method |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010245431.XA CN111594391A (en) | 2020-03-31 | 2020-03-31 | Wind power generation tower inclination online monitoring method |
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| Publication Number | Publication Date |
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| CN111594391A true CN111594391A (en) | 2020-08-28 |
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| CN202010245431.XA Pending CN111594391A (en) | 2020-03-31 | 2020-03-31 | Wind power generation tower inclination online monitoring method |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107168854A (en) * | 2017-06-01 | 2017-09-15 | 北京京东尚科信息技术有限公司 | Detection method, device, equipment and readable storage medium storing program for executing are clicked in Internet advertising extremely |
| CN107829884A (en) * | 2017-10-25 | 2018-03-23 | 西安锐益达风电技术有限公司 | A kind of wind-driven generator tower health status monitoring method and dedicated test system |
| CN207598434U (en) * | 2017-12-13 | 2018-07-10 | 国家电投集团滨海海上风力发电有限公司 | A kind of offshore wind farm set tower drum and the safe on-Line Monitor Device of pile foundation |
| CN108534756A (en) * | 2018-04-14 | 2018-09-14 | 杭州职业技术学院 | Wind turbines tower inclination checking method |
| CN108562854A (en) * | 2018-04-08 | 2018-09-21 | 华中科技大学 | A kind of motor abnormal condition on-line early warning method |
| CN110514179A (en) * | 2019-09-05 | 2019-11-29 | 中船重工海为(新疆)新能源有限公司 | A kind of measurement Wind turbines tower gradient method |
-
2020
- 2020-03-31 CN CN202010245431.XA patent/CN111594391A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107168854A (en) * | 2017-06-01 | 2017-09-15 | 北京京东尚科信息技术有限公司 | Detection method, device, equipment and readable storage medium storing program for executing are clicked in Internet advertising extremely |
| CN107829884A (en) * | 2017-10-25 | 2018-03-23 | 西安锐益达风电技术有限公司 | A kind of wind-driven generator tower health status monitoring method and dedicated test system |
| CN207598434U (en) * | 2017-12-13 | 2018-07-10 | 国家电投集团滨海海上风力发电有限公司 | A kind of offshore wind farm set tower drum and the safe on-Line Monitor Device of pile foundation |
| CN108562854A (en) * | 2018-04-08 | 2018-09-21 | 华中科技大学 | A kind of motor abnormal condition on-line early warning method |
| CN108534756A (en) * | 2018-04-14 | 2018-09-14 | 杭州职业技术学院 | Wind turbines tower inclination checking method |
| CN110514179A (en) * | 2019-09-05 | 2019-11-29 | 中船重工海为(新疆)新能源有限公司 | A kind of measurement Wind turbines tower gradient method |
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Application publication date: 20200828 |
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