CN112253406B - Environment load prediction method and vibration pre-control system for offshore wind turbine generator - Google Patents
Environment load prediction method and vibration pre-control system for offshore wind turbine generator Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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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
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- F03D7/0296—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor to prevent, counteract or reduce noise emissions
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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Abstract
The invention discloses an environmental load prediction method and a vibration pre-control system of an offshore wind turbine, which comprise an offshore wind turbine structure, and a wind speed measuring device, a magneto-rheological damper array, a wave height measuring device, a flow speed measuring device and a structural vibration control terminal which are fixedly connected with the wind turbine structure respectively; the structure vibration control terminal carries out empirical mode decomposition and autoregressive sliding average model construction on real-time data measured by the wind speed measuring device, the wave height measuring device and the flow velocity measuring device, load prediction on wind speed, wave height and flow velocity is achieved, and then the control force of the magnetorheological damper array is output by combining with the digital twin model, and multi-frequency vibration control of the offshore motor set structure is achieved. The invention can obtain load influence before the load acts on the structure, realizes advanced control of structure vibration, further avoids transient great response generated by the structure and reduces the damage of the structure and a mechanical device.
Description
Technical Field
The invention relates to the field of offshore wind power development, in particular to an environmental load prediction method and a vibration pre-control system for an offshore wind power generation unit.
Background
The offshore wind turbine structure is a multi-subsystem combined engineering device and comprises an upper wind turbine, a middle wind turbine tower, a lower structure foundation (a fixed foundation and a floating foundation) and other auxiliary components. The subsystems have different dynamic performances, bear different loads in operation and have an inseparable coupling relation with each other.
During the service period of the offshore wind turbine structure, various complex random loads including wind, wave, current, ice, tide, ship berthing and the like are always borne, particularly, the fixed offshore wind turbine structure can be influenced by earthquake, and the floating offshore wind turbine structure can be influenced by mooring load. Therefore, the vibration source of the offshore wind turbine generator system structure is extremely complex, and the coupling effect among environmental loads, the coupling effect among subsystem dynamic responses and the coupling effect between the system dynamic responses and the environmental loads are obvious. It is known that the upper wind generator of a wind turbine structure is a vibration sensitive device, and when the acceleration of the nacelle reaches a certain threshold, the wind turbine automatically brakes in an emergency to protect the mechanical components. In many offshore wind farms that are already in production at present, the shutdown of the wind turbine due to excessive vibration is not uncommon. Frequent and excessive vibration can seriously affect the service life of each mechanical component in the fan, and the operation and maintenance cost is increased; frequent braking and stopping can greatly reduce the power generation time of the fan and reduce the power generation efficiency. Therefore, the effective structural vibration control system provided for the complex vibration source of the offshore wind turbine generator system has extremely strong engineering significance.
At present, most of the structural vibration control means commonly used in the engineering field are passive control dampers, such as tuned mass dampers, multi-tuned mass dampers and tuned liquid column dampers. A large number of researches and engineering practices show that the passive damper control can control the load of the fan to a certain extent and weaken the dynamic response amplitude of the structure. However, as is known, the damper control methods all belong to single-frequency control, and can effectively control a certain narrow-frequency load, but aerodynamic loads, wave loads, sea ice loads and the like acting on the offshore wind turbine structure are typical random loads, contain abundant frequency components, and are typical broadband loads, and it is conceivable that these existing single-frequency control methods cannot really realize effective control on the dynamic response of the offshore wind turbine structure random loads with abundant frequency components.
The magneto-rheological damper is a structural vibration intelligent control device with simple mechanism, quick response, large dynamic range, good durability and strong reliability. The magneto-rheological fluid in the magneto-rheological damper is a special material composed of tiny magnetic particles and non-magnetic conductive liquid, can change the rheological property of the magneto-rheological damper along with the change of the external magnetic field strength, and can instantly change from free flowing linear viscous fluid into semisolid with certain controllable yield strength under the action of a magnetic field. However, the nonlinear physical properties of magnetorheological fluids are still difficult to express by physical models.
At present, in devices which adopt a magnetorheological damper to carry out structural vibration reduction, real-time acceleration signals and displacement sensor signals obtained by an acceleration sensor and a displacement sensor are mostly used as the input of a vibration reduction device, and a control current of the magnetorheological damper is obtained by utilizing a neural network or other fuzzy control programs. The control mode can achieve the aim of multi-frequency control to a certain extent, the neural network and the fuzzy control program solve the problem that a nonlinear physical model of the magnetorheological fluid is difficult to establish to a certain extent, but the control based on the structural response real-time monitoring signal is a hysteresis control, and in the face of sudden extreme load, the structure is likely to be damaged and injured before a control instruction is given by the device. For offshore wind turbines, low-altitude torrent, turbulence, thunderstorm, storm surge, malformed waves and focused waves are typical severe short-term loads, so that transient extreme responses generated by the structure are rare, and hysteresis control is difficult to control the sudden extreme loads. In addition, the sensor for monitoring real-time response is difficult to install in practical engineering, especially in the underwater part of the structure, and the sensor partially pre-installed in a dock and a factory is extremely easy to damage in towing and construction processes, for example, damage and falling off due to impact in the piling operation of a wind turbine foundation.
Based on the method, the future environmental load is predicted in advance through the environmental load monitoring device arranged at the position of the fan, the physical information of the structure is obtained through the digital twin system, and a control instruction is sent to the magneto-rheological damper under the action of extreme load, so that the vibration pre-control of the structure under the action of multi-source random load is realized.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an environmental load prediction method and a vibration pre-control system of an offshore wind turbine. The environmental load prediction method provided by the invention is used for predicting the wind, wave and flow data in advance by collecting the wind, wave and flow monitoring data around the offshore wind turbine generator based on a signal processing technology. The vibration pre-control system provided by the invention integrates an environmental load prediction method; adopting a digital twin model to represent the dynamic response performance of the structure and calculate the physical information of the structure; and a magneto-rheological damper array is adopted to realize multi-frequency control of structural response. The vibration pre-control system provided by the invention does not need to be provided with excessive sensors on the structure so as to realize the monitoring of the physical information of the structure; the output control force of the magnetorheological damper can be obtained before the sudden load acts on the structure, the pre-control of the structure vibration is realized, the transient great response generated by the structure is avoided, and the damage of the structure and a mechanical device (such as the emergency brake of a fan) is reduced.
In order to solve the technical problems, the invention is realized by the following technical scheme:
in one aspect, the invention provides a method for predicting environmental load of an offshore wind turbine generator, comprising the following steps:
s1, preprocessing the monitored real-time wave height data, wind speed data and flow speed data by adopting a monitoring data processing system, and removing environmental noise;
s2, performing Empirical Mode Decomposition (EMD) on the wave height data, the wind speed data and the flow speed data after the noise is removed to obtain Intrinsic Mode Functions (IMF) of the monitoring data;
s3, constructing an Autoregressive moving average model (ARMA model) based on an intrinsic mode function by adopting an environmental load prediction system, and solving a model coefficient;
s4, obtaining IMF prediction time course data based on an ARMA model;
and S5, restoring the IMF prediction time course data by adopting a digital twin model system to obtain the prediction time course data of wave height data, wind speed data and flow speed data.
In another aspect, the present invention further provides a pre-control system for an offshore wind turbine, comprising: the device comprises an offshore wind turbine generator structure, and a magnetorheological damper array, a wave height measuring device, a flow velocity measuring device, a wind speed measuring device and a control terminal which are fixedly connected with the wind turbine generator structure respectively.
The magneto-rheological damper array, the wave height measuring device, the wind speed measuring device and the flow speed measuring device realize data transmission with the control terminal through a wireless technology.
The control terminal comprises a monitoring data processing system, an environmental load prediction system and a digital twin model system.
As a preferable technical scheme of the invention, the offshore wind turbine generator system structure mainly comprises blades, a hub, a cabin, a tower, a floating foundation and an anchoring system, wherein the tower is formed by connecting a plurality of sections of steel cylindrical structures through flanges.
As a preferred technical scheme of the invention, a plurality of magnetorheological damper arrays are arranged at intervals in the height direction of the tower, and each magnetorheological damper array is fixedly connected with the flange through a steel frame.
As a preferred technical scheme of the invention, each magneto-rheological damper array is composed of a plurality of magneto-rheological dampers arranged on the periphery of a steel frame.
As a preferred technical scheme of the present invention, a plurality of wave height measuring devices and flow velocity measuring devices are installed around the floating foundation, and the wave height measuring devices and the flow velocity measuring devices are arranged near the floating foundation on the water plane of the offshore wind turbine structure.
As a preferred technical scheme of the invention, the wind speed measuring device is arranged at the front end of the hub to monitor the real-time wind speed at the elevation position of the hub.
As a preferred technical solution of the present invention, the structural vibration control terminal is installed in the nacelle and is used for receiving and processing the monitored real-time data.
In conclusion, compared with the prior art, the invention has the following advantages and beneficial effects:
1) the environment load prediction algorithm provided by the invention is integrated in the environment load prediction and control terminal, and the algorithm is beneficial to combining the EMD decomposition and the ARMA model. The EMD can perform multi-resolution stripping on the broadband complex signal, the obtained IMF greatly reduces the construction difficulty of the ARMA model, and the short-term time sequence accurate prediction of the environmental load can be realized.
2) The environmental load prediction algorithm provided by the invention can provide input for the digital twin model, further predict the detailed physical information of the structure by the digital twin model, realize the pre-control of the structure response, solve the time lag problem of the traditional control system and avoid the instantaneous extreme response.
3) The invention obtains the acceleration information and the stress information of all parts of the structure through the digital twin model, and does not need to arrange a large number of acceleration sensors and stress sensors on the structure, thereby reducing the cost of a control system on one hand and avoiding the problems that the sensors are difficult to install and easy to damage in the actual engineering on the other hand.
4) The digital twin model established by the invention can effectively simulate the control performance of the magneto-rheological sensor on the structural vibration, thereby establishing the digital mapping from the environmental load to the output restoring force of the magneto-rheological sensor.
Drawings
FIG. 1 is a schematic diagram of one embodiment of the present invention;
FIG. 2 is a schematic view of a magnetorheological damper array in accordance with an embodiment of the invention;
fig. 3 is a basic schematic diagram of the control system of the present invention.
Detailed Description
In order that those skilled in the art will better understand the technical solutions of the present invention, the following description of the preferred embodiments of the present invention is provided in conjunction with specific examples, but it should be understood that the drawings are for illustrative purposes only and should not be construed as limiting the patent; for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted. The positional relationships depicted in the drawings are for illustrative purposes only and are not to be construed as limiting the present patent.
Referring to fig. 1 to 3, the invention provides an environmental load prediction method and a vibration pre-control system for an offshore wind turbine, which includes an offshore wind turbine structure, and a magnetorheological damper array 6, a wave height measuring device 10, a flow velocity measuring device 11, a structural vibration control terminal 5, and a wind speed measuring device 4, which are respectively and fixedly connected with the wind turbine structure.
Specifically, the offshore wind turbine structure mainly comprises a blade 1, a hub 2, a nacelle 3, a tower 8, a floating foundation 9 and an anchoring system 12; the tower 8 adopts a sectional construction technology and is formed by connecting a plurality of sections of steel cylinder structures through 4 flanges 7.
Furthermore, a magnetorheological damper array 6 is correspondingly installed on the flange 7 and used for adjusting vibration control force and controlling vibration reduction. Each magnetorheological damper array 6 is composed of 4 magnetorheological dampers 602, and respectively corresponds to four directions of the south, the east, the west and the north, so as to control the vibration in each direction. A steel frame 601 is arranged in the middle of the 4 magnetorheological dampers 602 and connected with the magnetorheological dampers, and the steel frame 601 is welded on the flange.
The front end of the hub 2 is provided with a wind speed measuring device 4 for measuring wind speed.
Specifically, wave height measuring devices 10 and flow velocity measuring devices 11 are arranged around the floating foundation 9, and respectively correspond to four directions of south, east and north (the wave height measuring device on the back is not shown in the figure) and are used for measuring the wave heights of the four directions of south, east and north; and the wave height measuring device 10 and the flow velocity measuring device 11 are arranged near a floating foundation of the offshore wind turbine structure at the water line level, or can be arranged on the sea surface near the machine position by using buoys.
Specifically, the structural vibration control terminal 5 is installed in the cabin 3, data measured by the wave height measuring device 10, the flow velocity measuring device 11 and the wind velocity measuring device 4 are transmitted to the structural vibration control terminal 5 in a wireless mode, and the control damping force required to be provided by the magnetorheological damper 602 is obtained through system calculation, so that the purpose of vibration control is achieved.
Further referring to fig. 3, the present invention provides a method for predicting an environmental load of an offshore wind turbine, comprising the following steps:
s1, preprocessing the monitored real-time wave height data, wind speed data and flow speed data, and removing environmental noise;
s2, performing Empirical Mode Decomposition (EMD) on the wave height data, the wind speed data and the flow speed data after the noise is removed to obtain Intrinsic Mode Functions (IMF) of the monitoring data;
by means of the monitoring data processing system, denoising and filtering processing are carried out on the real-time data measured by the wave height measuring device 10, the wind speed measuring device 4 and the flow velocity measuring device 11, EMD decomposition is carried out on the real-time data, and IMF signals of the wave height data, the wind speed data and the flow velocity data are obtained.
S3, constructing an Autoregressive moving average model (ARMA model) based on the eigenmode function, and solving a model coefficient;
s4, obtaining IMF prediction time course data based on an ARMA model;
through an environmental load prediction system, IMF signals are received, an ARMA model is established, time sequence prediction is carried out on the IMF, linear summation is carried out on the predicted IMF signals, short-time prediction on complex broadband signals such as wave height data, wind speed data, flow speed data and the like is achieved, and the obtained predicted environmental load time sequence is used as the input of a digital twin model.
S5, restoring the IMF prediction time course data to obtain wave height data, wind speed data and flow speed data;
by means of the digital twin model system, the simulation process of multiple physical quantities, multiple scales and multiple probabilities is integrated, and the simulation process is a mirror image of the physical entity of the offshore wind turbine generator in a virtual space. The digital twin model system can digitally define and model the characteristics, functions and performance of the offshore wind turbine generator system structure, and further can obtain the output restoring force of the magnetorheological damper array through input wave height prediction data, wind speed prediction data and flow speed prediction data, so that structural vibration control is realized.
According to the description and the drawings of the invention, a person skilled in the art can easily make or use the method for predicting the environmental load and the vibration pre-control system of the offshore wind turbine and can generate the positive effects recorded in the invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications and equivalent variations of the above embodiments according to the technical spirit of the present invention are included in the scope of the present invention.
Claims (10)
1. The method for predicting the environmental load of the offshore wind turbine is characterized by comprising the following steps:
s1, preprocessing the monitored real-time wave height data, wind speed data and ocean current flow speed data by adopting a monitoring data processing system to remove environmental noise;
s2, performing Empirical Mode Decomposition (EMD) on the wave height data, the wind speed data and the flow speed data after the noise is removed to obtain Intrinsic Mode Functions (IMF) of the monitoring data;
s3, constructing an autoregressive moving average model (ARMA) based on an Intrinsic Mode Function (IMF) by adopting an environmental load prediction system, and solving a model coefficient;
s4, obtaining IMF prediction time course data based on an ARMA model;
s5, adding the IMF prediction time course data by adopting a digital twin model system to obtain the prediction time course data of wave height data, wind speed data and flow speed data;
the environmental load prediction system constructs an ARMA model based on the IMF obtained by the monitoring data processing system, and predicts environmental load data; the environment load prediction algorithm provides input for the digital twin model, and then the acceleration information and the stress information of the structure are predicted by the digital twin model, so that the pre-control of the structure response is realized; a plurality of magneto-rheological damper arrays (6) are arranged in the height direction of the tower (8) at intervals, and the digital twin model system receives predicted environmental load data output by the environmental load prediction system to obtain the control restoring force required by the magneto-rheological damper arrays.
2. The vibration pre-control system of the offshore wind turbine generator system to which the environmental load prediction method according to claim 1 is applied is characterized in that: the device comprises an offshore wind turbine structure, and a wind speed measuring device (4), a magnetorheological damper array (6), a wave height measuring device (10), a flow velocity measuring device (11) and a structural vibration control terminal (5) which are fixedly connected with the wind turbine structure respectively; the wind speed measuring device (4), the magnetorheological damper array (6), the wave height measuring device (10) and the flow velocity measuring device (11) are in wireless connection with the structural vibration control terminal (5) to realize information data transmission; the structure vibration control terminal (5) responds to real-time data measured by the wind speed measuring device (4), the wave height measuring device (10) and the flow velocity measuring device (11) to give control force of the magnetorheological damper array (6), and accordingly multi-frequency vibration control of the offshore motor set structure is achieved.
3. The vibration pre-control system for the offshore wind turbine according to claim 2, wherein: the offshore wind turbine generator system mainly comprises blades (1), a hub (2), a cabin (3), a tower (8), a floating foundation (9) and an anchoring system (12), wherein the tower (8) is formed by connecting a plurality of sections of steel cylindrical structures through flanges (7).
4. The vibration pre-control system for the offshore wind turbine according to claim 3, wherein: a plurality of magnetorheological damper arrays (6) are arranged on the tower (8) at intervals in the height direction, and each magnetorheological damper array (6) is fixedly connected with a flange (7) through a steel frame (601).
5. The vibration pre-control system for the offshore wind turbine according to claim 4, wherein: each magnetorheological damper array (6) is composed of a plurality of magnetorheological dampers (602) arranged on the periphery of a steel frame (601).
6. The vibration pre-control system for the offshore wind turbine according to claim 3, wherein: a plurality of wave height measuring devices (10) and flow velocity measuring devices (11) are installed around the floating foundation (9), and the wave height measuring devices (10) and the flow velocity measuring devices (11) are arranged near the floating foundation of the offshore wind turbine structure located on the water plane.
7. The vibration pre-control system for the offshore wind turbine according to claim 2, wherein: the structural vibration control terminal (5) is arranged in the engine room (3) and is used for receiving and processing monitored real-time data; a monitoring data processing system, an environmental load prediction system and a digital twin model system are integrated in the structural vibration control terminal (5).
8. The vibration pre-control system for the offshore wind turbine according to claim 7, wherein: the monitoring data processing system carries out denoising, filtering and EMD decomposition on the monitoring data.
9. The vibration pre-control system for the offshore wind turbine according to claim 7, wherein: and the environment load prediction system constructs an ARMA model based on the IMF obtained by the monitoring data processing system, and predicts the environment load data.
10. The vibration pre-control system for the offshore wind turbine according to claim 7, wherein: and the digital twin model system receives the predicted environmental load data output by the environmental load prediction system to obtain the control restoring force required by the magnetorheological damper array.
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| CN113212678B (en) * | 2021-05-24 | 2022-11-29 | 中国电建集团华东勘测设计研究院有限公司 | Active-passive combined control system of floating offshore wind power structure and implementation method |
| CN113530765A (en) * | 2021-08-11 | 2021-10-22 | 华能烟台新能源有限公司 | System and method for monitoring influence of earthquake on vibration of offshore wind turbine |
| CN113933016B (en) * | 2021-08-26 | 2023-01-06 | 华北电力大学 | Wind tunnel test device and method for simulating floating type wind turbine generator movement response |
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| CN115387967B (en) * | 2022-06-29 | 2024-08-23 | 华电电力科学研究院有限公司 | Arrangement method of tower stress detection points and stress analysis method |
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101901209A (en) * | 2010-02-04 | 2010-12-01 | 福州大学 | Structural response analysis method based on improved EMD (Empirical Mode Decomposition) and ARMA (Autoregressive Moving-Average) model |
| CN102004831A (en) * | 2010-11-17 | 2011-04-06 | 昆明理工大学 | Method for establishing time series model for predicting multi-phase mixed effect and based on empirical mode decomposition (EMD) |
| CN102568205A (en) * | 2012-01-10 | 2012-07-11 | 吉林大学 | Traffic parameter short-time prediction method based on empirical mode decomposition and classification combination prediction in abnormal state |
| CN102937668A (en) * | 2012-11-08 | 2013-02-20 | 电子科技大学 | Electric system low-frequency oscillation detection method |
| CN204553090U (en) * | 2015-01-04 | 2015-08-12 | 江苏海事职业技术学院 | Intelligent vibration damping moldeed depth sea floating blower fan |
| CN106126896A (en) * | 2016-06-20 | 2016-11-16 | 中国地质大学（武汉） | The mixed model wind speed forecasting method learnt based on empirical mode decomposition and the degree of depth and system |
| CN107201991A (en) * | 2017-06-05 | 2017-09-26 | 上海交通大学 | A kind of new marine windmill floating platform |
| CN110318945A (en) * | 2019-07-16 | 2019-10-11 | 大连理工大学 | A kind of magnetorheological intelligent controller reducing blower fan pylon vibration |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102588211B (en) * | 2012-02-29 | 2013-08-14 | 沈阳华人风电科技有限公司 | Model prediction control method and model prediction control system for all working conditions of wind generating set |
| CN102891770A (en) * | 2012-10-22 | 2013-01-23 | 哈尔滨工业大学深圳研究生院 | Method for predicating long correlation sequences by utilizing short correlation model |
| CN104019000B (en) * | 2014-06-23 | 2017-03-15 | 宁夏银星能源股份有限公司 | The loading spectrum of wind power generating set is determined and perspective maintenance system |
| CN204212172U (en) * | 2014-09-12 | 2015-03-18 | 中国电建集团华东勘测设计研究院有限公司 | Single pile adds quant formula supporting pile offshore wind turbine foundation structure |
| CN104533724B (en) * | 2015-01-04 | 2017-05-17 | 江苏海事职业技术学院 | Intelligent vibration damping type deep sea floating fan |
| CN105930938B (en) * | 2016-05-10 | 2019-06-21 | 重庆大学 | Floatation type blower off-load method based on MR damper semi-active structural co ntrol |
| CN106593777B (en) * | 2017-01-20 | 2018-11-16 | 江苏德克玛电气有限公司 | A kind of wind power generation system |
| CN109798920A (en) * | 2019-02-18 | 2019-05-24 | 兰州交通大学 | Based on the MEMS gyro stochastic error modeling filtering method for improving EMD |
| CN111241673B (en) * | 2020-01-07 | 2021-10-22 | 北京航空航天大学 | Health state prediction method for industrial equipment in noisy environment |
-
2020
- 2020-09-29 CN CN202011047507.4A patent/CN112253406B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101901209A (en) * | 2010-02-04 | 2010-12-01 | 福州大学 | Structural response analysis method based on improved EMD (Empirical Mode Decomposition) and ARMA (Autoregressive Moving-Average) model |
| CN102004831A (en) * | 2010-11-17 | 2011-04-06 | 昆明理工大学 | Method for establishing time series model for predicting multi-phase mixed effect and based on empirical mode decomposition (EMD) |
| CN102568205A (en) * | 2012-01-10 | 2012-07-11 | 吉林大学 | Traffic parameter short-time prediction method based on empirical mode decomposition and classification combination prediction in abnormal state |
| CN102937668A (en) * | 2012-11-08 | 2013-02-20 | 电子科技大学 | Electric system low-frequency oscillation detection method |
| CN204553090U (en) * | 2015-01-04 | 2015-08-12 | 江苏海事职业技术学院 | Intelligent vibration damping moldeed depth sea floating blower fan |
| CN106126896A (en) * | 2016-06-20 | 2016-11-16 | 中国地质大学（武汉） | The mixed model wind speed forecasting method learnt based on empirical mode decomposition and the degree of depth and system |
| CN107201991A (en) * | 2017-06-05 | 2017-09-26 | 上海交通大学 | A kind of new marine windmill floating platform |
| CN110318945A (en) * | 2019-07-16 | 2019-10-11 | 大连理工大学 | A kind of magnetorheological intelligent controller reducing blower fan pylon vibration |
Non-Patent Citations (3)
| Title |
|---|
| 基于EMD-LSTM的光伏发电预测模型;朱玥等;《电力工程技术》;20200328(第02期);全文 * |
| 基于EMD-SVR的光纤陀螺随机误差预测;陈强强等;《导航定位与授时》;20200115(第01期);全文 * |
| 大型风力发电机组故障诊断综述;曾军等;《电网技术》;20171211(第03期);全文 * |
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