CN117404261A - Marine wind power tower barrel modal identification system and method based on vision and vibration perception - Google Patents
Marine wind power tower barrel modal identification system and method based on vision and vibration perception Download PDFInfo
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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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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract
The invention provides a system and a method for identifying a mode of a marine wind power tower barrel based on vision and vibration perception, belonging to the technical field of marine wind power monitoring, wherein the system comprises: the high-definition camera, vibration data acquisition device and data analysis system, data analysis system includes fan impeller rotational speed identification module, cabin yaw position identification module and fan vibration response collection module, fan impeller rotational speed identification module includes video processing module, conversion module and calculation module. According to the invention, only one high-definition camera is needed to be added at the bottom end of the wind power tower or on the outer platform (on the water), so that the wind power tower is low in cost, simple to operate and accurate in analysis, and integrated monitoring of the rotation speed of the impeller, yaw of the engine room and vibration of the tower can be realized.
Description
Technical Field
The invention belongs to the technical field of offshore wind power monitoring, and particularly relates to an offshore wind power tower modal identification system and method based on vision and vibration perception.
Background
The tower section of thick bamboo part of aerogenerator plays the effect of supporting wind turbine generator system and absorption wind turbine generator system vibration energy. During use of wind turbines, wind turbine towers are often exposed to extreme wind conditions, and large deflection deformations and repeated stress cycles can result in damage to the tower. As a support member for the assembly, its damage may lead to catastrophic failure of the structure.
By measuring the dynamic response of the tower, vibration response data of the tower can be obtained, and further structural frequency, damping ratio and modal shape of the tower can be extracted from the vibration response data, and the parameters can be used for damage detection and structural identification of the fan tower. However, on the one hand, the conventional modal identification technique cannot be directly applied to modal identification of an offshore wind tower, for the following reasons: yaw and rotation of the wind turbine are critical to modal identification of wind power. The cabin yaw enables the cabin coordinate system to be coupled with the sensor coordinate system, vibration (such as acceleration) information measured by the sensor is not real vibration information of the fan in the front-back direction and the left-right direction, and the mode identified by the information is coupling in two directions instead of independent modes; the impeller rotates to enable a great amount of harmonic components to be fused in the acceleration response of the tower, so that the real mode of the structure is covered. On the other hand, while the SCADA system of the nacelle records yaw, rotation information, the SCADA system typically has a sampling period of 10 minutes during which the wind turbine may undergo numerous large yaw or rotational speed changes that cannot be used for analysis of vibration data (the sampling period is typically 0.02 seconds or less). Meanwhile, SCADA data is generally mastered in the hands of fan manufacturers, vibration data is mastered by monitoring companies, a unified vibration monitoring system is not formed, and a gap exists between data interactions.
The invention with publication number CN112326987A provides a non-contact impeller rotating speed monitoring method for an offshore wind turbine based on underwater acoustic signals, which uses a hydrophone to collect underwater noise in the operation period of the offshore wind turbine near the wind turbine in real time, extracts line spectrum frequency of the underwater noise in the operation period by using a stochastic resonance method, and then uses the frequency to counter the impeller rotating speed of the offshore wind turbine. The defects of the method are as follows: the method comprises the following steps of (1) monitoring underwater by adopting an instrument, and having difficult operation; (2) Because of wave and water flow operation, noise in the underwater environment is serious, the tower is high, and after vibration caused by rotation of the impeller is transmitted to the water through the tower, signal attenuation is serious; (3) The method can only test the rotating speed of the impeller, and can not obtain the yaw information of the engine room.
The invention with publication number of CN110159494A provides an independent module for measuring and protecting the rotating speed of a wind power fan, and the independent module uses a state identification unit and a gyroscope to identify the rotating speed of an impeller. The technical scheme is a monitoring mode based on a mechanical principle, and a sensor is required to be installed on an impeller rotating bearing. The module is a sub-module of the fan SCADA system, needs to be integrated into the SCADA system, is installed inside the fan cabin along with the whole system, and has high performance requirements on the sensor. And as mentioned above, the SCADA system and the vibration monitoring system installed on the tower are mutually independent, the data interactivity and the synchronism are poor, and meanwhile, the comparison technology cannot identify the yaw information of the engine room at the same time.
Disclosure of Invention
Aiming at the problem that the integrated accurate monitoring of vibration signals, cabin yaw and impeller rotation speed information cannot be realized in the prior art, the invention provides a marine wind power tower modal identification system based on vision and vibration sensing, which comprises the following components: the high-definition camera is used for continuously shooting the fan impeller and the engine room; the vibration data acquisition device is used for acquiring the vibration of the fan; the data analysis system comprises a fan impeller rotating speed identification module, a cabin yaw position identification module and a fan vibration response acquisition module, wherein the fan impeller rotating speed identification module comprises a video processing module, a conversion module and a calculation module, and the video processing module is used for processing data information of the high-definition camera and fitting a track of the high-definition camera by adopting an ellipse; the conversion module converts the elliptic track into a perfect circle to obtain a slope curve with a plurality of numerical abrupt points formed by wave troughs and wave peaks; the calculation module obtains the average rotating speed of the impeller through the number of peak points and the number of frames.
Further, the vibration data acquisition device comprises a vibration data acquisition instrument and at least two double-shaft vibration sensors, wherein each sensor and the high-definition camera are installed on the same vertical line on the surface of the tower.
Further, the nacelle yaw position identification module is used for identifying an included angle between the elliptical short axis and the central axis of the video picture and is used as a nacelle yaw angle.
Further, the fan vibration response acquisition module comprises a coordinate transformation module, a harmonic extraction module and a vibration response output module, wherein the coordinate transformation module transforms signals acquired by the vibration sensor to a cabin coordinate system, the harmonic extraction module obtains impeller cycle domain frequency according to average rotating speed and extracts harmonic components of corresponding frequency conversion, and the vibration response output module outputs tower vibration response signals under natural load of the tower.
The invention further provides a marine wind power tower modal identification method based on vision and vibration perception, which comprises fan impeller rotating speed identification, cabin yaw position identification and fan vibration response acquisition, and is characterized in that the fan impeller rotating speed identification comprises the following steps: a1, continuously shooting videos of a fan impeller and a cabin through a high-definition camera to obtain the outer contour of the blade, and determining the blade tip position;
a2, obtaining a motion trail of the blade tip through ellipse fitting;
a3, projecting the elliptical track to obtain a perfect circular track;
a4, connecting the circle center of the perfect circle with each perfect circle track point into a straight line to obtain radian corresponding to the slope of the straight lineToFrame number->Is a transverse axis and radian->For the vertical axis, a slope curve is plotted, trapping +.>Peak point of radian, number of peak points is recorded +.>The difference between the last peak point frame number and the first peak point frame number is recorded as +.>；
A5, calculating the average rotating speed of the impeller。
Further, the nacelle yaw position identification includes: in the step A2, the included angle between the minor axis of the ellipse and the central axis of the video picture is identified as the yaw angle of the nacelle。
Further, the fan vibration response acquisition includes:
b1, transforming the signals acquired by the vibration sensor into a cabin coordinate system, namely、，/>Signals in two orthogonal directions in a plane, which are acquired by the vibration sensor, respectively;
b2 average rotation speed obtained according to A5Calculating the frequency of the periodic domain corresponding to 1 time, 3 times and 6 times of rotation frequency of the impeller, and further calculating the corresponding Labernoulli matrix +.>、/>、/>Projecting the original signal to a Labernoulli matrix, extracting harmonic components corresponding to 1 time, 3 times and 6 times of frequency conversion>，/>Wherein->；
B3, through，/>Removing 1 times, 3 times and 6 times harmonic components to obtain tower vibration response signals +.>、/>。
Further, the method further comprises the following steps: from signals by random subspace method、/>And identifying modal parameters of the wind power tower, wherein the modal parameters comprise natural frequency, modal shape and damping ratio.
Compared with the prior art, the invention has the following advantages and positive effects:
(1) According to the marine wind power tower modal identification system provided by the invention, only one high-definition camera is needed to be added to the bottom end or the outer platform of the wind power tower, so that synchronous monitoring of the rotating speed of a fan impeller and yaw of a cabin is realized, and the defect that the existing underwater acoustic signal detection technology and gyroscope technology only can identify the rotating speed of the impeller is overcome;
(2) According to the invention, only the high-definition camera is required to be installed on water, and special equipment is not required to be installed in an underwater or SCADA system of a fan cabin, so that the invention has the advantages of low cost and simplicity in operation;
(3) Different from the acoustic signal detection technology, the invention is used for identifying the rotating speed of the fan impeller and the yaw of the engine room based on the computer vision technology, is not interfered by the underwater environment, and has high identification accuracy. Meanwhile, the yaw position of the engine room and the rotating speed identification process of the fan impeller are simple and easy to implement, automation can be realized, the efficiency of offshore monitoring is greatly improved, and the problem of short offshore monitoring construction window period is solved;
(4) The impeller rotating speed and cabin yaw recognition method based on computer vision can be conveniently integrated into a power monitoring system, realizes the integration and real-time sensing of tower vibration, impeller rotating speed and cabin yaw, overcomes the defect that the sampling rate of a fan SCADA system is too low to be used for power analysis, realizes the decoupling of tower power monitoring data from a sensor coordinate system to a cabin coordinate system, effectively removes harmonic component interference, and greatly improves the accuracy of modal recognition.
Drawings
FIG. 1 is a schematic diagram of a simulated offshore wind power structure;
in the figure: 1-1, a tower barrel; 1-2, an outer platform; 1-3, a high-definition camera;
FIG. 2 is a fan, blade profile and tip trajectory for a high definition camera view;
in the figure: 2-1, blade tips; 2-2, blade profile; 2-3, blade tip track; 2-4, a cabin;
FIG. 3 is a fitted tip ellipse trajectory;
in the figure: 3-1, long axis; 3-2, short axis; 3-3, center E;3-4, an elliptic orbit; 3-5, central axis;
FIG. 4 is a trace point and ellipse circle center connection;
FIG. 5 is a graph of radians versus frame number corresponding to an elliptical trajectory;
FIG. 6 is a graph of radian versus frame number (non-camera view) for a real tip trajectory;
FIG. 7 is a transformed tip circle trajectory;
FIG. 8 is a graph of frame number versus radian for a transformed perfect circle;
fig. 9 is a frequency stabilization diagram corresponding to the random subspace method.
Detailed Description
The invention is described in further detail below with reference to the drawings and detailed description.
First embodiment, referring to FIG. 1, the present embodiment proposes a system for identifying a mode of an offshore wind turbine tower 1-1 based on computer vision, comprisingThe system comprises a double-shaft vibration sensor, 1 vibration data acquisition instrument, 1 high-definition camera 1-3, 1 computer and a data analysis system configured in the computer. The double-shaft vibration sensor and the vibration data acquisition instrument form a vibration data acquisition device which is used for acquiring the vibration of the fan; the high-definition camera 1-3 is used for identifying the rotating speed of the fan impeller and the yaw position of the engine room 2-4; each vibration sensor is uniformly connected to a vibration data acquisition instrument to acquire vibration response of the tower 1-1. The high-definition camera 1-3 and the data acquisition instrument are connected to a computer in a unified way, and the mode identification of the tower 1-1 is realized in the data analysis system.
The data analysis system comprises a fan impeller rotating speed identification module, a cabin yaw position identification module and a fan vibration response acquisition module, wherein the fan impeller rotating speed identification module comprises a video processing module, a conversion module and a calculation module, the video processing module is used for processing data information of the high-definition camera, and an ellipse is adopted to fit the track of the high-definition camera; the conversion module converts the elliptic orbit into a perfect circle to obtain a slope curve with a plurality of numerical abrupt points formed by wave troughs and wave peaks; the calculation module obtains the average rotating speed of the impeller through the number of peak points and the number of frames.
The nacelle yaw position identification module is used for identifying an included angle between the elliptical short axis and the central axis of the video picture as a nacelle yaw angle. The fan vibration response acquisition module comprises a coordinate transformation module, a harmonic extraction module and a vibration response output module, wherein the coordinate transformation module transforms signals acquired by the vibration sensor into a cabin coordinate system, the harmonic extraction module obtains the periodic domain frequency of the impeller according to the average rotating speed and extracts harmonic components of corresponding rotating frequency, and the vibration response output module outputs tower vibration response signals under the natural load of the tower.
The marine wind power tower modal identification system provided by the invention has the advantages that only one high-definition camera is needed to be added at the bottom end of the wind power tower or on an outer platform (on water), the cost is low, the operation is simple, the analysis is accurate, and the integrated monitoring of the impeller rotating speed and the cabin yaw can be realized.
In a second embodiment, the present embodiment proposes a method for identifying a mode of an offshore wind turbine tower based on computer vision, including: fan impeller rotation speed identification, cabin yaw position identification and fan vibration response acquisition.
1. The fan impeller rotating speed and the cabin yaw position are identified as follows:
s101, fixing a high-definition camera on a certain position of the surface of a tower or an outer platform, and simultaneously adjusting the visual angle of the high-definition camera from bottom to top to enable the central axis of the tower to coincide with the left and right central lines of video pictures of the high-definition camera, wherein the top end of the tower is just located at the central point of the video picturesAnd simultaneously, the focal length of the high-definition camera is adjusted, so that the video picture of the high-definition camera can just accommodate the plane of the fan impeller.
S102, estimating the rotating speed of the fanAnd calculates the rotation period to +.>。
S103, carrying out continuous video shooting on a fan impeller and a cabin through a high-definition camera, wherein each second is a time periodAnd extracting the frames frame by frame from the video through a data analysis system. In->In the frame picture, capturing one contour line containing the most pixels as the outer contour of the blade, and selecting +.>Furthest pixel->As the tip position of the blade, the sitting mark is +.>。
S104, rotating the periodAll tip positions in->Writing tip trajectory data setsAnd performing ellipse fitting on all data points in the data set to obtain the motion trail of the blade tip. Wherein the coordinates of the ellipse center E are +.>The long and short axes are divided into->、/>The included angle between the elliptic minor axis and the central axis of the video picture is +.>，/>The included angle between the high-definition camera and the axis of the engine room is the same.
S105, calculating a projection matrixWherein->And (3) withIs->Cosine, sine values of (c). Projecting all the tip elliptic orbit data points according to a projection matrix to obtain right circular orbit points +.>Coordinates->I.e. +.>Projecting the elliptical center E track according to a projection matrix to obtain a perfect circular track and a coordinate +.>I.e. +.>。
S106, centering the circle centerAnd every right circular locus point->Connected into a straight line, and calculates the radian corresponding to the slope of the straight line. In number of frames->Is a transverse axis and radian->And drawing a slope curve for the vertical axis, wherein a plurality of numerical abrupt points formed by trough-wave crest exist on the curve, and each abrupt point represents one blade to sweep through the high-definition camera once. Catch->Peak point of radian, number of peak points is recorded +.>The difference between the last peak point frame number and the first peak point frame number is recorded as +.>。
S107, calculating the average rotation speed of the impeller。
2. The fan vibration response acquisition is carried out according to the following process:
s201, willThe double-shaft vibration sensors are arranged at the designated positions on the inner wall of the tower barrel and form a straight line with the high-definition camera from top to bottom, so that the yaw position of the cabin relative to the vibration sensors is +.>. At sampling frequency +.>Vibration acquisition is performed, and signals acquired by a vibration sensor are +.>Conversion to cabin seatingUnder the standard, i.e.)>、。
S202, average rotation speed obtained according to S107Calculating the frequency of a periodic domain corresponding to 1 time, 3 times and 6 times of rotation frequency of the impeller，/>，/>Further calculate the corresponding Labernoulli matrix +.>、/>、. Projecting the original signal to a Labernoulli matrix, and extracting harmonic components corresponding to 1 time, 3 times and 6 times of frequency conversion>，Wherein->。
S203, through，/>Remove 1 timeHarmonic components of 3 times and 6 times are used for obtaining tower vibration response signals of the tower under natural loads such as wind, wave and the like>、/>. From signal by random subspace method>、/>And identifying modal parameters of the wind power tower, including natural frequency, modal shape and damping ratio.
3. The simulation application is for example as follows:
FIG. 1 is a simulated offshore wind power generation state, the first-order design frequency of the structure is between 0.29 and 0.31 Hz, the rotating speed is the rated rotating speed, namely 12 revolutions per second (impeller rotating period is 5 seconds), and the yaw angle of the engine room is 30 degrees. In implementation, firstly, a high-definition camera 1-3 is installed at the joint of a tower 1-1 and an outer platform 1-2, the visual angle is determined to be right upper lower upper, the camera position and focal length are adjusted, so that the central axis 3-5 of the tower 1-1 coincides with the left and right central lines of the video pictures of the high-definition camera 1-3, the top end of the tower 1-1 is just located at the central point A of the video pictures, meanwhile, the focal length of the high-definition camera 1-3 is adjusted, the video pictures of the high-definition camera 1-3 can just accommodate the plane of a fan impeller, and the adjusted visual angle of the camera is shown in fig. 2. In the implementation process of the invention, the shooting frame rate of the camera is controlled to be 30 frames per second.
Next, firstly, the blade profile 2-2 closest to the high-definition camera 1-3 is extracted, and further, the point farthest from the point a in the profile is extracted as the blade tip 2-1. The tip 2-1 position of each frame is marked in fig. 2, and the tip track 2-3 can be obtained. From fig. 2, it is found that, although the actual locus of the blade tip 2-1 is a perfect circle, the blade tip locus 2-3 is elliptical in view of the high definition camera 1-3. Therefore, the ellipse is adopted to fit the track to obtain the ellipse length, the ellipse short axis 3-2, the ellipse center point E and the ellipse dip angle29.4 ° (i.e., the angle of the elliptical short axis 3-2 with respect to the central axis 3-5 of the video frame). From fig. 3 it is found that the elliptical short axis 3-2 is exactly parallel or coincident with the axis of the fan nacelle 2-4, so that the yaw angle of the nacelle 2-4 relative to the high definition camera 1-3 is exactly elliptical inclination +.>. It follows that the yaw angle estimated using this scheme is extremely close to the true yaw angle of 30 °.
A coordinate system XEY is established with the center E of the ellipse as the origin of coordinates, as shown in fig. 4. Simultaneously, two special points B1 and B2 on the elliptic track 3-4 are selected and respectively connected with the point E to form a straight line. B1 and B2 are the points closest to the Y axis among all the points 2-3 of the tip locus, and according to mathematical knowledge, when the two points are close enough to the Y axis, the slope of the EB1 line approaches negative infinity (corresponding to radian-1.5 or so), and the slope of the EB2 line approaches positive infinity (corresponding to radian+1.5 or so). Then the slope of the line jumps from-1.5 to +1.5 once every time the blade sweeps across the one and two quadrant boundaries (Y axis).
Fig. 5 shows a graph of the linear radian versus the number of video frames for a rotation period, and it can be seen that exactly three jumps occur for a rotation period, i.e. three leaves sweep across the one and two quadrant boundaries. The time of sweep of a blade can thus be obtained, and the impeller speed can then be calculated.
The inventors found that there are still two significant problems with identifying rotational speed in the manner described above. First: to improve the monitoring and analysis efficiency, the peak point (trip point) needs to be automatically identified by a computer to determine the rotation period, which requires that the waveform of the radian-frame curve is irregular. However, on the curve of radian-frame number corresponding to the elliptical track, the maximum and minimum values are always changed, and errors may occur when a computer is used for automatically picking up the peak value. Second, with the spacing of the two blades, the average rotational speed swept by a single blade can be calculated, but the estimate is inaccurate and the real-time rotational speed cannot be obtained.
After further analysis it was found that: in fig. 5, the horizontal axis is the number of frames and the vertical axis is the radian, and then the slope of the radian-frame curve is actually the angular velocity. Although the actual fan rotates at a constant speed, the angular speed is constant, and due to the optical principle, the speed of the fan becomes negligence in the view angle of the camera. As shown in fig. 4, the rotational speed is fastest near the minor axis of the ellipse, the trace points are very sparse, and the rotational speed is slowest near the major axis, and the trace points are very dense. This results in a situation: the track of the former blade captured by the high-definition camera may be the point B2, the latter blade may be the point B3, and the slope difference between them is very large, so that the peak value and the valley value are negligent. Meanwhile, since B2 and B3 are not coincident, the two jump points do not completely correspond to 1/3 period, so that the calculated average rotating speed is inaccurate. In addition, since the rotation speed is not constant in the camera view angle (corresponding to fig. 5, the slope of the curve is not constant, but is large near the short axis 2 and small near the long axis in real time), the real-time rotation speed cannot be calculated by the slope of the curve.
The actual blade tip track is a perfect circle, when the impeller rotates at a constant speed, track points are uniformly distributed on the circle, if the corresponding radian-frame number curve is irregular, the maximum and minimum values are respectively near +1.5 and-1.5 radians, and the radian curve between two jump points is a straight line (the slope is constant), as shown in fig. 6. According to fig. 6, the trip point can be easily picked up by a computer and the average or real-time rotational speed calculated.
To obtain the effect diagram shown in fig. 6, the present invention transforms the elliptical trajectory into a perfect circle. Assuming that the ellipse length and the minor axis length are b and a, respectively, then the projection matrix is transformed from ellipse to perfect circleWherein->And->Is an ellipse inclination +>Cosine, sine values of (2), in the matrix +.>、/>The two terms have a proportionality coefficient->The stretching device is used for stretching the video picture to enable the ellipse to be a perfect circle, as shown in fig. 3; the other items are to make the picture translate and rotate around the center of the ellipse to prevent the perfect circle from being moved out of the picture after transformation. Connecting the center of the perfect circle with the locus point of the perfect circle to form a plurality of straight lines, wherein typical straight lines are shown as a straight line CD1 and a straight line CD2 in FIG. 7. Obviously, compared with the two points B1 and B2 of FIG. 4, the points D1 and D2 are closer to the Y axis, the corresponding straight line slope is more approximate to minus infinity and plus infinity, and the radian value is more approximate to minus 1.5 and plus 1.5. And in this area, the points are uniformly and densely distributed, so that the calculated peak and valley point sizes of the curve of radian-frame number are approximately consistent (as shown in fig. 8), and the curve is extremely easy to automatically capture. In fig. 7, the track points are distributed more uniformly along the full circle, and the corresponding rotation speed is approximately constant, as in fig. 8, the slope of the curve between the two peak points is approximately a straight line. Thus, the actual rotational speed thereof can be estimated. In this example, the average rotational speed of the fan impeller calculated by the present invention was 12.0 revolutions per second, which is completely consistent with the actual value.
Meanwhile, 4 acceleration sensors are arranged on the fan from top to bottom, and acceleration information of four positions of the tower is acquired. Decoupling the acceleration of the yaw angle by adopting the estimated yaw angle; meanwhile, 1-time, 3-time and 6-time harmonic components are removed according to the estimated frequency conversion, and finally, a random subspace method is adopted for mode identification, so that a stable diagram is obtained, three rows of stable points can be clearly obtained from the stable diagram, and the three-order mode of the corresponding structure is obtained. Wherein the first order frequency 0.2947 hz meets the design value.
The embodiments of the present invention described above do not limit the scope of the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention as set forth in the appended claims.
Claims (8)
1. An offshore wind power tower modal identification system based on vision and vibration perception, comprising:
the high-definition camera is used for continuously shooting the fan impeller and the engine room;
the vibration data acquisition device is used for acquiring the vibration of the fan;
the data analysis system comprises a fan impeller rotating speed identification module, a cabin yaw position identification module and a fan vibration response acquisition module, wherein the fan impeller rotating speed identification module comprises a video processing module, a conversion module and a calculation module, and the video processing module is used for processing data information of the high-definition camera and fitting a track of the high-definition camera by adopting an ellipse; the conversion module converts the elliptic track into a perfect circle to obtain a slope curve with a plurality of numerical abrupt points formed by wave troughs and wave peaks; the calculation module obtains the average rotating speed of the impeller through the number of peak points and the number of frames.
2. The marine wind power tower modal identification system based on vision and vibration sensing according to claim 1, wherein the vibration data acquisition device comprises a vibration data acquisition instrument and at least two double-shaft vibration sensors, and each sensor and the high-definition camera are installed on the same vertical line on the surface of the tower.
3. The marine wind tower modal identification system based on visual and vibration sensing according to claim 1, wherein the nacelle yaw position identification module is configured to identify an angle between a minor axis of an ellipse and a central axis of a video frame as a nacelle yaw angle.
4. The marine wind power tower modal identification system based on vision and vibration perception according to claim 1, wherein the fan vibration response acquisition module comprises a coordinate transformation module, a harmonic extraction module and a vibration response output module, the coordinate transformation module transforms signals acquired by a vibration sensor into a cabin coordinate system, the harmonic extraction module obtains impeller cycle domain frequency according to average rotation speed and extracts harmonic components of corresponding rotation frequency, and the vibration response output module outputs tower vibration response signals under natural load of the tower.
5. The visual and vibration perception-based offshore wind turbine tower modal identification method of claim 1, comprising fan impeller speed identification, nacelle yaw position identification and fan vibration response acquisition, wherein the fan impeller speed identification comprises:
a1, continuously shooting videos of a fan impeller and a cabin through a high-definition camera to obtain the outer contour of the blade, and determining the blade tip position;
a2, obtaining a motion trail of the blade tip through ellipse fitting;
a3, projecting the elliptical track to obtain a perfect circular track;
a4, connecting the circle center of the perfect circle with each perfect circle track point into a straight line to obtain radian corresponding to the slope of the straight lineIn number of frames->Is a transverse axis and radian->For the vertical axis, a slope curve is plotted, trapping +.>Peak point of radian, number of peak points is recorded +.>The difference between the last peak point frame number and the first peak point frame number is recorded as +.>；
A5, calculatingAverage rotation speed of impeller。
6. The method for identifying a mode of a marine wind power tower based on vision and vibration perception of claim 5, wherein the identifying a yaw position of the nacelle comprises: in the step A2, the included angle between the minor axis of the ellipse and the central axis of the video picture is identified as the yaw angle of the nacelle。
7. The method for identifying the mode of the offshore wind turbine tower based on vision and vibration perception according to claim 6, wherein the fan vibration response acquisition comprises the following steps: b1, transforming the signals acquired by the vibration sensor into a cabin coordinate system, namely、/>，/>Signals in two orthogonal directions in a plane, which are acquired by the vibration sensor, respectively; b2, average rotation speed according to A5->Calculating the frequency of the periodic domain corresponding to 1 time, 3 times and 6 times of rotation frequency of the impeller, and further calculating the corresponding Labernoulli matrix +.>、/>、/>Projecting the original signal to a Labernoulli matrix, extracting harmonic components corresponding to 1 time, 3 times and 6 times of frequency conversion>，/>Wherein->；
B3, through，/>Removing 1 times, 3 times and 6 times harmonic components to obtain tower vibration response signals +.>、/>。
8. The method for identifying the mode of the offshore wind turbine tower based on vision and vibration perception according to claim 7, further comprising: from signals by random subspace method、/>And identifying modal parameters of the wind power tower, wherein the modal parameters comprise natural frequency, modal shape and damping ratio.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103411659A (en) * | 2013-08-12 | 2013-11-27 | 国电联合动力技术有限公司 | Wind driven generator blade and method and system for monitoring tower barrel states |
| EP3002455A1 (en) * | 2014-10-02 | 2016-04-06 | RWE Innogy GmbH | Method and device for determining the operating parameters of a wind power plant |
| 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 |
| CN208651052U (en) * | 2018-05-06 | 2019-03-26 | 新疆维吾尔自治区风能研究所 | Wind turbines In-service testing device |
| CN109869286A (en) * | 2019-02-12 | 2019-06-11 | 苏州热工研究院有限公司 | Vibration of wind generating set state monitoring method |
| CN111379670A (en) * | 2018-12-27 | 2020-07-07 | 新疆金风科技股份有限公司 | Method, device and system for measuring rotating speed of wind generating set and storage medium |
| US20200263666A1 (en) * | 2015-12-04 | 2020-08-20 | Envision Energy (Denmark) Aps | A Wind Turbine and a Method of Operating a Wind Turbine for Reducing Edgewise Vibrations |
| CN113836762A (en) * | 2021-08-25 | 2021-12-24 | 中国大唐集团新能源科学技术研究院有限公司 | Wind turbine and wind power plant digital mirror image simulation display system |
| CN114810508A (en) * | 2022-04-12 | 2022-07-29 | 华能国际电力股份有限公司河北清洁能源分公司 | Image processing-based method and system for measuring rotating speed of fan blade of wind driven generator |
| CN116091957A (en) * | 2022-11-15 | 2023-05-09 | 上海能源科技发展有限公司 | Vertical axis small wind turbine rotating speed prediction method and system |
| US20230196612A1 (en) * | 2020-08-20 | 2023-06-22 | Top Seven Gmbh & Co. Kg | Method and system for object detection |
| CN117052606A (en) * | 2023-08-30 | 2023-11-14 | 国能投(河南)清洁能源有限责任公司 | Wind turbine generator system state monitoring system and monitoring method |
-
2023
- 2023-12-15 CN CN202311722589.1A patent/CN117404261B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103411659A (en) * | 2013-08-12 | 2013-11-27 | 国电联合动力技术有限公司 | Wind driven generator blade and method and system for monitoring tower barrel states |
| EP3002455A1 (en) * | 2014-10-02 | 2016-04-06 | RWE Innogy GmbH | Method and device for determining the operating parameters of a wind power plant |
| US20200263666A1 (en) * | 2015-12-04 | 2020-08-20 | Envision Energy (Denmark) Aps | A Wind Turbine and a Method of Operating a Wind Turbine for Reducing Edgewise Vibrations |
| 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 |
| CN208651052U (en) * | 2018-05-06 | 2019-03-26 | 新疆维吾尔自治区风能研究所 | Wind turbines In-service testing device |
| CN111379670A (en) * | 2018-12-27 | 2020-07-07 | 新疆金风科技股份有限公司 | Method, device and system for measuring rotating speed of wind generating set and storage medium |
| CN109869286A (en) * | 2019-02-12 | 2019-06-11 | 苏州热工研究院有限公司 | Vibration of wind generating set state monitoring method |
| US20230196612A1 (en) * | 2020-08-20 | 2023-06-22 | Top Seven Gmbh & Co. Kg | Method and system for object detection |
| CN113836762A (en) * | 2021-08-25 | 2021-12-24 | 中国大唐集团新能源科学技术研究院有限公司 | Wind turbine and wind power plant digital mirror image simulation display system |
| CN114810508A (en) * | 2022-04-12 | 2022-07-29 | 华能国际电力股份有限公司河北清洁能源分公司 | Image processing-based method and system for measuring rotating speed of fan blade of wind driven generator |
| CN116091957A (en) * | 2022-11-15 | 2023-05-09 | 上海能源科技发展有限公司 | Vertical axis small wind turbine rotating speed prediction method and system |
| CN117052606A (en) * | 2023-08-30 | 2023-11-14 | 国能投(河南)清洁能源有限责任公司 | Wind turbine generator system state monitoring system and monitoring method |
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