CN112329220A - Visual dynamics simulation method for fan blade structure - Google Patents
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- 238000004088 simulation Methods 0.000 title claims abstract description 44
- 238000000034 method Methods 0.000 title claims abstract description 33
- 230000000007 visual effect Effects 0.000 title claims abstract description 29
- 230000004044 response Effects 0.000 claims abstract description 51
- 230000005284 excitation Effects 0.000 claims abstract description 37
- 238000002474 experimental method Methods 0.000 claims abstract description 13
- 230000003993 interaction Effects 0.000 claims abstract description 7
- 238000012544 monitoring process Methods 0.000 claims abstract description 7
- 238000006073 displacement reaction Methods 0.000 claims description 8
- 238000005259 measurement Methods 0.000 claims description 8
- 230000003321 amplification Effects 0.000 claims description 6
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 6
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- 238000005316 response function Methods 0.000 claims description 3
- 108700039855 mouse a Proteins 0.000 claims description 2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/12—Geometric CAD characterised by design entry means specially adapted for CAD, e.g. graphical user interfaces [GUI] specially adapted for CAD
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/20—Configuration CAD, e.g. designing by assembling or positioning modules selected from libraries of predesigned modules
Abstract
The invention discloses a visual dynamics simulation method of a fan blade structure, which relates to the technical field of dynamics simulation and comprises the following steps: establishing a visual vibration monitoring experiment system of a fan blade structure; applying an exciting force to a fan blade structure in a video in a man-machine interaction mode; comprehensively generating dynamic response of a new blade structure under excitation; generating simulation animation of dynamic response prediction of the blade structure in real time; response prediction accuracy is calculated. By implementing the method, the dynamic response of the blade structure under different excitation forces can be simulated, other complex geometric modeling and finite element modeling are not needed, a complex model correction process is also not needed, the simulation calculation speed is high, and the efficiency is high.
Description
Technical Field
The invention relates to the technical field of dynamics simulation, in particular to a visual dynamics simulation method for a fan blade structure.
Background
The blade structure of the wind driven generator is an important component of a fan, and the research on the dynamic characteristics of the blade structure is important for the working performance of the fan. The dynamic simulation of the fan blade structure is an important means for identifying structural modal parameters and analyzing the dynamic response of the structure, is beneficial to analyzing the dynamic response characteristics of the blade structure under the action of external load, and has important significance for the safe service, stability and reliability of the wind driven generator.
The traditional dynamic simulation method is generally based on finite element software, and a complex geometric model and a finite element model of a blade structure are established to analyze the dynamic characteristics of the blade. The method needs professional personnel, is complex to operate and difficult to model, and the established finite element model is very different from the result of an actual experiment, so that a complex correction process is needed to obtain an available finite element model. In addition, the finite element analysis method requires long modeling and simulation calculation time, and the kinetic analysis period is long and the efficiency is low.
The vibration measurement based on vision is an important method for monitoring the dynamic response of the fan blade structure and evaluating the health condition of the structure. A camera is adopted to shoot a structural vibration video, and structural vibration information and structural modal parameters can be extracted from video data. However, most of the existing visual vibration analysis methods for the blade structure can only monitor and identify modal parameters from existing video data, and cannot simulate and predict the dynamic response of the fan blade under a new excitation force. In fact, video monitoring data of blade structure vibration, which contains abundant static and dynamic structural information, can be used to analyze and predict the dynamic response of the blade under new excitation force, and thus, a vision-based wind turbine blade structure dynamic simulation method needs to be developed.
Therefore, technical personnel in the field are dedicated to developing a visual dynamics simulation method of a fan blade structure, the problems that when finite element analysis is adopted in the prior art, professionals are required to perform complex and tedious geometric modeling and physical modeling on a target structure, time consumption is long, efficiency is low, and a complex model correction process is required to meet experimental measurement results are solved, and the visual dynamics simulation is adopted, so that the method is convenient, fast, efficient and high in calculation speed, and the period of dynamics analysis is greatly shortened.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the technical problems to be solved by the present invention are: the traditional dynamics simulation method aims at solving the problems of complex geometric modeling and finite element modeling of the fan blade structure, low simulation efficiency and complex correction caused by inconsistency of a finite element model and an experimental result.
In order to achieve the purpose, the invention provides a visual dynamics simulation method of a fan blade structure, which comprises the following steps:
and 5, calculating response prediction accuracy.
Further, the step 1 further comprises: obtaining video data of a blade structure from an experiment, identifying full-field modal parameters, and obtaining a modal shape phi and a natural frequency omegadAnd modal damping ξ.
Further, the applying of the excitation force in the human-computer interaction manner in step 2 specifically includes: manually moving the mouse to any point (x, y) on the leaf structure, pressing the left button of the mouse and simultaneously moving the mouse a certain distance in a certain direction, and then at a new position (x)e,ye) The left mouse button is released.
Further, the action point of the applied exciting force is (x, y), the applied direction of the exciting force is the moving direction of the mouse, and the magnitude of the exciting force is proportional to the moving distance of the mouse.
Further, the excitation force is:
Fu(x,y,t)＝λ(xe-x)F(t)
Fv(x,y,t)＝λ(ye-y)F(t)
wherein, Fu(x, y, t) and Fv(x, y, t) is the component of the applied excitation force F (x, y, t) in the horizontal and vertical directions; λ is a scale factor; f (t) isA function of the time variation, representing the type of excitation.
Further, the f (t) may be a pulsed excitation, a random excitation, or a swept excitation.
Further, the dynamic response expression in step 3 is:
wherein U (x, y, t) is the dynamic response of the blade structure, and comprises a horizontal displacement response U (x, y, t) and a vertical displacement response v (x, y, t); q is the truncated modal order; phi is aiIs the ith order mode shape; q. q.si(t) is the ith order modal coordinate; q. q.si(t) is:
wherein, (.)TAnd
respectively representing transpose and convolution operations; h isi(t) is a unit impulse response function, and the expression is as follows:
wherein m isiAnd ωniRespectively, the ith order modal mass and the undamped natural frequency.
Further, in step 4, each frame of the simulation animation is subjected to motion amplification, and the animation frame at time t is:
I(x+αu,y+αv,t)＝I(x,y,0)
where α is a motion amplification factor.
Further, the step 5 further comprises: and calculating the cross-correlation coefficient of the simulation result and the experimental result by adopting a cross-correlation method.
Further, the step 5 further comprises: the response actual measurement result obtained by the experiment is G (x, y, t), the visual simulation response prediction result is U (x, y, t), and the specific expression of the cross-correlation coefficient is as follows:
wherein r (G, U) is the cross-correlation coefficient of the two, Cov (G, U) is the covariance of G and U, and Var [ G ] and Var [ U ] are the variance of G and U.
Compared with the prior art, the invention at least has the following beneficial technical effects:
1. the invention establishes a visual dynamics simulation model of the fan blade structure, can simulate the dynamics response of the blade structure under different excitation forces, and intuitively, conveniently and efficiently realizes the dynamics analysis of the fan blade structure;
2. establishing a dynamic visual simulation model of the fan blade structure based on the video data without other complicated geometric modeling and finite element modeling and a complicated model correction process;
3. the visual dynamics simulation calculation speed is high, the efficiency is high, and the effect of real-time simulation calculation can be achieved;
4. and the correlation degree of the simulation result and the experimental actual measurement result is accurately evaluated by adopting the cross-correlation coefficient, so that the response prediction accuracy of the visual simulation can be evaluated.
The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.
Drawings
FIG. 1 is a schematic view of a visual vibration monitoring experiment system of a fan blade structure of the present invention;
FIG. 2 is a first eight-order modal shape of a fan blade structure extracted from video data according to the present invention;
FIG. 3 is a schematic diagram of the excitation point A and vibration pick-up point B of the present invention;
FIG. 4 is a waveform of the response prediction at vibration pick-up point B of the present invention;
FIG. 5 is a diagram illustrating the accuracy of response prediction evaluation according to the present invention.
Detailed Description
The technical contents of the preferred embodiments of the present invention will be more clearly and easily understood by referring to the drawings attached to the specification. The present invention may be embodied in many different forms of embodiments and the scope of the invention is not limited to the embodiments set forth herein.
Step 1: as shown in fig. 1, firstly, a visual vibration monitoring experiment system of a fan blade structure is set up, video data of the blade structure is obtained from the experiment, full-field modal parameters are identified, and modal shape phi and natural frequency omega are obtaineddAnd modal damping ξ. This is the data preparation phase of the present invention. The extraction of modality parameters from video data is shown in fig. 2.
Step 2: and (4) applying exciting force by the visual dynamics simulation of the fan blade structure.
As shown in fig. 3, excitation force is applied to a fan blade structure in a video in a man-machine interaction manner. And applying an excitation force in a man-machine interaction mode, namely manually moving the mouse to any point (x, y) on the blade structure, pressing a left mouse button and simultaneously moving the mouse for a certain distance in a certain direction, then releasing the left mouse button at a new position (xe, ye), moving the mouse to a point A on the fan blade structure in the process, pressing the left mouse button and moving the left mouse button for a certain distance in the horizontal direction, and releasing the mouse to finish the application of the excitation force. And selecting the point B as a vibration pickup point for comparing the experimental result with the visual simulation result. The applied direction of the exciting force is the moving direction of the mouse, the size is in direct proportion to the moving distance, the exciting force is divided into the horizontal direction and the vertical direction, and then the specific expression of the exciting force is as follows:
Fu(x,y,t)＝λ(xe-x)F(t)
Fv(x,y,t)＝λ(ye-y)F(t)
wherein, Fu(x, y, t) and Fv(x, y, t) is the component of the applied excitation force F (x, y, t) in the horizontal and vertical directions; λ is a scale factor to control the magnitude of the force; f (t) is timeAnd the function of the chemical equation represents the excitation type, such as pulse excitation, random excitation, sweep excitation and the like.
And step 3: and (5) a fan blade structure visual dynamics simulation result. The response prediction waveform at point B is shown in fig. 4. And comprehensively generating the dynamic response of the blade structure under the new excitation. The dynamic response expression is:
wherein U (x, y, t) is the dynamic response of the blade structure, and comprises a horizontal displacement response U (x, y, t) and a vertical displacement response v (x, y, t); q is the truncated modal order; phi is aiIs the ith order mode shape; q. q.siAnd (t) is the ith order modal coordinate. q. q.si(t) can be expressed as:
wherein, (.)TAnd
respectively representing transpose and convolution operations; h isi(t) is a unit impulse response function, and the expression is as follows:
wherein m isiAnd ωniRespectively, the ith order modal mass and the undamped natural frequency.
After excitation is applied, the dynamic response of the fan blade structure under the excitation force can be automatically simulated and predicted, and the response result can be displayed in a video in real time. From B point vibration pickup, the consistency of the experimental result and the simulation result of blade response prediction is verified, and the fact that the response prediction waveforms of the two are very close to each other and the cross correlation coefficient is as high as 0.85 can be found.
And 4, step 4: and generating simulation animation of dynamic response prediction of the blade structure in real time. In the steps, displacement responses u (x, y, t) and v (x, y, t) of each pixel point in the horizontal and vertical directions after excitation is applied are obtained, so that simulation animation of dynamic response of the blade structure can be generated in real time, and each frame of the animation is subjected to motion amplification processing to enable tiny motion to be visualized. The animation frame at time t may be expressed as:
I(x+αu,y+αv,t)＝I(x,y,0)
where α is a motion amplification factor. For amplifying micro-movements (u, v) in horizontal and vertical directions. Note that the step is mainly assignment operation, the calculation amount is small and far lower than that of the traditional complex gold tower algorithm, and therefore the real-time animation simulation can be realized.
And 5: and evaluating the accuracy of the simulation response prediction of the visual dynamics of the fan blade structure. And calculating the cross-correlation coefficient of the simulation result and the experimental result by adopting a cross-correlation method, wherein the response actual measurement result obtained by the experiment is G (x, y, t), the visual simulation response prediction result is U (x, y, t), and the specific expression of the cross-correlation coefficient is as follows:
wherein r (G, U) is the cross-correlation coefficient of the two, Cov (G, U) is the covariance of G and U, and Var [ G ] and Var [ U ] are the variance of G and U.
And (3) calculating the cross-correlation coefficient between the experimental measurement result of all the pixel points on the fan blade structure and the visual simulation result, as shown in fig. 5, finding that the correlation of the response prediction result is only weak at the root position of the blade because the root displacement is almost 0. In addition, the experimental actual measurement and the visual simulation response prediction results have good correlation at most positions, which shows that the response prediction accuracy of the visual dynamics simulation of the fan blade structure is high.
According to the visual dynamics simulation method for the fan blade structure, the camera is used for shooting the structural vibration video, modal parameters can be extracted from video data, the dynamic response of the blade structure under different excitation forces is simulated, other complex geometric modeling and finite element modeling are not needed, a complex model correction process is not needed, the simulation calculation speed is high, and the efficiency is high.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. A visual dynamics simulation method of a fan blade structure is characterized by comprising the following steps:
step 1, establishing a visual vibration monitoring experiment system of a fan blade structure;
step 2, applying an exciting force to a fan blade structure in a video in a man-machine interaction mode;
step 3, comprehensively generating a dynamic response of a new blade structure under excitation;
step 4, generating a simulation animation of dynamic response prediction of the blade structure in real time;
and 5, calculating response prediction accuracy.
2. The method of claim 1, wherein step 1 further comprises: obtaining video data of a blade structure from an experiment, identifying full-field modal parameters, and obtaining a modal shape phi and a natural frequency omegadAnd modal damping ξ.
3. The method of claim 1, wherein the applying the excitation force in a human-computer interaction manner in step 2 specifically comprises: manually moving the mouse to any point (x, y) on the leaf structure, pressing the left button of the mouse and simultaneously moving the mouse a certain distance in a certain direction, and then at a new position (x)e,ye) The left mouse button is released.
4. The method of claim 3, wherein the point of application of the excitation force is (x, y), the direction of application of the excitation force is the direction of mouse movement, and the magnitude of the excitation force is proportional to the distance of mouse movement.
5. The method of claim 4, wherein the energizing force is:
Fu(x,y,t)＝λ(xe-x)F(t)
Fv(x,y,t)＝λ(ye-y)F(t)
wherein, Fu(x, y, t) and Fv(x, y, t) is the component of the applied excitation force F (x, y, t) in the horizontal and vertical directions; λ is a scale factor; f (t) is a function of time, representing the excitation type.
6. The method of claim 5, wherein F (t) can be pulsed excitation, random excitation, or swept excitation.
7. The method of claim 1, wherein the dynamic response expression in step 3 is:
wherein U (x, y, t) is the dynamic response of the blade structure, and comprises a horizontal displacement response U (x, y, t) and a vertical displacement response v (x, y, t); q is the truncated modal order; phi is aiIs the ith order mode shape; q. q.si(t) is the ith order modal coordinate; q. q.si(t) is:
wherein, (.)TAnd
respectively representing transpose and convolution operations; h isi(t) is a unit impulse response function, and the expression is as follows:
wherein m isiAnd ωniRespectively, the ith order modal mass and the undamped natural frequency.
8. The method of claim 1, wherein in step 4, each frame of the simulation animation is subjected to motion amplification, and the animation frames at time t are:
I(x+αu,y+αv,t)＝I(x,y,0)
where α is a motion amplification factor.
9. The method of claim 1, wherein step 5 further comprises: and calculating the cross-correlation coefficient of the simulation result and the experimental result by adopting a cross-correlation method.
10. The method of claim 9, wherein step 5 further comprises: the response actual measurement result obtained by the experiment is G (x, y, t), the visual simulation response prediction result is U (x, y, t), and the specific expression of the cross-correlation coefficient is as follows:
wherein r (G, U) is the cross-correlation coefficient of the two, Cov (G, U) is the covariance of G and U, and Var [ G ] and Var [ U ] are the variance of G and U.
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