CN117269941A - Time domain wind load calculation method considering radar wind field and self-vibration - Google Patents
Time domain wind load calculation method considering radar wind field and self-vibration Download PDFInfo
- Publication number
- CN117269941A CN117269941A CN202311558721.XA CN202311558721A CN117269941A CN 117269941 A CN117269941 A CN 117269941A CN 202311558721 A CN202311558721 A CN 202311558721A CN 117269941 A CN117269941 A CN 117269941A
- Authority
- CN
- China
- Prior art keywords
- wind
- self
- wind speed
- vibration
- radar
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004364 calculation method Methods 0.000 title claims abstract description 23
- 238000000034 method Methods 0.000 claims abstract description 90
- 230000008569 process Effects 0.000 claims abstract description 39
- 238000004088 simulation Methods 0.000 claims abstract description 32
- 230000004044 response Effects 0.000 claims abstract description 30
- 230000009471 action Effects 0.000 claims abstract description 16
- 238000004458 analytical method Methods 0.000 claims abstract description 16
- 238000006073 displacement reaction Methods 0.000 claims abstract description 13
- 230000003595 spectral effect Effects 0.000 claims abstract description 13
- 238000001308 synthesis method Methods 0.000 claims abstract description 10
- 238000005316 response function Methods 0.000 claims abstract description 8
- 238000012886 linear function Methods 0.000 claims abstract description 5
- 230000003068 static effect Effects 0.000 claims description 26
- 238000001228 spectrum Methods 0.000 claims description 20
- 239000011159 matrix material Substances 0.000 claims description 19
- 230000006870 function Effects 0.000 claims description 17
- 238000013016 damping Methods 0.000 claims description 16
- 238000005314 correlation function Methods 0.000 claims description 3
- 238000000354 decomposition reaction Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 7
- 230000002035 prolonged effect Effects 0.000 abstract description 3
- 238000013461 design Methods 0.000 description 7
- 230000009467 reduction Effects 0.000 description 7
- 230000005284 excitation Effects 0.000 description 6
- 230000008859 change Effects 0.000 description 4
- 230000010349 pulsation Effects 0.000 description 4
- 238000012937 correction Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000000737 periodic effect Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 238000005452 bending Methods 0.000 description 2
- 238000005094 computer simulation Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 239000006096 absorbing agent Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012482 interaction analysis Methods 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000035939 shock Effects 0.000 description 1
- 238000010561 standard procedure Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/497—Means for monitoring or calibrating
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/495—Counter-measures or counter-counter-measures using electronic or electro-optical means
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Pure & Applied Mathematics (AREA)
- Computational Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Algebra (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Computer Networks & Wireless Communication (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Aerodynamic Tests, Hydrodynamic Tests, Wind Tunnels, And Water Tanks (AREA)
Abstract
The invention discloses a time domain wind load calculation method considering a radar wind field and self vibration, belonging to the technical field of load calculation, comprising the following steps: setting wind field entry conditions and average wind speed profiles, calculating the wind speed space correlation among a plurality of simulation points in the wind field, simulating the pulsating wind load by using a harmonic synthesis method of a multipoint random process, obtaining a wind speed time course curve of the wind field and the power spectral density of the wind field, using the power spectral density of the wind field as input, and calculating and evaluating vibration response by using a buffeting analysis method; the self-excitation force of the airborne radar is calculated by using a self-excitation force time domain model expressed by an impulse response function, and the self-excitation force is expressed as a linear function of structural vibration displacement and speed; the computer-borne radar is subjected to the action of various loads. According to the method, the self-vibration and the buffeting are considered at the same time, so that the interference is reduced or eliminated, and the precision and the accuracy of a radar system are improved; and the self-vibration and buffeting effects are controlled, the service life of the system is prolonged, and the reliability of the system is improved.
Description
Technical Field
The invention discloses a time domain wind load calculation method considering a radar wind field and self vibration, and belongs to the technical field of load calculation.
Background
In the wind field, because the unmanned aerial vehicle is light in weight and small in size and the structural characteristics of the laser radar, in the flight process, the unmanned aerial vehicle interacts with the atmospheric environment and can be influenced by air flow to generate wind vibration response (wind vibration refers to the vibration influence of the air flow in the wind field on the unmanned aerial vehicle and the laser radar, and can lead to the increase of measurement errors of the laser radar and influence the quality and accuracy of data). Such vibrations can negatively impact the performance and accuracy of the radar system. Therefore, the wind resistance of the unmanned aerial vehicle laser radar has important significance for ensuring the safe operation of the system. The existing radar vibration system mainly solves the problem of corresponding single corresponding vibration reduction and has no design of superposition vibration reduction. The existing technology can not solve the buffeting and self-vibration problems at the same time. Some of the prior art can effectively suppress the vibration, such as using a damper or shock absorber to reduce the influence of external vibration on the system, but none of these methods can solve the self-vibration problem of the system itself, so the system may still be disturbed by the self-vibration.
Disclosure of Invention
The invention aims to provide a time domain wind load calculation method considering a radar wind field and self vibration, so as to solve the problem that an airborne laser radar is easy to be interfered by vibration in the prior art.
A time domain wind load calculation method considering radar wind field and self vibration comprises the following steps:
s1, setting a wind field inlet condition and an average wind speed profile, and calculating the wind speed space correlation among a plurality of simulation points in a wind field;
s2, combining the result of the S1, simulating the pulsating wind load of the airborne radar in the matlab by using a harmonic synthesis method of a multipoint random process, obtaining a wind speed time-course curve of a wind field and the power spectral density of the wind field, using the power spectral density of the wind field as input, and calculating and evaluating vibration response by using a buffeting analysis method;
s3, calculating the self-excitation force of the airborne radar by using a self-excitation force time domain model expressed by an impulse response function, and expressing the self-excitation force as a linear function of structural vibration displacement and speed;
s4, the computer airborne radar is subjected to the action of each load.
S1 comprises the following steps:
s1.1, setting wind field inlet conditions and average wind speed profile;
setting the wind field inlet as average wind, describing an average wind speed profile through an exponential function and wind parameters at a standard height of 10 meters, and setting the inlet wind speed and the inlet turbulence intensity according to the following formula in a gradient wind height range:
；
in the method, in the process of the invention,and->Is a height +>Inlet wind speed and inlet turbulence intensity at +.>And->Wind speed and turbulence intensity at a standard height of 10 meters.
S1 comprises the following steps:
s1.2, calculating the wind speed at any height at any moment;
the wind speed at the height z at time t is:
；
in the method, in the process of the invention,for the average wind speed at height z +.>For the pulsating wind speed at time t height z, < >>Wind speed at height z at time t;
the average wind speed at altitude z is described by an exponential function:
；
in the method, in the process of the invention,、/>average wind speed and altitude at standard altitude 10 meters, +.>Is the roughness coefficient of the ground.
S1 comprises the following steps:
s1.3, calculating a fluctuating wind speed power cross spectrum matrix, and establishing a fluctuating wind speed power cross spectrum matrix of m simulation points in a wind field：
；
In the method, in the process of the invention,as a function of the cross-spectral density>Is the circular frequency;
；
in the method, in the process of the invention,the spatial correlation function of the simulated points i and j represents the spatial correlation between the time course data of the fluctuating wind speed at the two points;
；
in the middle ofAnd->Coordinate value for simulation point i, +.>And->Coordinate value of simulation point j, +.>And->Average wind speed +.A corresponding to the simulated points i, j respectively>Is->And->Corresponding exponential decay coefficients, +.>Is->And->Corresponding exponential decay coefficients.
S1 comprises the following steps:
s1.4, based on a fluctuating wind speed power cross spectrum matrix, simulating to obtain zero-mean random wind speed time interval data corresponding to a point j through the following steps：
；
In the method, in the process of the invention,for a random phase angle uniformly distributed in [0,2 pi), a random phase angle of->The power cross spectrum matrix of the fluctuating wind speed is a Georgi decomposition matrix, N is the frequency division number, < ->For index circle frequency, +.>Is at->The angle of the lower simulation point j;
；
and calculating zero-mean random wind speed time-course data of other simulation points to obtain the wind speed space correlation among a plurality of simulation points in the wind field.
S2 comprises the following steps:
the buffeting force to which the airborne radar structure is subjected is expressed as:
；
in the method, in the process of the invention,、/>、/>the vibration resistance, the vibration lift force and the vibration moment of the airborne radar are respectively +.>Is the average wind attack angle; />、/>、/>Respectively the drag, lift and lift moment coefficients; />、/>、/>Resistance, lift and lift moment coefficients versus angle of attack, respectively>Is a derivative of (2); />For average wind speed>And->Respectively horizontal and vertical pulsating wind speed, < ->For air density->Is the radar cross-sectional width.
Considering 6 pneumatic admittances for the airborne radar, namely horizontal damping admittance, horizontal mass admittance, horizontal rigidity admittance, vertical damping admittance, vertical mass admittance and vertical rigidity admittance, and the buffeting force model after pneumatic admittance correction is as follows:
；
in the method, in the process of the invention,respectively a horizontal damping admittance, a vertical damping admittance, a horizontal mass admittance, a vertical mass admittance, a horizontal stiffness admittance and a vertical stiffness admittance.
S3 comprises the following steps:
；
wherein:for self-excitation impulse response function, < >>Respectively self-exciting lift force, moment and resistance; />For the time course, ->、/>、/>Three pneumatic parameters related to the speed of the motion state, which are in particular functions of pressure, speed and flow with respect to time course.
S4 comprises the following steps:
the airborne radar is subjected to the action of various loadsExpressed as:
；
in the method, in the process of the invention,load of gravity->For static wind load->For buffeting force, < ->Is self-exciting force;
the buffeting force and the self-exciting force are obtained by combining the respective lifting force and the resistance binding force moment.
And calculating a static force three-component force coefficient, determining the magnitude of static force and the position of an acting point, and further calculating the static force load.
Compared with the prior art, the invention has the following beneficial effects: according to the method, the self-vibration and the buffeting are considered at the same time, so that the interference is reduced or eliminated, and the precision and the accuracy of a radar system are improved; and the self-vibration and buffeting effects are effectively controlled, the service life of the system is prolonged, and the reliability of the system is improved.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions in the present invention will be clearly and completely described below, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
A time domain wind load calculation method considering radar wind field and self vibration comprises the following steps:
s1, setting a wind field inlet condition and an average wind speed profile, and calculating the wind speed space correlation among a plurality of simulation points in a wind field;
s2, combining the result of the S1, simulating the pulsating wind load of the airborne radar in the matlab by using a harmonic synthesis method of a multipoint random process, obtaining a wind speed time-course curve of a wind field and the power spectral density of the wind field, using the power spectral density of the wind field as input, and calculating and evaluating vibration response by using a buffeting analysis method;
s3, calculating the self-excitation force of the airborne radar by using a self-excitation force time domain model expressed by an impulse response function, and expressing the self-excitation force as a linear function of structural vibration displacement and speed;
s4, the computer airborne radar is subjected to the action of each load.
S1 comprises the following steps:
s1.1, setting wind field inlet conditions and average wind speed profile;
setting the wind field inlet as average wind, describing an average wind speed profile through an exponential function and wind parameters at a standard height of 10 meters, and setting the inlet wind speed and the inlet turbulence intensity according to the following formula in a gradient wind height range:
；
in the method, in the process of the invention,and->Is a height +>Inlet wind speed and inlet turbulence intensity at +.>And->Wind speed and turbulence intensity at a standard height of 10 meters.
S1 comprises the following steps:
s1.2, calculating the wind speed at any height at any moment;
the wind speed at the height z at time t is:
；
in the method, in the process of the invention,for the average wind speed at height z +.>For the pulsating wind speed at time t height z, < >>Wind speed at height z at time t;
the average wind speed at altitude z is described by an exponential function:
；
in the method, in the process of the invention,、/>average wind speed and altitude at standard altitude 10 meters, +.>Is the roughness coefficient of the ground.
S1 comprises the following steps:
s1.3, calculating a fluctuating wind speed power cross spectrum matrix, and establishing a fluctuating wind speed power cross spectrum matrix of m simulation points in a wind field：
；
In the method, in the process of the invention,as a function of the cross-spectral density>Is the circular frequency;
；
in the method, in the process of the invention,the spatial correlation function of the simulated points i and j represents the spatial correlation between the time course data of the fluctuating wind speed at the two points;
；
in the middle ofAnd->Coordinate value for simulation point i, +.>And->Is a simulation pointCoordinate value of j>And->Average wind speed +.A corresponding to the simulated points i, j respectively>Is->And->Corresponding exponential decay coefficients, +.>Is->And->Corresponding exponential decay coefficients.
S1 comprises the following steps:
s1.4, based on a fluctuating wind speed power cross spectrum matrix, simulating to obtain zero-mean random wind speed time interval data corresponding to a point j through the following steps：
；
In the method, in the process of the invention,for a random phase angle uniformly distributed in [0,2 pi), a random phase angle of->The power cross spectrum matrix of the fluctuating wind speed is a Georgi decomposition matrix, N is the frequency division number, < ->For index circle frequency, +.>Is at->The angle of the lower simulation point j;
；
and calculating zero-mean random wind speed time-course data of other simulation points to obtain the wind speed space correlation among a plurality of simulation points in the wind field.
S2 comprises the following steps:
the buffeting force to which the airborne radar structure is subjected is expressed as:
；
in the method, in the process of the invention,、/>、/>the vibration resistance, the vibration lift force and the vibration moment of the airborne radar are respectively +.>Is the average wind attack angle; />、/>、/>Respectively the drag, lift and lift moment coefficients; />、/>、/>Resistance, lift and lift moment coefficients versus angle of attack, respectively>Is a derivative of (2); />For average wind speed>And->Respectively horizontal and vertical pulsating wind speed, < ->For air density->Is the radar cross-sectional width.
Considering 6 pneumatic admittances for the airborne radar, namely horizontal damping admittance, horizontal mass admittance, horizontal rigidity admittance, vertical damping admittance, vertical mass admittance and vertical rigidity admittance, and the buffeting force model after pneumatic admittance correction is as follows:
；
in the method, in the process of the invention,respectively a horizontal damping admittance, a vertical damping admittance, a horizontal mass admittance, a vertical mass admittance, a horizontal stiffness admittance and a vertical stiffness admittance.
S3 comprises the following steps:
；
wherein:for self-excitation impulse response function, < >>Respectively self-exciting lift force, moment and resistance; />For the time course, ->、/>、/>Three pneumatic parameters related to the speed of the motion state, which are in particular functions of pressure, speed and flow with respect to time course.
S4 comprises the following steps:
the airborne radar is subjected to the action of various loadsExpressed as:
；
in the method, in the process of the invention,load of gravity->For static wind load->For buffeting force, < ->Is self-exciting force;
the buffeting force and the self-exciting force are obtained by combining the respective lifting force and the resistance binding force moment.
And calculating a static force three-component force coefficient, determining the magnitude of static force and the position of an acting point, and further calculating the static force load.
The invention designs the vibration reduction structure to control by considering the vibration response of the wind field to the airborne radar and the self-vibration generated by the self-excitation vibration of the radar, thereby achieving the effects of reducing the vibration of the radar and improving the accuracy of the radar.
According to the wind field model building method, wind field simulation and vibration response analysis are combined, and a wind field model is built. The stress condition, the deformation condition and the safety performance of the structure can be evaluated through the simulation of the wind field and the response analysis of the structure. In this process, complex wind fields and structures are accurately analyzed and predicted by means of numerical calculation methods and computer simulation techniques. The unmanned aerial vehicle laser radar is used as a research object, buffeting and self-excitation response of the unmanned aerial vehicle under the action of the superimposed wind field are analyzed, the state change of the unmanned aerial vehicle is analyzed, the reason for causing vibration is researched, a novel vibration reduction structure is creatively provided, and the novelty and the effectiveness of the vibration reduction structure are verified.
Both self-vibration and buffeting can cause instability of the radar system, resulting in inaccuracy of the measurement results. By taking both self-vibration and buffeting into account, these disturbances can be reduced or eliminated, improving the accuracy and precision of the radar system. The self-vibration and buffeting can produce a certain degree of fatigue and loss to the system structure and components. The self-vibration and buffeting effects are effectively controlled, the service life of the system can be prolonged, and the reliability of the system can be improved.
Because random vibration of a wind field is a main source of vibration, the design of the wind field is carried out, average wind and pulsating wind are considered, a pulsating wind load is simulated in matlab by using a harmonic synthesis method of a multipoint random process by using a pulsating wind speed spectrum, the wind field can generate impact load on the radar, a buffeting time domain analysis method is used for corresponding to buffeting effect of the airborne radar, and a buffeting force model is established. And taking self-vibration into consideration, establishing a time-domain mathematical model of the self-excitation force, and obtaining the self-excitation force of coupling in three directions of lateral bending, vertical bending and torsion. The vibration is superimposed, and a time-domain wind load (dead wind force caused by average wind (standard method), buffeting force caused by pulsating wind and self-excitation force caused by fluid-solid coupling) is calculated as a vibration source.
Since random vibration of the wind field is a main source of vibration, the design of the wind field is first performed. Natural wind can be decomposed into average wind and pulsating wind. Average wind is expressed in terms of average velocity, which does not change over time; the mean value of the pulsating wind is zero, and the pulsation component of the pulsating wind changes with time. The corresponding natural wind action can be divided into a static wind response and a pulsating response.
The static wind response is a response under the action of average wind, and when the height is large, the static wind response can cause static wind instability of the machine body; the impulse response is a response under the action of impulse wind, and is caused by irregular wind, and the strength of the impulse load changes randomly along with time. The static wind response and the pulsation response of the body are respectively studied.
The static load generated by the average wind is called static wind load for short. The three component force coefficients are a set of dimensionless parameters describing the static wind load. In the body axis coordinate system, by using three component force coefficients, the lifting force, the resistance and the lifting moment of the structural unit extension can be expressed as:
；
in the method, in the process of the invention,is air density; />Average wind speed for incoming flows farther from the section; />For effective angle of attack, +.>Is the average wind attack angle in the structure balance state, +.>An additional attack angle (0 in a static wind state) caused by the pulsating wind; />Is the height of the radar support structure; />、/>、/>Respectively the lift force, the resistance and the torque under a body axis coordinate system; />、/>Respectively the lift, the resistance and the torque coefficient under the body axis coordinate system.
The static wind load acting on the radar main support unit length can be expressed as:
；
in the method, in the process of the invention,、/>、/>respectively, the lift force, the resistance and the torque under the wind axis coordinate system.
Because of the complexity of the natural environment, the natural wind shows strong randomness, and the statistical rule can be obtained through a mathematical statistical method. A large number of measured records of wind speed show that: wind in the atmospheric boundary layer can be divided into two parts, a long period average wind and a short period pulsating wind. Wherein the average wind is stationary and the pulsating wind reflects the turbulence characteristics of the atmospheric boundary layer.
The wind speed at the z-altitude at any t moment can be expressed as the sum of the average wind speed and the pulsating wind speed, and then the average wind and the pulsating wind suffered by the airborne radar are respectively defined and designed.
For small-sized low-altitude unmanned aerial vehicles, the height of 0-1km is a main active area of the unmanned aerial vehicle, and main flight subjects such as take-off, landing, cruising and the like are covered. Because the altitude range belongs to an atmospheric boundary layer, the influence effect of ground friction and roughness is considered, an exponential formula is often used for describing the average wind speed distribution, and the rule of the average wind speed along the altitude change can be described by an exponential function.
And (3) performing steady-state calculation, setting the wind field speed inlet condition as average wind, and determining the average wind speed profile according to the national load specification, wherein the average wind speed profile is described by an exponential model and wind parameters of standard height 10 m. And calculating the exponential profile average wind of the inlet condition according to the steady state, carrying out power spectrum based on the fluctuating wind speed, and providing improvement, adopting harmonic synthesis method to simulate and obtain each high fluctuating wind speed of the inlet boundary, and taking the combination of the average wind model as the buffeting condition of the wind field.
The method is based on Fourier series expansion, and decomposes one non-periodic signal into superposition synthesis of a plurality of periodic signals. The harmonic synthesis method is used for carrying out the pulse wind speed time course simulation.
The invention uses a harmonic synthesis method of a multipoint random process to simulate the pulsating wind load of the airborne radar in matlab based on the Davenport wind speed spectrum. The related initial parameters are (1) the basic wind speed V10 = 30m/s, the ground roughness class is class C, the air density = 1.225, the ground roughness k = 0.00464, and (2) the time and frequency parameters. Wind load arrival time t=0.1 s, total time interval tmax=180 s time stept=0.2 s, cut-off frequency +.>=8pi rad/s, the frequency range equal fraction n=500.
Combining the result of the S1, using a harmonic synthesis method of a multipoint random process to simulate the pulsating wind load of the airborne radar in matlab, obtaining a wind speed time-course curve of a wind field and the power spectral density of the wind field, using the power spectral density of the wind field as input, and calculating and evaluating the vibration response by using a buffeting analysis method;
the harmonic synthesis method is also called a spectrum representation method, and can be divided into single-point simulation and multi-point simulation according to different simulation points. Specifically, the invention inverts the power spectrum matrix of the random excitation of the pulsating wind load according to the power spectrum matrix of the random response of the pulsating wind load, which is the inverse problem of random vibration. The invention provides an inverse virtual excitation method for solving the problem, which decomposes a known or actually measured random response power spectrum matrix into a plurality of mutually incoherent virtual simple harmonic responses, and then inverts each virtual simple harmonic excitation, thereby combining the real random excitation power spectrum matrix. Thus, the inverse problem of random vibration is converted into the inverse problem of simple harmonic vibration, so that the problem which is difficult originally is simplified.
Sample function for smooth random processThe simulation can be performed as follows:
；
for amplitude +.>Angular velocity +.>Deflection angle for sample function +.>Is time.
The pulsating wind field is simulated by MATLAB, and the method comprises the following steps of:
setting simulation parameters, defining a time range and a step length, defining a peak value and an average value of wind speed, determining a characteristic period and frequency of a pulsating wind field, generating random pulsation, performing filtering treatment to simulate the pulsating wind field with specific frequency characteristics, generating pulsating wind speed time course data by combining the generated random pulsation with the set wind speed peak value and average value, calculating time course change of wind power according to the wind speed time course data and the characteristics of a structure, obtaining a frequency domain signal through Fourier transform (FFT), and constructing a spectrogram according to the amplitude and phase information of an FFT result to further solve the power spectral density. The wind field is obtained through computer simulation, a wind speed time-course curve of the wind field and the power spectral density of the wind field are obtained, the power spectral density of the wind field is used as input, and the buffeting analysis method is utilized for calculating and evaluating vibration response.
For an ideal airborne radar surface, since there are pulsating wind in both horizontal and vertical directions in the incoming flow, the pulsating wind in each direction will have an effect on drag, lift and lift. Therefore, when the unsteady characteristic of the buffeting force is considered, an aerodynamic admittance function depending on the frequency characteristic of the pulsating wind is introduced to correct the quasi-steady buffeting force model.
For the airborne radar, 6 pneumatic admittances are considered, namely horizontal damping admittance, horizontal mass admittance, horizontal rigidity admittance, vertical damping admittance, vertical mass admittance and vertical rigidity admittance. These admittances reflect the extent to which pulsating wind affects structural drag, lift and lift moment.
For turbulent flow in a high-frequency section, because of the unsteady characteristic, the buffeting force model under the quasi-steady assumption may deviate greatly from the true stress state of the structure. Therefore, during the buffeting analysis, the unsteady characteristic of the turbulent flow is also required to be considered, and corresponding correction is made so as to achieve a more accurate result. In actual buffeting analysis, the pneumatic admittance function and the value which are applicable to the unmanned airborne radar are not available at present, and the invention is safely taken as 1.
And carrying out numerical simulation on a near-ground wind field of the peripheral area of the flight line of the unmanned aerial vehicle radar by adopting CFD flow field numerical simulation, and researching the characteristics of the near-ground wind field under the condition of complex terrain.
For the wind farm calculation model, the invention takes the following assumptions:
(a) Air flow in near-ground wind farms can be considered three-dimensional incompressible flow;
(b) The size of the component is far smaller than the calculation scale of the wind field near the ground, and the influence of the structure on the wind field calculation can be ignored;
(c) Most of the selected terrains are forests and seaside shoals, and the ground roughness conditions can be regarded as consistent.
And constructing a near-ground wind field calculation domain, wherein the whole size of the radar wind field design domain is 5000m multiplied by 1600m.
Table 1 buffeting force (unit N) of airborne radar structure based on pulsating wind
。
It can be seen from table 1 that the buffeting occupancy is relatively large in the fuselage and the connection, and vibration damping can be performed at these two locations.
And researching buffeting displacement generated by radar impact of the wind field, and simulating the wind field to transversely impact the airborne radar structure in three directions of x, y and z, wherein the y direction is the downwind field direction.
Table 2 buffeting displacement (unit mm) of airborne radar structure based on pulsating wind
。
Table 2 shows that the buffeting displacement generated by the impact of the wind field on the radar is mainly concentrated on the fuselage and the connection part of the fuselage and the radar, and the fuselage is greatly displaced because of the influence of the unmanned aerial vehicle propeller. The buffeting is represented by the small difference of the displacement generated by the upper part and the lower part of the radar. Attention is paid to the vibration reduction problem of the connection part of the fuselage and the radar.
When the wind field impacts on the radar structure, an acting force is exerted on the structure, and the structure generates certain vibration response. If the natural frequency of the structure is very close to the external excitation frequency, the excitation will be amplified, resulting in an increasing vibration, resulting in self-excitation forces causing self-vibration. The self-excitation force of the airborne radar is calculated by a self-excitation force time domain model expressed by an impulse response function, and the self-excitation force is expressed as a linear function of structural vibration displacement and speed.
According to the actual situation, the lift force and the torque of the self-exciting force can be calculated, and in the wind field, the vibration displacement generated by the self-exciting force is smaller than the impact of the wind field, as shown in table 3.
TABLE 3 self-excitation force lift and torque
。
In the unmanned airborne radar wind vibration engineering field, wind load acting on each part of the structure is treated into three parts: static wind force caused by average wind, buffeting force caused by pulsating wind and self-excitation force caused by fluid-solid coupling. The static force load can determine the magnitude and the action point position of the static force according to the static force three-component force coefficient obtained by the segment model test and the numerical calculation. The buffeting force is a periodic aerodynamic force caused by the pulsating wind of the wind farm. The magnitude and frequency characteristics of the buffeting force can be determined by superposition of wind field models, numerical calculation and other methods. Self-exciting forces are self-exciting vibratory forces due to the interaction of wind fields with the structure. The evaluation and processing can be performed by structural vibration theory and wind-vibration-structural interaction analysis.
In the invention, nonlinear time-course analysis (nonlinear time-course analysis is a calculation method combining numerical techniques such as a finite element method and the like and is used for researching dynamic response of a structure under the action of nonlinear force) is adopted to describe actual behaviors of the structure under the action of external loads such as time-domain wind load and the like. This analysis method takes into account the nonlinear characteristics of the structural material and the connector, providing a more accurate prediction of response.
In the calculation process, a finite element model of the airborne radar structure is firstly established, the structure is divided into discrete units, and nonlinear behaviors of materials and nonlinear characteristics of connectors are defined. The invention selects a direct integration method suitable for general nonlinearity, and carries out time-course analysis of dynamic response on the structure according to the nonlinearity characteristic of external wind load. In each time step, the nonlinear response of the structure and the interaction of the nonlinear wind field are considered by solving a nonlinear equation set to solve the dynamic response of the structure.
By nonlinear time-course analysis, detailed dynamic response information of the structure under the action of time-domain wind load, including displacement of various parts of force and the like, can be obtained. Such information may be used to evaluate the performance of the structure under the influence of the wind field, determine the stability and reliability of the structure, and guide the design optimization and improvement of the vibration damping structure. The calculation results in the transverse displacement of the airborne radar under the condition of considering various vibration, as shown in table 4, and is used for guiding the subsequent vibration reduction structure design.
Table 4 airborne radar time domain wind load lateral displacement (unit mm)
。
The above embodiments are only for illustrating the technical aspects of the present invention, not for limiting the same, and although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may be modified or some or all of the technical features may be replaced with other technical solutions, which do not depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A time domain wind load calculation method taking into account radar wind field and self-vibration, comprising:
s1, setting a wind field inlet condition and an average wind speed profile, and calculating the wind speed space correlation among a plurality of simulation points in a wind field;
s2, combining the result of the S1, simulating the pulsating wind load of the airborne radar in the matlab by using a harmonic synthesis method of a multipoint random process, obtaining a wind speed time-course curve of a wind field and the power spectral density of the wind field, using the power spectral density of the wind field as input, and calculating and evaluating vibration response by using a buffeting analysis method;
s3, calculating the self-excitation force of the airborne radar by using a self-excitation force time domain model expressed by an impulse response function, and expressing the self-excitation force as a linear function of structural vibration displacement and speed;
s4, the computer airborne radar is subjected to the action of each load.
2. The method for calculating the time-domain wind load taking into account radar wind field and self-vibration according to claim 1, wherein S1 comprises:
s1.1, setting wind field inlet conditions and average wind speed profile;
setting the wind field inlet as average wind, describing an average wind speed profile through an exponential function and wind parameters at a standard height of 10 meters, and setting the inlet wind speed and the inlet turbulence intensity according to the following formula in a gradient wind height range:
；
in the method, in the process of the invention,and->Is a height +>Inlet wind speed and inlet turbulence intensity at +.>And->Wind speed and turbulence intensity at a standard height of 10 meters.
3. A method of time domain wind load calculation taking into account radar wind fields and self-vibrations as defined in claim 2, wherein S1 comprises:
s1.2, calculating the wind speed at any height at any moment;
the wind speed at the height z at time t is:
；
in the method, in the process of the invention,for the average wind speed at height z +.>For the pulsating wind speed at time t height z, < >>Wind speed at height z at time t;
the average wind speed at altitude z is described by an exponential function:
；
in the method, in the process of the invention,、/>average wind speed and altitude at standard altitude 10 meters, +.>Is the roughness coefficient of the ground.
4. A time-domain wind load calculation method taking into account radar wind fields and self-vibrations according to claim 3, wherein S1 comprises:
s1.3, calculating a fluctuating wind speed power cross spectrum matrix, and establishing a fluctuating wind speed power cross spectrum matrix of m simulation points in a wind field：
；
In the method, in the process of the invention,as a function of the cross-spectral density>Is the circular frequency;
；
in the method, in the process of the invention,the spatial correlation function of the simulated points i and j represents the spatial correlation between the time course data of the fluctuating wind speed at the two points;
；
in the middle ofAnd->Coordinate value for simulation point i, +.>And->Coordinate value of simulation point j, +.>And->Average wind speed +.A corresponding to the simulated points i, j respectively>Is->And->Corresponding exponential decay coefficients, +.>Is->And->Corresponding exponential decay coefficients.
5. The method for calculating the time-domain wind load taking into account radar wind field and self-vibration according to claim 4, wherein S1 comprises:
s1.4, based on a fluctuating wind speed power cross spectrum matrix, simulating to obtain zero-mean random wind speed time interval data corresponding to a point j through the following steps：
；
In the method, in the process of the invention,for a random phase angle uniformly distributed in [0,2 pi), a random phase angle of->The power cross spectrum matrix of the fluctuating wind speed is a Georgi decomposition matrix, N is the frequency division number, < ->For index circle frequency, +.>Is at->The angle of the lower simulation point j;
；
and calculating zero-mean random wind speed time-course data of other simulation points to obtain the wind speed space correlation among a plurality of simulation points in the wind field.
6. The method for calculating the time-domain wind load taking into account radar wind field and self-vibration according to claim 5, wherein S2 comprises:
the buffeting force to which the airborne radar structure is subjected is expressed as:
；
in the method, in the process of the invention,、/>、/>the vibration resistance, the vibration lift force and the vibration moment of the airborne radar are respectively +.>Is the average wind attack angle; />、/>、/>Respectively the drag, lift and lift moment coefficients; />、/>、/>Resistance, lift and lift moment coefficients versus angle of attack, respectively>Is a derivative of (2); />For average wind speed>And->Respectively horizontal and vertical pulsating wind speed, < ->In order to achieve an air density of the air,is the radar cross-sectional width.
7. The method for calculating the time domain wind load considering the radar wind field and the self vibration according to claim 6, wherein for the airborne radar, 6 pneumatic admittances are considered, namely horizontal damping admittance, horizontal mass admittance, horizontal stiffness admittance, vertical damping admittance, vertical mass admittance and vertical stiffness admittance, and a buffeting force model corrected by the pneumatic admittance is as follows:
；
in the method, in the process of the invention,respectively a horizontal damping admittance, a vertical damping admittance, a horizontal mass admittance, a vertical mass admittance, a horizontal stiffness admittance and a vertical stiffness admittance.
8. The method for calculating the time-domain wind load taking into account radar wind field and self-vibration according to claim 7, wherein S3 comprises:
；
wherein:for self-excitation impulse response function, < >>Respectively self-exciting lift force, moment and resistance; />For the time course, ->、/>、/>Three pneumatic parameters related to the speed of the motion state, which are in particular functions of pressure, speed and flow with respect to time course.
9. The method for calculating the time-domain wind load taking into account radar wind field and self-vibration according to claim 8, wherein S4 comprises:
the airborne radar is subjected to the action of various loadsExpressed as:
；
in the method, in the process of the invention,load of gravity->For static wind load->For buffeting force, < ->Is self-exciting force;
the buffeting force and the self-exciting force are obtained by combining the respective lifting force and the resistance binding force moment.
10. The method for calculating the time-domain wind load taking radar wind field and self-vibration into consideration according to claim 9, wherein the static three-component force coefficient is calculated, the magnitude of the static wind force and the position of the action point are determined, and then the static wind load is calculated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311558721.XA CN117269941A (en) | 2023-11-22 | 2023-11-22 | Time domain wind load calculation method considering radar wind field and self-vibration |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311558721.XA CN117269941A (en) | 2023-11-22 | 2023-11-22 | Time domain wind load calculation method considering radar wind field and self-vibration |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117269941A true CN117269941A (en) | 2023-12-22 |
Family
ID=89206727
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311558721.XA Pending CN117269941A (en) | 2023-11-22 | 2023-11-22 | Time domain wind load calculation method considering radar wind field and self-vibration |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117269941A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118468674A (en) * | 2024-07-10 | 2024-08-09 | 聊城大学 | Structural acceleration response calculation method under coupling of wind and induced load |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101221553A (en) * | 2008-01-04 | 2008-07-16 | 东南大学 | Buffeting response analysis time-domain method for large span bridge under inclined wind action |
| CN111898304A (en) * | 2020-08-06 | 2020-11-06 | 西南交通大学 | Method and system for analyzing coupling vibration of flow bridge of windmill |
| CN115544830A (en) * | 2022-09-27 | 2022-12-30 | 上海电机学院 | Method for analyzing power response of wind turbine under random wind load |
| CN116522600A (en) * | 2023-04-04 | 2023-08-01 | 西华大学 | Complex wind field wind speed simulation method, device, equipment and medium |
-
2023
- 2023-11-22 CN CN202311558721.XA patent/CN117269941A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101221553A (en) * | 2008-01-04 | 2008-07-16 | 东南大学 | Buffeting response analysis time-domain method for large span bridge under inclined wind action |
| CN111898304A (en) * | 2020-08-06 | 2020-11-06 | 西南交通大学 | Method and system for analyzing coupling vibration of flow bridge of windmill |
| CN115544830A (en) * | 2022-09-27 | 2022-12-30 | 上海电机学院 | Method for analyzing power response of wind turbine under random wind load |
| CN116522600A (en) * | 2023-04-04 | 2023-08-01 | 西华大学 | Complex wind field wind speed simulation method, device, equipment and medium |
Non-Patent Citations (5)
| Title |
|---|
| 乔山林: "风载荷对雷达天线座的影响与评估", 现代雷达, vol. 39, no. 10, pages 0 - 1 * |
| 刘岩;钱宏亮;范峰;: "超大口径天线结构的风振响应", 振动.测试与诊断, no. 03, 15 June 2016 (2016-06-15) * |
| 张增太: "风载荷在雷达天线结构设计中的考虑", 雷达科学与技术, no. 04, 31 December 1997 (1997-12-31) * |
| 金雷: "关于雷达天线风荷载的几个问题", 电子机械工程, no. 01, 25 February 2003 (2003-02-25) * |
| 韩万水: "大跨度斜拉桥抖振时域分析理论实例验证及影响因素分析", 土木工程学报, vol. 39, no. 6, pages 1 - 2 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118468674A (en) * | 2024-07-10 | 2024-08-09 | 聊城大学 | Structural acceleration response calculation method under coupling of wind and induced load |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Neumann et al. | Gust response: Simulation of an aeroelastic experiment by a fluid–structure interaction method | |
| CN105241630A (en) | Pulse type rod strain balance applied to shock tunnel dynamometric test | |
| Spalart et al. | Sensitivity of landing-gear noise predictions by large-eddy simulation to numerics and resolution | |
| Zhang et al. | A flutter prediction method with low cost and low risk from test data | |
| CN117269941A (en) | Time domain wind load calculation method considering radar wind field and self-vibration | |
| CN115879331B (en) | Spring-damping vibration reduction structure parameter optimization analysis method based on Kelvin model | |
| JP2016103101A (en) | Aseismic analysis apparatus, method and program | |
| CN110096779B (en) | Servo mechanism dynamic characteristic analysis method | |
| Raveh et al. | Wind-tunnel study of the ARMA flutter prediction method | |
| Wang et al. | Modified Tikhonov regularization in model updating for damage identification | |
| Li et al. | A new aerodynamic identification technology for short-time hypersonic wind tunnels while considering inertial force interference | |
| Yang et al. | Dynamic Force Reconstruction for Structural Support Platforms Based on the Combined Strategy of Experiment and Simulation | |
| CN115033977B (en) | Ground actually-measured pulsating pressure parameter identification method based on neural network technology | |
| Arunajatesan et al. | Validation of an FSI modeling framework for internal captive carriage applications | |
| Brehm et al. | Open rotor computational aeroacoustic analysis with an immersed boundary method | |
| Shkarayev et al. | Kinematics and inertial effects in locust flapping wings | |
| Vatsa et al. | Aeroacoustic simulations of a nose landing gear using FUN3D on Pointwise unstructured grids | |
| Cooper et al. | Wind tunnel testing of a high aspect ratio wing model | |
| Kawashima et al. | Measurements of Unsteady Force Response on Airfoils with Arbitrarily Shaped Thickness due to Incident Large-Scale Turbulence | |
| CN115962963A (en) | Method and device for testing dynamic characteristics of air suspension system | |
| Zhu | Reconstruction of distributed wind load on structures from response samples | |
| CN106126915B (en) | Prediction method for vibration signal stable value of wind tunnel balance | |
| Wang et al. | Using structural intensity approach to characterize vibro-acoustic behavior of the cylindrical shell structure | |
| Joels et al. | Dynamic Shape Sensing of the A3TB Wind Tunnel Model Using Fiber Optics Strain Data and the Kalman State Estimator | |
| Maruyama et al. | Effects of heaving and pitching motions on underside aerodynamics of a sedan vehicle |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20231222 |
|
| RJ01 | Rejection of invention patent application after publication |