CN103364170A - Ground simulation predicting method and system for aeroelasticity stability - Google Patents

Ground simulation predicting method and system for aeroelasticity stability Download PDF

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CN103364170A
CN103364170A CN2013102827226A CN201310282722A CN103364170A CN 103364170 A CN103364170 A CN 103364170A CN 2013102827226 A CN2013102827226 A CN 2013102827226A CN 201310282722 A CN201310282722 A CN 201310282722A CN 103364170 A CN103364170 A CN 103364170A
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吴志刚
马成骥
张仁嘉
杨超
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Beihang University
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Abstract

The invention provides a ground simulation predicting method and a ground simulation predicting system for aeroelasticity stability and is used for predicting the aeroelasticity stability boundary of a structure to be tested. The whole system comprises a support system, a tested structure, a moving signal sensor, a data collecting card, a force sensor, an aerodynamic computation computer and force loading equipment. The method can be directly applied to the practical structure, so the inherent characteristics of the structure can be reserved, and testing results are truer and more reliable. The method and the system have the advantages that the defects of the traditional testing can be effectively overcome, the advantages of ground vibration tests and wind tunnel tests are combined, the aeroelasticity stability predication can be completed in a short time and at lower cost, and meanwhile, the risk of flight tests can also be avoided.

Description

Ground simulation Forecasting Methodology and the system of aeroelastic stability
Technical field
The present invention relates to ground simulation Forecasting Methodology and the system of aeroelastic stability, specifically be used for determining the aeroelasticity critical stable state.
Background technology
At present, the aeroelastic stability prediction mainly contains theoretical analysis and two kinds of approach of test.The former requires the aircraft object is carried out mathematical modeling, and need to introduce certain hypothesis at structure, the aspect such as pneumatic at the aeroelasticity modeling process, be difficult to the various non-linear factors impacts of considering that real structure exists during calculating, and there is certain error in the modeling meeting.The latter comes the correctness of proof theory method, further guarantees aircraft security by the dynamic characteristic test of carrying out aircraft.Aeroelastic effect test mainly comprises Ground Vibration Test, three kinds of wind tunnel test and flight tests.Ground Vibration Test is Live Flying device structure, but can not consider Aerodynamic force action.Wind tunnel test can be considered the impact of aerodynamic force, but be subject to the impacts such as tunnel size and wind speed restriction, the deviser carries out the practical flight device size contracting ratio usually, there are certain difference in scale model and real structure, and because the inherent limitations such as wind tunnel wall interference, support interference, results of wind tunnel and Live Flying device characteristic have different; For situations such as high speed, thermal environments, the somewhat expensive of wind tunnel test and performance difficulty are at present still without the high research technique of cost performance in addition.Flight test uses the Live Flying device to carry out scene flight, has advantages of not to be subjected to various simplification and assumption restrictions, and test findings is the most true and reliable, but flight test also has its unique complicacy and danger.
The ground simulation method of described prediction aeroelastic stability can directly be applied on the practical structures, so the inherent characteristic of structure can keep, test findings is more true and reliable.It is the advantage of combined ground vibration test and wind tunnel test effectively, finishes at lower cost prediction within a short period of time, can also evade the danger of flight test simultaneously.
Summary of the invention
The technical issues that need to address of the present invention are: non-Unsteady Flow quick calculation method, distributed aerodynamic force decrease design and optimization method; The accurate control of power output of power loading equipemtn etc.
Advantage of the present invention comprises: one, take material object as tested structure, carry out the aeroelastic stability prediction, the result is more credible; Two, than wind tunnel test, can save plenty of time and expense; Three, than flight test, safety is without dangerous more.
System according to an embodiment of the invention comprises: back-up system, tested structure, motion signal sensor, data collecting card, aerodynamic force computing computer, power sensor, power loading equipemtn.
In according to one embodiment of present invention:
1. tested structure is installed on the back-up system.
2. by optimized algorithm, determine exciting point position, and installing force loading equipemtn, power sensor and motion signal sensor.
3. tested structure moves under the initial disturbance effect, and motion signal sensor records its response.
4. the aerodynamic force computing computer calculate in real time non-Unsteady Flow, and equivalence becomes to reduce the concentrated force of load(ing) point according to the motion signal sensor signal of data collecting card Real-time Collection and the flight operating mode of the tested structure that sets.
5. instruction applies acting force to tested structure to the power loading equipemtn according to the aerodynamic force computing computer, forms new disturbance, so moves in circles, and makes the structure generation vibration.
6. judge by the motor message that gathers whether tested structure is stable under this flight operating mode.As stable, progressively change of flight speed makes tested structure by the stable neutrality that becomes, and this moment, corresponding state of flight was the aeroelasticity critical stable state, and corresponding speed is corresponding neutrality speed.
According to an aspect of the present invention, provide a kind of ground simulation prognoses system of aeroelastic stability, it is characterized in that:
Back-up system is used to tested structure that rigid support or elasticity support are provided;
A plurality of power loading equipemtns, each power loading equipemtn are used for loading application point in power of tested structure layout,
A plurality of power sensors are arranged a power sensor on the tested structure at each power loading application point place;
A plurality of motion signal sensor measuring points are arranged a motion signal sensor on the tested structure at each measuring point place;
Data collecting card is used for the signal that the Real-time Collection motion signal sensor is surveyed, and obtains the dynamic perfromance of tested structure;
The aerodynamic force calculating section is used for the motor message according to the data collecting card collection, calculates in real time corresponding non-permanent aerodynamic pressure distribution, and this distributed force is loaded on the tested structure real-time and accurately by the power loading equipemtn,
The wherein acting force on the power Sensor monitoring load(ing) point, and Real-time Feedback is to the aerodynamic force calculating section, in order to carry out the power output calibration.
According to another aspect of the present invention, provide a kind of ground simulation Forecasting Methodology of aeroelastic stability, it is characterized in that:
By back-up system, for tested structure provides rigid support or elasticity support;
At tested structure loading force, wherein each power loading equipemtn arranges that in tested structure a power loads application point with a plurality of power loading equipemtns,
Detect the tested structural power that is carried in a plurality of power sensors, wherein load a power sensor of tested structure layout at application point place in each power;
Detect tested structural motor message with a plurality of motion signal sensor measuring points, wherein arrange a motion signal sensor in the tested structure at each measuring point place;
With the signal that data collecting card Real-time Collection motion signal sensor is surveyed, obtain the dynamic perfromance of tested structure;
Use the aerodynamic force calculating section, according to the motor message that data collecting card gathers, calculate in real time corresponding non-permanent aerodynamic pressure distribution, and this distributed force is loaded on the tested structure real-time and accurately by the power loading equipemtn,
The wherein acting force on the power Sensor monitoring load(ing) point, and Real-time Feedback is to the aerodynamic force calculating section, in order to carry out the power output calibration.
Description of drawings
Fig. 1 is the configuration schematic diagram of the ground simulation prognoses system of aeroelastic stability according to an embodiment of the invention.
The reference numeral explanation:
1-back-up system 2-tested structure 3-motion signal sensor signal
4-data collecting card, 5-data cable, 6-force sensor signals
7-aerodynamic force computing computer, 8-power loading equipemtn
Embodiment
As shown in Figure 1, be the equipment configuration be used to the ground simulation prognoses system of implementing a kind of aeroelastic stability according to an embodiment of the invention, wherein:
Back-up system (1) provides rigid support or elasticity support for tested structure (2);
Tested structure (2) is generally wing structure, guided missile rudder face structure or missile airframe etc.;
Tested structure (2) is upper arranges that a plurality of power load application point, and each application point place arranges a power sensor (by corresponding signal wire 6 expressions) and a power loading equipemtn (8);
Upper a plurality of motion signal sensor measuring points, the motion signal sensor of each measuring point place layout (by corresponding signal wire 3 expressions) of arranging of tested structure (2);
The signal that data collecting card (4) Real-time Collection motion signal sensor (3) is surveyed obtains the dynamic perfromance of tested structure (2);
Aerodynamic force calculating section (7) is usually with the computer realization that has loaded corresponding application, motor message according to data collecting card (4) collection, calculate in real time corresponding non-permanent aerodynamic pressure distribution, and this distributed force is loaded on the tested structure (2) real-time and accurately by power loading equipemtn (8);
By the acting force on power sensor (6) the monitoring load(ing) point, and Real-time Feedback is to aerodynamic force calculating section (7), in order to carry out the power output calibration.
According to an embodiment, the parameters such as flying speed, atmospheric density that aerodynamic force calculating section (7) can be according to motion signal sensor (3) have been set before the signal collected and test, calculate in real time the non-Unsteady Flow that acts on tested structure (2), by equivalent cut down algorithm force per unit area is reduced concentrated force for selected several power load(ing) points.
Be the ground simulation Forecasting Methodology of realization aeroelastic stability and the real-time loading of system, the computing time of non-Unsteady Flow must be less than the sampling period of test.And based on the aerodynamic force computing method of Fluid Mechanics Computation (CFD), usually computing time oversize, can't be applicable to this ground simulation Forecasting Methodology and system, therefore adopt non-Unsteady Flow computing method commonly used on the engineering:
1. in the subsonic speed scope, often adopt the subsonic speed Doubiet Lattice Method, its main formulas is:
Δp = 1 2 ρV 2 D - 1 w
In the formula: ρ is atmospheric density, and V is flying speed, and D represents aerodynamic influence matrix, and w represents lower downwash velocity array of washing the place, reference mark, and Δ p represents the pressure distribution array at the pressure-acting point place of grid division.
2. for very thin thickness and the very high aerofoil of flight Mach number in wing section, usually adopt piston theory, its main formulas is:
Δp = - 2 ρaV ( ∂ ∂ x + 1 V ∂ ∂ t ) z ( x , y , t )
In the formula: ρ is atmospheric density; A is local velocity of sound, and V is flying speed, and z (x, y, t) is the vibration displacement array of grid, and Δ p represents the pressure distribution array at the pressure-acting point place of grid division.
3. for slender bodies structure (general slenderness ratio is greater than about 10), adopt the aerodynamic derivative method, its main formulas is:
Y = - 1 2 ρV 2 SC N α ( ∂ z ∂ x + 1 V ∞ ∂ z ∂ t )
In the formula: ρ is atmospheric density, and V is flying speed, and S is aerodynamic force computing reference area, Represent the slope of lift curve at this pneumatic segmenting pressure heart place, can obtain from the wind tunnel test of model,
Figure BDA00003470562900045
Be non-permanent local angle of attack, wherein
Figure BDA00003470562900046
And
Figure BDA00003470562900047
The respectively corresponding pneumatic segmenting of item is pressed the instantaneous slope in heart place and vibration velocity, and Y is the lift of this aerodynamic force computing reference area.
For aerodynamic force equivalence cut down algorithm:
1. for the rigidity aerofoil, because deformation does not occur airfoil structure, can simulate the motion of whole aerofoil by two degree of freedom
F 1 F 2 = y 1 y 2 x 1 x 2 - 1 M x ( z 1 , z 2 , z · 1 , z · 2 ) - M y ( z 1 , z 2 , z · 1 , z · 2 )
In the formula: F 1, F 2Be the concentrated force of the load(ing) point that calculates, x 1, y 1, x 2, y 2Be the coordinate position of two load(ing) points under the given coordinate system, z 1, z 2Represent respectively the z of two load(ing) points to displacement,
Figure BDA00003470562900052
Figure BDA00003470562900053
For the moment difference of aerodynamic loading about x axle and y axle, can carry out integration by aerodynamic force and try to achieve.
2. for the elasticity aerofoil, the motion process structure can produce elastic deformation, aerodynamic force and movable information are no longer linear, frequency domain form by non-Unsteady Flow computing method, obtain the transitive relation of non-Unsteady Flow and structural response, set up contacting between the concentrated force of load(ing) point and the structure motion information by the curved surface spline method again, use again minimum state (MS) method to carry out rational function approximation, obtain concentrated force and in the approximate form of Laplace domain be
f s = 1 2 ρV 2 ( A 0 + b V A 1 s + b 2 V 2 A 2 s 2 ) z s + 1 2 ρV 2 ( sI - V b R ) - 1 Esz s
In the formula: ρ is atmospheric density, and V is flying speed, A 0, A 1, A 2With D, E be the matrix of consequence that the minimum state method obtains, b is reference length, z sBe the displacement at motion signal sensor measuring point place, I is the unit diagonal matrix, and R is the diagonal matrix take aerodynamic force hysteresis root as diagonal element, and s is Laplce's variable, f sBe the load(ing) point concentrated force.
Following formula is carried out inverse Laplace transform, and what obtain namely is displacement, the speed of the concentrated force of load(ing) point and motion signal sensor measuring point, the time domain relational expression of acceleration.
3. for the slender bodies structure, the vibration shape of its lower mode is relatively smooth, under this condition, can be the equivalence of the aerodynamic pressure distribution of slender bodies reality the concentrated force that acts on the pressure heart position of minority pneumatic segmenting.Generally, slender bodies is divided into the needs that 4～5 pneumatic segmentings can satisfy aeroelastic analysis.For given tested slender bodies structure, after slope of lift curve is known, only need to survey the local angle of attack that the heart is pressed in each segmentation by sensor, according to the aerodynamic derivative method of slender bodies, can calculate the concentrated force of load(ing) point.
According to another embodiment, in the ground simulation method of above-mentioned prediction aeroelastic stability, limited layout design that loads application point is through optimizing, and the to the full extent equivalence of concentrated force that loads thereon approaches distributed aerodynamic force.
According to another embodiment, in the ground simulation method of above-mentioned prediction aeroelastic stability, power loading equipemtn (8) has good mechanical characteristic, its power output can overlap with the command signal of input, so can accurately export the concentrated force of the selected power load(ing) point that aerodynamic force computing computer (7) calculates.
According to another embodiment, in the ground simulation method of above-mentioned prediction aeroelastic stability, set a flight operating mode that comprises flying speed, atmospheric density etc. before testing beginning, the test beginning is rear, gives (2) initial disturbances of tested structure.Such as motion signal sensor (3) survey response convergence, illustrate that then tested structure (2) is stable under this flight operating mode; Such as motion signal sensor (3) survey response be continuous oscillation, illustrate that then tested structure (2) is neutrality under this flight operating mode; Such as motion signal sensor (3) survey response disperse, illustrate that then tested structure (2) is unsettled under this flight operating mode.Usually, observe tested structure (2) by the stable process that is transitioned into neutrality by progressively change of flight speed, the corresponding flying speed of critical stable state is the neutrality speed that the method will be predicted.
Beneficial effect of the present invention comprises:
1. compare with Ground Vibration Test, the method can the aerial pneumatic stand under load situation of simulated flight device, is the aeroelasticity stability boundaris of measurable aircraft before making a flight test, and reduces the uncertain factor in the flight test, avoids the risk of flight test.
2. compare with wind tunnel test, the method tested object is Live Flying device structure, need not to carry out the scale model design, has reduced structural failure, test setup time and cost.And test repeatability is good, the overall process of being convenient to observe Results of Aeroelastic Instability; Trial stretch is wide in addition, for the different Mach number situation, only need set up out corresponding Aerodynamic Model and get final product.
3. compare with theoretical calculating of aeroelastic stability, the method does not need to survey the structural parameters such as the generalized mass, broad sense rigidity of structure, and these parameters also can not accurately obtain in theoretical the calculating, on this meaning, the result of the method is more accurate than result of calculation, particularly when there was non-linear factor in structure, the method can be avoided the calculating of many complexity.
4. the method can remedy the deficiency of traditional experiment method effectively.In case the method applies to matured product, will have broad application prospects, and for the experimental study of Flight Vehicle Design brings huge facility, greatly reduce development cost and the cycle of aircraft.

Claims (10)

1. the ground simulation prognoses system of an aeroelastic stability is characterized in that:
Back-up system (1) is used to tested structure (2) that rigid support or elasticity support are provided;
A plurality of power loading equipemtns (8), each power loading equipemtn (8) are used for loading application point in power of tested structure (2) layout,
A plurality of power sensors (6), each power load the upper power sensor (6) of arranging of tested structure (2) at application point place;
A plurality of motion signal sensor measuring points (3), the upper motion signal sensor (3) of arranging of the tested structure (2) at each measuring point place;
Data collecting card (4) is used for the signal that Real-time Collection motion signal sensor (3) is surveyed, and obtains the dynamic perfromance of tested structure (2);
Aerodynamic force calculating section (7), be used for the motor message according to data collecting card (4) collection, calculate in real time corresponding non-permanent aerodynamic pressure distribution, and this distributed force is loaded on the tested structure (2) real-time and accurately by power loading equipemtn (8)
Wherein power sensor (6) is monitored the acting force on the load(ing) point, and Real-time Feedback is to aerodynamic force calculating section (7), in order to carry out the power output calibration.
2. the ground simulation prognoses system of aeroelastic stability according to claim 1, it is characterized in that, aerodynamic force calculating section (7) is according to the signal collected and predefined parameter of motion signal sensor (3), calculate in real time the non-Unsteady Flow that acts on tested structure (2), and by equivalent cut down algorithm force per unit area is reduced concentrated force for selected several power load(ing) points.
3. the ground simulation prognoses system of aeroelastic stability according to claim 1, it is characterized in that, limited layout that loads application point is optimized by this way, namely so that the concentrated force that loads at described limited loading application point can equivalence approach distributed aerodynamic force.
4. the ground simulation prognoses system of aeroelastic stability according to claim 1 is characterized in that, the concentrated force of the selected power load(ing) point that power loading equipemtn (8) output aerodynamic force calculating section (7) calculates.
5. the ground simulation prognoses system of aeroelastic stability according to claim 2 is characterized in that, described predefined parameter comprises a plurality of minutes line parameters, this a plurality of minutes line parameters comprise flying speed and atmospheric density, after the simulation beginning, give (2) initial disturbances of tested structure
Such as motion signal sensor (3) survey response convergence, illustrate that then tested structure (2) is stable under this flight operating mode;
Such as motion signal sensor (3) survey response be continuous oscillation, illustrate that then tested structure (2) is neutrality under this flight operating mode;
Such as motion signal sensor (3) survey response disperse, illustrate that then tested structure (2) is unsettled under this flight operating mode,
By progressively changing described flying speed, make tested structure (2) by the stable process that is transitioned into neutrality, and the corresponding flying speed of critical stable state is defined as the neutrality speed that the method will be predicted.
6. the ground simulation Forecasting Methodology of an aeroelastic stability is characterized in that:
By back-up system (1), for tested structure (2) provides rigid support or elasticity support;
At tested structure (2) loading force, wherein each power loading equipemtn (8) arranges that in tested structure (2) power loads application point with a plurality of power loading equipemtns (8),
Detect the power that is carried on the tested structure (2) with a plurality of power sensors (6), wherein load tested structure (a 2) layout power sensor (6) at application point place in each power;
Detect motor message on the tested structure (2) with a plurality of motion signal sensor measuring points (3), wherein arrange a motion signal sensor (3) in the tested structure (2) at each measuring point place;
With the signal that data collecting card (4) Real-time Collection motion signal sensor (3) is surveyed, obtain the dynamic perfromance of tested structure (2);
With aerodynamic force calculating section (7), motor message according to data collecting card (4) collection, calculate in real time corresponding non-permanent aerodynamic pressure distribution, and this distributed force is loaded on the tested structure (2) real-time and accurately by power loading equipemtn (8)
Wherein power sensor (6) is monitored the acting force on the load(ing) point, and Real-time Feedback is to aerodynamic force calculating section (7), in order to carry out the power output calibration.
7. the ground simulation Forecasting Methodology of aeroelastic stability according to claim 6 is characterized in that:
With aerodynamic force calculating section (7) according to the signal collected and predefined parameter of motion signal sensor (3), calculate in real time the non-Unsteady Flow that acts on tested structure (2), and by equivalent cut down algorithm force per unit area is reduced concentrated force for selected several power load(ing) points.
8. the ground simulation Forecasting Methodology of aeroelastic stability according to claim 6 is characterized in that,
Limited layout that loads application point is optimized by this way, namely so that the concentrated force that loads at described limited loading application point can equivalence approach distributed aerodynamic force.
9. the ground simulation Forecasting Methodology of aeroelastic stability according to claim 6 is characterized in that, the concentrated force of the selected power load(ing) point that loading equipemtn (8) the output aerodynamic force calculating section (7) of exerting oneself calculates.
10. the ground simulation Forecasting Methodology of aeroelastic stability according to claim 7 is characterized in that, described predefined parameter comprises a plurality of minutes line parameters, and this a plurality of minutes line parameters comprise flying speed and atmospheric density, and described method further comprises
After the simulation beginning, give (2) initial disturbances of tested structure,
Such as motion signal sensor (3) survey response convergence, illustrate that then tested structure (2) is stable under this flight operating mode;
Such as motion signal sensor (3) survey response be continuous oscillation, illustrate that then tested structure (2) is neutrality under this flight operating mode;
Such as motion signal sensor (3) survey response disperse, illustrate that then tested structure (2) is unsettled under this flight operating mode,
Progressively change described flying speed, make tested structure (2) by the stable process that is transitioned into neutrality,
The corresponding flying speed of critical stable state is defined as the neutrality speed that the method will be predicted.
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Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105424311A (en) * 2015-11-10 2016-03-23 中国空气动力研究与发展中心高速空气动力研究所 Wind tunnel force measurement test method of model of large slender ratio revolution body with tail vane
CN105825035A (en) * 2016-05-16 2016-08-03 中国航空工业集团公司西安飞机设计研究所 Equivalent treating method for surface distribution force generated when wing supporting poles are axially pressed
CN107144412A (en) * 2017-05-17 2017-09-08 北京航空航天大学 A kind of aerodynamic response collection of energy ground simulating system
CN108268025A (en) * 2018-01-03 2018-07-10 北京航空航天大学 Random perturbation lower network networked control systems elasticity assessment method
CN108489702A (en) * 2018-03-05 2018-09-04 北京航空航天大学 The binary channels air force load testing machine of double pendulum vector spray
CN109459206A (en) * 2018-12-17 2019-03-12 西北工业大学 Ground experiment unsteady aerodynamic force loading method
CN109738144A (en) * 2018-10-31 2019-05-10 中国飞机强度研究所 A kind of prominent wind response ground simulation experiment method
CN110674599A (en) * 2019-09-24 2020-01-10 西北工业大学 Rational approximate optimization method for unsteady pneumatic load of pneumatic servo elastic system
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CN116424548A (en) * 2023-03-30 2023-07-14 湖南山河华宇航空科技有限公司 Electric proportional flight control system, control method and application

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101419117A (en) * 2008-11-28 2009-04-29 北京航空航天大学 Aeroelastic flutter generating device
US20090314076A1 (en) * 2008-06-19 2009-12-24 Airbus France Hybrid method for estimating the ground effect on an aircraft
CN101793591A (en) * 2010-03-26 2010-08-04 北京航空航天大学 Aircraft aero-servo-elasticity ground simulating test system
CN102305699A (en) * 2011-05-19 2012-01-04 北京航空航天大学 Wind tunnel experiment system for free flight model
CN102589840A (en) * 2012-01-12 2012-07-18 清华大学 Vertical or short-distance takeoff and landing aircraft ground effect test system
CN102866637A (en) * 2012-10-07 2013-01-09 西北工业大学 Quadratic order-reduction based method for simulating unsteady aerodynamic force of aerofoil with operation surface

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090314076A1 (en) * 2008-06-19 2009-12-24 Airbus France Hybrid method for estimating the ground effect on an aircraft
CN101419117A (en) * 2008-11-28 2009-04-29 北京航空航天大学 Aeroelastic flutter generating device
CN101793591A (en) * 2010-03-26 2010-08-04 北京航空航天大学 Aircraft aero-servo-elasticity ground simulating test system
CN102305699A (en) * 2011-05-19 2012-01-04 北京航空航天大学 Wind tunnel experiment system for free flight model
CN102589840A (en) * 2012-01-12 2012-07-18 清华大学 Vertical or short-distance takeoff and landing aircraft ground effect test system
CN102866637A (en) * 2012-10-07 2013-01-09 西北工业大学 Quadratic order-reduction based method for simulating unsteady aerodynamic force of aerofoil with operation surface

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
杨超 等: ""高超声速飞行器气动弹性力学研究综述"", 《航空学报》, vol. 31, no. 1, 25 January 2010 (2010-01-25), pages 1 - 11 *
许云涛 等: ""地面颤振模拟试验中的非定常气动力模拟"", 《航空学报》, 30 August 2012 (2012-08-30), pages 1 - 10 *

Cited By (27)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105424311B (en) * 2015-11-10 2017-12-15 中国空气动力研究与发展中心高速空气动力研究所 A kind of high-fineness ratio tail rudder body of revolution model wind tunnel dynamometer check method
CN105424311A (en) * 2015-11-10 2016-03-23 中国空气动力研究与发展中心高速空气动力研究所 Wind tunnel force measurement test method of model of large slender ratio revolution body with tail vane
CN105825035B (en) * 2016-05-16 2019-03-22 中国航空工业集团公司西安飞机设计研究所 The equivalent way of surface distributed force when a kind of wing strut axial compression
CN105825035A (en) * 2016-05-16 2016-08-03 中国航空工业集团公司西安飞机设计研究所 Equivalent treating method for surface distribution force generated when wing supporting poles are axially pressed
CN107144412A (en) * 2017-05-17 2017-09-08 北京航空航天大学 A kind of aerodynamic response collection of energy ground simulating system
CN107766611B (en) * 2017-09-08 2023-04-18 中国飞行试验研究院 Real-time calculation method for vibration monitoring parameters of power device accessory system in flight test
CN108268025B (en) * 2018-01-03 2020-01-03 北京航空航天大学 Elasticity evaluation method for networked control system under random disturbance
CN108268025A (en) * 2018-01-03 2018-07-10 北京航空航天大学 Random perturbation lower network networked control systems elasticity assessment method
CN108489702A (en) * 2018-03-05 2018-09-04 北京航空航天大学 The binary channels air force load testing machine of double pendulum vector spray
CN109738144A (en) * 2018-10-31 2019-05-10 中国飞机强度研究所 A kind of prominent wind response ground simulation experiment method
CN109738144B (en) * 2018-10-31 2021-05-07 中国飞机强度研究所 Gust response ground simulation test method
CN109459206A (en) * 2018-12-17 2019-03-12 西北工业大学 Ground experiment unsteady aerodynamic force loading method
CN109459206B (en) * 2018-12-17 2020-10-27 西北工业大学 Ground test unsteady aerodynamic force loading method
CN112393876A (en) * 2019-08-16 2021-02-23 北京空天技术研究所 Dynamic pneumatic derivative prediction method suitable for internal and external flow integrated appearance
CN110674599B (en) * 2019-09-24 2020-08-28 西北工业大学 Rational approximate optimization method for unsteady pneumatic load of pneumatic servo elastic system
CN110674599A (en) * 2019-09-24 2020-01-10 西北工业大学 Rational approximate optimization method for unsteady pneumatic load of pneumatic servo elastic system
CN111324991A (en) * 2019-12-10 2020-06-23 中国飞机强度研究所 Reconstruction method of aerodynamic model in ground flutter test
CN111324991B (en) * 2019-12-10 2024-01-12 中国飞机强度研究所 Reconstruction method of aerodynamic model in ground flutter test
CN112033636A (en) * 2020-08-06 2020-12-04 大连理工大学 Dimensionality reduction monitoring method for random multidimensional vibration of aircraft model
CN112033636B (en) * 2020-08-06 2021-06-18 大连理工大学 Dimensionality reduction monitoring method for random multidimensional vibration of aircraft model
CN112706945A (en) * 2020-12-11 2021-04-27 中国特种飞行器研究所 Pneumatic load loading method
CN112706945B (en) * 2020-12-11 2022-11-01 中国特种飞行器研究所 Pneumatic load loading method
CN113504064A (en) * 2021-07-09 2021-10-15 哈尔滨工业大学 Online simulation driven aircraft structure thermodynamic combined test system and method
CN113830326A (en) * 2021-11-01 2021-12-24 中国商用飞机有限责任公司 Static aeroelasticity ground simulation system and method for airplane
CN113830326B (en) * 2021-11-01 2024-06-04 中国商用飞机有限责任公司 Aeroplane static pneumatic elastic ground simulation system and method
CN116424548A (en) * 2023-03-30 2023-07-14 湖南山河华宇航空科技有限公司 Electric proportional flight control system, control method and application
CN116424548B (en) * 2023-03-30 2024-05-10 湖南山河华宇航空科技有限公司 Electric proportional flight control system, control method and application

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