CN103530511A - Flutter boundary prediction method in wind tunnel flutter test under turbulence excitation condition - Google Patents
Flutter boundary prediction method in wind tunnel flutter test under turbulence excitation condition Download PDFInfo
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Abstract
The invention discloses a flutter boundary prediction method in a wind tunnel flutter test under a turbulence excitation condition. At first, time domain response signals of typical measuring points in the process of the wind tunnel test are collected, trend removal and smooth pretreatment are carried out on the signals, self-correlation processing is conducted on processed turbulence response data, the processed turbulence response data serve as impulse responses of a system, band-pass filtering is carried out on the processed turbulence response data, and frequency selected by filtering is determined by dangerous modal frequency measured by a model ground resonance test; secondly, spectral analysis and modal parameter identification are carried out on the obtained and processed impulse responses with noise, and an MPM with high anti-noise performance is adopted to identify various order modal parameters; at last, frequency and damping ratios of various order modals are arranged according to different wind speeds when data are collected, and a mode that straight line fitting and polynomial fitting are combined is adopted to extrapolate a flutter boundary. According to the method, the flutter boundary under the turbulence excitation condition can be forecasted, a traditional flutter judgment method is improved, and improvements of accuracy and safety of the test are facilitated.
Description
Technical field
The present invention relates to a kind of Modal Parameters Identification, relate in particular to the wind-tunnel flutter test Flutter Boundaries Forecasting Methodology under a kind of turbulence excitation condition, belong to Modal Parameter Identification technical field.
Background technology
Flutter test is an important step essential in Flight Vehicle Design work, and the Flutter Boundaries obtaining by test can be determined the flight envelope of aircraft, and then passes judgment on aircraft performance and ensure flight safety.
Yet in wind-tunnel flutter test, the acquisition of flutter speed also depends on the working experience of testing crew conventionally at present.Testing crew is usingd the Flutter Boundaries of FEM (finite element) calculation as with reference to value, starting stage in blowing can be improved wind speed with certain wind speed ladder, then constantly reduce the speedup of its wind speed ladder, when wind speed loads near theoretical flutter wind speed, the micro-increasing of wind speed is dispersed vibration gradually carefully, the Vibration Condition of dispersing situation and testpieces by observing the decay of response signal judges that whether Flutter Boundaries arrives, and obtains flutter speed with this.If yet blowing model exist undiscovered design defect cause actual flutter speed and notional result error larger, very possible disintegration and failure in the situation that staff has little time reaction when improving wind speed, even can damage wind-tunnel, therefore only according to artificial experience, judge that Flutter Boundaries exists risk and inaccuracy.
In wind-tunnel flutter test, can obtain shock response, identification modal damping the Flutter Boundaries of extrapolating by the mode being similar in the excitation of wing tip installation mouse.Yet the method equipment relative complex, complex operation.In wind tunnel test, the most frequently used energisation mode is turbulent natural excitation, and these motivational techniques do not need extra excitation set, easy and simple to handle, can effectively reduce costs.
At present, for turbulence excitation condition, there is document to adopt Modal Parameter by Random Decrement to carry out assembly on average to obtain the shock response of system to output response signal, yet Modal Parameter by Random Decrement need to be chosen suitable trigger condition and the average time of subsignal, and the two is to be mutually related, so the method in use needs further to debug according to signal, this has just caused the inaccurate and unstable of acquired results.
Summary of the invention
The present invention is directed to the wind-tunnel flutter test under turbulence excitation condition, the Forecasting Methodology of the wind-tunnel flutter test Flutter Boundaries under a kind of turbulence excitation condition is provided, be intended to solve the Modal Parameter Identification problem of turbulent natural excitation response in wind tunnel test.
The present invention adopts following technical scheme: the wind-tunnel flutter test Flutter Boundaries Forecasting Methodology under a kind of turbulence excitation condition, it comprises the steps
(1) point position of the curved and twisting die state of Selection Model is pasted sensor, Real-time Collection each point response under certain blowing wind speed;
(2), under the blowing wind speed of step (1), survey response is carried out to trend and remove and smoothing processing pre-service;
(3) each is measured to the pretreated turbulent response signal of passage and do auto-correlation processing;
(4) frequency of each rank mode of combined ground resonance test, does the free damping response of each measuring point of step (3) gained that frequency domain converts and carry out filtering to remove the frequency domain information outside the contained mode of each measuring point;
(5) each model frequency and the damping ratio parameter of gained response after each measuring point filtering of employing Modal Parameter Identification pencil of matrix method identification step (4) gained;
(6) each modal parameter of recording step (5) gained under each blowing wind speed, make every rank damping ratios with respect to the change curve of wind speed, the damping ratio that carries out curve fitting and extrapolate is reduced to 0 wind speed as the predicted boundary point under measuring wind this moment, and guides the heap(ed) capacity of next step wind speed;
(7) the suitable selection wind speed of border wind speed of predicting according to step (6) under each cold air blast velocity loads, repeating step (2)-(6), matched curve in step of updating (6) the new future position of extrapolating, until current wind speed and prediction of wind speed reach unanimity, judge flutter critical point.
Described turbulent signal processing method is auto-correlation processing.
Described each outside forecast frontier point is by for instructing the heap(ed) capacity of next step wind speed.
The present invention has following beneficial effect: the wind-tunnel flutter test Flutter Boundaries Forecasting Methodology under turbulence excitation condition of the present invention can be predicted the Flutter Boundaries under turbulence excitation condition, improve traditional flutter determination methods, contribute to improve accuracy and the security of test.
Accompanying drawing explanation
Fig. 1 is the turbulence excitation time domain response of torsion with in-plane bending measuring point.
Fig. 2 is pretreated turbulent flow response.
Fig. 3 is the response after auto-correlation processing.
Fig. 4 is that the filtering of frequency domain is processed.
Fig. 5 is the fitting a straight line extrapolation of two each measuring points of wind speed.
Fig. 6 is the fitting a straight line extrapolation and quadratic term matching extrapolation of three each measuring points of wind speed.
The fitting a straight line extrapolation that Fig. 7 is each measuring point of wind speed of renewal and quadratic term matching extrapolation.
Fig. 8 is that frequency spectrum after in-plane bending mode turbulent flow response auto-correlation processing is with the variation of wind speed.
Fig. 9 is that frequency spectrum after torsion mode turbulent flow response auto-correlation processing is with the variation of wind speed.
Figure 10 is that frequency spectrum after wing tip turbulent flow response auto-correlation processing is with the variation of wind speed.
Embodiment
Below in conjunction with accompanying drawing, technical scheme of the present invention is elaborated:
Please refer to shown in Fig. 1 to Figure 10, the wind-tunnel flutter test Flutter Boundaries Forecasting Methodology under turbulence excitation condition of the present invention comprises the following steps:
(1) point position of the curved and twisting die state of Selection Model is pasted sensor, Real-time Collection each point response in blowing process, and sample frequency is 4096Hz, when wind speed is 41m/s, torsion response is as shown in Figure 1;
(2) under this wind speed, survey response is carried out to trend removal and smoothing processing, to reach the object of removing burr and bad point, the response after processing is as shown in Figure 2;
(3) each is measured to the pretreated turbulent response signal of passage and do auto-correlation processing, to reach the object that turbulent natural excitation response is converted into free damping response, the response after processing as shown in Figure 3;
(4) frequency of each rank mode of combined ground resonance test, does the free damping response of each measuring point of step (3) gained that frequency domain converts and carry out filtering, to remove the frequency domain information outside the contained mode of each measuring point.It is 18.46Hz that one of ground resonance test is turned round frequency, and in face, two curved frequencies are 13.75Hz.After frequency domain conversion, this two rank model frequency, respectively in 18.8Hz and 13.9Hz left and right, is chosen suitable frequency range and is carried out bandpass filtering, and filtering result as shown in Figure 4;
(5) each model frequency and the damping ratio parameter of gained response after each measuring point filtering of employing Modal Parameter Identification pencil of matrix method identification step (4) gained.The torsion frequency that under this wind speed, identification obtains is 13.94Hz, and damping ratio is 0.0105; Corner frequency is 18.85Hz, and damping ratio is 0.0243;
(6) each modal parameter of recording step (5) gained under each blowing wind speed, make every rank damping ratios with respect to the change curve of wind speed, the damping ratio that carries out curve fitting and extrapolate is reduced to 0 wind speed as the predicted boundary point under measuring wind this moment, to instruct the heap(ed) capacity of next step wind speed, as shown in Figure 5, now predicted boundary point is 42.64m/s, so next step wind speed is loaded as 41m/s;
(7) wind speed between suitable these two wind speed of selection of the border wind speed that provides according to step (6) under each cold air blast velocity is put and loads, repeating step (2)-(6), matched curve in step of updating (6) the new future position of extrapolating, as Figure 6-Figure 7.In conjunction with the frequency spectrum judgement of each measuring point under each wind speed, there will be the mode of flutter simultaneously, consider emphatically the variation tendency of this damping ratios, until current wind speed and prediction of wind speed reach unanimity, can judge flutter critical point.Spectral change figure is as shown in Fig. 8 to Figure 10, crooked measuring point in Fig. 8 is in the uprushed frequency domain branch of torsion mode of 42m/s, torsion mode in Fig. 9 is obvious gradually, in Figure 10, wing tip responds and when 41m/s, has uprushed torsion mode and when 42m/s, become main mode, this has all shown that this torsion mode is tending towards gradually dispersing so that there will be flutter, and this is also consistent with torsion extrapolation in Fig. 6, Fig. 7.Therefore the predicted boundary point of being extrapolated by Fig. 7 is 42.063m/s, and now wind speed has been loaded into 42m/s, now assert that being loaded into the sector-style hole of going forward side by side, border stops.
Wind-tunnel flutter test Flutter Boundaries Forecasting Methodology under turbulence excitation condition of the present invention can be predicted the Flutter Boundaries under turbulence excitation condition, improves traditional flutter determination methods, contributes to improve accuracy and the security of test.
The above is only the preferred embodiment of the present invention, it should be pointed out that for those skilled in the art, can also make some improvement under the premise without departing from the principles of the invention, and these improvement also should be considered as protection scope of the present invention.
Claims (3)
1. the wind-tunnel flutter test Flutter Boundaries Forecasting Methodology under turbulence excitation condition, is characterized in that: it comprises the steps
(1) point position of the curved and twisting die state of Selection Model is pasted sensor, Real-time Collection each point response under certain blowing wind speed;
(2), under the blowing wind speed of step (1), survey response is carried out to trend and remove and smoothing processing pre-service;
(3) each is measured to the pretreated turbulent response signal of passage and do auto-correlation processing;
(4) frequency of each rank mode of combined ground resonance test, does the free damping response of each measuring point of step (3) gained that frequency domain converts and carry out filtering to remove the frequency domain information outside the contained mode of each measuring point;
(5) each model frequency and the damping ratio parameter of gained response after each measuring point filtering of employing Modal Parameter Identification pencil of matrix method identification step (4) gained;
(6) each modal parameter of recording step (5) gained under each blowing wind speed, make every rank damping ratios with respect to the change curve of wind speed, the damping ratio that carries out curve fitting and extrapolate is reduced to 0 wind speed as the predicted boundary point under measuring wind this moment, and guides the heap(ed) capacity of next step wind speed;
(7) the suitable selection wind speed of border wind speed of predicting according to step (6) under each cold air blast velocity loads, repeating step (2)-(6), matched curve in step of updating (6) the new future position of extrapolating, until current wind speed and prediction of wind speed reach unanimity, judge flutter critical point.
2. the wind-tunnel flutter test Flutter Boundaries Forecasting Methodology under turbulence excitation condition as claimed in claim 1, is characterized in that: described turbulent signal processing method is auto-correlation processing.
3. the wind-tunnel flutter test Flutter Boundaries Forecasting Methodology under turbulence excitation condition as claimed in claim 1, is characterized in that: described each outside forecast frontier point is by for instructing the heap(ed) capacity of next step wind speed.
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Cited By (10)
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| CN104443427A (en) * | 2014-10-15 | 2015-03-25 | 西北工业大学 | Aircraft flutter prediction system and method |
| CN104881585A (en) * | 2015-03-24 | 2015-09-02 | 南京航空航天大学 | Flutter boundary prediction method of two-degree-of-freedom wing |
| CN107860548A (en) * | 2017-09-12 | 2018-03-30 | 南京航空航天大学 | A kind of online flutter boundary prediction method of approximation |
| CN108195543A (en) * | 2017-11-29 | 2018-06-22 | 中国航空工业集团公司沈阳飞机设计研究所 | A kind of aircraft wind tunnel model flutter blowing test system |
| CN109063290A (en) * | 2018-07-20 | 2018-12-21 | 中国航空工业集团公司沈阳飞机设计研究所 | A kind of flutter prediction technique based on nerual network technique |
| CN109086501A (en) * | 2018-07-20 | 2018-12-25 | 中国航空工业集团公司沈阳飞机设计研究所 | A kind of flutter prediction technique |
| CN109885854A (en) * | 2018-11-23 | 2019-06-14 | 南京航空航天大学 | The real-time forecasting system of Flutter Boundaries and prediction technique based on arma modeling |
| CN110657939A (en) * | 2019-08-30 | 2020-01-07 | 中国空气动力研究与发展中心高速空气动力研究所 | Flutter critical prediction method and device |
| CN113267304A (en) * | 2021-04-25 | 2021-08-17 | 上海机电工程研究所 | Missile servo vibration subcritical test and stable boundary prediction system and method |
| CN114608795A (en) * | 2022-05-11 | 2022-06-10 | 中国飞机强度研究所 | Wind tunnel system resonance boundary determining method for airplane blowing test |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104443427A (en) * | 2014-10-15 | 2015-03-25 | 西北工业大学 | Aircraft flutter prediction system and method |
| CN104443427B (en) * | 2014-10-15 | 2016-08-31 | 西北工业大学 | Aircraft tremor prognoses system and method |
| CN104881585A (en) * | 2015-03-24 | 2015-09-02 | 南京航空航天大学 | Flutter boundary prediction method of two-degree-of-freedom wing |
| CN107860548A (en) * | 2017-09-12 | 2018-03-30 | 南京航空航天大学 | A kind of online flutter boundary prediction method of approximation |
| CN108195543A (en) * | 2017-11-29 | 2018-06-22 | 中国航空工业集团公司沈阳飞机设计研究所 | A kind of aircraft wind tunnel model flutter blowing test system |
| CN109086501A (en) * | 2018-07-20 | 2018-12-25 | 中国航空工业集团公司沈阳飞机设计研究所 | A kind of flutter prediction technique |
| CN109063290A (en) * | 2018-07-20 | 2018-12-21 | 中国航空工业集团公司沈阳飞机设计研究所 | A kind of flutter prediction technique based on nerual network technique |
| CN109885854A (en) * | 2018-11-23 | 2019-06-14 | 南京航空航天大学 | The real-time forecasting system of Flutter Boundaries and prediction technique based on arma modeling |
| CN109885854B (en) * | 2018-11-23 | 2023-07-11 | 南京航空航天大学 | ARMA model-based chatter boundary real-time prediction system and prediction method |
| CN110657939A (en) * | 2019-08-30 | 2020-01-07 | 中国空气动力研究与发展中心高速空气动力研究所 | Flutter critical prediction method and device |
| CN113267304A (en) * | 2021-04-25 | 2021-08-17 | 上海机电工程研究所 | Missile servo vibration subcritical test and stable boundary prediction system and method |
| CN114608795A (en) * | 2022-05-11 | 2022-06-10 | 中国飞机强度研究所 | Wind tunnel system resonance boundary determining method for airplane blowing test |
| CN114608795B (en) * | 2022-05-11 | 2022-07-22 | 中国飞机强度研究所 | Method for determining resonance boundary of wind tunnel system for airplane blowing test |
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Application publication date: 20140122 |