譚博+鄭華+裴承鳴
摘 要: 針對連續(xù)變速顫振試驗(yàn)實(shí)測信號的特點(diǎn)及在線處理需求,提出一種基于基函數(shù)展開的時(shí)變參數(shù)建模方法。通過對結(jié)構(gòu)響應(yīng)信號建模和穩(wěn)定性判據(jù)的趨勢分析,得到顫振邊界隨時(shí)間變化的預(yù)測曲線。依據(jù)顫振試驗(yàn)機(jī)理,采用白噪聲激勵(lì)多模態(tài)耦合系統(tǒng)的方式生成了相應(yīng)的仿真信號,進(jìn)而在不同信噪比下驗(yàn)證了方法的數(shù)值性能。最后通過氣彈模型低速風(fēng)洞試驗(yàn)進(jìn)一步檢驗(yàn)本文方法的工程實(shí)用性。
關(guān)鍵詞: 連續(xù)變速顫振試驗(yàn); 基函數(shù); 時(shí)變參數(shù)建模; 顫振邊界預(yù)測
中圖分類號: TN911.7?34; TP391.9 文獻(xiàn)標(biāo)識(shí)碼: A 文章編號: 1004?373X(2014)13?0047?03
Method for progression variable speed flutter boundary prediction
based on basis function decomposition
TAN Bo, ZHENG Hua, PEI Cheng?ming
(Data Processing Center, Northwestern Polytechnical University, Xian 710072, China)
Abstract: According to the characteristics and online processing requirements of the actual measuring signal in flutter test with progression variable speed (FTPVS), a time?varying parameter modeling algorithm based on basis function expansion is presented in this paper. The prediction curves of flutter boundary versus time variation were obtained on the basis of modeling of structural response signal and trend analysis of the stability criterion. According to the mechanism of flutter test, the correspon?ding simulation signal is generated with the mode that the white noise stimulates the multi?modal coupling system. The numerical performance of the method was verified at different SNRs. The practical applicability of the method was checked in aeroelastic model wind?tunnel test.
Keywords: flutter test with progression variable speed; basis function; time?varying parameter modeling; flutter boundary prediction
0 引 言
連續(xù)變速顫振試驗(yàn)是近年來從飛機(jī)結(jié)構(gòu)強(qiáng)度專業(yè)角度提出的一種全新顫振試驗(yàn)概念,指由于研究對象的實(shí)際工作狀態(tài)或試驗(yàn)方法的需要,馬赫數(shù)、速度、高度等參數(shù)連續(xù)變化的一類顫振試驗(yàn)技術(shù)。與傳統(tǒng)的臺(tái)階式顫振試驗(yàn)方法相比,具有試驗(yàn)周期短、試驗(yàn)開支小、技術(shù)約束少、更符合實(shí)際使用狀態(tài)等優(yōu)勢,但同時(shí)也存在更大的試驗(yàn)風(fēng)險(xiǎn)[4]。因此,在試驗(yàn)中能否基于實(shí)測信號快速準(zhǔn)確地完成顫振邊界預(yù)測是保證該類試驗(yàn)安全有效的關(guān)鍵技術(shù)之一。
連續(xù)變速顫振試驗(yàn)的結(jié)構(gòu)響應(yīng)信號是非平穩(wěn)隨機(jī)過程,這一特點(diǎn)使得傳統(tǒng)的顫振試驗(yàn)數(shù)據(jù)處理方法難以直接應(yīng)用。因此,本文提出一種基于基函數(shù)展開的時(shí)變參數(shù)建模方法,通過實(shí)測信號建立測試對象的時(shí)變參數(shù)模型,從而提取信號中所蘊(yùn)含的穩(wěn)定性特征量,并根據(jù)該特征量的趨勢進(jìn)行外推分析,以獲取每個(gè)時(shí)刻的顫振邊界預(yù)測值,為試驗(yàn)過程的實(shí)時(shí)監(jiān)控及試驗(yàn)安全提供技術(shù)保障。
1 方法簡述
在平穩(wěn)系統(tǒng)模型建立中,非時(shí)變隨機(jī)信號可以看作是線性系統(tǒng)的白噪聲激勵(lì)響應(yīng),如下式:
[y(n)=-k=1paky(n-k)+k=0qbku(n-k)] (1)
式中:[y(n)]為非時(shí)變隨機(jī)信號;[u(n)]為系統(tǒng)的白噪聲激勵(lì)。
相應(yīng)的,由于在連續(xù)變速顫振試驗(yàn)中,試驗(yàn)對象的結(jié)構(gòu)模態(tài)參數(shù)會(huì)隨時(shí)間發(fā)生變化,因此,對公式(1)中的系數(shù)進(jìn)行改變,即可得到時(shí)變線性系統(tǒng)的參數(shù)模型,表示為:
[y(n)=-k=1pak(n)y(n-k)+k=0qbk(n)u(n-k)] (2)
公式(2)也被稱為非平穩(wěn)隨機(jī)信號的時(shí)變自回歸滑動(dòng)平均模型。若系數(shù)[bk(n)=0, k=1,2,3,…,]則模型變?yōu)榉瞧椒€(wěn)隨機(jī)信號的時(shí)變自回歸模型(TVAR)。
類似于平穩(wěn)系統(tǒng)模型的建立,時(shí)變隨機(jī)信號可以看作非平穩(wěn)線性系統(tǒng)的白噪聲激勵(lì)響應(yīng),在實(shí)際應(yīng)用中,通常采用時(shí)變自回歸模型,由公式⑵可以得到TVAR的參數(shù)模型為:
[y(n)=-k=1pak(n)y(n-k)+u(n)] (3)
式中:[y(n)]是時(shí)變隨機(jī)信號;[p]是模型階數(shù);[ak(n)]是時(shí)變AR系數(shù);[u(n)]是白噪聲激勵(lì)。
為求解時(shí)變AR系數(shù),將[ak(n)]用函數(shù)空間基函數(shù)的加權(quán)和表示為:
[ak(n)=i=0mbkifi(n)] (4)
式中:[bki]為加權(quán)系數(shù);[fi(n)]為選定函數(shù)空間的基函數(shù);[m]為函數(shù)空間的維數(shù)。
相應(yīng)的TVAR模型公式變?yōu)椋?/p>
[y(n)=-k=1pi=0mbki[fi(n)y(n-k)]+u(n)] (5)
定義矢量[Y(N-k)]和[θ:]
[Y(N-k)=[f0(n)y(n-k),…,fm(n)y(n-k)]] (6)
[θ=[a10,…,a1m,…,ap0,…,qpm]] (7)
這時(shí),TVAR模型的矩陣形式為:
[y(n)=-[Y(N-1),…,Y(n-p)]θT+u(n)] (8)
由此,將線性時(shí)變AR系數(shù)[ak(n)]的求解轉(zhuǎn)化成為求解線性時(shí)不變系統(tǒng)的加權(quán)系數(shù)向量[θ]的問題。解出[θ]后,結(jié)合選定函數(shù)空間的基函數(shù)[fi(n),]由公式(4)即可得到所建模型的時(shí)變AR系數(shù)。
本文選擇傅里葉基函數(shù)對時(shí)變AR系數(shù)進(jìn)行求解,其構(gòu)造公式為:
[fk(n)=coskπn2N,k為偶數(shù)sin(k+1)πn2N,k為奇數(shù)] (9)
由解得的時(shí)變AR系數(shù)[ak(n),]可以提取[n]時(shí)刻的穩(wěn)定性判據(jù),如Jury判據(jù),Lyapunov判據(jù)以及阻尼比系數(shù)等。依據(jù)[n]時(shí)刻對應(yīng)的速度值,以曲線擬合的方式對顫振邊界進(jìn)行預(yù)測。
2 仿真試驗(yàn)及結(jié)果
根據(jù)典型結(jié)構(gòu)顫振機(jī)理及其響應(yīng)信號特征,采用白噪聲激勵(lì)時(shí)變系統(tǒng)生成的仿真信號來測試本文方法的數(shù)值性能。
不排除一般性,典型的顫振現(xiàn)象往往在兩階結(jié)構(gòu)模態(tài)耦合時(shí)出現(xiàn),為此,模擬連續(xù)變速顫振響應(yīng)信號可由以下系統(tǒng)生成:
[x(t)=i=1nAie-ξi(t)fi(t)2πtcos2πfi(t)1-ξ2i(t)t] (10)
式中:[n]為模態(tài)個(gè)數(shù);[f]為頻率;[ξ]為阻尼比。在0時(shí)刻,各參數(shù)的初值分別為:[f1=]10 Hz,[f2=]20 Hz,[v=0,][ξ1=0.11,ξ2=0.1。]
為了模擬顫振發(fā)生過程,在歸一化速度線性增加的情況下,兩階模態(tài)的頻率逐漸靠攏直至完全重合,而阻尼比則逐漸衰減至零。經(jīng)過64 s運(yùn)行后仿真系統(tǒng)發(fā)生顫振,在采樣頻率為128 Hz情況下得到長度為8 192的隨機(jī)響應(yīng)信號,此時(shí)對應(yīng)的頻率為[f1=f2=]15 Hz,相應(yīng)的阻尼比系數(shù)為[ξ1=ξ2=0,]歸一化顫振速度為[v=1。]
在上述條件下生成的無噪聲仿真信號的時(shí)間歷程如圖1所示,相應(yīng)的聯(lián)合時(shí)頻分布如圖2所示。
圖1 仿真信號的時(shí)間歷程
圖2 仿真信號的聯(lián)合時(shí)頻圖
應(yīng)用本文方法對無噪聲干擾的仿真信號進(jìn)行顫振邊界外推計(jì)算,所得結(jié)果如圖3所示。圖中,縱軸為速度,[v=1]的直線標(biāo)示了顫振邊界的真值,橫軸為時(shí)間。由圖3可以看出,在無噪聲的情況下,本文方法計(jì)算的外推值從時(shí)刻[n=40]開始快速上升在[n=50]時(shí)到達(dá)真實(shí)值[v=1,]在其后的時(shí)間內(nèi),外推值在真值附近小幅波動(dòng),也就是說可以快速得到準(zhǔn)確穩(wěn)定的顫振邊界預(yù)測值。
為了進(jìn)一步測試本文方法在噪聲環(huán)境下的數(shù)值性能,定義信噪比:
[SNR=10×logPsignalPnoise] (11)
式中:[P]為信號的功率,在此定義下,計(jì)算并得到了信噪比分別為20 dB,14 dB,10 dB和8 dB的外推值曲線,如圖4所示。
圖3 無噪聲環(huán)境的顫振邊界預(yù)測結(jié)果
圖4 噪聲環(huán)境下顫振邊界預(yù)測結(jié)果
由圖4可以看出,信噪比為20 dB時(shí),外推值曲線盡管隨時(shí)間變化的趨勢有少許不同,但還是在[n=50]左右達(dá)到了真實(shí)值。當(dāng)信噪比下降到14 dB時(shí),外推值趨勢與無噪聲情況類似,但最終外推值在到達(dá)[v=]1.2附近時(shí)才趨于穩(wěn)定,顫振邊界預(yù)測值的精度也有所下降。若信噪比進(jìn)一步降低,可以看到外推值的平穩(wěn)趨勢開始消失,所得的外推結(jié)果已經(jīng)不宜在試驗(yàn)中作為參考。由此可見,本文方法對噪聲相對敏感。為此,在實(shí)際應(yīng)用中應(yīng)盡可能保證測試、采集、記錄等響應(yīng)信號獲取過程各環(huán)節(jié)的質(zhì)量。
3 試驗(yàn)數(shù)據(jù)處理
為了驗(yàn)證所研究方法的工程實(shí)用性,先后進(jìn)行了多次物理試驗(yàn)。作為舉例,這里僅給出一組試驗(yàn)結(jié)果。
試驗(yàn)數(shù)據(jù)取自某飛機(jī)氣彈模型低速風(fēng)洞試驗(yàn),對應(yīng)試驗(yàn)狀態(tài)由傳統(tǒng)臺(tái)階等速試驗(yàn)得到的顫振臨界速度為40.8 m/s。
實(shí)測信號的時(shí)間歷程及對應(yīng)的試驗(yàn)風(fēng)速變化曲線如圖5所示。
圖5 連續(xù)變速顫振試驗(yàn)實(shí)測數(shù)據(jù)
由圖5可見,選取的實(shí)測信號對應(yīng)的風(fēng)速以近似于線性增長的方式,經(jīng)過29 s從25 m/s提升至38 m/s。采用本文方法對該段實(shí)測數(shù)據(jù)進(jìn)行處理,所求的顫振邊界預(yù)測值曲線如圖6所示。
圖6 實(shí)測數(shù)據(jù)的顫振邊界預(yù)測結(jié)果
由圖6可以看出,本文方法的計(jì)算結(jié)果,于20 s左右達(dá)到了顫振臨界速度[v=]40.8 m/s附近,并趨于平穩(wěn)。此時(shí)對應(yīng)的速度為[v=]35 m/s,距離顫振速度尚有較大的安全空間。這表明,本文方法在連續(xù)變速顫振試驗(yàn)中,可以對顫振邊界進(jìn)行有效預(yù)測,并且保留了較大的安全裕量。
4 結(jié) 論
本文研究了基于基函數(shù)展開的時(shí)變參數(shù)建模方法及其在連續(xù)變速顫振試驗(yàn)中的應(yīng)用問題。通過數(shù)值仿真,驗(yàn)證并分析了方法的精度及抗噪性能。結(jié)果表明,該方法在較高信噪比下,可以得到滿意的預(yù)測值,但其精度會(huì)隨信噪比的減小而下降。而氣彈模型風(fēng)洞試驗(yàn)的應(yīng)用結(jié)果表明,該方法完全可以滿足工程實(shí)際的物理需求。
本文研究為豐富和擴(kuò)展連續(xù)變速顫振試驗(yàn)的在線監(jiān)控方法提供了一種新的手段,在航空、航天、導(dǎo)彈、亞太空等領(lǐng)域的結(jié)構(gòu)顫振試驗(yàn)方面有著潛在的應(yīng)用前景。
參考文獻(xiàn)
[1] COWAN T J, ARENA A S, GUPTA K K. Accelerating CFD?based aero elastic predictions using system identification [R/OL]. [2010?01?02]. http://www. citeseerx.ist.psu.edu.
[2] NAMARA J J, FRIEDMANN P P. Flutter boundary identification for time?domain computational aero elasticity [J]. American Institute of Aeronautics and Astronautics. 2007, 45(7): 1546?1554.
[3] MAHER Damien, Combined time and frequency domain approaches to the operational identification of vehicle suspension [D]. Ireland: School of Mechanical and Manufacturing Engineering, Dublin City University, 2011.
[4] Garrick I E, Reed W H. Historical development of aircraft flutter [J]. Journal of Aircraft, 1981, 18(11): 897?912.
[5] BAE J, KIM J, LEE I, et al. Extension of flutter prediction parameter for multimode flutter systems [J] Journal of Aircraft, 2005, 42(1): 285?288.
[6] MATSUZAKI Y, TORII H. Flutter boundary prediction of an adaptive smart wing during process of adaptation using steady?state response data [C]// 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Newport, RI: AIAA, 2006: 2132?2139.
[7] THURUTHIMATTAM, B J, FRIEDMANN P P, MCNAMARA J J, et al. Modeling approaches to hypersonic aerothermoelasticity with application to reusable launch vehicles [C]// 44th AIAA/ASME/ASCE/AHS Structures, Structural Dynamics and Materials Conference. Norfolk, VA: AIAA, 2003: 1967?1977.
[8] 朝倫巴根,賈德彬.數(shù)值計(jì)算方法[M].北京:中國水利水電出版社,2006.
[9] 王宏禹.非平穩(wěn)隨機(jī)信號分析與處理[M].北京:國防工業(yè)出版社,1999.
[10] 林青,戴慧珺,馬文濤.基于正交基函數(shù)神經(jīng)網(wǎng)絡(luò)的圖像加密算法仿真[J].計(jì)算機(jī)仿真,2013,30(10):416?421.
參考文獻(xiàn)
[1] COWAN T J, ARENA A S, GUPTA K K. Accelerating CFD?based aero elastic predictions using system identification [R/OL]. [2010?01?02]. http://www. citeseerx.ist.psu.edu.
[2] NAMARA J J, FRIEDMANN P P. Flutter boundary identification for time?domain computational aero elasticity [J]. American Institute of Aeronautics and Astronautics. 2007, 45(7): 1546?1554.
[3] MAHER Damien, Combined time and frequency domain approaches to the operational identification of vehicle suspension [D]. Ireland: School of Mechanical and Manufacturing Engineering, Dublin City University, 2011.
[4] Garrick I E, Reed W H. Historical development of aircraft flutter [J]. Journal of Aircraft, 1981, 18(11): 897?912.
[5] BAE J, KIM J, LEE I, et al. Extension of flutter prediction parameter for multimode flutter systems [J] Journal of Aircraft, 2005, 42(1): 285?288.
[6] MATSUZAKI Y, TORII H. Flutter boundary prediction of an adaptive smart wing during process of adaptation using steady?state response data [C]// 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Newport, RI: AIAA, 2006: 2132?2139.
[7] THURUTHIMATTAM, B J, FRIEDMANN P P, MCNAMARA J J, et al. Modeling approaches to hypersonic aerothermoelasticity with application to reusable launch vehicles [C]// 44th AIAA/ASME/ASCE/AHS Structures, Structural Dynamics and Materials Conference. Norfolk, VA: AIAA, 2003: 1967?1977.
[8] 朝倫巴根,賈德彬.數(shù)值計(jì)算方法[M].北京:中國水利水電出版社,2006.
[9] 王宏禹.非平穩(wěn)隨機(jī)信號分析與處理[M].北京:國防工業(yè)出版社,1999.
[10] 林青,戴慧珺,馬文濤.基于正交基函數(shù)神經(jīng)網(wǎng)絡(luò)的圖像加密算法仿真[J].計(jì)算機(jī)仿真,2013,30(10):416?421.
參考文獻(xiàn)
[1] COWAN T J, ARENA A S, GUPTA K K. Accelerating CFD?based aero elastic predictions using system identification [R/OL]. [2010?01?02]. http://www. citeseerx.ist.psu.edu.
[2] NAMARA J J, FRIEDMANN P P. Flutter boundary identification for time?domain computational aero elasticity [J]. American Institute of Aeronautics and Astronautics. 2007, 45(7): 1546?1554.
[3] MAHER Damien, Combined time and frequency domain approaches to the operational identification of vehicle suspension [D]. Ireland: School of Mechanical and Manufacturing Engineering, Dublin City University, 2011.
[4] Garrick I E, Reed W H. Historical development of aircraft flutter [J]. Journal of Aircraft, 1981, 18(11): 897?912.
[5] BAE J, KIM J, LEE I, et al. Extension of flutter prediction parameter for multimode flutter systems [J] Journal of Aircraft, 2005, 42(1): 285?288.
[6] MATSUZAKI Y, TORII H. Flutter boundary prediction of an adaptive smart wing during process of adaptation using steady?state response data [C]// 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Newport, RI: AIAA, 2006: 2132?2139.
[7] THURUTHIMATTAM, B J, FRIEDMANN P P, MCNAMARA J J, et al. Modeling approaches to hypersonic aerothermoelasticity with application to reusable launch vehicles [C]// 44th AIAA/ASME/ASCE/AHS Structures, Structural Dynamics and Materials Conference. Norfolk, VA: AIAA, 2003: 1967?1977.
[8] 朝倫巴根,賈德彬.數(shù)值計(jì)算方法[M].北京:中國水利水電出版社,2006.
[9] 王宏禹.非平穩(wěn)隨機(jī)信號分析與處理[M].北京:國防工業(yè)出版社,1999.
[10] 林青,戴慧珺,馬文濤.基于正交基函數(shù)神經(jīng)網(wǎng)絡(luò)的圖像加密算法仿真[J].計(jì)算機(jī)仿真,2013,30(10):416?421.