彭凡+王樑+肖健+胡絢+韋冰峰2
摘 要:基于加速度頻響函數(shù)矩陣反演頻域動(dòng)載荷是病態(tài)逆問題,反求的結(jié)果精度差,對(duì)數(shù)據(jù)的小擾動(dòng)敏感,基于Tikhonov正則化方法,提出一種反演途徑,將測(cè)點(diǎn)響應(yīng)與待求激勵(lì)進(jìn)行歸一化變換,在此基礎(chǔ)上引入變換后的頻響函數(shù)矩陣和正則化泛函進(jìn)行求解,應(yīng)用廣義交叉驗(yàn)證準(zhǔn)則選取最優(yōu)正則化參數(shù).考慮簡支矩形薄板上的4個(gè)動(dòng)載荷的識(shí)別問題,分析激勵(lì)點(diǎn)和響應(yīng)測(cè)點(diǎn)的不同位置以及動(dòng)載荷大小之間相差程度不同的4個(gè)算例,將本文方法與不采用歸一化變換的正則化求解結(jié)果進(jìn)行2種相對(duì)誤差的均方根比較.結(jié)果表明,利用歸一化變換可提高動(dòng)載荷反演精度,增強(qiáng)正則化方法的抗噪能力,當(dāng)測(cè)點(diǎn)之間的響應(yīng)以及各動(dòng)載荷大小相差較大時(shí),明顯改善了識(shí)別精度.
關(guān)鍵詞:動(dòng)態(tài)載荷;頻響函數(shù);反問題;正則化;歸一化
中圖分類號(hào):O326;O347.1 文獻(xiàn)標(biāo)志碼:A
A Regularization Approach of Dynamic Load Identification
in Frequency Domain by Acceleration Responses
PENG Fan1 ,WANG Liang1,XIAO Jian2,HU Xuan1 , WEI Bingfeng2
( 1. College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China;
2. Research Institute of Beijing Structure and Environment Engineering,Beijing 100076, China)
Abstract:Load identification based on acceleration frequency response matrix is an ill-conditioned problem. The identification accuracy can obviously be affected by small perturbations of the response data. Based on Tikhonov regularization method, a new approach is proposed in which both the response data at measured points and the loads to be identified are normalized, the transformed frequency response matrix and regularization function are introduced, and the corresponding problem of functional minimum is solved to obtain the loads. The optimal regularization parameters are determined by generalized cross validation criterion. The identification of four transverse dynamic loads on a rectangular thin plate with simply supported edges is performed. Four numerical examples are designed to have different application locations of loads and measured points as well as different magnitude ratio of dynamic loads in frequency domain. The results show that the new approach of dynamic load identification in frequency domain is effective to improve the identification accuracy and the noise resistance. Particularly, the errors of the identification can be significantly reduced in the cases where the large difference between the magnitudes of dynamic loads in frequency domain exists, or when excitation positions are close to structural boundaries.
Key words:dynamic loads; frequency response function; inverse problem; regularization; normalization
載荷識(shí)別的理論和應(yīng)用研究受到了研究者越來越多的重視[1-5],目前,人們已提出了多種頻域內(nèi)反演動(dòng)態(tài)載荷的技術(shù),其中頻響函數(shù)矩陣求逆是一類重要方法[6-7].然而,反演的病態(tài)特性使得量測(cè)數(shù)據(jù)的小擾動(dòng)導(dǎo)致結(jié)果不準(zhǔn)確,甚至不可信.當(dāng)以測(cè)點(diǎn)的加速度頻域響應(yīng)作為輸入時(shí),低頻段的反演誤差非常明顯.正則化方法是提高反求精度和穩(wěn)健性的一條重要途徑,典型的正則化方法包括截?cái)嗥娈愔捣纸夂蚑ikhonov正則化方法[8].截?cái)嗥娈愔捣纸夥ǖ幕舅枷胧菍⑺玫膹V義解式子右端進(jìn)行截?cái)郲9],即只保留前面若干個(gè)對(duì)應(yīng)于較大奇異值的部分,將后面的對(duì)應(yīng)于較小奇異值的部分過濾掉,如何選取截?cái)嚅撝担窃摲椒ǖ碾y點(diǎn).Tikhonov正則化方法通過引入包含響應(yīng)殘差和激勵(lì)的模的泛函,由泛函對(duì)載荷的一階偏導(dǎo)為零,得到正則化以后的激勵(lì)求解列式[10-11].文獻(xiàn)[12-13]提出綜合使用奇異值分解法與Tikhonov正則化的載荷識(shí)別策略,當(dāng)頻響函數(shù)矩陣的條件數(shù)大于某一臨界值時(shí),使用正則化技術(shù),反之,由奇異值分解法實(shí)施反求.張磊等[14]提出在總體最小二乘算法的基礎(chǔ)上進(jìn)行Tikhonov正則化,利用共軛梯度法解算該目標(biāo)函數(shù)的最優(yōu)化問題.然而,當(dāng)各響應(yīng)測(cè)點(diǎn)的響應(yīng)之間、響應(yīng)與激勵(lì)之間以及激勵(lì)與激勵(lì)之間在數(shù)量上差別大,會(huì)導(dǎo)致正則化方法效果差,有必要重新考察變分泛函的構(gòu)造.為此,文中由歸一化變換使得加速度響應(yīng)和激勵(lì)的模值在一個(gè)相近的范圍內(nèi)變化,在此基礎(chǔ)上重新構(gòu)造變分泛函,給出一種Tikhonov正則化求解途徑,通過簡支矩形薄板的多點(diǎn)載荷反求算例檢驗(yàn)其有效性.
2 算例及討論
2.1 算例設(shè)計(jì)及誤差定義
2.2 算例1
對(duì)于表1所示位置組合Ⅰ的動(dòng)載荷,考慮加載條件Ⅰ,分別采用不經(jīng)歸一化處理和經(jīng)過歸一化處理的正則化方法反求載荷,結(jié)果如圖2所示.由圖2可知, 4個(gè)反演載荷均在低頻范圍內(nèi)波動(dòng)大,在較高頻段內(nèi),反求值與實(shí)際值相差很小.這是因?yàn)榛诩铀俣确辞蟮哪孢\(yùn)算項(xiàng)之模值隨頻率減小而顯著增加,隨頻率增加而減小,故在低頻段,頻響函數(shù)矩陣求逆的條件數(shù)較大,導(dǎo)致較大的誤差與波動(dòng).圖2表明,歸一化變換后的正則化求解能提高識(shí)別精度,尤其在低頻段內(nèi),效果明顯.而在大于二階基頻(約45 Hz)的頻率段,兩種反演途徑給出的結(jié)果接近相同.
分析載荷頻域值相同的加載條件Ⅱ,識(shí)別誤差結(jié)果如表4所示.由表4可知,2種正則化途徑所得結(jié)果的誤差相比表3列出的對(duì)應(yīng)值減小,歸一化處理對(duì)F1,F(xiàn)2和F3的識(shí)別效果改善較小,但明顯提高了F4的識(shí)別精度.這是因?yàn)镕4接近邊界,產(chǎn)生的測(cè)點(diǎn)加速度響應(yīng)小,歸一化變換將其影響放大了,使得其識(shí)別精度得到提高.
2.3 算例2
分析位置組合Ⅱ,首先考慮載荷條件Ⅰ,誤差結(jié)果如表5所示.比較表5與表3可見, F4的誤差減小,而F1的誤差有所增加,主要原因是此位置組合中的F4作用點(diǎn)靠近板中部,從而激發(fā)了較強(qiáng)的響應(yīng),而F1相對(duì)其余3個(gè)載荷更靠近邊界.歸一化變換改善了反求的總體精度,且明顯降低了F4的相對(duì)誤差.
考慮載荷條件Ⅱ,誤差如表6所示.從總體和個(gè)體來看,2種正則化途徑所給結(jié)果的識(shí)別精度接近相同,原因在于4個(gè)頻域載荷相同,且作用點(diǎn)離邊界較遠(yuǎn)以及各測(cè)點(diǎn)頻域相應(yīng)的強(qiáng)度接近相同.同樣由于F1離邊界相對(duì)最近,故識(shí)別誤差最大的載荷由F4變成了F1,而歸一化處理使得F1的識(shí)別誤差略有減小.
3 結(jié) 論
在頻域中采用歸一化變換,將各測(cè)點(diǎn)響應(yīng)和待求載荷的大小變化調(diào)整到相近的范圍,構(gòu)造新的Tikhonov泛函進(jìn)行正則化求解.利用數(shù)值仿真所得結(jié)果可知:
1)歸一化處理能從整體和個(gè)體上提高各動(dòng)載荷的反演精度.
2)當(dāng)頻域動(dòng)載荷大小相差較明顯,或者載荷作用點(diǎn)靠近邊界時(shí),歸一化處理使得相應(yīng)荷載的反求精度明顯改善,抵抗測(cè)量噪性干擾的能力增強(qiáng).
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