基于UKF的橋梁空間結(jié)構(gòu)損傷識別研究
發(fā)布時間：2018-07-20 11:55
【摘要】：橋梁結(jié)構(gòu)受自然環(huán)境和人為等因素的影響,在正常使用期間會出現(xiàn)損傷,并會隨時間逐步積累,最終可能導(dǎo)致嚴(yán)重的工程事故。在事故發(fā)生前通過結(jié)構(gòu)健康監(jiān)測,識別結(jié)構(gòu)損傷,掌握結(jié)構(gòu)工作狀態(tài),對于保障結(jié)構(gòu)安全、預(yù)防突發(fā)事故具有重大價(jià)值。在眾多損傷識別方法中,基于UT變換的無跡卡爾曼濾波方法(UKF)是一種遞推型的模型修正方法。與傳統(tǒng)時域方法相比,UKF可以通過遞推的方式得到狀態(tài)的最優(yōu)估計(jì);與擴(kuò)展卡爾曼濾波方法相比,對于非線性系統(tǒng)參數(shù)識別問題,不需要求解復(fù)雜的雅克比矩陣且具有更高的精度。針對UKF在結(jié)構(gòu)損傷識別反問題中存在的不適定性,本文基于偽測量技術(shù)提出了結(jié)合pl范數(shù)正則化的UKF方法,可以有效利用不同類型的橋梁損傷先驗(yàn)信息來提高損傷識別效果;并以此為基礎(chǔ)將結(jié)合正則化的UKF應(yīng)用到考慮空間特性的橋梁損傷識別中。具體的研究工作如下:(1)利用模態(tài)坐標(biāo)代替結(jié)構(gòu)節(jié)點(diǎn)響應(yīng)構(gòu)建UKF的狀態(tài)向量,采取模態(tài)截?cái)嗉记捎行Эs減狀態(tài)向量維數(shù);并將損傷參數(shù)添加到狀態(tài)向量當(dāng)中,構(gòu)造結(jié)構(gòu)狀態(tài)與結(jié)構(gòu)參數(shù)混合識別問題;進(jìn)而利用結(jié)構(gòu)的自由振動觀測值,通過遞推計(jì)算在得到狀態(tài)最優(yōu)估計(jì)的同時識別損傷。(2)為充分利用人工巡檢等方式得到的橋梁損傷先驗(yàn)信息,本文基于偽測量技術(shù),提出將UKF結(jié)合pl范數(shù)正則化方法識別結(jié)構(gòu)損傷。根據(jù)結(jié)構(gòu)的損傷特點(diǎn)可以選擇不同的正則化方法,有效緩解了反問題求解的不適定性,提高了損傷識別的精度。論文首先以簡支梁為代表的數(shù)值算例對兩種pl正則化方法進(jìn)行了比較,分析了不同正則化方法的識別效果和適用的損傷情況;進(jìn)而考慮具有局部損傷特點(diǎn)結(jié)構(gòu),以平面桁架為代表重點(diǎn)驗(yàn)證了結(jié)合1l范數(shù)正則化的UKF方法有效性。(3)在橋梁結(jié)構(gòu)損傷識別分析中,簡化的梁式結(jié)構(gòu)是目前最為常見的分析模型;但實(shí)際的橋梁都是三維結(jié)構(gòu),具有空間特性�？紤]空間橋梁結(jié)構(gòu)時,結(jié)構(gòu)變形、損傷分區(qū)和測點(diǎn)布置跟一維梁式結(jié)構(gòu)都有很大的區(qū)別。論文選取板梁橋和T型梁橋兩種代表性橋梁作為研究對象,進(jìn)行損傷識別的研究。首先利用ANSYS建立了具有空間特性的板梁橋結(jié)構(gòu),考慮結(jié)構(gòu)損傷為局部損傷,研究UKF結(jié)合1l范數(shù)正則化方法對板梁橋的識別效果,重點(diǎn)研究板梁橋的空間分區(qū)和測點(diǎn)布置方案對損傷識別的影響;在針對T型梁橋的分析中,分別以濕接縫、橫隔板、主梁為損傷對象進(jìn)行損傷識別,同時還分析了不同的模態(tài)信息、不同的分區(qū)數(shù)目、不同的測點(diǎn)布置方案對濕接縫的識別影響。結(jié)果表明,對于具有空間特性的橋梁空間結(jié)構(gòu),UKF結(jié)合正則化方法可以有效識別損傷,同時具備很強(qiáng)的魯棒性和一定的抗噪聲能力。
[Abstract]:Under the influence of natural environment and human factors, the bridge structure will be damaged during normal use and will accumulate gradually with time, which may eventually lead to serious engineering accidents. Before the accident happens, it is of great value to monitor the structure health, identify the structural damage and master the working state of the structure to ensure the safety of the structure and to prevent the sudden accident. The unscented Kalman filter (UKF) based on UT transform is a recursive model correction method among many damage identification methods. Compared with the traditional time domain method, the UKF can obtain the optimal state estimation by recursive method, and compared with the extended Kalman filtering method, the parameter identification problem of nonlinear systems can be obtained. It is not necessary to solve complex Jacobian matrix and has higher accuracy. In view of the ill-posed nature of UKF in the inverse problem of structural damage identification, a new UKF method combining pl norm regularization is proposed based on pseudo-measurement technique, which can effectively use different prior information of bridge damage to improve the damage identification effect. Based on this, the UKF combined with regularization is applied to bridge damage identification considering spatial characteristics. The specific research works are as follows: (1) the state vector of UKF is constructed by using modal coordinate instead of structural node response, the dimension of state vector is reduced effectively by modal truncation technique, and the damage parameter is added to the state vector. The problem of mixed identification of structural state and structural parameters is discussed, and then the free vibration observation value of the structure is used. In order to make full use of the prior information of bridge damage obtained by manual inspection, this paper is based on pseudo-measurement technology. The UKF combined with pl norm regularization method is proposed to identify structural damage. According to the damage characteristics of structures, different regularization methods can be chosen, which can effectively alleviate the ill-posed problem solving and improve the accuracy of damage identification. In this paper, the numerical example of simply supported beam is given to compare the two pl regularization methods, and the identification effect and the applicable damage of the different regularization methods are analyzed, and then the local damage characteristic structure is considered Taking plane truss as the representative, the validity of UKF method combined with 1l norm regularization is verified. (3) in the damage identification analysis of bridge structures, the simplified beam structure is the most common analysis model, but the actual bridges are three-dimensional structures. It has spatial characteristics. When considering the spatial bridge structure, the structural deformation, damage zoning and measuring point arrangement are different from the one-dimensional beam structure. In this paper, two kinds of representative bridges, slab girder bridge and T beam bridge, are selected as research objects to study damage identification. Firstly, the structure of slab girder bridge with spatial characteristics is established by ANSYS. Considering the damage of the structure as local damage, the recognition effect of UKF combined with 1l norm regularization method for slab girder bridge is studied. In the analysis of T-beam bridge, the wet joint, transverse diaphragm and main girder are respectively used as the damage objects to identify the damage. At the same time, the effects of different modal information, different number of zones and different layout of measuring points on the identification of wet joints are analyzed. The results show that the UKF combined with regularization method can effectively identify the damage, and has strong robustness and anti-noise ability.
【學(xué)位授予單位】：南昌大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U441.4
本文編號：2133436
[Abstract]:Under the influence of natural environment and human factors, the bridge structure will be damaged during normal use and will accumulate gradually with time, which may eventually lead to serious engineering accidents. Before the accident happens, it is of great value to monitor the structure health, identify the structural damage and master the working state of the structure to ensure the safety of the structure and to prevent the sudden accident. The unscented Kalman filter (UKF) based on UT transform is a recursive model correction method among many damage identification methods. Compared with the traditional time domain method, the UKF can obtain the optimal state estimation by recursive method, and compared with the extended Kalman filtering method, the parameter identification problem of nonlinear systems can be obtained. It is not necessary to solve complex Jacobian matrix and has higher accuracy. In view of the ill-posed nature of UKF in the inverse problem of structural damage identification, a new UKF method combining pl norm regularization is proposed based on pseudo-measurement technique, which can effectively use different prior information of bridge damage to improve the damage identification effect. Based on this, the UKF combined with regularization is applied to bridge damage identification considering spatial characteristics. The specific research works are as follows: (1) the state vector of UKF is constructed by using modal coordinate instead of structural node response, the dimension of state vector is reduced effectively by modal truncation technique, and the damage parameter is added to the state vector. The problem of mixed identification of structural state and structural parameters is discussed, and then the free vibration observation value of the structure is used. In order to make full use of the prior information of bridge damage obtained by manual inspection, this paper is based on pseudo-measurement technology. The UKF combined with pl norm regularization method is proposed to identify structural damage. According to the damage characteristics of structures, different regularization methods can be chosen, which can effectively alleviate the ill-posed problem solving and improve the accuracy of damage identification. In this paper, the numerical example of simply supported beam is given to compare the two pl regularization methods, and the identification effect and the applicable damage of the different regularization methods are analyzed, and then the local damage characteristic structure is considered Taking plane truss as the representative, the validity of UKF method combined with 1l norm regularization is verified. (3) in the damage identification analysis of bridge structures, the simplified beam structure is the most common analysis model, but the actual bridges are three-dimensional structures. It has spatial characteristics. When considering the spatial bridge structure, the structural deformation, damage zoning and measuring point arrangement are different from the one-dimensional beam structure. In this paper, two kinds of representative bridges, slab girder bridge and T beam bridge, are selected as research objects to study damage identification. Firstly, the structure of slab girder bridge with spatial characteristics is established by ANSYS. Considering the damage of the structure as local damage, the recognition effect of UKF combined with 1l norm regularization method for slab girder bridge is studied. In the analysis of T-beam bridge, the wet joint, transverse diaphragm and main girder are respectively used as the damage objects to identify the damage. At the same time, the effects of different modal information, different number of zones and different layout of measuring points on the identification of wet joints are analyzed. The results show that the UKF combined with regularization method can effectively identify the damage, and has strong robustness and anti-noise ability.
【學(xué)位授予單位】：南昌大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U441.4
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 張春麗;呂中榮;;基于響應(yīng)靈敏度分析的橋梁結(jié)構(gòu)損傷和車輛參數(shù)的識別[J];振動與沖擊;2016年09期
2 張喜剛;劉高;馬軍海;吳宏波;付佰勇;高原;;中國橋梁技術(shù)的現(xiàn)狀與展望[J];科學(xué)通報(bào);2016年Z1期
3 邱飛力;張立民;張衛(wèi)華;;基于模態(tài)柔度矩陣的結(jié)構(gòu)損傷識別[J];噪聲與振動控制;2015年04期
4 雷鷹;李青;;基于擴(kuò)展卡爾曼濾波的框架梁柱節(jié)點(diǎn)地震損傷識別[J];土木工程學(xué)報(bào);2013年S1期
5 杜永峰;李萬潤;李慧;劉迪;;基于時間序列分析的結(jié)構(gòu)損傷識別[J];振動與沖擊;2012年12期
6 劉娟;黃維平;石湘;;基于遺傳算法的海洋平臺損傷診斷[J];振動.測試與診斷;2012年02期
7 尹強(qiáng);周麗;;基于EKF方法的橡膠隔震支座參數(shù)識別實(shí)驗(yàn)研究[J];南京航空航天大學(xué)學(xué)報(bào);2012年01期
8 周麗;汪新明;尹強(qiáng);;利用序貫非線性最小二乘技術(shù)識別隔震支座模型的參數(shù)[J];振動工程學(xué)報(bào);2010年01期
9 謝強(qiáng);唐和生;邸元;;SVD-Unscented卡爾曼濾波的非線性結(jié)構(gòu)系統(tǒng)識別[J];應(yīng)用力學(xué)學(xué)報(bào);2008年01期
10 朱勁松;肖汝誠;;基于定期檢測與遺傳算法的大跨度斜拉橋損傷識別[J];土木工程學(xué)報(bào);2006年05期
相關(guān)博士學(xué)位論文 前3條
1 劉宇飛;基于模型修正與圖像處理的多尺度結(jié)構(gòu)損傷識別[D];清華大學(xué);2015年
2 孫杰;基于多模態(tài)參數(shù)的橋梁結(jié)構(gòu)損傷識別方法研究[D];武漢理工大學(xué);2013年
3 譚冬梅;基于小波分析的空間桿系結(jié)構(gòu)的損傷識別[D];武漢理工大學(xué);2007年
相關(guān)碩士學(xué)位論文 前5條
1 楊洋;基于時域響應(yīng)結(jié)構(gòu)有限元模型修正方法研究[D];蘭州理工大學(xué);2016年
2 洪祖江;基于正則化有限元模型修正方法的結(jié)構(gòu)損傷識別[D];南昌大學(xué);2013年
3 張健;自適應(yīng)子結(jié)構(gòu)擬動力試驗(yàn)方法[D];哈爾濱工業(yè)大學(xué);2010年
4 張吉剛;基于模態(tài)應(yīng)變能的梁橋損傷識別[D];西南交通大學(xué);2007年
5 武魏娜;土木工程結(jié)構(gòu)參數(shù)識別時域法研究[D];天津大學(xué);2006年
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