本文選題：自錨式懸索橋　切入點(diǎn)：損傷識別　出處：《蘭州交通大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：結(jié)構(gòu)工程在服役期內(nèi),長期受到靜、動(dòng)態(tài)荷載作用,結(jié)構(gòu)材料遭到大氣環(huán)境的腐蝕和破壞,隨著時(shí)間的增長必有損傷發(fā)生。如若結(jié)構(gòu)損傷不能得以發(fā)現(xiàn)并及時(shí)修復(fù),必然存在著極大的安全隱患。尤其橋梁結(jié)構(gòu)是公路和鐵路的咽喉,一旦發(fā)生破壞造成的損傷和影響是極大的。所以及時(shí)檢測發(fā)現(xiàn)橋梁損傷位置及損傷大小,進(jìn)行維修加固并對橋梁結(jié)構(gòu)工作狀態(tài)進(jìn)行安全評估,是當(dāng)下的熱門研究課題,同時(shí)也具有非常重要的研究意義和實(shí)用意義。結(jié)構(gòu)損傷識別是橋梁結(jié)構(gòu)健康監(jiān)測的重要組成部分,現(xiàn)階段根據(jù)測量數(shù)據(jù)的不同將結(jié)構(gòu)損傷檢測識別分為兩大類:即基于靜態(tài)測量數(shù)據(jù)和基于動(dòng)態(tài)測量數(shù)據(jù)進(jìn)行損傷識別,利用結(jié)構(gòu)的動(dòng)靜態(tài)參數(shù)的變化來識別結(jié)構(gòu)的損傷是一個(gè)研究熱點(diǎn),相比于動(dòng)態(tài)數(shù)據(jù),靜態(tài)數(shù)據(jù)易采集且精度較高,對結(jié)構(gòu)損傷較敏感,因此本文主要是基于靜態(tài)測量數(shù)據(jù)進(jìn)行懸索橋的損傷識別。本文在系統(tǒng)了解結(jié)構(gòu)損傷識別方法和現(xiàn)狀的基礎(chǔ)上,基于灰色關(guān)聯(lián)理論和遺傳算法兩步法進(jìn)行損傷識別。通過對自錨式懸索橋損傷識別數(shù)值研究證明了該方法有效性。主要研究內(nèi)容如下:(1)運(yùn)用Midas有限元軟件建立跨湟水河自錨式懸索橋的有限元模型,進(jìn)行初始平衡狀態(tài)分析。對于自錨式懸索橋,其易損構(gòu)件為主梁,其損傷后會(huì)對吊桿產(chǎn)生影響,使吊桿內(nèi)力重新分配。因此在自錨式懸索橋有限元模型中,通過調(diào)整不同吊桿的初拉力改變吊桿力模擬由于主梁損傷引起的吊桿內(nèi)力變化,并提取由此引起的靜態(tài)數(shù)據(jù)位移變化值進(jìn)行損傷識別;(2)基于灰色關(guān)聯(lián)理論知識,運(yùn)用靜態(tài)位移曲率置信因子(SDCAC)識別橋梁損傷發(fā)生位置。根據(jù)損傷前后結(jié)構(gòu)節(jié)點(diǎn)位移曲率置信因子大小,判斷節(jié)點(diǎn)損傷前后的位移曲率關(guān)聯(lián)度大小,進(jìn)而識別損傷發(fā)生的位置。通過對簡支梁損傷識別結(jié)果得出該方法對結(jié)構(gòu)局部位置損傷定位的有效性。十種吊桿力變化工況下湟水河自錨式懸索橋橋跨方向上梁單元節(jié)點(diǎn)SDCAC曲線變化,判斷不同的損傷位置,結(jié)果表明該方法對于大型復(fù)雜的懸索橋也是有效的。(3)基于遺傳算法知識,對基本的遺傳算法進(jìn)行改進(jìn),采用最優(yōu)保存策略及自適應(yīng)交叉和變異概率,提高遺傳算法的優(yōu)化性能。以結(jié)構(gòu)損傷前后應(yīng)變差最小建立目標(biāo)函數(shù),對結(jié)構(gòu)損傷程度大小進(jìn)行識別。在第一步損傷定位的基礎(chǔ)上識別懸索橋在不同損傷工況下的損傷程度。懸索橋數(shù)值研究結(jié)果該方法識別損傷程度大小的有效性。(4)總結(jié)本文研究內(nèi)容,指出懸索橋損傷識所用方法的優(yōu)勢和存在的不足,并對結(jié)構(gòu)損傷識別未來的發(fā)展方向做了展望,將動(dòng)態(tài)和靜態(tài)數(shù)據(jù)項(xiàng)結(jié)合進(jìn)行結(jié)構(gòu)的損傷識別。
[Abstract]:During the service period, structural engineering is subjected to static and dynamic loads for a long time, structural materials are corroded and destroyed by atmospheric environment, and damage will occur with the increase of time. If the structural damage can not be found and repaired in time, The bridge structure is the throat of the highway and the railway, and the damage and influence caused by the damage is great. Therefore, the damage location and the damage size of the bridge are detected in time. It is a hot research topic to carry out maintenance and reinforcement and evaluate the safety of bridge structure working state. At the same time, it also has very important research significance and practical significance. Structural damage identification is an important part of bridge structure health monitoring. At present, according to the difference of measurement data, structural damage detection and identification is divided into two categories: static measurement data and dynamic measurement data to identify damage. It is a hot topic to identify the damage of structure by using the change of dynamic and static parameters. Compared with the dynamic data, the static data is easy to collect and the accuracy is high, and it is sensitive to the damage of the structure. Therefore, the damage identification of suspension bridge is mainly based on static measurement data. Based on grey correlation theory and genetic algorithm two-step method for damage identification, the effectiveness of the method is proved by numerical research on self-anchored suspension bridge. The main research contents are as follows: 1) using Midas finite element software to establish span. Finite element Model of Self-anchored suspension Bridge in Huangshui River, For the self-anchored suspension bridge, the damage of the main beam of the vulnerable member will affect the suspension rod and make the internal force of the suspension rod redistribution. Therefore, in the finite element model of the self-anchored suspension bridge, the internal force of the suspension rod will be redistributed, so in the finite element model of the self-anchored suspension bridge, the internal force of the suspension rod will be redistributed. By adjusting the initial tension of different suspenders to change the force of the suspenders, simulating the changes of the internal forces of the suspenders caused by the damage of the main beam, and extracting the values of the static data displacement changes caused by the changes, the damage identification is carried out on the basis of the grey correlation theory. The static displacement curvature confidence factor (SDCAC) is used to identify the location of bridge damage. According to the magnitude of displacement curvature confidence factor of structural nodes before and after damage, the correlation degree of displacement curvature before and after damage is determined. Through the result of damage identification of simply supported beam, the effectiveness of this method for location of local location damage of structure is obtained. On the condition of 10 kinds of suspender force changing working conditions, the upper beam of Huangshui River self-anchored suspension bridge in span direction is obtained from the result of damage identification of simply supported beam. Unit node SDCAC curve change, The results show that this method is effective for large and complex suspension bridges. Based on the knowledge of genetic algorithm, the basic genetic algorithm is improved, and the optimal preservation strategy and adaptive crossover and mutation probability are adopted. In order to improve the optimization performance of genetic algorithm, the objective function is established based on the minimum strain difference before and after structural damage. Based on the first step of damage location, the damage degree of suspension bridge under different damage conditions is identified. The numerical results of the suspension bridge show that the method is effective in identifying the damage degree. Summarizing the contents of this paper, This paper points out the advantages and disadvantages of the damage identification methods of suspension bridges, and looks forward to the development of structural damage identification in the future. The dynamic and static data items are combined to identify the structural damage.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U446;U448.25

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