本文關(guān)鍵詞：高層建筑風(fēng)荷載識(shí)別研究　出處：《武漢理工大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 風(fēng)工程 時(shí)程分析 參數(shù)識(shí)別 復(fù)合反演

【摘要】：近一百年來,高層建筑飛速發(fā)展,高層建筑越來越高,結(jié)構(gòu)的柔度越來越大,盡管至今還沒有因?yàn)轱L(fēng)荷載導(dǎo)致高層建筑倒塌的事故發(fā)生,但是在強(qiáng)風(fēng)的過程中超高層建筑因?yàn)檎駝?dòng)過大致使使用者不適的現(xiàn)象卻常有發(fā)生。在這種情況下風(fēng)荷載應(yīng)該成為超高層建筑設(shè)計(jì)安全性和實(shí)用性的控制荷載;所以,我們需要了解風(fēng)荷載。但是因?yàn)轱L(fēng)荷載的很多數(shù)據(jù)都是來自氣象部門或者是軍事部門,并且與風(fēng)工程研究的方向不同,因此關(guān)于風(fēng)荷載的記錄比較少;直接去測(cè)量風(fēng)荷載是很難的,而對(duì)響應(yīng)的測(cè)量會(huì)簡(jiǎn)單很多,所以近些年來,通過測(cè)量出結(jié)構(gòu)的響應(yīng)再來反演出風(fēng)荷載成為獲得風(fēng)荷載數(shù)據(jù)的新方法,本文就將詳細(xì)介紹風(fēng)荷載復(fù)合反演的內(nèi)容。本文運(yùn)用的方法是荷載歸一化統(tǒng)計(jì)平均算法,這種方法是在脈動(dòng)風(fēng)相關(guān)性的假定下,運(yùn)用動(dòng)力系統(tǒng)狀態(tài)方程的經(jīng)典形式和最小二乘準(zhǔn)則,在成功的推導(dǎo)出荷載歸一化統(tǒng)計(jì)平均算法以后,為后面的實(shí)例分析提供了方法上的支持;然后對(duì)此方法進(jìn)行了收斂性證明。在實(shí)際工程中,分為下面幾種情況:1.有噪聲和無噪聲情況的區(qū)別,2.不同的噪聲水平對(duì)反演結(jié)果的影響,3.不同脈動(dòng)風(fēng)相關(guān)性假定對(duì)反演結(jié)果的影響等。無噪聲的情況下進(jìn)行結(jié)構(gòu)的物理參數(shù)識(shí)別,取不同的初值,經(jīng)計(jì)算最大誤差不超過0.99%;同樣,反演出的風(fēng)荷載與真實(shí)值的誤差也較小,在1.25%以內(nèi)說明此方法在剛度識(shí)別方面的準(zhǔn)確性與假設(shè)的初始剛度無關(guān),結(jié)果令人滿意。我們?cè)谠肼曀綖?5%的情況下觀察剛度識(shí)別結(jié)果和風(fēng)荷載反演結(jié)果在脈動(dòng)風(fēng)相關(guān)性系數(shù)ρ分別為4、8、12的三種情況;結(jié)果發(fā)現(xiàn),不同脈動(dòng)風(fēng)相關(guān)性系數(shù)對(duì)剛度的識(shí)別結(jié)果和反演結(jié)果影響不大,但是在相關(guān)性系數(shù)ρ最小為4的時(shí)候,剛度識(shí)別結(jié)果風(fēng)荷載反演結(jié)果較好,更符合實(shí)際情況。為了驗(yàn)證該算法的抗噪聲性能,我們加入不同噪聲水平的高斯白噪聲到理論計(jì)算中,結(jié)果說明,在低噪聲情況下(5%,15%),由于剛度識(shí)別的準(zhǔn)確度很高,所以反演得到的風(fēng)荷載也具有較好的準(zhǔn)確性;可是如果噪聲水平達(dá)到30%,風(fēng)荷載的識(shí)別結(jié)果出現(xiàn)的誤差較大達(dá)到9.3%。整體來看,大量的理論分析和數(shù)值分析表明了本文提出的荷載歸一化復(fù)合反演算法的有效性和實(shí)用性。
[Abstract]:In the past one hundred years, the rapid development of high-rise buildings, high-rise building more and more high, more and more flexibility structure, although has not occurred because of wind load to high-rise building collapse accidents, but in the process of high-rise building in strong winds because the vibration will be over user discomfort but often occur in this case. Wind load should be the design of super high-rise building safety and practicality of the control load; therefore, we need to understand the wind load. But because of a lot of data of wind load are from the meteorological department or military departments, and research and wind engineering in different directions, so less about the wind load directly to the measurement of wind records; the load is very difficult, but the response measurement will be much simpler, so in recent years, by measuring the response of the structure and performance of wind load for anti wind load data The new method, this paper introduces the wind load composite inversion content. This paper uses the method of load is the normalized statistical average algorithm, this method is the assumption that the correlation of fluctuating wind power system, using the classical form of state equation and least square criterion, a normalized load statistical average algorithm in the derivation of success, provided a method for the back of the case analysis; then this method of convergence is proved. In practical engineering, divided into the following situations: the difference between the 1. noise and no noise. The effect of 2. different noise levels on the inversion results, 3. different wind correlation assumptions of the inversion results. To identify the physical parameters of the structure without noise under the condition of different initial value, the calculation of the maximum error is less than 0.99%; the same error, the wind load and the value of the real. The smaller, less than 1.25% in the initial description and accuracy of this method in the assumption of stiffness identification of stiffness has nothing to do with satisfactory results. We are in the noise level of 15% cases observed stiffness identification results and wind load inversion results in fluctuating wind relativity coefficient for each of the three 4,8,12 the results showed that different; the fluctuating wind correlation coefficient has little influence on the stiffness of the identification results and the inversion results, but the minimum relativity coefficient is 4 when the stiffness identification results of wind load inversion results is better, more in line with the actual situation. In order to verify the anti noise performance of the algorithm, we added different noise levels of Gauss white noise to the theoretical calculation the results shows that, in low noise conditions (5%, 15%), because the stiffness identification accuracy is very high, so the wind load obtained has good accuracy; but if the noise level of Up to 30%, the error of wind load identification results is larger than that of 9.3%.. As a whole, a large number of theoretical analysis and numerical analysis show that the proposed load normalization composite inversion algorithm is effective and practical.

【學(xué)位授予單位】：武漢理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TU973.213

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