【摘要】：近年來國(guó)家對(duì)基礎(chǔ)設(shè)施的投資規(guī)模不斷擴(kuò)大,各種大型復(fù)雜結(jié)構(gòu)不斷涌現(xiàn)。它們?cè)诜燮陂g,由于外界和自身因素的影響,不可避免地發(fā)生損傷。為了及早發(fā)現(xiàn)結(jié)構(gòu)損傷,降低對(duì)人們生命及財(cái)產(chǎn)安全的威脅,一個(gè)有效的手段就是在大型結(jié)構(gòu)上安裝健康監(jiān)測(cè)系統(tǒng)。作為結(jié)構(gòu)健康監(jiān)測(cè)系統(tǒng)的核心內(nèi)容,結(jié)構(gòu)參數(shù)識(shí)別和損傷識(shí)別一直是國(guó)內(nèi)外學(xué)者的研究焦點(diǎn),致力于尋找一種大型復(fù)雜結(jié)構(gòu)在線監(jiān)測(cè)的損傷診斷方法。本文將復(fù)雜追蹤算法應(yīng)用于土木工程結(jié)構(gòu)模態(tài)參數(shù)和損傷識(shí)別中,為結(jié)構(gòu)識(shí)別提供新思路,豐富和完善結(jié)構(gòu)健康監(jiān)測(cè)理論。本文主要研究?jī)?nèi)容及成果如下:(1)闡述了本課題的研究背景及意義,對(duì)當(dāng)前結(jié)構(gòu)模態(tài)參數(shù)識(shí)別和損傷識(shí)別的研究方法及存在的問題進(jìn)行了系統(tǒng)論述,并簡(jiǎn)單介紹了盲源分離的發(fā)展及在結(jié)構(gòu)識(shí)別中的應(yīng)用。(2)簡(jiǎn)單介紹了復(fù)雜追蹤的相關(guān)數(shù)學(xué)知識(shí)、基本原理、預(yù)處理方法,并對(duì)目標(biāo)函數(shù)的建立以及梯度優(yōu)化算法進(jìn)行了論述。原梯度算法迭代過程使用固定步長(zhǎng)和非線性函數(shù),使得算法的自適應(yīng)性不足。為此,根據(jù)峭度及最優(yōu)步長(zhǎng)對(duì)原梯度算法的迭代過程進(jìn)行了改進(jìn),形成了適用性更廣、分離效果更好的自適應(yīng)復(fù)雜追蹤算法。(3)發(fā)展出復(fù)雜追蹤結(jié)合希爾伯特變換識(shí)別結(jié)構(gòu)模態(tài)參數(shù)的新方法。對(duì)多自由度結(jié)構(gòu)系統(tǒng)動(dòng)力響應(yīng)與復(fù)雜追蹤模型之間的關(guān)系進(jìn)行了探討,通過復(fù)雜追蹤算法分離出結(jié)構(gòu)的各階模態(tài)響應(yīng)及振型,再利用希爾伯特變換解析出結(jié)構(gòu)的模態(tài)頻率及阻尼比。采用不同的模型驗(yàn)證了該方法準(zhǔn)確識(shí)別結(jié)構(gòu)模態(tài)參數(shù)的可靠性。(4)發(fā)展出復(fù)雜追蹤結(jié)合集合經(jīng)驗(yàn)?zāi)B(tài)分解識(shí)別結(jié)構(gòu)損傷的新方法。結(jié)構(gòu)損傷會(huì)引起響應(yīng)信號(hào)的突變,通過集合經(jīng)驗(yàn)?zāi)B(tài)分解提取包含損傷分量的高頻本征模函數(shù),再利用復(fù)雜追蹤算法,從噪聲信號(hào)中分離出該損傷分量。根據(jù)信號(hào)突變點(diǎn)的位置識(shí)別損傷發(fā)生的時(shí)間,再根據(jù)混合矩陣識(shí)別損傷發(fā)生的位置。通過不同的模型,驗(yàn)證了該方法可準(zhǔn)確有效地識(shí)別結(jié)構(gòu)損傷發(fā)生的時(shí)刻與位置。
[Abstract]:In recent years, the scale of national investment in infrastructure has been expanding, and various large and complex structures are emerging. During their service, injuries inevitably occur due to the influence of external and self-factors. In order to detect structural damage as early as possible and reduce the threat to people's life and property, an effective method is to install health monitoring system on large structures. As the core of structural health monitoring system, structural parameter identification and damage identification have been the research focus of scholars at home and abroad, dedicated to find a large and complex structure online monitoring damage diagnosis method. In this paper, the complex tracking algorithm is applied to the modal parameters and damage identification of civil engineering structures, which provides a new idea for structural identification and enriches and perfects the theory of structural health monitoring. The main contents and achievements of this paper are as follows: (1) the research background and significance of this subject are expounded, and the research methods and existing problems of structural modal parameter identification and damage identification are systematically discussed. The development of blind source separation and its application in structure recognition are briefly introduced. (2) the mathematical knowledge, basic principle, preprocessing method of complex tracing are briefly introduced, and the establishment of objective function and gradient optimization algorithm are discussed. The iterative process of the original gradient algorithm uses fixed step size and nonlinear function, which makes the algorithm self-adaptive. Therefore, the iterative process of the original gradient algorithm is improved according to the kurtosis and the optimal step size, resulting in a wider applicability. An adaptive complex tracking algorithm with better separation effect is proposed. (3) A new method of identifying structural modal parameters by complex tracing combined with Hilbert transform is developed. The relationship between dynamic response and complex tracking model of multi-degree-of-freedom structural system is discussed. The modal responses and modes of structures are separated by complex tracking algorithm. Then the modal frequency and damping ratio of the structure are analyzed by Hilbert transform. Different models are used to verify the reliability of the method. (4) A new method is developed to identify structural damage with complex tracing and set empirical mode decomposition. Structural damage can cause sudden change of response signal. The high frequency eigenmode function containing damage component is extracted by means of set empirical mode decomposition, and the damage component is separated from noise signal by complex tracking algorithm. The time of damage is identified according to the location of the signal mutation point, and then the location of the damage is identified according to the mixed matrix. Through different models, it is verified that the method can accurately and effectively identify the time and position of structural damage.
【學(xué)位授予單位】：蘇州科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TU317

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