【摘要】：框架結(jié)構(gòu)形式在工程中被廣泛采用,由于結(jié)構(gòu)在使用過程中往往存在初始損傷或因使用年限的增加,外荷載頻繁作用使結(jié)構(gòu)損傷的積累,可能導(dǎo)致結(jié)構(gòu)抗力的減弱,當(dāng)結(jié)構(gòu)的某一部分出現(xiàn)損傷時(shí)可能會(huì)致使結(jié)構(gòu)的其它部分甚至整個(gè)結(jié)構(gòu)出現(xiàn)破壞,所以研究框架結(jié)構(gòu)的穩(wěn)定性與安全性不僅可以防止社會(huì)財(cái)富的損失,更重要的是能夠保障人民的生命安全。因此,監(jiān)測(cè)結(jié)構(gòu)的工作狀況,研究框架結(jié)構(gòu)的損傷診斷方法,有著十分重要的工程及現(xiàn)實(shí)意義。小波變換能夠分析信號(hào)在時(shí)、頻兩域的局部特征,神經(jīng)網(wǎng)絡(luò)具有很好的自組織能力、很強(qiáng)的非線性映射能力,通過將小波分析與神經(jīng)網(wǎng)絡(luò)相結(jié)合的方法實(shí)現(xiàn)對(duì)框架結(jié)構(gòu)的損傷位置和損傷程度的識(shí)別,運(yùn)用的基本方法是：通過建立損傷框架結(jié)構(gòu)的有限元模型并對(duì)其動(dòng)力特征進(jìn)行分析,將得到的曲率模態(tài)進(jìn)行連續(xù)小波變換可以得到結(jié)構(gòu)的小波系數(shù),由小波系數(shù)模極大值確定損傷的位置。以損傷后結(jié)構(gòu)的固有頻率作為神經(jīng)網(wǎng)絡(luò)輸入?yún)?shù)構(gòu)造神經(jīng)網(wǎng)絡(luò),從而實(shí)現(xiàn)對(duì)框架結(jié)構(gòu)損傷程度的識(shí)別。本文以框架結(jié)構(gòu)為研究對(duì)象,建立了框架結(jié)構(gòu)的有限元模型(一層一跨多處損傷的框架結(jié)構(gòu)、一層兩跨多處損傷的框架結(jié)構(gòu)),運(yùn)用小波分析原理,采用Lanczos法得到框架結(jié)構(gòu)的曲率模態(tài),對(duì)其曲率模態(tài)進(jìn)行連續(xù)小波變換可以得到結(jié)構(gòu)的小波系數(shù),由小波系數(shù)模極大值確定損傷的位置。以損傷后結(jié)構(gòu)的固有頻率作為神經(jīng)網(wǎng)絡(luò)輸入?yún)?shù)構(gòu)造神經(jīng)網(wǎng)絡(luò),從而實(shí)現(xiàn)對(duì)框架結(jié)構(gòu)損傷程度的識(shí)別,建立了一種基于小波神經(jīng)網(wǎng)絡(luò)算法的框架結(jié)構(gòu)損傷識(shí)別方法。本文在簡(jiǎn)單的框架結(jié)構(gòu)基礎(chǔ)上,將上述方法應(yīng)用到較復(fù)雜的兩層一跨、兩層兩跨多處損傷框架結(jié)構(gòu)上,建立了框架結(jié)構(gòu)的有限元模型,由小波系數(shù)模極大值確定損傷的位置,由構(gòu)造的神經(jīng)網(wǎng)絡(luò)來確定損傷的程度,驗(yàn)證了方法的有效性。本文提出的方法可供結(jié)構(gòu)損傷診斷的工程應(yīng)用參考。
[Abstract]:Frame structure is widely used in engineering. Because of the initial damage or the increase of service life of the structure, the accumulation of structural damage is caused by the frequent action of external load, which may lead to the weakening of structural resistance. When a part of the structure is damaged, it may cause damage to other parts of the structure or even the whole structure, so the study of the stability and safety of the frame structure can not only prevent the loss of social wealth. More importantly, it can ensure the safety of people's lives. Therefore, it is of great engineering and practical significance to monitor the working condition of the structure and study the damage diagnosis method of the frame structure. Wavelet transform can analyze the local characteristics of signal in time and frequency domains. Neural network has good self-organization ability and strong nonlinear mapping ability. By combining wavelet analysis with neural network to identify the damage location and degree of frame structure, the basic method is to establish the finite element model of damaged frame structure and analyze its dynamic characteristics. The wavelet coefficients of the structure can be obtained by continuous wavelet transform of the curvature modes, and the damage location can be determined by the modulus Maxima of wavelet coefficients. The natural frequency of the damaged structure is used as the input parameter of the neural network to construct the neural network, so as to realize the identification of the damage degree of the frame structure. In this paper, taking the frame structure as the research object, the finite element model of the frame structure (one story, one span and multiple damage frame structure, one layer, two span multiple damage frame structure) is established, and the wavelet analysis principle is used. The curvature mode of frame structure is obtained by Lanczos method. The wavelet coefficient of the structure can be obtained by continuous wavelet transform of curvature mode, and the damage position can be determined by the modulus Maxima of wavelet coefficient. The natural frequency of the damaged structure is used as the input parameter of the neural network to construct the neural network, so as to realize the identification of the damage degree of the frame structure, and a damage identification method of the frame structure based on wavelet neural network algorithm is established. In this paper, on the basis of simple frame structure, the above method is applied to the complex two-story one-span, two-story two-span multi-damage frame structure, and the finite element model of the frame structure is established, and the damage location is determined by the modulus Maxima of wavelet coefficients. The degree of damage is determined by the constructed neural network, and the effectiveness of the method is verified. The method proposed in this paper can be used as a reference for the engineering application of structural damage diagnosis.
【學(xué)位授予單位】：長(zhǎng)沙理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TU317
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本文編號(hào)：2484184