發(fā)布時(shí)間：2018-05-12 02:18

  本文選題：隨機(jī)不確定性 + 可靠性分析　； 參考：《西北工業(yè)大學(xué)》2015年博士論文

【摘要】：函數(shù)替代方法是可靠性和可靠性靈敏度分析方法的重要組成部分,在可靠性研究領(lǐng)域有著極其廣泛地應(yīng)用。代理模型的運(yùn)用在一定程度上實(shí)現(xiàn)了計(jì)算效率與計(jì)算精度的權(quán)衡。本文在概率可靠性的研究范疇內(nèi),分別結(jié)合人工神經(jīng)網(wǎng)絡(luò)、Kriging模型和多項(xiàng)式響應(yīng)面模型探討了代理模型在可靠性和可靠性靈敏度分析中的應(yīng)用,研究提出了一系列的分析求解方法,同時(shí)編制開(kāi)發(fā)了具有較強(qiáng)通用性的結(jié)構(gòu)機(jī)構(gòu)可靠性分析設(shè)計(jì)軟件系統(tǒng),并進(jìn)一步針對(duì)某型導(dǎo)彈關(guān)鍵結(jié)構(gòu)和典型機(jī)構(gòu)開(kāi)展了工程應(yīng)用研究。論文的主要研究?jī)?nèi)容及創(chuàng)新點(diǎn)如下:1.結(jié)合馬爾科夫鏈對(duì)傳統(tǒng)人工神經(jīng)網(wǎng)絡(luò)的實(shí)驗(yàn)設(shè)計(jì)方法進(jìn)行了改進(jìn),并分別結(jié)合重要抽樣、截?cái)嘀匾闃右约岸喑闃又行闹匾闃尤N抽樣方法進(jìn)一步提出了用于可靠性分析的結(jié)合人工神經(jīng)網(wǎng)絡(luò)的數(shù)字模擬方法。所提方法充分利用了馬爾科夫鏈的自適應(yīng)性以及人工神經(jīng)網(wǎng)絡(luò)優(yōu)秀的非線性擬合性能,降低了傳統(tǒng)方法對(duì)實(shí)驗(yàn)設(shè)計(jì)的依賴(lài),通過(guò)人工神經(jīng)網(wǎng)絡(luò)模型實(shí)現(xiàn)了對(duì)數(shù)字模擬樣本的高精度預(yù)測(cè),從而保證了可靠性分析結(jié)果的計(jì)算精度,同時(shí)有效提高了可靠性分析的計(jì)算效率。相關(guān)算例分析結(jié)果表明,所提方法具有較好的適用性,能夠用于對(duì)多種類(lèi)型可靠性問(wèn)題的求解,能夠以較高的計(jì)算效率得到精度較好的失效概率分析求解結(jié)果。2.針對(duì)工程實(shí)際中大量存在的隱式可靠性問(wèn)題,提出了基于主動(dòng)學(xué)習(xí)Kriging模型的自適應(yīng)數(shù)字模擬方法。所提方法繼承了主動(dòng)學(xué)習(xí)機(jī)制、馬爾科夫鏈以及Kriging代理模型的諸多優(yōu)點(diǎn),在保證計(jì)算精度的前提下顯著提高了可靠性分析的計(jì)算效率。馬爾科夫鏈的運(yùn)用提高了所提方法的自適應(yīng)性,保證了用于Kriging模型構(gòu)建的實(shí)驗(yàn)設(shè)計(jì)樣本的質(zhì)量;主動(dòng)學(xué)習(xí)機(jī)制的引入充分利用了Kriging模型提供的預(yù)測(cè)方差信息,有效改進(jìn)了Kriging模型的擬合能力,提高了對(duì)數(shù)字模擬樣本的預(yù)測(cè)精度;Kriging模型的使用使得所提方法對(duì)真實(shí)極限狀態(tài)函數(shù)的計(jì)算次數(shù)大幅降低,從而提高了計(jì)算效率。算例分析結(jié)果證明了所提方法的計(jì)算效率和適用性。3.基于多項(xiàng)式響應(yīng)面模型提出了分布函數(shù)靈敏度和重要性測(cè)度分析的半解析方法。分別推導(dǎo)得到了多項(xiàng)式情況下響應(yīng)量的概率矩和概率矩對(duì)分布參數(shù)的偏導(dǎo)數(shù),并給出了通過(guò)矩估計(jì)方法求解分布函數(shù)靈敏度的具體公式;推導(dǎo)得到了變量獨(dú)立和變量相關(guān)兩種情況下條件期望以及條件方差的求解公式,給出了具體的求解步驟,實(shí)現(xiàn)了對(duì)重要性測(cè)度的求解。所提方法結(jié)合多項(xiàng)式響應(yīng)面模型通過(guò)半解析手段求解得到了各個(gè)輸入變量的分布函數(shù)靈敏度和基于方差的重要性測(cè)度,實(shí)現(xiàn)了對(duì)可靠性靈敏度指標(biāo)的高效求解,給出的輸入變量重要程度排序信息能夠?yàn)楦倪M(jìn)結(jié)構(gòu)設(shè)計(jì)提供有效指導(dǎo)。4.提出了基于Kriging模型進(jìn)行分布函數(shù)靈敏度和重要性測(cè)度分析的數(shù)字模擬方法�？紤]到Kriging模型對(duì)非線性函數(shù)優(yōu)秀的擬合近似能力,所提方法具有更為廣泛的適用性,能夠在保證計(jì)算精度的前提下大幅提高可靠性靈敏度分析的計(jì)算效率。所提方法對(duì)數(shù)字模擬策略進(jìn)行了一定改進(jìn),減少了用于靈敏度分析的數(shù)字模擬樣本,進(jìn)一步降低了計(jì)算量。數(shù)字模擬的求解策略保證了在Kriging模型基礎(chǔ)上所得到的可靠性靈敏度分析結(jié)果的正確性。對(duì)數(shù)值和簡(jiǎn)單工程算例的分析結(jié)果證實(shí)了所提方法的適用性。5.編制開(kāi)發(fā)了具有較強(qiáng)通用性的結(jié)構(gòu)機(jī)構(gòu)可靠性分析設(shè)計(jì)軟件系統(tǒng),實(shí)現(xiàn)了可靠性和可靠性靈敏度分析方法的軟件化。軟件系統(tǒng)集成了多種概率分布模型和多種可靠性及可靠性靈敏度分析方法,能夠用于對(duì)各類(lèi)可靠性問(wèn)題的求解。軟件系統(tǒng)能夠與其他商用CAE分析軟件進(jìn)行通信,實(shí)現(xiàn)了通過(guò)商用CAE軟件進(jìn)行可靠性分析的可能,進(jìn)而實(shí)現(xiàn)了對(duì)隱式可靠性問(wèn)題的求解,增強(qiáng)了實(shí)用性。軟件系統(tǒng)擁有簡(jiǎn)潔直觀的用戶(hù)界面設(shè)計(jì),能夠以圖表方式給出豐富的分析結(jié)果信息,同時(shí)支持簡(jiǎn)單報(bào)告的生成,方便用戶(hù)的使用。眾多數(shù)值和工程算例的應(yīng)用結(jié)果證明了軟件系統(tǒng)的強(qiáng)大功能,展示出良好的工程應(yīng)用前景。6.針對(duì)某型導(dǎo)彈舵翼面結(jié)構(gòu)以及某型滑翔彈彈翼展開(kāi)機(jī)構(gòu)對(duì)所提出的可靠性和靈敏度方法進(jìn)行了工程應(yīng)用研究。實(shí)現(xiàn)了對(duì)舵翼面結(jié)構(gòu)有限元模型和彈翼展開(kāi)機(jī)構(gòu)虛擬樣機(jī)模型的參數(shù)化處理,得到了對(duì)應(yīng)的參數(shù)化仿真模型。構(gòu)建了能夠準(zhǔn)確預(yù)測(cè)舵翼面結(jié)構(gòu)力學(xué)性能響應(yīng)和彈翼展開(kāi)機(jī)構(gòu)運(yùn)動(dòng)特性響應(yīng)的Kriging代理模型。通過(guò)數(shù)字模擬手段求解得到了舵翼面結(jié)構(gòu)和彈翼展開(kāi)機(jī)構(gòu)的失效概率、分布函數(shù)靈敏度以及基于方差的重要性測(cè)度分析結(jié)果。在考慮不確定性因素的前提下得到了舵翼面結(jié)構(gòu)和彈翼展開(kāi)機(jī)構(gòu)的安全性能評(píng)估,并進(jìn)一步給出了提高性能的具體措施。
[Abstract]:The function substitution method is an important part of the reliability and reliability sensitivity analysis method. It is widely used in the field of reliability research. The application of the agent model has realized the trade-off between the calculation efficiency and the calculation accuracy to a certain extent. In this paper, the artificial neural network (artificial neural network, Kri) is combined in the research category of the probability reliability. The ging model and the polynomial response surface model are used to discuss the application of the agent model in reliability and reliability sensitivity analysis. A series of analytical solutions are proposed. At the same time, a software system for reliability analysis and design of structural mechanisms with strong generality is developed, and the key structure and typical model of a certain type of missile are further studied. The main research contents and innovation points of this paper are as follows: 1. the experimental design method of traditional artificial neural network is improved with the combination of Markoff chain, and three sampling methods, including important sampling, truncating important sampling and multi sampling center sampling, are further proposed to be used for reliability. The proposed method makes full use of the adaptability of the Markov chain and the excellent nonlinear fitting performance of the artificial neural network, reduces the dependence of the traditional method on the experimental design, and realizes the high precision prediction of the digital analog samples by the artificial neural network model. The calculation accuracy of the reliability analysis results is guaranteed and the efficiency of the reliability analysis is effectively improved. The results of the correlation analysis show that the proposed method has good applicability and can be used to solve many types of reliability problems and can get a better result of failure probability analysis with a higher calculation efficiency. .2. has proposed an adaptive digital simulation method based on active learning Kriging model, which inherits the advantages of active learning mechanism, Markov chain and Kriging agent model, which greatly improves the reliability analysis under the premise of ensuring the accuracy of calculation. The application of Markov chain improves the adaptability of the proposed method and guarantees the quality of the experimental design samples used in the Kriging model. The introduction of active learning mechanism makes full use of the predictive variance information provided by the Kriging model, improves the fitting ability of the Kriging model effectively, and improves the preview of the digital analog samples. Measurement accuracy; the use of the Kriging model makes the proposed method greatly reduce the number of calculation times of the real limit state function, thus improving the computational efficiency. The calculation efficiency and applicability of the proposed method are proved by the numerical example..3. based on the polynomial response surface model presents the semi analytic of the sensitivity of the distribution function and the importance measure analysis. The partial derivative of the probability moment and the probability moment of the response quantity under the polynomial condition is derived, and the specific formula for solving the sensitivity of the distribution function by the moment estimation method is given. The formula of the conditional expectation and the conditional variance under two cases of variable independence and variable correlation are derived. The proposed method combines the polynomial response surface model with the polynomial response surface model to obtain the sensitivity of the distribution functions of each input variable and the importance measure based on the variance. The efficient solution to the reliability sensitivity index is realized. The input variables are important to the degree of importance. The sequence information can provide effective guidance for the improvement of the structure design..4. proposed a digital simulation method based on the Kriging model for the sensitivity and importance measure analysis of the distribution function. Considering the excellent fitting approximation ability of the Kriging model to the nonlinear function, the proposed method has more extensive applicability and can ensure the accuracy of the calculation. The computational efficiency of the reliability sensitivity analysis is greatly improved. The proposed method has improved the digital simulation strategy to reduce the numerical simulation samples for sensitivity analysis and further reduce the amount of calculation. The solution strategy of digital simulation guarantees the reliability sensitivity analysis results based on the Kriging model. The results of the numerical and simple engineering examples confirm the applicability of the proposed method.5.. The software system for reliability analysis and design of structural mechanisms with strong generality is developed, and the software of reliability and reliability sensitivity analysis method is realized. The reliability and reliability sensitivity analysis method can be used to solve all kinds of reliability problems. The software system can communicate with other commercial CAE analysis software, realize the possibility of reliability analysis through commercial CAE software, and then realize the solution of the implicit reliability questions and enhance the practicability. The software system owns the software system. The simple and intuitive user interface design can give a rich analysis of the result information on the chart, support the generation of simple reports and facilitate the use of the users. The application results of many numerical and engineering examples demonstrate the powerful function of the software system, and show a good application prospect.6. for a missile rudder wing structure. And a certain type of gliding projectile wing deployment mechanism is applied to the engineering application of the proposed reliability and sensitivity method. The parameterized processing of the finite element model of the rudder wing structure and the virtual prototype model of the wing deployable mechanism is realized, and the corresponding parameterized simulation model is obtained. The mechanical properties of the rudder wing structure can be accurately predicted. The Kriging agent model, which can respond to the response of the wing unfolded mechanism, obtains the failure probability, the sensitivity of the distribution function and the analysis result of the importance measure based on the variance by the numerical simulation method. The rudder wing structure is obtained on the premise of considering the uncertainty. The safety performance evaluation of the missile wing deployment mechanism is given, and the specific measures for improving the performance are given.

【學(xué)位授予單位】：西北工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：O213.2;TP183
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本文編號(hào)：1876684