發(fā)布時(shí)間：2018-06-30 17:49

  本文選題：關(guān)聯(lián)強(qiáng)度 + 多源數(shù)據(jù)融合�。� 參考：《浙江大學(xué)》2014年博士論文

【摘要】：復(fù)雜產(chǎn)品的結(jié)構(gòu)組成復(fù)雜、運(yùn)行工況多變、設(shè)計(jì)變量數(shù)量眾多、多性能目標(biāo)相互耦合,使得產(chǎn)品的性能設(shè)計(jì)異常困難,難以獲得產(chǎn)品整體性能最優(yōu)的設(shè)計(jì)方案。模型復(fù)雜性和計(jì)算復(fù)雜性是復(fù)雜產(chǎn)品性能設(shè)計(jì)難點(diǎn)之一。本文在對(duì)復(fù)雜產(chǎn)品性能設(shè)計(jì)相關(guān)技術(shù)的研究現(xiàn)狀進(jìn)行總結(jié)和分析的基礎(chǔ)上,針對(duì)設(shè)計(jì)變量與性能關(guān)聯(lián)強(qiáng)度計(jì)算、設(shè)計(jì)模型解耦和設(shè)計(jì)模型等效簡(jiǎn)化等問(wèn)題進(jìn)行了深入研究,根據(jù)研究成果開(kāi)發(fā)了大型空分裝備性能設(shè)計(jì)系統(tǒng),在杭氧8萬(wàn)等級(jí)空分裝備設(shè)計(jì)中進(jìn)行了應(yīng)用驗(yàn)證。論文的主要研究?jī)?nèi)容包括：第一章概述了復(fù)雜產(chǎn)品性能設(shè)計(jì)的研究現(xiàn)狀,綜述了設(shè)計(jì)變量與性能間關(guān)聯(lián)強(qiáng)度分析、設(shè)計(jì)模型解耦、模型等效簡(jiǎn)化、性能求解等關(guān)鍵技術(shù),給出了本文擬解決的問(wèn)題,介紹了本文的研究?jī)?nèi)容和組織結(jié)構(gòu)。第二章提出了多源數(shù)據(jù)融合的設(shè)計(jì)變量與性能關(guān)聯(lián)強(qiáng)度計(jì)算方法。使用響應(yīng)面擬合法和灰色神經(jīng)網(wǎng)絡(luò)法實(shí)現(xiàn)了多源數(shù)據(jù)的融合分析及性能設(shè)計(jì)模型的構(gòu)建�；趩我蛩孛舾卸刃畔㈧氐木岛蜆�(biāo)準(zhǔn)差,將設(shè)計(jì)變量劃分為強(qiáng)關(guān)聯(lián)變量、弱關(guān)聯(lián)變量和變關(guān)聯(lián)變量。構(gòu)建了變關(guān)聯(lián)矩陣,在性能求解中實(shí)現(xiàn)了設(shè)計(jì)變量與性能間關(guān)聯(lián)強(qiáng)度的精確計(jì)算及設(shè)計(jì)變量的自適應(yīng)調(diào)節(jié)。第三章提出了設(shè)計(jì)變量與性能間多重耦合聚類分析與設(shè)計(jì)模型解耦技術(shù)。根據(jù)設(shè)計(jì)變量與性能的關(guān)聯(lián)強(qiáng)度構(gòu)建了包含設(shè)計(jì)變量與性能間耦合關(guān)聯(lián)、變量間耦合關(guān)聯(lián)和性能間耦合關(guān)聯(lián)等多重耦合信息的綜合耦合度矩陣。通過(guò)綜合耦合度矩陣的降維分析和變量性能二元樹(shù)的分支耦合度比較,實(shí)現(xiàn)了設(shè)計(jì)變量與性能的聚類分析。提出了聚合度的概念進(jìn)行設(shè)計(jì)模型解耦效果評(píng)價(jià),以聚合度為指標(biāo)進(jìn)行了設(shè)計(jì)模型解耦。第四章提出了相似組合模型的參數(shù)攝動(dòng)等效簡(jiǎn)化技術(shù)。分析了相似組合模型的特點(diǎn),根據(jù)同類變量的小擾動(dòng)分析結(jié)果,進(jìn)行了參數(shù)的奇異攝動(dòng)分析。提出了相似組合模型等效簡(jiǎn)化的系數(shù)設(shè)置準(zhǔn)則,包括組合模型劃分準(zhǔn)則、敏感子模型選取準(zhǔn)則和修正系數(shù)求解準(zhǔn)則。應(yīng)用于精餾上塔開(kāi)環(huán)響應(yīng)和閉環(huán)響應(yīng)下的產(chǎn)品純度預(yù)測(cè),保證了產(chǎn)品純度預(yù)測(cè)結(jié)果的準(zhǔn)確性。第五章提出了參數(shù)不確定性分析的模型等效簡(jiǎn)化技術(shù)。進(jìn)行了各類參數(shù)不確定性的來(lái)源分析和定量表征,構(gòu)建了性能不確定性度量函數(shù)�；谛阅茴A(yù)測(cè)區(qū)間進(jìn)行設(shè)計(jì)變量采樣點(diǎn)選取,基于模型均方誤差進(jìn)行系統(tǒng)參數(shù)采樣點(diǎn)選取,構(gòu)建了性能不確定性驅(qū)動(dòng)的等效簡(jiǎn)化模型。應(yīng)用于換熱器的傳熱性能求解,提高了換熱器翅片結(jié)構(gòu)設(shè)計(jì)結(jié)果的穩(wěn)健性。第六章實(shí)現(xiàn)了大型空分裝備性能設(shè)計(jì)系統(tǒng)的研制。將本文提出的理論方法應(yīng)用于大型空分裝備的性能設(shè)計(jì),介紹了軟件系統(tǒng)的體系結(jié)構(gòu),詳細(xì)闡述了軟件的各項(xiàng)功能。并將該軟件應(yīng)用于杭氧8萬(wàn)等級(jí)空分裝備的設(shè)計(jì),驗(yàn)證了研制軟件的有效性。第七章對(duì)本文進(jìn)行了總結(jié),歸納了本文的主要研究成果和創(chuàng)新點(diǎn),展望了今后的研究工作。
[Abstract]:Complex product has complex structure, variable operating conditions, large number of design variables and coupling of multi performance targets, which makes the product performance design difficult and difficult to obtain the best overall performance of the product. Model complexity and computational complexity are one of the difficulties in complex product performance design. On the basis of the summary and analysis of the research status of related technology, the problems of design model decoupling and design model equivalent simplification are studied. The performance design system of large air separation equipment is developed according to the research results, and the design of the 80 thousand grade air separation equipment is introduced. The main contents of this paper are as follows: in the first chapter, the research status of the performance design of complex products is summarized. The key technologies such as the analysis of the correlation strength between the design variables and the performance, the decoupling of the design model, the model equivalent simplification and the performance solution are summarized. The problems to be solved in this paper are given, and the contents of this paper are introduced and the contents of this paper are introduced. The second chapter puts forward the calculation method of the correlation strength between the design variables and the performance of multi source data fusion. Using the response surface fitting method and the grey neural network method, the fusion analysis of multi source data and the construction of the performance design model are realized. Based on the mean and standard deviation of the information entropy of single factor sensitivity, the design variable is divided into a strong pass. The variable correlation matrix is constructed. In the performance solution, the precise calculation of the correlation strength between the design variables and the performance and the adaptive adjustment of the design variables are realized in the performance solution. The third chapter puts forward the decoupling technique of the multiple coupling cluster analysis and the design model between the design variables and the performance. A comprehensive coupling degree matrix which includes the coupling correlation between the design variables and the performance, the coupling correlation between the variables and the coupling relationship between the properties is constructed. The cluster analysis of the design variables and performance is realized by the reduction of the dimension analysis of the integrated coupling matrix and the branch coupling of the two element tree with variable performance. The concept of degree of polymerization is put forward to evaluate the decoupling effect of the design model, and the design model is decoupled with the degree of polymerization. The fourth chapter puts forward the equivalent simplification technique of the parameter perturbation of the similar combination model. The characteristics of the similar combination model are analyzed. The singular perturbation analysis of the parameters is carried out according to the small perturbation analysis results of the same kind of variables. The equivalent simplified coefficient setting criterion of the similar combination model is proposed, including the combination model division criterion, the sensitive submodel selection criterion and the correction coefficient solution criterion, which is applied to the product purity prediction under the open loop response and closed loop response of the distillation tower, and the accuracy of the product purity prediction results is guaranteed. The fifth chapter puts forward the uncertainty of the parameters. The model equivalent simplification technology of qualitative analysis is used. The source analysis and quantitative characterization of various parameter uncertainties are carried out. The measurement function of performance uncertainty is constructed. Based on the performance prediction interval, the sampling points of the design variables are selected. Based on the mean square error of the model, the sampling points of the system parameters are selected, and the driving of performance uncertainty is constructed. The simplified model is applied to the heat transfer performance of the heat exchanger, and the stability of the design results of the fin structure of the heat exchanger is improved. The sixth chapter realizes the development of the performance design system of the large air separation equipment. The theory method proposed in this paper is applied to the performance design of the large air separation equipment, and the architecture of the software system is introduced and elaborated in detail. The software is applied to the design of the 80 thousand grade air separation equipment of Hangzhou oxygen. The validity of the software is verified. The seventh chapter summarizes the main research results and innovation points of this paper, and looks forward to the future research work.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TQ116.11;TH122

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