本文選題：復(fù)雜產(chǎn)品　切入點(diǎn)：性能增強(qiáng)設(shè)計(jì)　出處：《浙江大學(xué)》2017年博士論文

【摘要】：針對(duì)復(fù)雜產(chǎn)品設(shè)計(jì)具有層次性、耦合性、模糊性、迭代性、認(rèn)知性等固有特點(diǎn),將性能設(shè)計(jì)與復(fù)雜產(chǎn)品設(shè)計(jì)過程進(jìn)行融合,系統(tǒng)性地提出了不確定條件下復(fù)雜產(chǎn)品性能增強(qiáng)設(shè)計(jì)理論和方法,對(duì)期望性能辨識(shí)、行為性能均衡、結(jié)構(gòu)性能適配以及預(yù)測性能評(píng)估等關(guān)鍵技術(shù)進(jìn)行了深入研究,并根據(jù)研究成果開發(fā)了復(fù)雜產(chǎn)品性能設(shè)計(jì)系統(tǒng)集成平臺(tái)并實(shí)際工程應(yīng)用,取得了良好的成果,驗(yàn)證了本文方法的有效性與可行性。本文的研究內(nèi)容主要包括:第一章概述了復(fù)雜產(chǎn)品性能設(shè)計(jì)的內(nèi)涵理解及其相關(guān)技術(shù)的研究現(xiàn)狀,并討論了產(chǎn)品性能增強(qiáng)設(shè)計(jì)與不確定設(shè)計(jì)的研究現(xiàn)狀,提出了不確定條件下復(fù)雜產(chǎn)品性能增強(qiáng)設(shè)計(jì)理論及方法,同時(shí)闡述了本文的研究內(nèi)容和總體結(jié)構(gòu)框架。第二章提出了基于狀態(tài)感知的產(chǎn)品期望性能解析辨識(shí)技術(shù)。根據(jù)性能在產(chǎn)品全生命周期逐層演化的特點(diǎn),構(gòu)建了期望性能閉環(huán)解析的機(jī)理模型;提出了不確定條件下期望性能正向遞推解析與狀態(tài)感知反饋的期望性能反向計(jì)算方法,并采用模糊積分對(duì)意圖重要度函數(shù)進(jìn)行補(bǔ)償修正,實(shí)現(xiàn)了需求域與過程域影響下的性能重要度非線性融合辨識(shí)及度量。第三章提出了基于解耦計(jì)算的產(chǎn)品行為性能均衡求解技術(shù)。基于模糊不確定的產(chǎn)品行為關(guān)聯(lián)準(zhǔn)則數(shù)據(jù),對(duì)產(chǎn)品構(gòu)型的耦合強(qiáng)度進(jìn)行計(jì)算;采用設(shè)計(jì)結(jié)構(gòu)矩陣聚類對(duì)產(chǎn)品進(jìn)行初次解耦規(guī)劃并計(jì)算解的行為單元性能指數(shù);以初次解耦行為單元為基礎(chǔ),構(gòu)建了以質(zhì)量穩(wěn)定性、維修成本與系統(tǒng)可用性為目標(biāo)以及相關(guān)閾值為約束的行為性能模型;提出了基于隨機(jī)搜索的離散粒子群算法對(duì)性能模型進(jìn)行多目標(biāo)優(yōu)化求解,并采用熵權(quán)理想點(diǎn)排序法識(shí)別最優(yōu)結(jié)果,從而獲得性能均衡的單元方案。第四章提出了基于約束傳遞的產(chǎn)品結(jié)構(gòu)性能模糊適配技術(shù)。首先對(duì)結(jié)構(gòu)性能的約束信息空間進(jìn)行約簡并以隸屬度的方式對(duì)約束空間中的信息進(jìn)行一致性轉(zhuǎn)換;以關(guān)聯(lián)相似度為依據(jù),提出了面向約束處理的二次過濾技術(shù),實(shí)現(xiàn)性能約束驅(qū)動(dòng)下的功能域到結(jié)構(gòu)域的關(guān)聯(lián)映射;構(gòu)建了以成本、質(zhì)量與物理相容性為目標(biāo)及相關(guān)閾值為約束的數(shù)學(xué)模型,提出了基于約束水平的離散差分進(jìn)化算法對(duì)帶約束的性能適配過程進(jìn)行多目標(biāo)優(yōu)化,同時(shí)采用一種約束滿足偏差最小的方案決策方法選取結(jié)構(gòu)性能最優(yōu)的適配結(jié)果。第五章提出了魯棒學(xué)習(xí)的產(chǎn)品預(yù)測性能可信評(píng)估技術(shù)。首先對(duì)樣本輸入數(shù)據(jù)進(jìn)行預(yù)處理,采用互信息估計(jì)對(duì)設(shè)計(jì)變量進(jìn)行篩選以降低預(yù)測模型的規(guī)模,采用k最近鄰法對(duì)數(shù)據(jù)樣本的異常點(diǎn)進(jìn)行識(shí)別以提高其精度;對(duì)隱式的性能參數(shù)一設(shè)計(jì)變量響應(yīng)模型進(jìn)行回歸擬合獲得穩(wěn)健的性能校核預(yù)測模型;提出基于Bootstrap統(tǒng)計(jì)推斷的性能可信度分析方法,實(shí)現(xiàn)了預(yù)測結(jié)果對(duì)數(shù)據(jù)不確定性的處理,并通過靈敏度分析識(shí)別影響性能的關(guān)鍵設(shè)計(jì)變量。第六章將論文的研究成果與實(shí)際應(yīng)用相結(jié)合,開發(fā)了復(fù)雜產(chǎn)品性能設(shè)計(jì)系統(tǒng)集成平臺(tái)并應(yīng)用于鍛壓裝備的產(chǎn)品設(shè)計(jì)過程中,驗(yàn)證了所提出方法和技術(shù)的可行性與有效性。第七章對(duì)論文進(jìn)行了總結(jié),歸納了論文工作的主要研究成果與創(chuàng)新點(diǎn),并對(duì)未來的研究工作進(jìn)行了展望。
[Abstract]:With the level of product design, aiming at the complex coupling, fuzzy, iterative, cognitive inherent characteristics, the design and performance of complex product design process integration, systematically put forward the uncertain complex product performance under the condition of enhanced design theory and method, the expected performance of behavior identification, the balance of performance, structural performance adaptation and key technology of forecast performance evaluation conducted in-depth research, development and performance of complex product design system integration platform and the practical engineering application according to the research results, and achieved good results, verify the feasibility and effectiveness of the proposed method. The main contents of this paper include: the first chapter summarizes the research status quo of the connotation of performance the understanding of complex product design and related technology, and discusses the research status of product performance enhancement design and uncertainty, put forward under the condition of uncertainty complex The product performance and enhance the design theory and method, and expounds the research content and framework of this paper. The second chapter puts forward the state aware product identification technology based on expected performance analysis. According to the characteristics of the product life cycle layer evolution, constructs the mechanism model of expected closed-loop analytical; put forward the conditions of uncertainty under the expected performance of recursive forward calculation method and analysis of the expected performance of reverse push perception of the state feedback, and the fuzzy integral to importance function is compensated and corrected, the identification and measurement of fusion performance importance nonlinear demand domain and process domain under the influence. The third chapter puts forward the product performance behavior equilibrium calculation based on decoupling technology. Product behavior relevance data fuzzy uncertainty based on the calculation of coupling strength on product configuration; using design structure matrix clustering The initial planning of the products and decoupling performance index calculation unit of behavior of solutions to the initial behavior; decoupling unit as the basis to construct the stability of quality, maintenance cost and availability of the system as the goal and the threshold for the behavior performance model constraint; discrete particle swarm optimization algorithm was proposed based on random search on the performance of multi-objective optimization model to solve, and the entropy weighting ideal point method to identify the optimal result, so as to obtain the unit scheme performance equilibrium. The fourth chapter puts forward the structural performance constraint fuzzy adaptation technique based on constraint information. The first space on the structure properties and reduction to the membership of the information in the space constraint consistency transformation based on relevance similarity; as the basis, puts forward two constraint handling filtering technology, realize the performance constraint driven function domain to the domain of the customs Joint mapping; construction of the cost, quality and physical compatibility as the goal and related mathematical model for threshold constraints, the proposed discrete difference constraint level based on genetic algorithm with constraints on the performance of the adaptation process of multi-objective optimization, using a constraint satisfaction scheme decision method of minimum deviation of selecting optimal performance structure the results of adaptation. The fifth chapter puts forward the performance prediction of trustworthy evaluation technology of robust learning products. The first sample input data were preprocessed by mutual information estimation are selected to reduce the prediction model of the scale of the design variables, using k nearest neighbor method of data outlier identification in order to improve the precision of performance check; the performance parameters of the implicit response model of design variable regression fitting robust prediction model; analyze the performance reliability of statistical inference is proposed based on the Bootstrap Method, realized the prediction results for data processing of uncertainty, and the sensitivity analysis of key design variables influence the performance of the recognition. The sixth chapter will research combining with the practical application of product design, process design system for complex product development integration platform and its application in forging press equipment, verified the feasibility of the proposed methods and techniques and effective. The seventh chapter summarizes the thesis, summarizes the main research results and innovation, and the future research work is prospected.

【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】：2017
【分類號(hào)】：TB472

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