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多質(zhì)量指標(biāo)的解耦與穩(wěn)健優(yōu)化設(shè)計(jì)
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    摘要:

    摘要分析了產(chǎn)品的多質(zhì)量特性指標(biāo)與設(shè)計(jì)參數(shù)的耦合關(guān)系,提出了一種耦合性強(qiáng)弱的度量指標(biāo)與解耦方法。在此基礎(chǔ)上,提出一種多質(zhì)量特性指標(biāo)的穩(wěn)健優(yōu)化設(shè)計(jì)方法,基本思路是:按信息公理的要求,對(duì)每個(gè)質(zhì)量特性指標(biāo)進(jìn)行穩(wěn)健優(yōu)化,減少其不確定性信息含量;按獨(dú)立性公理要求,對(duì)多個(gè)質(zhì)量指標(biāo)進(jìn)行近似解耦,以提高多個(gè)質(zhì)量指標(biāo)的整體穩(wěn)健性。為了提高模型求解效率,用BP神經(jīng)網(wǎng)絡(luò)作為非線性隨機(jī)函數(shù)的替代模型,并與遺傳算法相結(jié)合,構(gòu)建了一種混合智能優(yōu)化算法。通過穩(wěn)健設(shè)計(jì)實(shí)例,對(duì)所提出的方法進(jìn)行了驗(yàn)證。

    Abstract:

    The coupling relations between the multi-quality characteristics and design parameters of products were analyzed. An index for measuring the coupling degree of multi-quality characteristics was defined and a robust design criterion was put forward to achieve the decoupling of characteristics approximately. A modeling method of the robust design with multi-quality characteristics was proposed. On one hand, according to the requirement of Suh’s first design axiom (the information axiom), the robustness of each characteristic was optimized to reduce its contents of uncertainties; on the other hand, according to the requirement of Suh’s second design axiom (the independence axiom), the characteristics of a product were decoupled approximately to improve the integrated robustness. A back-propagation neural network was designed as the substitution for the nonlinear stochastic functions in the established model. With genetic algorithm combined with stochastic simulations, an intelligent optimization algorithm was developed for solving the established model effectively. An example was presented, and the results show that this method is effective and feasible. 

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郭惠昕,任丕順,張國(guó)平.多質(zhì)量指標(biāo)的解耦與穩(wěn)健優(yōu)化設(shè)計(jì)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2009,40(1):203-207.[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(1):203-207.

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