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基于動(dòng)態(tài)指數(shù)平滑模型的小批量制造過程質(zhì)量預(yù)測
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    摘要:

    在對(duì)傳統(tǒng)指數(shù)平滑預(yù)測模型局限性分析的基礎(chǔ)上,通過引入動(dòng)態(tài)平滑參數(shù)和動(dòng)態(tài)平滑初值的概念,,提出一種能自動(dòng)適應(yīng)預(yù)測進(jìn)程的新模型,,并將其應(yīng)用于小批量生產(chǎn)過程的預(yù)測補(bǔ)償控制領(lǐng)域。通過基于最速梯度法的優(yōu)化算法,,模型的動(dòng)態(tài)平滑參數(shù)和平滑初值能隨著新觀測值的加入而自動(dòng)調(diào)整,。將該模型作為關(guān)鍵技術(shù)應(yīng)用于柱塞套內(nèi)孔加工質(zhì)量預(yù)測,并與時(shí)序AR模型,、灰色GM模型及傳統(tǒng)指數(shù)平滑模型的結(jié)果進(jìn)行對(duì)比,,表明提出的模型具有一定的優(yōu)越性。

    Abstract:

    After analyzing the deficiency of traditional exponential smoothing prediction model, a novel prediction model with the concepts of dynamic smoothing parameter and initial value was proposed and applied to prediction compensation-control in small-batch production. In the presented model, with an optimal algorithm based on steepest-descent, the dynamic smoothing parameter and initial value were adjusted with new sample of the time-series automatically. Moreover, the presented model was used as the key technology of quality predicting in machining plungers of oil pump mouth, the practical results showed that compared with auto-regressive(AR), gray and traditional exponential smoothing model, the presented one is higher in precision and better in adaptation.

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吳德會(huì).基于動(dòng)態(tài)指數(shù)平滑模型的小批量制造過程質(zhì)量預(yù)測[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2008,39(8):164-168.[J]. Transactions of the Chinese Society for Agricultural Machinery,2008,39(8):164-168.

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