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基于知識工程的玉米果穗剝皮裝置設(shè)計
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國家重點研發(fā)計劃項目(2017YFD0700101)和國家自然科學(xué)基金項目(51805536)


Design of Corn Ear Peeling Device Based on Knowledge-based Engineering
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    摘要:

    收獲機械結(jié)構(gòu)復(fù)雜多樣,使用季節(jié)性強,且用戶多樣性、定制化需求特征明顯,傳統(tǒng)研發(fā)模式存在設(shè)計周期長、效率低和質(zhì)量難以保證等問題。本文以玉米聯(lián)合收獲機果穗剝皮裝置為研究對象,根據(jù)剝皮裝置結(jié)構(gòu)特征、技術(shù)參數(shù)和性能評價指標之間的關(guān)系,提出了基于知識工程的玉米果穗剝皮裝置設(shè)計方法。首先明確剝皮裝置設(shè)計流程,制定模塊化設(shè)計方案,按照功能劃分為專用件模塊、通用件模塊和標準件模塊,其中專用件模塊為剝皮裝置核心組成部件,主要包括剝皮輥、壓送器,通用件模塊包括喂入輥、輸送機構(gòu)、排雜器、傳動機構(gòu)和果穗回收機構(gòu)等,標準件模塊包括傳動件、連接緊固件和軸承等。然后按照標準、規(guī)范和約束范圍,建立剝皮裝置相關(guān)設(shè)計知識庫,分析玉米品種特性、作業(yè)形式、傳動方案、結(jié)構(gòu)參數(shù)和工作參數(shù)之間的數(shù)學(xué)關(guān)系,同時利用框架式表示法對剝皮裝置進行分解,建立自頂向下的譜系層次結(jié)構(gòu)?;诠脒\動學(xué)和動力學(xué)分析,融合文獻資料、試驗數(shù)據(jù)和專家經(jīng)驗,建立了剝皮裝置工作性能評價模型,包括苞葉剝凈率評價模型、籽粒損失率評價模型和籽粒破碎率評價模型。基于Visual Studio平臺,融合知識庫、推理機、評價模型和系統(tǒng)人機界面,開發(fā)了基于知識工程的玉米剝皮裝置設(shè)計系統(tǒng),實現(xiàn)用戶需求參數(shù)輸入下設(shè)計參數(shù)的實時計算輸出及參數(shù)評價?;谏鲜鲅芯浚訲PJ16型玉米果穗剝皮裝置參數(shù)為例,在交互界面輸入功率7.5kW、喂入量16.6t,計算獲取剝皮裝置關(guān)鍵結(jié)構(gòu)參數(shù)和運動參數(shù),并進行設(shè)計參數(shù)的性能評價,求解結(jié)果表明該剝皮裝置的苞葉剝凈率為96.01%,籽粒破碎率為1.42%,籽粒損失率為3.25%。

    Abstract:

    As one of the important agricultural equipment, the design of harvesting machinery has many typical characteristics, such as complex and diverse structures, strong seasonality, and obvious characteristics of users diversity and customization requirements. The traditional R&D mode have some problems, such as long design cycle, low efficiency and difficult quality assurance. Taking the ear peeling device of corn combine harvester as the research object, according to the relationship among the structural characteristics, technical parameters and performance evaluation indexes of the peeling device, the design method of the ear peeling device based on knowledge was presented. Firstly, the design process of peeling device was clarified, and the modular design scheme was formulated, which was divided into special parts module, general parts module, and standard parts module according to functions. The special module was the core component of the peeling device, mainly including the peeling roller and the pressure feeder; the general module included the feeding roller, the conveying mechanism, the impurity eliminator, the driving mechanism and the fruit spike recovery mechanism and so on; the standard module included the driving part, the connecting fastener and the bearing and so on. Secondly, according to the scope of standards, rules and constraints, the related design knowledge base of peeling device was established, the mathematical relationship between the features, operation form corn varieties, transmission scheme, structure parameters, and operating parameters were analyzed. The representation and storage method of the design knowledge of corn ear peeling device was studied. Meanwhile, the framework representation method was used to decompose the husking plant, and a topdown hierarchical structure was designed. Finally, the computer aided design (CAD) and knowledge engineering were integrated to study the reasoning mechanism design of corn ear peeling device. In addition, the working performance evaluation model of corn ear peeling device was established, including the component life calculation model, the bract stripping rate evaluation model, the grain loss rate evaluation model, and the grain breakage rate evaluation model. Based on the Visual Studio platform, the knowledge base, reasoning machine, evaluation model and humanmachine interface of system were integrated, and a design system of corn ear peeling device with knowledge was developed, which realized the realtime calculation output and parameter evaluation of design parameters under the input of users demand parameters. On the basis of the above research, taking the parameters of TPJ16 corn ear peeling device as an example, the input power at the interface was 7.5kW, the feeding amount was 16.6t, the key structural parameters and motion parameters of the peeling device were calculated and evaluated, and the performance of the design parameters was evaluated. The solution results showed that the peeling rate of bract leaves, grain crushing rate and grain loss rate of the peeling device were 96.01%, 1.42% and 3.25%, respectively. The research results provided a reference for the rapid design of agricultural machinery and equipment.

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杜岳峰,賀詩,毛恩榮,朱忠祥,栗曉宇,楊帆.基于知識工程的玉米果穗剝皮裝置設(shè)計[J].農(nóng)業(yè)機械學(xué)報,2020,51(s2):249-260. DU Yuefeng, HE Shi, MAO Enrong, ZHU Zhongxiang, LI Xiaoyu, YANG Fan. Design of Corn Ear Peeling Device Based on Knowledge-based Engineering[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(s2):249-260.

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  • 收稿日期:2020-07-25
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  • 在線發(fā)布日期: 2020-12-10
  • 出版日期: 2020-12-10
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