侯加林,王后新,牛子孺,席 芮,李天華
大蒜取種裝置取種清種性能離散元模擬與試驗
侯加林1,2,王后新1,3,牛子孺1,2,席 芮1,李天華1,2※
(1. 山東農(nóng)業(yè)大學(xué)機械與電子工程學(xué)院,泰安 271018;2. 山東省農(nóng)業(yè)裝備智能化工程試驗室,泰安 271018;3. 山東臨工工程機械有限公司,臨沂 276400)
針對當(dāng)前大蒜機械化種植單粒率低的問題,采用“取多留一”的設(shè)計思路,設(shè)計了爪式循環(huán)單粒取種裝置,采用離散元技術(shù)建立大蒜充種與清種動力學(xué)模型,通過單因素仿真試驗明晰了該裝置完成單粒取種的內(nèi)在機理。充種過程以取種爪中間板圓弧半徑、圓心角及側(cè)板橫向間距為試驗因素,以目標率為試驗指標,通過Box-Behnken試驗設(shè)計原理進行多因素仿真試驗,得到影響目標率的參數(shù)依次為取種爪側(cè)板橫向間距、中間板圓心角、中間板圓弧半徑;清種過程以清種柵板傾角為試驗因素,以合格率、漏播率為試驗指標,通過One-Factor試驗設(shè)計原理進行清種性能試驗,得到其響應(yīng)曲線。采用Design-Expert8.0.6進行取種參數(shù)優(yōu)化,結(jié)果表明各參數(shù)最優(yōu)值分別為中間板圓弧半徑為48.52 mm,中間板圓心角為72.59°,側(cè)板橫向間距為25.11 mm,柵板傾斜角度為7.41°;模型預(yù)測的目標率為90.64%,合格率為92.52%,漏播率為3.30%。開展了室內(nèi)及大田試驗,試驗數(shù)據(jù)與優(yōu)化結(jié)果一致,為大蒜機械化播種單粒取種技術(shù)研究提供了參考。
農(nóng)業(yè)機械;離散元方法;設(shè)計優(yōu)化;大蒜;單粒取種;響應(yīng)面
2018年中國大蒜種植面積超過83.5萬hm2,占全球種植面積的60%以上,但主要以人工種植為主,工作效率低、勞動強度大。市場上現(xiàn)有的大蒜種植機械漏播、重播現(xiàn)象嚴重,難以滿足“一穴一蒜”的農(nóng)藝種植要求,單粒取種技術(shù)滯后嚴重束縛了大蒜種植機械化的快速發(fā)展[1-6]。
很多學(xué)者開展了大蒜取種裝置的研究,多數(shù)采用“一次一粒”的方式[7-10]。薦世春等[7]設(shè)計了一款旋轉(zhuǎn)式蒜種單粒定向取種器;崔榮江等[8]設(shè)計了一種勺鏈式大蒜取種器,在高速取種時漏取現(xiàn)象較為嚴重;孫雪[9]設(shè)計了一款懸掛式大蒜播種機,采用指夾式大蒜取種結(jié)構(gòu),同樣存在高速取種漏取現(xiàn)象嚴重的問題。梁開星[10]采用氣吸式取種原理設(shè)計了一種大蒜單粒取種裝置。由于蒜種的背面和2個側(cè)面對吸氣面的要求不一樣,圓筒形的取種裝置比較適合吸取蒜種背面,而吸取2個平面時由于漏氣易導(dǎo)致蒜種掉落;圓盤形的取種器,在吸取蒜種的弧形背面時,同樣原因易使蒜種掉落;而增大氣量將會導(dǎo)致重播率的增加,因此,氣吸式取種裝置對蒜種形狀適應(yīng)性較差,易導(dǎo)致漏播或重播現(xiàn)象。
將離散元技術(shù)用于農(nóng)業(yè)機械排種裝置來模擬顆粒物質(zhì)的微觀動力學(xué)行為,已獲得成熟應(yīng)用[11-21]。通過離散元仿真可完成窩眼輪式小麥精量排種器設(shè)計中關(guān)鍵參數(shù)對充種性能影響的單因素試驗[12]。采用離散元和有限元軟件的耦合實現(xiàn)盤吸式水稻排種器吸種動力學(xué)過程模擬,可得到籽粒離散運動狀態(tài)穩(wěn)定最優(yōu)種層厚度[13]。在大豆高速精密播種機凸勺排種器設(shè)計與試驗中,可確定凸勺半徑和凸勺傾角的較優(yōu)取值范圍[14-17]。
針對大蒜單粒種植農(nóng)藝要求,本文采用“取多留一”的設(shè)計原則,研制爪式循環(huán)單粒取種裝置,通過離散元仿真試驗分析充種及清種機制,采用Box-Behnken中心試驗法和One-Factor試驗原理,并利用Design-Expert8.0.6軟件計算得到最優(yōu)取種、清種參數(shù)組合,以期為大蒜播種機械取種裝置設(shè)計優(yōu)化提供一種全新參考。
圖1a為爪式循環(huán)大蒜單粒取種裝置,由取種爪、鏈條、鏈輪、種箱、柵板組成,鏈輪帶動鏈條傳動,鏈條帶動取種爪運動,兩者速度一致。圖1b中的柵板傾角決定清種效果。充種階段,取種爪取到2~3粒蒜種;清種階段,取種爪沿著傾斜柵板構(gòu)成的清種滑道向上移動,容種空間逐漸減小,并在弧線7和斜線6交匯處達到最小。在柵板擠壓力和自身重力作用下,多取的蒜種被清掉并回落到種箱,取種爪內(nèi)只剩1粒蒜種,形成單粒取種,圖1c為取種爪結(jié)構(gòu)。
1.取種爪 2.鏈條 3.鏈輪 4.種箱 5.柵板 6.清種軌跡線 7.清種結(jié)束弧線
1.Seed-picking claw 2.Chain 3.Sprocket 4.Seed box 5.Grid 6.Seed-cleaning trace 7.Clean-ending arc
注:為圓弧半徑,mm;為圓心角,(°);為橫向?qū)挾?,mm;為傾角,(°)。
Note:is the arc radius, mm;is the central angle, (°);is the lateral width, mm;is the slope angle, (°).
圖1 爪式循環(huán)大蒜單粒取種裝置
Fig.1 Claw-type circulation single seed-picking device of garlic
選用山東省蘭陵Ⅱ型蒜種[22],長度為32.1±2.5 mm,寬度為18±2 mm,高度為18±2.5 mm;隨機選取200粒蒜種,沿拱背對稱面切成均勻兩半,用掃描儀掃描出蒜種成像模型,通過GetData Graph Digitizer軟件依次選取拱背弧線坐標點,獲得拱背數(shù)據(jù)點云樣本,利用Python3軟件繪制點云并確定取值域邊界后擬合生成曲線。采用二次多項式擬合得到平均中間曲線方程為
式中為蒜背高度參數(shù)變量,為蒜背寬度參數(shù)變量;為曲率半徑,mm。
將由式(2)計算得到的曲率半徑12.5~55.2 mm作為取種爪中間板圓弧半徑的設(shè)計取值范圍。而對于兩側(cè)板的形狀,在內(nèi)側(cè)與蒜種接觸的圓弧處做與中間板同直徑的1/8圓,安裝時,兩側(cè)板圓弧比中間板圓弧徑向高出3~5 mm。由于蒜種的縱向長度比橫向要大,因此以縱向長度作為依據(jù)統(tǒng)計拱背曲線,可滿足橫向放置以及介于兩者之間的任意擺放。由于蒜種拱背與平面接觸是單點接觸,因此中間板曲率半徑的設(shè)計充分考慮了蒜種拱背與取種爪更好的仿形接觸,提高充種穩(wěn)定性,而2~3粒取種目標取決于圓弧半徑、圓心角、側(cè)板橫向間距3個參數(shù)共同組成的充種空間。
為保證蒜種“取多”而不至于過多造成清種后的重播現(xiàn)象,以抓取2~3粒作為取種爪容種設(shè)計目標,容種量取決于蒜種體積以及蒜群孔隙率
式中為蒜群孔隙率;1為自然狀態(tài)體積,m3;2為密實體積,m3;為質(zhì)量,kg;為單個蒜種密度,=1080 kg/m3。
采用不同容器計算蒜群自然狀態(tài)體積1,并采用單粒投放、多粒投放以及一次性傾倒進行蒜種堆積,每種方式均進行50次試驗,孔隙率計算結(jié)果如表1所示,取值范圍為0.46~0.49,取平均孔隙率計算取種爪容種空間
式中3為取種爪容種空間,m3;為抓取蒜種粒數(shù),為實現(xiàn)取種2~3粒,=3。蒜群孔隙率為0.475,計算得出容種空間3為2.85×10-5m3。
表1 蒜群孔隙率
為減少仿真時間,取種模型簡化為柵板、種箱、取種爪3部分[23]。采用三維建模軟件建立與試驗用參數(shù)相同的取種裝置及蘭陵Ⅱ類大蒜的CAD模型[24],并分別導(dǎo)入到EDEM中。為滿足實際種群蒜種幾何尺寸差異,使用顆粒工廠功能并采用Random分布隨機生成蒜種,分布系數(shù)為構(gòu)建蒜種模型大小的0.92~1.07倍,共生成蒜種總質(zhì)量為3 kg,鱗芽朝向設(shè)定為隨機。
根據(jù)《GBZ26578—20大蒜生產(chǎn)技術(shù)規(guī)范》,平畦種植時株距為80~100 mm,行距為160~200 mm,作業(yè)速度為0.06~0.14 m/s[24]。取種速度通過式(6)計算
式中為取種速度,m/s;1為作業(yè)速度,m/s;為鏈條節(jié)距,mm;為2個取種爪間隔的鏈節(jié)個數(shù)。根據(jù)GB/T1243—1997,選取鏈條參數(shù)為08B-1-60,設(shè)置取種爪間距為5個鏈節(jié)63 mm,株距取100 mm,帶入式(6)得種取爪速度為0.04~0.09 m/s。
因為蒜種之間、蒜種與取種裝置之間均無黏附作用,所以模型中均采用Hertz-Mindlin無滑動接觸模型[12],柵板、種箱、取種爪設(shè)置為45號鋼,仿真所采用的物料本征參數(shù)、接觸參數(shù)如表2所示[22],以20%的時間步長作為計算步長。
表2 大蒜取種仿真參數(shù)
3.1.1 取種爪結(jié)構(gòu)對充種性能的影響
取種爪結(jié)構(gòu)決定容種空間大小,當(dāng)空間偏小時,一次抓取單粒蒜種,易掉落造成漏播;增大容種空間可滿足多粒取種要求,一次抓取3粒蒜種為較理想取種狀態(tài);當(dāng)超過3粒時,靠近柵板的蒜種穩(wěn)定性差,易同時留住或清掉,出現(xiàn)留多或漏播現(xiàn)象。
基于取種爪的容種空間以及蒜種外形參數(shù),同時根據(jù)實際大蒜種植取種經(jīng)驗,蒜種取種爪中間板圓弧半徑30~50mm,中間板圓心角60°~80°,兩側(cè)板橫向?qū)挾?8~30mm比較適合大蒜取種的要求。選取=40 mm,=70°,=24 mm;=30 mm,=60°,=24 mm;=30 mm,=70°,=30 mm分別為工況1、工況2、工況3的參數(shù),以取種速度為單因素進行取種效果仿真試驗,結(jié)果如圖2所示。
圖2 不同結(jié)構(gòu)參數(shù)取種效果
將1次抓取2~3粒蒜種的次數(shù)在總?cè)》N次數(shù)中所占的比例稱為抓取目標率,由圖2可知,在同一速度下不同的取種爪參數(shù)對充種性能有不同的影響,且目標率相差較大;當(dāng)以速度為單因素進行試驗時,同一種取種爪參數(shù)的目標率各異,且不同速度下工況1的目標率均為最佳,說明此取種爪參數(shù)適用于不同取種速度。
3.1.2 取種速度對充種性能的影響
良好的充種需滿足上一級取種后留下的空間能夠被種箱內(nèi)蒜種迅速填充,保證下一級取種爪有足量蒜種抓取。在取種爪參數(shù)為中間板圓弧=40 mm、圓心角=70°、橫向?qū)挾?24 mm的條件下,進行速度分別為0.04、0.07和0.1 m/s的仿真試驗。
速度為0.04 m/s時,蒜種速度以低速為主,回填較慢,充種效果較好;但取種爪內(nèi)小蒜群蒜種之間達成極穩(wěn)受力平衡,清種困難。0.1 m/s時,高速蒜種增多,回填減弱,充種不充分,蒜種不宜喂入;爪上蒜種與大蒜群速度差異較大,易充種失敗。
當(dāng)取種速度為0.07 m/s時,圖3是同一個維度的2 種顯示模式,圖3a為矢量模式,可以顯示蒜種運動速度矢量方向。由圖可知,取種后紅圈內(nèi)的空間被迅速回填,瞬時孔隙率較低,下一次取種時取種爪充種較充分,種箱內(nèi)的蒜群形成順時針“喂入運動”,易于充種;圖 3b為默認模式,蒜種以速度顏色為梯度擺放,種群內(nèi)以紅色、綠色標示的中高速蒜種數(shù)量較多。取種爪上的小蒜群速度與周邊的大蒜群速度呈現(xiàn)一定差異,可保證取到的蒜種受到周邊蒜種的適當(dāng)作用,不被壓實,易于清種。
圖3 取種速度為0.07 m·s-1仿真試驗
3.2.1 清種速度對清種性能的影響
設(shè)定清種速度為0.04、0.07、0.1 m/s,選取柵板角度為7.5°,中間板圓弧半徑48.52 mm,圓心角72.59°,兩側(cè)板間距為25.11 mm,以被清掉蒜種為研究對象,進行基于流線型顯示的運動軌跡仿真。
由圖4可知,速度為0.04 m/s時,在尖點區(qū)附件被清掉蒜種隨取種爪作近似圓弧運動,并在頂點處被清掉,清種軌跡與回落開始段區(qū)分不明顯,表明2個過程過渡平緩,蒜種較難被清掉;0.07 m/s時,清種與回落出現(xiàn)明顯的直線段,過程區(qū)分明顯,表明清種效果良好;0.1 m/s時,蒜種隨取種爪上升至高點后清掉回落,此時為圓弧運動的初始段,清種軌跡不明顯,運移軌跡和拋落軌跡無交叉但跨度小,表明蒜種極易被清掉。
圖5為被推掉蒜種實時平均速度曲線,清種速度為0.04 m/s時,1.5~1.8 s為清種開始到蒜種回落到種箱的時間段,曲線呈單峰狀態(tài),表明2個階段之間無受力突變,清種能力較弱,易產(chǎn)生“一爪多蒜”現(xiàn)象;0.07 m/s時,0.9~1.2 s為清種開始到回落到種箱的時間段,曲線呈現(xiàn)雙峰狀態(tài),表明2個階段有較顯著的受力突變,清種能力較強;0.1 m/s時,0.4~0.6 s為清種階段,曲線為單峰狀態(tài),蒜種受力較大,極易掉落,造成植后“空穴現(xiàn)象”。
注:v為取種速度,m?s-1;Note: v isspeed of picking seeds, m?s-1.
圖5 不同速度被推掉蒜種速度-時間圖
3.2.2 柵板傾角對清種性能的影響
設(shè)定清種速度為0.07 m/s,柵板傾角分別為4°、7.5°、11°,取種爪參數(shù)同3.2.1,對清掉蒜種進行基于流線型顯示的運動軌跡仿真。
圖6為被推掉蒜種取種-清掉-落回的運動軌跡,柵板角度為4°時,被清掉蒜種隨取種爪作近似圓弧運動,并在頂點處被清掉,清種與回落過渡平穩(wěn),蒜種較難被清掉;角度為11°時,無明顯清種軌跡,說明蒜種極易被清掉,上升與回落軌跡交叉,說明蒜種剛進入清種區(qū)或部分蒜種沒有進入清種區(qū)就已掉落,運移不穩(wěn)定,易發(fā)生蒜種全部被清掉現(xiàn)象。柵板角度為7.5°時,工況和圖4中速度為0.07 m/s時相同。
圖7為蒜種速度-時間曲線,在柵板角度為4°時,0.9~1.2 s為清種開始到蒜種回落到種箱時間段,曲線呈單峰狀態(tài),表明2個階段之間無受力突變,清種能力較弱,易產(chǎn)生“一爪多蒜”現(xiàn)象;在柵板角度為11°時,0.7~0.9 s時間段清種呈現(xiàn)單峰狀態(tài),由于無明顯清種軌跡,表明蒜種運移中直接掉落種箱,0~0.7 s為蒜種運移上升階段,被推掉蒜種的受力有一定程度的波動,運移不穩(wěn)定,易造成漏播。在柵板角度為7.5°時的曲線如圖 5中所示。
圖6 不同角度被推掉蒜種速度-軌跡過程云圖
圖7 不同角度被推掉蒜種速度-時間曲線
選取柵板傾角分別為4°、7.5°、11°,進行清種速度單因素試驗,傾角為4°,速度為0.07 m/s時合格率為90.3%,為0.1 m/s時為68.2%;傾角為7.5°,速度為0.07 m/s時合格率達最高93.1%,為0.1 m/s時最低為70.4%;傾角為11°,速度為0.07 m/s時合格率為86.3%,為0.1 m/s時最低為62.5%。因此,不同柵板傾角在清種速度為0.07 m/s時合格率均達到了最優(yōu),而最優(yōu)柵板傾角為7.5°。
為了獲得取種爪中間板圓弧半徑、圓心角、側(cè)板橫向間距及柵板傾角的最佳參數(shù),依據(jù)Box-Behnken試驗設(shè)計方法,進行多因素性能試驗[25-27],試驗因素和水平如表3所示,其中最優(yōu)充種及清種速度按單因素試驗結(jié)果取0.07 m/s。
表3 試驗因素和水平
根據(jù)“取多留一”的要求,充種時一次抓取2~3粒蒜種,清種后剩余1粒蒜種,充種和清種試驗分開進行,評價指標通過(7)式計算
式中1、2、3分別為目標率、為合格率、為漏播率,%;為取到2~3粒蒜種的次數(shù);為充種試驗總次數(shù);為剩余1粒蒜種的次數(shù);為剩余0粒蒜種的次數(shù);為清種試驗的總次數(shù)。裝置運行穩(wěn)定后,每種工況下統(tǒng)計200次取種爪的充種及清種情況,根據(jù)平均值計算評價指標。
4.2.1 試驗結(jié)果
試驗方案和結(jié)果如表4所示,表中1、2、3、4表示各因素編碼值。
4.2.2 回歸模型建立與顯著性檢驗
根據(jù)表4中充種數(shù)據(jù)樣本,利用Design-Expert 8.0.6軟件進行二次多元回歸擬合,建立1回歸方程式(8),試驗結(jié)果及方差分析見表5,<0.001表明模型高度顯著,失擬項>0.05表明擬合度高,參數(shù)可用該模型來優(yōu)化[28-30]。1中12,12對試驗影響不顯著(>0.05)。剔除后的方程如式(9),優(yōu)化后的模型<0.000 1、失擬項=0.880 1,可知模型可靠,各因素對目標率、貢獻率大小順序為:橫向?qū)挾?圓心角>圓弧半徑。建立2、3與柵板傾角的二次多項式回歸擬合方程,如式(10)、式 (11),并進行表5所示方差分析。2、3回歸模型的<0.001,表明模型高度顯著;失擬項>0.05,表明方程擬合度高。清種參數(shù)可以用該模型來優(yōu)化。2中2個回歸項影響極顯著(<0.01),無回歸項對試驗影響不顯著;漏播率3中2個回歸項影響極顯著(<0.01),無回歸項對試驗影響不顯著。
表4 試驗設(shè)計方案以及響應(yīng)值
表5 回歸方程方差分析
注:<0.01(極顯著,**)<0.05(顯著,*)
Note:<0.01 (highly significant,**),<0.05 (significant,*)
4.2.3 因素影響效應(yīng)分析
利用Design-Expert8.0.6分別繪制圓弧半徑、圓心角、橫向?qū)挾葘δ繕寺实捻憫?yīng)面及柵板傾角對合格率、漏播率的影響曲線,分別如圖8、圖9所示。圖8a為圓弧半徑位于中心水平(40 mm),目標率隨橫向間距和圓心角的增大先增大后減小,橫向間距對目標率的影響略顯著于圓心角。圖8b為橫向間距位于中心水平(24 mm),圓弧半徑一定時目標率隨圓心角的增大先增大后減?。粓A心角一定時目標率隨圓弧半徑的增大而增大,圓心角對目標率的影響顯著于圓弧半徑。圖8c為圓心角位于中心水平(70°),目標率隨著橫向間距的增大先增大后減小,當(dāng)橫向?qū)挾仍?8~28 mm范圍時,目標率隨著圓弧半徑的增大而增大,當(dāng)橫向?qū)挾仍?8~30 mm范圍時,目標率隨著圓弧半徑的增大而減小,橫向?qū)挾葘δ繕寺实挠绊戯@著于圓弧半徑。由圖9可知,合格率隨柵板傾角的增大先增大后減小,柵板傾角7°左右合格率達到最大值;漏播率隨著柵板傾角的增大先減小后增大,但是減小的幅度較小,柵板傾角6.5°左右漏播率達到最低。
a. Y1(40, X2, X3)b. Y1(X1, 24, X2)c. Y1(X1, X3, 70)
a. 合格率 a. Qualified rateb. 漏播率 b. Missing rate
4.2.4 參數(shù)優(yōu)化
采用Design-Expert8.0.6計算充種和清種最佳參數(shù)組合,結(jié)合各因素邊界條件建立的優(yōu)化模型為
得出各參數(shù)最優(yōu)值為取種爪中間板圓弧半徑為48.52 mm、圓心角為72.59°、側(cè)板橫向間距為25.11 mm,柵板傾角為7.41°,模型預(yù)測目標率為90.64%,合格率為92.52%,漏播率為3.30%。
5.1.1 試驗材料與過程
為驗證取種裝置的有效性,在山東農(nóng)業(yè)大學(xué)機電學(xué)院107試驗室進行如圖10所示取種試驗。
1.種箱 2.柵板 3.鏈條 4.鏈輪 5.取種爪
用于試驗的取種爪中間板圓弧半徑為48 mm,圓心角為72°,側(cè)板橫向間距為25 mm,傾角為7°,通過變頻器控制取種速度。
圖11為高速攝像機記錄的充種和清種過程,圖中圓圈標記的為即將掉落的蒜種,其中圖11a為3粒蒜種變2粒的過程,圖11b為2粒變1粒的過程,圖11c為留下的1粒蒜種隨取種爪達到輸送軌道,整個清種過程和仿真基本類似,定性的說明離散元技術(shù)可以較好地模擬取種過程。
圖11 大蒜取種清種試驗
5.1.2 試驗結(jié)果與分析
取種裝置運行穩(wěn)定后,每種工況下統(tǒng)計200次取種爪的充種及清種情況,并計算評價指標,將室內(nèi)試驗統(tǒng)計數(shù)據(jù)與仿真試驗結(jié)果進行對比,如圖12所示。最優(yōu)參數(shù)條件下,在速度為0.07 m/s時,室內(nèi)試驗的目標率為89%,與優(yōu)化值90.64%的相對誤差為1.8%;室內(nèi)試驗的合格率為91.50%,與優(yōu)化值92.52%的相對誤差為1.1%;室內(nèi)試驗的漏播率為4.5%,優(yōu)化值3.30%。因此,優(yōu)化模型可靠,參數(shù)優(yōu)化正確。
a. 目標率b. 合格率c. 漏播率 a. Target rate b. Qualified rate c. Missing rate
5.2.1 試驗條件
2019年5月在山東省臨沂市界前新村大蒜生產(chǎn)機械化作業(yè)示范基地,根據(jù)《GB/T 6973—2005 單位(精密)播種機試驗方法》進行了大田試驗,如圖13所示。試驗材料為蘭陵大蒜分級后的Ⅱ號蒜種,蒜種含水率為45%~60%;試驗地塊地表平整,土壤類型為壤土;作業(yè)速度為0.06~0.16 m/s,以作業(yè)速度為單因素變量統(tǒng)計200個蒜穴對應(yīng)的目標率、合格率、漏播率。
圖13 樣件現(xiàn)場作業(yè)
5.2.2 試驗結(jié)果與分析
每種工況下統(tǒng)計200穴種植情況,并根據(jù)平均值計算評價指標,將大田試驗統(tǒng)計數(shù)據(jù)與室內(nèi)試驗結(jié)果進行對比。在取種速度為0.07 m/s時,大田試驗合格率為93.1%,室內(nèi)試驗合格率91.5%;大田試驗漏播率為3.8%,室內(nèi)試驗漏播率4.5%??梢?,大蒜大田種植的合格率、漏播率與室內(nèi)試驗結(jié)果具有較好的一致性。
本文基于大蒜勺鏈式取種裝置,基于“取多留一”的設(shè)計思想,研制了三爪循環(huán)式大蒜取種裝置,通過仿真和試驗驗證,該裝置切實提高了大蒜單粒播種率,在一定程度上補齊了大蒜機械化種植單粒取種效果差的短板。
1)通過離散元技術(shù)對三爪循環(huán)式大蒜取種裝置充種、清種進行了單因素仿真分析,研究不同速度、柵板傾角以及取種爪結(jié)構(gòu)參數(shù)對取種效果的影響,明晰了“取多留一”取種方式的內(nèi)在機理。
2)以取種爪圓弧半徑、圓心角、橫向?qū)挾葹樵囼炓蛩?,以目標率為試驗指標,采用Box-Behnken試驗設(shè)計,進行多因素充種試驗,得到影響目標率的參數(shù)主次順序為橫向?qū)挾?、圓心角、圓弧半徑。采用Design-Expert8.0.6進行參數(shù)優(yōu)化,以目標率為試驗指標,得出圓弧半徑為48.52 mm、圓心角為72.59°、橫向?qū)挾葹?5.11 mm,模型預(yù)測目標率為90.64%。經(jīng)過試驗驗證了優(yōu)化結(jié)果。
3)以柵板傾斜角度為試驗因素,以合格率、漏播率為試驗指標,采用One-Factor試驗設(shè)計原理進行清種試驗;利用Design-Expert8.0.6優(yōu)化得到柵板最優(yōu)傾角為7.41°,預(yù)測合格率為92.52%、漏播率為3.30%,與試驗驗證結(jié)果基本一致。
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Discrete element simulation and experiment of picking and clearing performance of garlic seed-picking device
Hou Jialin1,2, Wang Houxin1,3, Niu Ziru1,2, Xi Rui1, Li Tianhua1,2※
(1.,,271018,; 2.,271018,; 3.,276400,)
In recent years, garlic planting area has become larger and larger in China, however, the level of mechanization of domestic garlic cultivation is low, at present, so all the garlic cultivation still mainly relies on manpower to complete, with low working efficiency and high labor intensity, moreover, the randomness of planting parameters is not conducive to the development of garlic mechanization. Aiming at the problem of low single seed rate in garlic mechanized planting, a claw type circulation single seed taking device was designed with the design idea of "taking more and keeping one". The dynamic model of garlic seed filling and clearing was established with discrete element technology. The internal mechanism of single seed picking was clarified through single factor simulation test. In the seed-picking process, the arc radius, center angle and lateral spacing of the middle plate of the seed taking claw were taken as the test factors, and the target rate was taken as the test index. Based on the box Behnken test design principle, the multi factor simulation test was carried out, and the parameters that affect the target rate were successively the lateral spacing of the side plate of the seed taking claw, the center angle of the middle plate and the arc radius of the middle plate. In the seed cleaning process, the inclination angle of the seed cleaning grid plate was taken as the test factors, taking the qualified rate and the missed seeding rate as the test indexes. Through the one factor test design principle, the seed cleaning performance test was carried out, and the response curve was obtained. Response curve was drawn using Design Expert 8.0.6 to investigate the effect of grid tilt angle on the response value of target rate, missing rate and replay rate, and optimize the parameters of seed selection. The response curve showed that the target rate increased first and then decreased with the increase of grid tilt angle, and the target rate reached the maximum value when the grid tilt angle was about 7°. The missing rate decreased first and then increased with the increase of grid tilt angle; the replay rate increased with the increase of grid tilt angle. The increase of gate inclination decreased first and then increased, but the increase amplitude was small. The results showed that the optimal values of the parameters were the arc radius of the middle plate was 48.52 mm, the center angle of the middle plate was 72.59%, the lateral spacing of the side plate was 25.11 mm, and the inclination angle of the grid plate was 7.41°. The predicted target rate of the model was 90.64%, the qualified rate was 92.52%, and the leakage rate was 3.30%. Laboratory and field experiments were carried out, and the experimental data were consistent with the optimization results, which provided a reference for the study of garlic mechanized seeding single seed picking technology.
agricultural machinery; discrete element method; design optimization; garlic; single seed picking; response surface
侯加林,王后新,牛子孺,席 芮,李天華. 大蒜取種裝置取種清種性能離散元模擬與試驗[J]. 農(nóng)業(yè)工程學(xué)報,2019,35(24):48-57. doi:10.11975/j.issn.1002-6819.2019.24.006 http://www.tcsae.org
Hou Jialin, Wang Houxin, Niu Ziru, Xi Rui, Li Tianhua. Discrete element simulation and experiment of picking and clearing performance of garlic seed-picking device[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(24): 48-57. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2019.24.006 http://www.tcsae.org
2019-06-05
2019-10-14
國家特色蔬菜產(chǎn)業(yè)技術(shù)體系(CARS-24-D-01)、山東省農(nóng)機裝備研發(fā)創(chuàng)新計劃項目(2017YF001)、山東省現(xiàn)代農(nóng)業(yè)產(chǎn)業(yè)技術(shù)體系蔬菜產(chǎn)業(yè)創(chuàng)新團隊項目(SDAIT-05-11)、泰安市大學(xué)生科技創(chuàng)新行動計劃項目(2017D021)
侯加林,博士,教授,主要從事智能農(nóng)機裝備的研究。Email:jlhou@sdau.edu.cn。
李天華,博士,副教授,主要從事智能農(nóng)機裝備的研究。Email:lth5460@163.com。
10.11975/j.issn.1002-6819.2019.24.006
S223.2+3
A
1002-6819(2019)-24-0048-10