王申瑩,胡志超,吳 峰,于昭洋,曹明珠,高學(xué)梅
全喂入花生撿拾收獲機(jī)喂入量建模與試驗
王申瑩,胡志超※,吳 峰,于昭洋,曹明珠,高學(xué)梅
(農(nóng)業(yè)農(nóng)村部南京農(nóng)業(yè)機(jī)械化研究所,南京 210014)
為解決中國全喂入花生撿拾收獲機(jī)作業(yè)時因喂入量波動導(dǎo)致作業(yè)性能下降甚至出現(xiàn)機(jī)械故障,而花生撿拾收獲機(jī)喂入量相關(guān)基礎(chǔ)研究又缺失的問題,該文以團(tuán)隊前期所研制的4HLJ-3000型全喂入花生撿拾收獲機(jī)為研究對象,提出了基于撿拾臺動力輸入軸扭矩的喂入量監(jiān)測方法。通過對撿拾臺進(jìn)行動力分析,得出了撿拾臺動力輸入軸扭矩和喂入量的數(shù)學(xué)模型。利用撿拾臺動力輸入軸轉(zhuǎn)速、扭矩和功率等工況數(shù)據(jù)監(jiān)測存儲分析管理系統(tǒng)進(jìn)行了扭矩和喂入量的道路監(jiān)測試驗。對試驗結(jié)果進(jìn)行了線性函數(shù)、冪函數(shù)、指數(shù)函數(shù)和二次函數(shù)擬合回歸分析,結(jié)果表明二次函數(shù)模型擬合度較高,其決定系數(shù)2為0.990。對二次函數(shù)擬合曲線進(jìn)行分析,結(jié)果表明,當(dāng)喂入量小于等于3.0 kg/s時,隨著喂入量的增加扭矩緩慢增加;當(dāng)喂入量大于3.0 kg/s時,隨著喂入量的增加,扭矩急劇增加,且轉(zhuǎn)速隨之降低。模型驗證試驗的結(jié)果表明,所建立的二次函數(shù)模型具有較好的準(zhǔn)確性,絕對偏差率范圍為0.42%~2.43%,平均偏差率為1.40%,且喂入量越大,偏差率越大。對喂入量和扭矩的函數(shù)模型進(jìn)行了田間試驗,結(jié)果表明,扭矩偏差率范圍為1.90%~3.58%,平均偏差率為2.65%。研究結(jié)果可為全喂入式花生及其他作物撿拾收獲機(jī)結(jié)構(gòu)優(yōu)化設(shè)計及喂入量的智能測控提供參考。
農(nóng)業(yè)機(jī)械;建模;試驗;花生;全喂入收獲機(jī);撿拾臺;喂入量;扭矩
花生是世界油料生產(chǎn)和貿(mào)易中僅次于大豆的油料作物和經(jīng)濟(jì)作物之一[1-3]。2017年,中國花生種植面積4.61×106hm2,產(chǎn)量1.71×107t,分別位居世界前列。但中國花生收獲機(jī)械化水平較美洲國家相對滯后,大部分花生種植區(qū)仍以半機(jī)械化和分段收獲為主[4-8],2017年,中國花生機(jī)械化收獲水平僅為39.72%[9]?,F(xiàn)有的花生撿拾收獲機(jī)的設(shè)計多參考國外技術(shù)或借鑒稻麥聯(lián)合收獲機(jī)相關(guān)技術(shù),專業(yè)的研究比較少,故障率高、作業(yè)性能質(zhì)量不理想,嚴(yán)重制約了花生產(chǎn)業(yè)的發(fā)展。喂入量的監(jiān)測和控制是花生撿拾收獲機(jī)設(shè)計中關(guān)鍵技術(shù)之一,各個部件的工作性能均與喂入量密切相關(guān)。收獲時若喂入量小于設(shè)計喂入量,會降低收獲機(jī)的作業(yè)效率,增加收獲成本;若大于設(shè)計喂入量,則會造成收獲機(jī)后續(xù)輸送、脫粒分離及清選等部件的作業(yè)性能下降,當(dāng)喂入量遠(yuǎn)超過各工作部件的承受能力時,將會出現(xiàn)擁堵現(xiàn)象甚至出現(xiàn)機(jī)械故障。
國外對農(nóng)作物聯(lián)合收獲機(jī)喂入量方面的研究起步早,但多集中在稻麥聯(lián)合收獲機(jī)方面[10-15],對花生收獲機(jī)喂入量的研究較少(因為國外花生品種多為蔓生形,收獲時花生果秧相互交織在一起類似地毯,喂入量相對均勻穩(wěn)定)。Robert[16]通過一定的控制算法改變稻麥?zhǔn)斋@機(jī)的行走速度穩(wěn)定滾筒負(fù)荷,從而獲得穩(wěn)定的喂入量。Miosz[17]對稻麥?zhǔn)斋@損失率及喂入量進(jìn)行了研究,建立了收割機(jī)作業(yè)速度控制模型。Gomez-Gil等[18]利用GPS技術(shù)和顆粒重量傳感器及田間試驗,建立了谷物聯(lián)合收割機(jī)喂入量和作業(yè)速度的數(shù)學(xué)模型。Bajema等[19]設(shè)計了馬鈴薯收獲機(jī)2級傳輸裝置,并根據(jù)第二級輸送裝置所承受的負(fù)載量控制收獲機(jī)的前進(jìn)速度。
中國花生收獲機(jī)械的研究多集中在半喂入聯(lián)合收獲機(jī)整機(jī)設(shè)計與試驗研究[20-23]、花生挖掘收獲機(jī)的研制[24-26]、花生收獲機(jī)摘果、清選和自動控制等關(guān)鍵部件的設(shè)計優(yōu)化研究[27-31]以及花生撿拾聯(lián)合收獲機(jī)撿拾器的結(jié)構(gòu)設(shè)計與試驗優(yōu)化[32-35]。目前,中國花生撿拾收獲機(jī)喂入量的大小主要憑借駕駛員的經(jīng)驗調(diào)控,針對全喂入花生撿拾收獲機(jī)喂入量的學(xué)術(shù)研究鮮有報道,喂入量的相關(guān)研究多集中在稻麥聯(lián)合收獲機(jī)方面。李耀明等[36]研究了谷物聯(lián)合收獲機(jī)喂入量與脫粒滾筒凹板篩后側(cè)油缸壓力和脫粒分離總損失的關(guān)系。陳進(jìn)等[37]借助試驗臺對谷物聯(lián)合收獲機(jī)傾斜輸送器喂入主動軸扭矩與喂入量的關(guān)系進(jìn)行了研究。劉元元等[38]分析了谷物聯(lián)合收割機(jī)割臺螺旋輸送器動力學(xué)模型,對螺旋輸送器功率和喂入量的關(guān)系進(jìn)行了研究。盧文濤等[39]設(shè)計了谷物聯(lián)合收獲機(jī)脫粒滾筒液壓無級變速系統(tǒng),并通過臺架試驗得出了喂入量與油壓力之間的關(guān)系方程。陳度等[40]對稻麥聯(lián)合收割機(jī)喂入量和收獲損失的影響因素進(jìn)行了分析,建立了喂入量與收獲過程損失的數(shù)學(xué)模型。介戰(zhàn)等[41]研究了一種由喂入量擠壓力測試原理、喂入量測試模型建立和當(dāng)量喂入量測試方法組成的GPS聯(lián)合收獲機(jī)隨機(jī)喂入量實時測試的理論和技術(shù)。張振乾等[42]設(shè)計了基于谷物聯(lián)合收割機(jī)割臺傳動軸扭矩的喂入量監(jiān)測系統(tǒng),并建立了喂入量預(yù)測模型。尤惠媛等[43]基于谷物聯(lián)合收獲機(jī)脫粒滾筒無級變速液壓缸油壓力設(shè)計了喂入量模糊控制系統(tǒng)。
本文旨在前期研制的全喂入花生撿拾收獲機(jī)的基礎(chǔ)上設(shè)計一種喂入量測量方法,建立撿拾臺動力輸入軸扭矩與喂入量的數(shù)學(xué)模型,以期為花生撿拾收獲機(jī)自動控制研究提供理論基礎(chǔ)和技術(shù)參考,主要研究內(nèi)容包括:1)分析全喂入花生收獲機(jī)撿拾臺動力輸入軸扭矩與喂入量間的數(shù)學(xué)模型;2)設(shè)計一種全喂入花生收獲機(jī)喂入量監(jiān)測系統(tǒng)和方法;3)通過試驗分析喂入量和輸入軸扭矩的具體函數(shù)關(guān)系。
前期所研制的4HLJ-3000型全喂入花生撿拾收獲機(jī)撿拾臺結(jié)構(gòu)如圖1所示,主要由限深輪、壓秧桿、滑秧板、撿拾彈齒、螺旋輸運器等組成。主要完成花生秧果撿拾、推送集中并向后輸送等作業(yè)。其傳動系統(tǒng)如圖2所示,其動力由撿拾臺動力輸入軸(3)提供,動力經(jīng)傳動鏈帶動螺旋輸運器軸(2)旋轉(zhuǎn),再經(jīng)撿拾器驅(qū)動鏈(8)和3個張緊輪(4、5、1)帶動撿拾器軸(7)的旋轉(zhuǎn),并實現(xiàn)螺旋輸運器和撿拾器的反向轉(zhuǎn)動。撿拾臺動力輸入軸和螺旋輸運器軸的傳動比1=1.0,螺旋輸運器軸和撿拾器軸的傳動比2=3.5。撿拾臺主要參數(shù)如表1所示。
1.撿拾彈齒 2.滑秧板 3.滑秧板交接支撐架 4.螺旋輸運器凹板 5.螺旋輸運器 6.限深輪 7.壓秧桿
1.第三張緊鏈輪 2.螺旋輸運器軸 3.撿拾臺動力輸入軸 4.第一張緊鏈輪 5.第二張緊鏈輪 6.撿拾器鏈輪 7.撿拾器軸 8.螺旋輸送器撿拾器傳動鏈 9.撿拾器驅(qū)動鏈輪
表1 撿拾輸送裝置主要參數(shù)
工作時,花生秧果在旋轉(zhuǎn)撿拾彈齒的帶動及與壓秧桿的相互作用下沿著滑秧板進(jìn)入到螺旋輸運器,在螺旋輸運器的旋轉(zhuǎn)聚攏作用下,花生秧果被聚集到中間并傳送給后續(xù)輸送裝置,運動路徑如圖1中箭頭所示。
收獲作業(yè)時,撿拾臺的動力分析如圖3所示。
注:T、T1、T2分別為撿拾臺動力輸入軸、撿拾器軸和螺旋輸運器軸的扭矩,N?m;n、n1和n2分別為撿拾臺動力輸入軸、撿拾器軸和螺旋輸運器軸的轉(zhuǎn)速,r?min-1;R為撿拾彈齒回轉(zhuǎn)半徑,m。
由圖3可知,撿拾臺總功率為
=/9550(1)
式中為撿拾臺動力輸入軸的總功率,kW;為撿拾臺動力輸入軸扭矩,N·m;為撿拾臺動力輸入軸轉(zhuǎn)速,r/min。
設(shè)鏈輪與輸送鏈以及軸承之間的功率損失為0,根據(jù)能量守恒原理,總功率可分解為
式中1為撿拾器軸的功率,kW;1為撿拾器軸的扭矩,N?m;1為撿拾器軸的轉(zhuǎn)速,r/min;2為螺旋輸運器軸的功率,kW;2為螺旋輸運器軸的扭矩,N?m;2為螺旋輸運器軸的轉(zhuǎn)速,r/min;0為鏈輪與輸送鏈以及軸承之間因摩擦引起的扭矩,為常數(shù),N?m。
撿拾器撿拾的花生果秧為自然鋪放狀態(tài),花生果秧與滑秧板之間的摩擦力比較小,可忽略;撿拾器軸主要受到由于花生果秧重力引起的扭矩。近似認(rèn)為花生果秧集中作用在撿拾彈齒端部,則
1=0(3)
=0(4)
式中為花生果秧自然鋪放密度,kg/m3;為撿拾臺寬度,m;為花生果秧自然鋪放厚度,m;0為收獲機(jī)前進(jìn)速度,m/s;為重力加速度,m/s2;為撿拾彈齒回轉(zhuǎn)半徑,m;為喂入量,kg/s。
由式(3)和式(4)可知
1=(5)
花生果秧經(jīng)撿拾器撿起并傳送到螺旋輸運器后,在螺旋輸運器擠壓、推送的作用下被輸送到后續(xù)輸送裝置。螺旋輸運器不僅受到垂直于螺旋葉片表面的花生果秧重力的作用,還受到沿螺旋葉片切向摩擦阻力F的作用。該摩擦阻力F和花生果秧與螺旋葉片間的擠壓力F成正比[36]。取花生莢果、花生葉和莖稈與螺旋輸運器之間的綜合摩擦系數(shù)為,則
2=/2+FD/2(6)
F=F(7)
參考文獻(xiàn)[36]和[44]可知,擠壓力F與花生果秧受擠壓程度有關(guān),且有
F=K(max/)(8)
max=/[(1+)ρvw](9)
式中K為系數(shù);max為非谷粒物料自然鋪放厚度,mm;為螺旋葉片與凹板之間的間隙,mm;為一實數(shù);為果秧質(zhì)量比;v為果秧在螺旋輸運器中的平均線速度,m/s;為螺旋輸運器寬度,m,即等于撿拾臺寬度。
由式(5)~(8)可知
由式(1)、式(2)、式(4)和式(9)以及上述傳動比可知撿拾臺總功率為
將式(1)帶入上式得
由上式可知,當(dāng)其他參數(shù)(花生果秧密度和果秧比)一定、撿拾收獲機(jī)穩(wěn)定均勻喂入時,撿拾臺動力輸入軸扭矩主要受喂入量的影響。上式可化簡為
式中0、1、2為常系數(shù)。
2.2.1 總體結(jié)構(gòu)
為實時測量試驗數(shù)據(jù),本文設(shè)計了花生撿拾臺工況監(jiān)測系統(tǒng),主要監(jiān)測撿拾臺動力輸入軸轉(zhuǎn)速、扭矩和功率。監(jiān)測系統(tǒng)結(jié)構(gòu)框圖如圖4所示,系統(tǒng)主要由傳感器單元、數(shù)據(jù)采集和數(shù)據(jù)存儲分析3個部分組成。傳感器單元把撿拾臺動力輸入軸扭矩和轉(zhuǎn)速轉(zhuǎn)換成頻率信號,數(shù)據(jù)采集模塊將頻率信號轉(zhuǎn)換成扭矩、轉(zhuǎn)速值顯示,并通過RS485總線和RS485轉(zhuǎn)USB傳送到計算機(jī)存儲。
圖4 監(jiān)測系統(tǒng)結(jié)構(gòu)框圖
2.2.2 傳感器單元
轉(zhuǎn)矩轉(zhuǎn)速傳感器采用北京三晶聯(lián)合科技有限公司生產(chǎn)的SL06-2000AT型扭矩傳感器,主要用來監(jiān)測撿拾臺總動力輸入軸的轉(zhuǎn)速和扭矩,主要參數(shù)如表2所示。
表2 傳感器主要參數(shù)
采用應(yīng)變電測原理測量扭矩,將應(yīng)變計粘貼在應(yīng)變軸上,當(dāng)應(yīng)變軸受扭力產(chǎn)生微小變形時,應(yīng)變計阻值發(fā)生相應(yīng)變化。測量電橋由具有相同應(yīng)變特性的應(yīng)變計組成,可將應(yīng)變電阻的變化轉(zhuǎn)化為電壓信號的變化,如圖5所示。電源經(jīng)能源輸入耦合器耦合后傳輸?shù)綉?yīng)變軸上,再經(jīng)穩(wěn)壓電路形成穩(wěn)定電壓。應(yīng)變橋?qū)?yīng)變軸的微小變形轉(zhuǎn)化為電壓信號,并經(jīng)放大器放大后送到V/F變換器,再經(jīng)輸出信號耦合器和信號輸出電路輸出調(diào)頻方波信號。
轉(zhuǎn)速的測量采用光電開關(guān)碼盤原理,當(dāng)測速碼盤連續(xù)旋轉(zhuǎn)時,通過光電開關(guān)輸出具有一定周期寬度的脈沖信號,轉(zhuǎn)速可根據(jù)下式計算得出
=60f/(14)
式中f為實測轉(zhuǎn)速輸出頻率值,Hz;為傳感器測速碼盤齒數(shù)。
1. 能源輸入耦合器 2.穩(wěn)壓電路 3.應(yīng)變橋 4.放大器 5.V/F變換器 6.輸出信號耦合器 7.信號輸出電路
傳感器的安裝方法為:將撿拾臺動力輸入軸剪斷分為2個半軸,傳感器通過兩端的內(nèi)外花鍵安裝在2個半軸中間。
2.2.3 數(shù)據(jù)采集
數(shù)據(jù)采集采用北京三晶聯(lián)合科技有限公司生產(chǎn)的轉(zhuǎn)矩轉(zhuǎn)速測試儀。該采集儀可實時監(jiān)測顯示撿拾臺動力輸入軸的扭矩、轉(zhuǎn)速,并可設(shè)定扭矩、轉(zhuǎn)速的小數(shù)點位置,同時通過計算顯示實時功率。該測試儀精度0.1%,外供電源12VDC,轉(zhuǎn)速輸入脈沖1~20000Hz,扭矩輸入脈沖5~15 kHz,扭矩變送4~20mA,轉(zhuǎn)速變送4~20mA,RS485數(shù)據(jù)輸出。
2.2.4 數(shù)據(jù)存儲分析
數(shù)據(jù)存儲分析軟件采用與數(shù)據(jù)采集控制器配套的M400數(shù)據(jù)采集管理軟件。該軟件可實時顯示扭矩、轉(zhuǎn)速和功率曲線及數(shù)值,亦可存儲歷史數(shù)據(jù)和曲線,并可調(diào)出任意時刻的曲線和數(shù)據(jù)。
為了確定喂入量與撿拾臺動力輸入軸扭矩的數(shù)學(xué)模型,利用4HLJ-3000型花生撿拾聯(lián)合收獲機(jī)在河南省駐馬店市進(jìn)行了道路收獲試驗。其它試驗器材有標(biāo)桿、秒表、卷尺、電子秤等。
試驗花生品種為皖花2號,種植模式為單壟雙行,土壤為沙壤土,壟距平均為800 mm,株距平均為260 mm,花生株高平均在400 mm,每株平均結(jié)果16顆,產(chǎn)量7 500 kg/hm2。花生果秧采用市場上常見的5HZ-175型花生挖掘收獲機(jī)挖掘后,放在田間自然晾曬3 d,花生秧含水率為20%~30%。
參照GB/T5262-2008《農(nóng)業(yè)機(jī)械試驗條件測定方法的一般規(guī)定》和NY/T 2204-2012《花生收獲機(jī)質(zhì)量評價技術(shù)規(guī)范》,試驗分別測定全喂入花生撿拾收獲機(jī)不同工作條件下的扭矩、轉(zhuǎn)速、前進(jìn)速度及喂入量。在花生試驗田內(nèi)隨機(jī)選取9個小區(qū)進(jìn)行試驗,每個小區(qū)長度為20 m,寬度為花生撿拾聯(lián)合收獲機(jī)作業(yè)幅寬。為方便試驗觀測、降低試驗成,人工將每個小區(qū)內(nèi)花生果秧收集并按照挖掘收獲后田間的狀態(tài)(小區(qū)內(nèi)花生挖掘收獲后呈現(xiàn)的長度、寬度和鋪放厚度)將花生果秧重新鋪放到水泥道路上。每次試驗待收獲機(jī)發(fā)動機(jī)轉(zhuǎn)速達(dá)到額定轉(zhuǎn)速進(jìn)入穩(wěn)定狀態(tài)后再進(jìn)行收獲試驗。應(yīng)用M400數(shù)據(jù)采集管理軟件對試驗過程中的撿拾臺動力輸入軸轉(zhuǎn)速和扭矩進(jìn)行實時監(jiān)測,選取每個試驗小區(qū)扭矩、轉(zhuǎn)速動態(tài)曲線達(dá)到穩(wěn)定后的時間段作為測定時間,將此時間段內(nèi)每0.5 s的扭矩和轉(zhuǎn)速數(shù)值導(dǎo)出,分別取此時間段內(nèi)扭矩和轉(zhuǎn)速的的平均值。用秒表監(jiān)測試驗時間,計算出每次試驗的平均前進(jìn)速度。每次試驗后,將掉落的花生秧果、集秧箱中花生秧及糧倉中的花生莢果進(jìn)行稱重,結(jié)合每次試驗所用的時間計算出每次試驗的平均喂入量。為減小誤差,試驗重復(fù)3次,結(jié)果取均值。試驗情況如圖6所示。
圖6 道路試驗情況
扭矩、轉(zhuǎn)速、前進(jìn)速度及喂入量的試驗結(jié)果如表3所示。
表3 道路試驗結(jié)果
應(yīng)用SPSS數(shù)據(jù)處理軟件對表3中的扭矩和喂入量進(jìn)行擬合回歸分析。參考文獻(xiàn)[40],利用線性函數(shù)、冪函數(shù)、指數(shù)函數(shù)和二次函數(shù)對試驗數(shù)據(jù)進(jìn)行擬合分析,擬合曲線如圖7所示。
從擬合結(jié)果可知,二次函數(shù)的2值最高,說明試驗所得的二次函數(shù)模型對該樣機(jī)的擬合精度較高,即在聯(lián)合收獲機(jī)工作穩(wěn)定、喂入均勻、作物狀態(tài)(密度和鋪放厚度)基本一致時,撿拾臺動力輸入軸扭矩與喂入量的二次函數(shù)模型與前述理論分析得出的數(shù)學(xué)模型式(13)吻合度較高。
由圖7二次函數(shù)擬合曲線可以看出,當(dāng)喂入量小于等于3 kg/s時,隨著喂入量的增加扭矩增加比較緩慢,因為該樣機(jī)的設(shè)計喂入量為2 kg/s,喂入量的小幅增加,主要是由于花生果秧重量的增加導(dǎo)致?lián)焓捌鬏S和螺旋輸運器軸的扭矩小幅增加,增加幅度尚在撿拾臺的容許范圍內(nèi)。但當(dāng)喂入量大于3 kg/s時,隨著喂入量的增加,扭矩急劇增加,這是因為喂入量的大幅增加,導(dǎo)致螺旋輸運器中花生果秧層厚增加,物料層和螺旋輸運器凹版之間的擠壓作用顯著增大,摩擦阻力快速增加,導(dǎo)致扭矩急劇增加。同時,由表3分析可知,隨著喂入量的大幅增加,動力輸入軸轉(zhuǎn)速也隨之降低,這是因為螺旋輸運器的摩擦阻力矩過大,而撿拾臺能提供的最大功率一定,轉(zhuǎn)速就會降低,導(dǎo)致花生果秧無法及時的向后輸送,堆積在螺旋輸運器中,物料層厚進(jìn)一步增大,轉(zhuǎn)速進(jìn)一步降低,直至堵塞卡死。這也解釋了實際收獲過程中,短暫的喂入量過大導(dǎo)致的撿拾臺堵死,甚至造成撿拾臺動力輸入軸安裝軸承斷裂現(xiàn)象發(fā)生的原因。
圖7 喂入量與扭矩不同關(guān)系模型擬合結(jié)果
為了檢測建立的數(shù)學(xué)模型的正確性,本文按照上述試驗方法和數(shù)據(jù)提取方法對建立的喂入量與撿拾臺動力輸入軸扭矩數(shù)學(xué)模型式(20)進(jìn)行了5次驗證性試驗。驗證試驗結(jié)果如表4所示。
表4 驗證試驗結(jié)果
從表4可以看出,實測撿拾臺動力輸入軸扭矩與數(shù)學(xué)模型計算值的偏差率。驗證試驗結(jié)果表明,根據(jù)道路監(jiān)測試驗樣本建立的喂入量與動力輸入軸扭矩的二次函數(shù)模型具有較好的準(zhǔn)確性,絕對偏差率范圍為0.42%~2.43%,平均偏差率為1.40%。同時,從表4可以看出,喂入量越大,偏差率越大,說明隨著喂入量的增加,撿拾臺動力輸入軸扭矩變化的不確定性增加,擬合的二次函數(shù)模型準(zhǔn)確性降低。
為了檢驗建立的二次函數(shù)數(shù)學(xué)模型在田間實際收獲時的適應(yīng)性和正確性,按照上述試驗方法和數(shù)據(jù)提取方法于2018年10月在河南省駐馬店市汝南縣馬鄉(xiāng)鎮(zhèn)進(jìn)行了田間試驗。試驗花生品種、種植模式、田間狀態(tài)及挖掘收獲方式等與道路試驗相同。挖掘后晾曬5 d,此時花生植株含水率為18%~25%。田間試驗如圖8所示,結(jié)果如表5所示。
圖8 田間試驗
表5 田間試驗結(jié)果
從表5可知,田間試驗的扭矩偏差率范圍為1.90%~3.58%,平均偏差率為2.65%。且實測扭矩較計算扭矩偏小,這可能是因為田間試驗的花生果秧在收獲前晾曬時間較道路試驗的長,為5 d,花生果秧含水率降低,果秧任性降低,脆性升高;收獲時,花生果秧易折斷,不易纏繞,所需扭矩減小。
1)本文所研究的花生撿拾收獲機(jī)喂入量與撿拾臺動力輸入軸扭矩的數(shù)學(xué)模型是通過水泥道路試驗的方式所得,花生果秧狀態(tài)與田間挖掘收獲機(jī)自然鋪放的有一定程度的不同,且聯(lián)合收獲機(jī)道路行走和田間行走存在一定差別,這對監(jiān)測試驗結(jié)果會有一定的影響。但田間試驗表明,雖然田間試驗的扭矩偏差率較道路試驗有所增大,但偏差率依然小于3.0%,擬合的二次函數(shù)模型仍具有較高的準(zhǔn)確性,對后續(xù)花生撿拾收獲機(jī)的智能測控及優(yōu)化設(shè)計具有較好的指導(dǎo)作用。
2)由于花生收獲季節(jié)的限制,本文僅對河南駐馬店皖花2號花生品種進(jìn)行了試驗,且果秧晾曬天數(shù)(即果秧含水率)對扭矩的偏差率有一定的影響,試驗結(jié)果具有一定的局限性,后續(xù)研究可加強對花生主產(chǎn)區(qū)不同花生品種不同晾曬天數(shù)的監(jiān)測試驗,以優(yōu)化喂入量和扭矩之間的函數(shù)關(guān)系,獲得更精確的數(shù)學(xué)模型。
以前期所研制的4HLJ-3000型全喂入花生聯(lián)合收獲機(jī)為研究對象,對撿拾臺進(jìn)行了動力分析,得出了撿拾臺動力輸入軸扭矩和喂入量的數(shù)學(xué)模型。并設(shè)計了撿拾臺動力輸入軸轉(zhuǎn)速、扭矩和功率等工況數(shù)據(jù)監(jiān)測存儲分析管理系統(tǒng)。
1)通過撿拾臺動力輸入軸扭矩和喂入量的道路監(jiān)測試驗和數(shù)據(jù)擬合回歸分析,得出扭矩和喂入量的二次函數(shù)模型為=83.27?30.38+7.082,且當(dāng)喂入量小于等于3 kg/s時,隨著喂入量的增加扭矩增加比較緩慢;當(dāng)喂入量大于3 kg/s時,隨著喂入量的增加,扭矩急劇增加,且轉(zhuǎn)速也隨之降低。
2)模型驗證試驗結(jié)果表明,所建立的二次函數(shù)模型具有較好的準(zhǔn)確性,偏差率范圍為0.42%~2.43%,平均偏差率為1.40%;田間試驗結(jié)果表明,偏差率范圍為1.90%~3.58%,平均偏差率為2.65%;且喂入量越大,偏差率越大。該研究可為全喂入花生撿拾收獲機(jī)以及其他作物喂入量的智能測控及優(yōu)化設(shè)計提供理論基礎(chǔ)和技術(shù)參考。
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Modeling and experiment of feeding rate for full-feed peanut pickup harvester
Wang Shenying, Hu Zhichao※, Wu Feng, Yu Zhaoyang, Cao Mingzhu, Gao Xuemei
(,s,210014,)
In order to solve the problem of performance degradation and even mechanical failure caused by fluctuation of feeding rate during the operation of full-feed peanut combine harvester in China, and the lack of basic research on feeding rate of full-feed peanut combine harvester, the structure and working principle of the pickup bench of the 4HLJ-3000 full-feeding peanut combine harvester developed by the author team were analyzed in this paper. The pickup bench is mainly composed of limited depth wheel, pressure rod, slide plate, pickup elastic teeth and screw conveyor. Based on the analysis of structure and working principle, a monitoring method of feeding rate based on the torque of power input shaft of pickup bench was proposed. Through the force analysis of the pickup bench, the mathematical relationship between the power input shaft torque and the feeding rate of the pickup bench was obtained. A working condition monitoring system of the speed input, shaft speed, torque and power of the power input shaft was designed, and the system was mainly composed of sensor unit, data acquisition, and data storage analysis. The sensor unit converts the torque and speed of the power input axis of the pickup bench into frequency signals, and the data acquisition module converts the frequency signals into torque and speed values and displays them, and transmits them to the computer for storage and analysis through RS485 bus and RS485 to USB. The data of torque and rotate speed of pickup bench power input shaft, forward speed of pickup harvester and feeding rate were obtained in different operating conditions by road monitoring tests. Linear function, power function, exponential function and quadratic function fitting regression analysis were used to obtain the function indicated the change of feeding rate with various torque based on the test results. The results showed that the quadratic function model had higher fitting precision, and its determination coefficient was0.990. The fitting curve of quadratic function was analyzed, and the results showed that when the feeding rate was less than 3 kg/s, the torque increased slowly with the increase of feeding rate, while the torque increased sharply and the rotation speed decreased with the increase of feeding rate. The model verification experiments were proposed, and the results showed that the established quadratic function model had good accuracy. The absolute deviation rate ranged from 0.42% to 2.43%, and the average deviation rate was 1.40%. The deviation rate increased with increasing the feeding rate. The field experiments also proved that there was a quadratic function relationship between feed rate and torque, and the torque deviation rate ranged from 1.90% to 3.58%, and the average deviation rate was 2.65% compared with the calculated results. This study can provide reference for the optimization design of the structure of full-feeding peanut picker and other crop pickers and the intelligent measurement and control of feed rate.
agricultural machinery;modeling; experiments; peanut; full-feed harvester; pickup bench; feeding rate; torque
王申瑩,胡志超,吳 峰,于昭洋,曹明珠,高學(xué)梅. 全喂入花生撿拾收獲機(jī)喂入量建模與試驗[J]. 農(nóng)業(yè)工程學(xué)報,2019,35(23):29-36.doi:10.11975/j.issn.1002-6819.2019.23.004 http://www.tcsae.org
Wang Shenying, Hu Zhichao, Wu Feng, Yu Zhaoyang, Cao Mingzhu, Gao Xuemei. Modeling and experiment of feeding rate for full-feed peanut pickup harvester[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(23): 29-36. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2019.23.004 http://www.tcsae.org
2019-07-20
2019-10-16
中央級公益性科研院所基本科研業(yè)務(wù)費專項“覆膜種植花生秧蔓飼料化利用關(guān)鍵技術(shù)與裝備研發(fā)”(S201916);國家重點研發(fā)計劃“花生智能化高效聯(lián)合收獲關(guān)鍵技術(shù)與裝備研發(fā)(2016YFD0702102);國家現(xiàn)代農(nóng)業(yè)花生產(chǎn)業(yè)技術(shù)體系收獲機(jī)械化崗位(CARS-13-收獲機(jī)械化崗位)。
王申瑩,助理研究員,主要從事農(nóng)業(yè)機(jī)械裝備設(shè)計及機(jī)電液一體化技術(shù)和虛擬仿真技術(shù)研究。Email:465499517@qq.com
胡志超,研究員,博士生導(dǎo)師,主要從事土下果實生產(chǎn)機(jī)械化技術(shù)與裝備研究。Email:nfzhongzi@163.com
10.11975/j.issn.1002-6819.2019.23.004
S225.7
A
1002-6819(2019)-23-0029-08