王紅英,范佳宇,王糧局,吳俊華,王 威,楊成才
?農(nóng)業(yè)裝備工程與機(jī)械化?
基于PID的飼料制粒調(diào)質(zhì)溫度控制系統(tǒng)設(shè)計(jì)與試驗(yàn)
王紅英,范佳宇,王糧局,吳俊華,王 威,楊成才
(中國農(nóng)業(yè)大學(xué)工學(xué)院,國家農(nóng)產(chǎn)品加工技術(shù)裝備研發(fā)分中心,北京 100083)
為解決顆粒飼料在制粒過程中調(diào)質(zhì)溫度依賴人工輔助控制問題,該研究設(shè)計(jì)了基于PID控制算法的調(diào)質(zhì)溫度控制系統(tǒng)。采用開環(huán)階躍響應(yīng)法建立電動比例調(diào)節(jié)閥與調(diào)質(zhì)溫度之間的控制模型。為了得到最優(yōu)的PID控制參數(shù)(比例系數(shù)K、積分系數(shù)T、微分系數(shù)T),通過Simulink仿真試驗(yàn)對比了Ziegler-Nichols整定法、衰減曲線法和臨界比例度法的PID響應(yīng)曲線,確定PID最優(yōu)控制參數(shù)為K=52.7,T=6.4,T=1.6。對小型制粒機(jī)調(diào)質(zhì)溫度控制系統(tǒng)進(jìn)行試驗(yàn),選用哺乳母豬配合粉料,調(diào)質(zhì)溫度分別設(shè)定為75、80和85 ℃,穩(wěn)定后的調(diào)質(zhì)溫度均能維持在設(shè)定范圍內(nèi);選取調(diào)質(zhì)溫度為80 ℃進(jìn)行穩(wěn)定性試驗(yàn),每1 min記錄調(diào)質(zhì)溫度,整個(gè)試驗(yàn)過程中調(diào)質(zhì)溫度基本穩(wěn)定在(80±1) ℃范圍內(nèi),調(diào)質(zhì)溫度平均相對誤差小于1%,調(diào)質(zhì)溫度變異系數(shù)小于0.5%,系統(tǒng)溫度控制穩(wěn)定,可自動采集制粒生產(chǎn)數(shù)據(jù),實(shí)現(xiàn)了制粒過程中調(diào)質(zhì)溫度的快速響應(yīng)和實(shí)時(shí)控制。研究結(jié)果可為顆粒飼料制粒機(jī)的自動化控制提供參考。
生產(chǎn)控制;品質(zhì);PID;調(diào)質(zhì)溫度;顆粒飼料;小型制粒機(jī)
小型制粒機(jī)主要用于飼料加工工藝試驗(yàn),樣本用量少、電能消耗少、作業(yè)成本低,可以在不同配方、工藝參數(shù)條件下針對產(chǎn)品進(jìn)行個(gè)性化品質(zhì)的研究[1-2]。與大型制粒機(jī)相比,小型制粒機(jī)制粒室內(nèi)空間較小,對顆粒的擠壓能力有限,為了保證小型制粒機(jī)處于穩(wěn)定的工作狀態(tài),需要提高調(diào)質(zhì)溫度和調(diào)質(zhì)水分的穩(wěn)定性、均勻性,在保證喂料量均勻穩(wěn)定的條件下,還要控制進(jìn)入調(diào)質(zhì)器內(nèi)的蒸汽流量。在調(diào)質(zhì)過程中通入適量蒸汽會增加物料的水分與溫度,軟化顆粒硬度,提高顆粒質(zhì)量[3-7],通入過量蒸汽則會導(dǎo)致調(diào)質(zhì)溫度過高,降低蛋白質(zhì)的消化率,還會造成制粒機(jī)壓輥打滑,不能正常工作[8-11]。
目前國內(nèi)最常見的調(diào)質(zhì)溫度控制大多是采用人工輔助控制方式,制粒工根據(jù)工作經(jīng)驗(yàn)調(diào)整蒸汽閥門開度和喂料量,實(shí)現(xiàn)對調(diào)質(zhì)溫度的控制。夏尚[12]根據(jù)制粒機(jī)溫度控制時(shí)滯性和非線性的特性,設(shè)計(jì)了IMC-Smith預(yù)估器,利用控制原理對參數(shù)進(jìn)行整定,加快系統(tǒng)的反應(yīng)時(shí)間,抗干擾能力明顯提升。吳勇等[13]研究了模糊免疫PID在顆粒飼料加工實(shí)驗(yàn)機(jī)中的控制機(jī)理,可以有效提高加工試驗(yàn)機(jī)的工作效率,保證顆粒飼料的質(zhì)量。錢素娟等[14]為了提高對比例閥流量控制精度,設(shè)計(jì)了一種新型模糊PID位置控制器,實(shí)現(xiàn)對先導(dǎo)閥芯位移的快速校正,使誤差降低到0.14,大幅降低了系統(tǒng)的振蕩幅度。賀剛等[15]設(shè)計(jì)了基于模糊PID控制算法的動態(tài)溫度控制系統(tǒng),采用PID參數(shù)在線模糊自整定和PID溫度控制模糊算法等實(shí)現(xiàn)動態(tài)調(diào)節(jié)奶液溫度,從而保證犢牛飲用奶液溫度控制在設(shè)定的范圍內(nèi)。
國外在制粒機(jī)自動控制方面技術(shù)研究開展較早,并取得了很大進(jìn)展[16-19]。COTABARREN等[20]針對制粒過程多變量耦合特性,提出了相對增益陣列分析系統(tǒng)變量配對的策略,研究表明單回路反饋控制器(PI)可以有效的消除多輸入多輸出之間的干擾。PEREIRA等[21]針對螺桿擠壓濕法制粒過程,提出了前饋/后饋復(fù)合控制策略,盡可能控制變量與設(shè)定值之間的偏差,降低了系統(tǒng)連續(xù)工作過程中的變異性。
目前國內(nèi)針對閥門開度與調(diào)質(zhì)溫度之間關(guān)系研究較少,本文結(jié)合飼料制粒工藝現(xiàn)狀以及科研試驗(yàn)數(shù)據(jù)采集要求,采用機(jī)理建模和模型辨識的方法,得到電動比例調(diào)節(jié)閥對調(diào)質(zhì)溫度的控制模型,設(shè)計(jì)了適用于小型制粒機(jī)的調(diào)質(zhì)溫度自動控制系統(tǒng),通過仿真模擬和試驗(yàn)對PID控制穩(wěn)定性進(jìn)行驗(yàn)證,以解決制粒機(jī)調(diào)質(zhì)溫度依靠人工經(jīng)驗(yàn)的問題,簡化了工作人員的操作,提高制粒過程的自動化水平。
小型制粒機(jī)系統(tǒng)主要由蒸汽管道、控制箱和制粒機(jī)組成。其中蒸汽管道系統(tǒng)如圖1所示,蒸汽發(fā)生器產(chǎn)生的水蒸汽經(jīng)過分汽缸,在重力和運(yùn)動慣性的作用下,水從分汽缸底部經(jīng)過疏水閥排出蒸汽管道,蒸汽則經(jīng)減壓閥作用后,壓力由0.7 MPa降為0.3 MPa,在減壓閥后安裝溫度傳感器測量蒸汽溫度,根據(jù)《飽和蒸汽溫度壓力對照表》可得出管道內(nèi)蒸汽的飽和度。蒸汽發(fā)生器運(yùn)行穩(wěn)定后,在人機(jī)交互界面輸入設(shè)定的調(diào)質(zhì)溫度值,PLC通過模擬量輸出模塊,輸出4~20 mA的控制信號到電動執(zhí)行器,產(chǎn)生軸向推力,通過連接桿改變閥芯與閥座間的流通面積,進(jìn)而改變流入調(diào)質(zhì)器內(nèi)的蒸汽流量。PT100溫度傳感器實(shí)時(shí)采集調(diào)質(zhì)器出口處的物料溫度,并將采集到的數(shù)據(jù)反饋給PLC,經(jīng)過PID閉環(huán)控制算法計(jì)算,適當(dāng)調(diào)整參數(shù)后再反饋給電動執(zhí)行器,通過改變流入調(diào)質(zhì)器內(nèi)蒸汽流量實(shí)現(xiàn)物料溫度的穩(wěn)定控制。
1.蒸汽發(fā)生器 2.球形閥 3.壓力表 4.減壓閥 5.溫度傳感器 6.截止閥 7.電磁比例調(diào)節(jié)閥 8.渦街流量計(jì) 9.調(diào)質(zhì)器 10.安全閥 11.分汽缸 12.疏水閥
小型制粒機(jī)調(diào)質(zhì)溫度控制系統(tǒng)結(jié)構(gòu)如圖2所示。硬件部分以西門子S7-200 Smart PLC為核心控制器,配有EM AR04、EM AM06模擬量輸入輸出模塊,通過傳感器實(shí)時(shí)監(jiān)測蒸汽管道內(nèi)溫度、壓力以及物料溫度變化,控制輸出模塊輸出,并且實(shí)時(shí)采集和記錄數(shù)據(jù)。
圖2 調(diào)質(zhì)溫度控制系統(tǒng)
電動比例調(diào)節(jié)閥由電動執(zhí)行機(jī)構(gòu)和閥體共同組成,電動執(zhí)行機(jī)構(gòu)內(nèi)置伺服控制器,控制器將電流信號轉(zhuǎn)化為電機(jī)的角行程信號后,由電機(jī)驅(qū)動齒輪和蝸桿帶動渦輪減速輸出,驅(qū)動閥桿做0°~90°回轉(zhuǎn)運(yùn)動,通過閥門開啟角度大小控制閥門開度和截面面積,進(jìn)而控制蒸汽管道內(nèi)的蒸汽流量。
小型制粒機(jī)最大生產(chǎn)量50 kg/h,物料初始溫度為20 ℃,調(diào)質(zhì)后的溫度達(dá)到80 ℃,蒸汽壓力為0.3 MPa,為了滿足調(diào)質(zhì)的要求,蒸汽用量需滿足:
式中G為蒸汽總量,kg/h;為顆粒機(jī)產(chǎn)量,kg/h;為調(diào)質(zhì)飼料的比熱,1.88 kJ/(kg?℃);1為物料初始溫度,℃;2為物料調(diào)質(zhì)溫度,℃;為蒸汽的熱容量,2.679 MJ/kg;G為水的比熱,4.186 kJ/(kg?℃)。
根據(jù)計(jì)算小型制粒機(jī)的蒸汽流量約為2.005 kg/h,因此調(diào)節(jié)閥的流量范圍為1~10 kg/h,選用上海臺臣閥門有限公司生產(chǎn)的TCJZDLP-16P型號電動調(diào)節(jié)閥,具體參數(shù)如表1所示。閥體采用304不銹鋼,閥芯內(nèi)件選用司太立合金,該合金具有優(yōu)良的高溫性能,較好的耐腐蝕性、韌性以及冷熱疲勞性能,閥芯內(nèi)件需要進(jìn)行縮頸處理以滿足小流量控制要求。
表1 TCJZDLP-16P閥門參數(shù)表
選用的主控制器是西門子公司的S7-200 smart PLC,其結(jié)構(gòu)緊湊、組態(tài)靈活適用于小型制粒機(jī)的控制系統(tǒng),主要的硬件配置選型如下:
1.3.1 CPU模塊
CPU模塊選用SR40CPU。其具有24個(gè)數(shù)字量輸入點(diǎn),16個(gè)數(shù)字量輸出點(diǎn),最多可以連接1個(gè)信號板和6個(gè)擴(kuò)展模塊,具有57 kb程序存儲區(qū)和16 kb用戶數(shù)據(jù)存儲區(qū),6個(gè)高速計(jì)數(shù)器和8個(gè)PID調(diào)節(jié)回路,廣泛應(yīng)用于中小型控制系統(tǒng)。
1.3.2 擴(kuò)展模塊
SR40CPU提供了足夠的數(shù)字量I/O口,只需要擴(kuò)展模擬量I/O口,EMAE06提供4路模擬量輸入和2路模擬量輸出,EMAR04提供4路熱電阻傳感器輸入。PLC模擬量端口分配情況如表2所示。
表2 PLC模擬量分配
人機(jī)交互界面采用深圳市金璽智控技術(shù)有限公司的KinSealStudio軟件開發(fā),如圖3所示。觸摸屏與PLC通過RS485通訊,參數(shù)設(shè)置為:波特率9.6 kb/s,8 bit,無校驗(yàn)。包含蒸汽和制粒參數(shù)監(jiān)測界面及調(diào)質(zhì)溫度實(shí)時(shí)顯示曲線,按照設(shè)定時(shí)間間隔自動記錄調(diào)質(zhì)溫度、閥門開度等參數(shù)。通過觸摸屏切換電動調(diào)節(jié)閥手動/自動兩種控制方式。
圖3 調(diào)質(zhì)溫度控制系統(tǒng)人工交互界面
PID算法是經(jīng)典控制理論中最早發(fā)展起來的控制策略之一,具有算法簡單、魯棒性好和可靠性高等優(yōu)點(diǎn),廣泛應(yīng)用于過程控制中[22]。為實(shí)現(xiàn)在顆粒飼料加工過程中調(diào)質(zhì)溫度的穩(wěn)定,本文設(shè)計(jì)了PID溫度控制以保證系統(tǒng)調(diào)質(zhì)溫度維持在設(shè)定值,PID控制原理如圖4所示。
注:x(t)為調(diào)質(zhì)溫度設(shè)定值,℃;e(t)為誤差,℃;y(t)為混合料實(shí)際溫度值,℃。
在調(diào)質(zhì)溫度控制系統(tǒng)中,將時(shí)刻溫度傳感器測得的混合料溫度實(shí)際值(())與設(shè)定值(())之間的誤差(() )輸入到PID控制器中,根據(jù)PID的控制策略調(diào)整電流信號的模擬值來控制電動比例調(diào)節(jié)閥的開度,進(jìn)而控制管道內(nèi)蒸汽的流量,使調(diào)質(zhì)溫度維持在設(shè)定值附近。PID控制算法公式為
式中()為時(shí)刻電流信號模擬值;T為積分系數(shù);T為微分系數(shù)。
調(diào)質(zhì)過程中,混合顆粒與飽和蒸汽進(jìn)行對流換熱,飽和蒸汽的熱量隨著時(shí)間而增加,首先確定模型為一階關(guān)系式。調(diào)質(zhì)器在通入飽和蒸汽以后,調(diào)質(zhì)器內(nèi)溫度增加,可以通過物理熱力學(xué)公式計(jì)算飽和蒸汽積累的熱量:
式中為飽和蒸汽所產(chǎn)生的熱量,MJ;為飼料粉料表面導(dǎo)熱系數(shù);為飼料溫度,℃;為傳熱時(shí)間,s。
飼料混合料在調(diào)質(zhì)器內(nèi)運(yùn)動時(shí),由于外界環(huán)境的影響,飽和蒸汽以熱傳導(dǎo)的形式損失部分熱量,從而產(chǎn)生熱能計(jì)算誤差,為了減少誤差積累所帶來的影響,在方程中增加熱能損失項(xiàng):
對式(4)進(jìn)行拉普拉斯變化可以得到蒸汽流量與調(diào)質(zhì)溫度之間的關(guān)系式為
式中為拉普拉斯變換中的復(fù)數(shù)變量。
對式(5)進(jìn)行等式變換,得到最終調(diào)質(zhì)溫度變化量的傳遞函數(shù)為
飼料的調(diào)質(zhì)過程是飼料與飽和蒸汽充分接觸的過程,物料與飽和蒸汽的熱傳導(dǎo)需要一定的傳輸時(shí)間,在建立調(diào)質(zhì)溫度模型的過程中需要考慮滯后時(shí)間給熱傳導(dǎo)過程帶來的影響,因此最終的調(diào)質(zhì)溫度控制模型修正為
采用開環(huán)階躍響應(yīng)試驗(yàn)得出系統(tǒng)的閥門開度與調(diào)質(zhì)溫度數(shù)據(jù),最后通過兩點(diǎn)建模方法得到模型中的參數(shù)值。根據(jù)電動比例調(diào)節(jié)閥調(diào)節(jié)范圍,確定閥門開度30%是最高頻率的工作狀態(tài),通過PLC控制閥門開度為30%[23],每隔60 s采集一次調(diào)質(zhì)器出口處的物料溫度,從而獲得近似于開環(huán)階躍響應(yīng)的完整輸入輸出數(shù)據(jù),將采集的數(shù)據(jù)導(dǎo)入Origin.(2022)中,為了避免異常點(diǎn)對實(shí)際控制模型產(chǎn)生較大影響,對輸出曲線進(jìn)行平滑擬合處理(2=0.976),得到如圖5所示的開環(huán)階躍響應(yīng)曲線。采用兩點(diǎn)法計(jì)算模型參數(shù)值,在曲線上取兩個(gè)點(diǎn)(1)和(2)滿足以下表達(dá)式:
在曲線上找到對應(yīng)的(1)和(2)兩點(diǎn),根據(jù)圖6可知(∞)=74,(0)=24,=30,可求出對應(yīng)的1=170,2=330。
根據(jù)以下關(guān)系式計(jì)算得到控制模型的參數(shù)值:
將上述參數(shù)帶入式(7),得到最終的調(diào)質(zhì)溫度控制模型為
圖5 開環(huán)階躍響應(yīng)曲線
調(diào)質(zhì)溫度控制系統(tǒng)的PID控制模型圖如圖6所示。
注:PID(s)為PID控制模塊;s是拉普拉斯變換中的復(fù)數(shù)變量。
PID控制器參數(shù)對系統(tǒng)的控制效果起著至關(guān)重要的作用,PID參數(shù)整定主要是根據(jù)控制對象的特性,確定比例系數(shù)(K)、積分系數(shù)(K)和微分系數(shù)(K)[24-25]。工程中常用的整定方法主要是Ziegler-Nichols(Z-N)整定法、衰減曲線法和臨界比例度法。
2.4.1 Ziegler-Nichols整定法
Z-N整定法是一種基于頻域設(shè)計(jì)PID控制器的方法[25],根據(jù)辨識出的控制模型,結(jié)合性能指標(biāo)推導(dǎo)出PID參數(shù)的整定公式。利用延遲時(shí)間、系統(tǒng)增益和系統(tǒng)時(shí)間常數(shù),根據(jù)表3確定K、T、T的值。
表3 Ziegler-Nichols法整定控制器參數(shù)
注:為滯后時(shí)間,s;為時(shí)間常數(shù),為系統(tǒng)增益。
Note:is the retardation time, s;is time constant,is system gain.
根據(jù)表3中的公式確定PID參數(shù)為K=22.6, K=22,K=5,將PID參數(shù)輸入到如圖7所示的控制模型中,預(yù)先設(shè)置調(diào)質(zhì)溫度為80 ℃,仿真時(shí)間設(shè)置為200 s,其調(diào)質(zhì)溫度響應(yīng)曲線如圖7所示。
圖7 Z-N整定法參數(shù)整定響應(yīng)結(jié)果
2.4.2 臨界比例度法
臨界比例度法適用于已知對象傳遞函數(shù)的控制系統(tǒng)中,在閉環(huán)控制系統(tǒng)中,首先將積分系數(shù)設(shè)置為∞,微分系數(shù)設(shè)置為0,即系統(tǒng)處于純比例控制作用下,從大到小改變調(diào)節(jié)器的比例度,得到等幅振蕩的過渡過程,如圖8所示。此時(shí)的比例系數(shù)成為臨界比例度,相鄰兩個(gè)波峰間的時(shí)間間隔記為臨界振蕩周期。
圖8 調(diào)質(zhì)溫度控制系統(tǒng)等幅振蕩曲線
本系統(tǒng)在比例系數(shù)K=31時(shí)出現(xiàn)等幅振蕩現(xiàn)象,此時(shí)臨界振蕩周期T=12.8,根據(jù)表4可計(jì)算出PID控制參數(shù),其中比例放大系數(shù)K=52.7,積分系數(shù)T=6.4,微分系數(shù)T=1.6,將得到的PID參數(shù)輸入到控制模型中,得到調(diào)質(zhì)溫度響應(yīng)曲線如圖9所示。
表4 臨界比例度法整定控制器參數(shù)
注:?為臨界比例度;T為臨界振蕩周期,s。
Note: ? is the critical scale degree; Tis the critical oscillation period, s.
圖9 臨界比例度法參數(shù)整定結(jié)果
2.4.3 衰減曲線法
衰減曲線法是根據(jù)衰減頻率特性整定PID控制器參數(shù)。與臨界比例法相同,先把控制系統(tǒng)中的PID參數(shù)置于純比例作用(T=∞,T=0),使系統(tǒng)處于閉環(huán)控制中,再把比例系數(shù)K從大到小逐漸調(diào)整,直到出現(xiàn)4∶1衰減過程曲線,如圖10所示。此時(shí)的比例系數(shù)為衰減比例度,兩個(gè)相鄰波峰間的時(shí)間間隔為衰減振蕩周期。
圖10 調(diào)質(zhì)溫度控制系統(tǒng)衰減曲線
當(dāng)K=41時(shí)出現(xiàn)如圖10所示的衰減曲線圖,此時(shí)在=6時(shí)出現(xiàn)第一個(gè)峰值為127 ℃,在=18時(shí)出現(xiàn)第二個(gè)峰值為92 ℃,計(jì)算此時(shí)的衰減度約為4∶1,衰減周期T=12。根據(jù)表5衰減曲線法公式可以得到PID控制參數(shù)K=32,T=3.6,T=1.2,將得到的PID參數(shù)輸入到控制系統(tǒng)模型中可得到如圖11所示的調(diào)質(zhì)溫度響應(yīng)曲線。
表5 衰減曲線法整定控制器參數(shù)
圖11 衰減曲線法參數(shù)整定響應(yīng)結(jié)果
為了比較調(diào)質(zhì)溫度控制系統(tǒng)的性能,利用Matlab軟件完成simulink控制系統(tǒng)程序設(shè)計(jì),并使用Step作為系統(tǒng)的輸入信號,觀察示波器scope的輸出,完成對3種參數(shù)整定方法響應(yīng)曲線的對比處理。在仿真輸入中分別將調(diào)質(zhì)溫度設(shè)定在75、80和85 ℃,對比Z-N整定法、衰減曲線法和臨界比例度法的PID控制器的控制曲線,結(jié)果如圖12所示。經(jīng)過臨界比例度法整定得到的PID參數(shù)能夠較好的完成調(diào)質(zhì)溫度的穩(wěn)定控制,響應(yīng)時(shí)間為14 s,超調(diào)量為3.3 ℃,響應(yīng)速度更快、曲線更平滑,在超調(diào)量和調(diào)節(jié)時(shí)間的性能指標(biāo)上明顯優(yōu)于其他兩種整定方法。因此本文設(shè)計(jì)的PID調(diào)質(zhì)溫度控制系統(tǒng)參數(shù)設(shè)定為K=52.7,T=6.4,T=1.6。
為了驗(yàn)證調(diào)質(zhì)溫度控制系統(tǒng)的工作性能,監(jiān)測系統(tǒng)的穩(wěn)定性,本研究對小型制粒機(jī)運(yùn)行軟件系統(tǒng)、管道蒸汽和物料的傳遞及調(diào)質(zhì)器的調(diào)質(zhì)效果進(jìn)行整機(jī)測定試驗(yàn)。試驗(yàn)于2022年7月10日—8月20日在北京通州區(qū)首農(nóng)畜牧發(fā)展有限公司飼料分公司進(jìn)行,圖13為樣機(jī)試驗(yàn)現(xiàn)場。
圖12 不同調(diào)質(zhì)溫度下不同參數(shù)整定方法響應(yīng)曲線對比
試驗(yàn)原料為哺乳母豬料,其原料配方如表6所示?;旌显喜捎?.5和2 mm孔徑篩片粉碎,初始溫度為26 ℃,水分含量為10.17%。
制粒機(jī)的喂料器轉(zhuǎn)速設(shè)為180 r/min(生產(chǎn)率為40 kg/h),調(diào)質(zhì)時(shí)間約為15 s,在控制系統(tǒng)中分別輸入設(shè)定的調(diào)質(zhì)溫度75、80和85 ℃,記錄調(diào)質(zhì)溫度達(dá)到穩(wěn)定所需時(shí)間,待溫度穩(wěn)定后每隔1 min采集一次調(diào)質(zhì)溫度值,共10 min,取其平均值,如表7所示。調(diào)質(zhì)溫度穩(wěn)定時(shí)間基本維持在10 min附近,與人工輔助調(diào)整方式相比,可以縮短調(diào)整時(shí)間,穩(wěn)定后的調(diào)質(zhì)溫度基本維持在設(shè)定范圍內(nèi),系統(tǒng)能夠達(dá)到有效的控制,仿真驗(yàn)證與實(shí)際數(shù)據(jù)偏差在0.3 ℃范圍內(nèi)。
圖13 樣機(jī)試驗(yàn)現(xiàn)場
表6 哺乳母豬料配方
表7 溫度采集結(jié)果
為了檢驗(yàn)調(diào)質(zhì)溫度控制系統(tǒng)的穩(wěn)定性,選取調(diào)質(zhì)溫度80 ℃,待調(diào)質(zhì)溫度穩(wěn)定后每隔1 min采集一次溫度數(shù)據(jù),共50 min,將整個(gè)工作過程劃分為5個(gè)時(shí)間間隔,計(jì)算調(diào)質(zhì)溫度的平均相對誤差[26]()和變異系數(shù)[27](),其計(jì)算方法如下:
式中x表示第時(shí)刻采集到的調(diào)質(zhì)溫度值,℃;表示時(shí)間間隔,這里=10 min;表示設(shè)定的調(diào)質(zhì)溫度值,℃;0表示各個(gè)時(shí)間段測得調(diào)質(zhì)溫度的標(biāo)準(zhǔn)差,℃。
試驗(yàn)結(jié)果如表8、表9所示,當(dāng)小型制粒機(jī)調(diào)質(zhì)溫度設(shè)定在80 ℃時(shí),在調(diào)質(zhì)器穩(wěn)定工作后,溫度基本控制在(80±1) ℃變化范圍內(nèi),調(diào)質(zhì)溫度平均相對誤差小于1%,變異系數(shù)小于0.5%,調(diào)質(zhì)溫度控制效果穩(wěn)定。
表8 調(diào)質(zhì)溫度控制數(shù)據(jù)
表9 平均相對誤差和變異系數(shù)
本文設(shè)計(jì)了一種適用于小型制粒機(jī)的調(diào)質(zhì)溫度控制系統(tǒng),首先確定了電動比例調(diào)節(jié)閥的型號、溫度傳感器選擇、控制器選擇及人機(jī)交互界面設(shè)計(jì)等。主要結(jié)論如下:
2)通過機(jī)理建模和兩點(diǎn)建模的模型辨識與獲取方法,得到了電動調(diào)節(jié)閥在30%開度下調(diào)質(zhì)溫度階躍響應(yīng)曲線,并建立了電動調(diào)節(jié)閥與調(diào)質(zhì)溫度間的控制模型。通過仿真試驗(yàn)對比分析,選擇臨界比例度法整定PID控制器參數(shù),此方法得到的PID控制器響應(yīng)時(shí)間為14 s、超調(diào)量為3.3 ℃,能夠?qū)崿F(xiàn)調(diào)質(zhì)溫度穩(wěn)定控制。
2)小型制粒機(jī)樣機(jī)試驗(yàn)表明,設(shè)定不同的調(diào)質(zhì)溫度值(75、80和85 ℃),系統(tǒng)最終都能穩(wěn)定在設(shè)定范圍內(nèi)。調(diào)質(zhì)溫度80 ℃時(shí),制粒機(jī)穩(wěn)定工作過程中,調(diào)質(zhì)溫度基本穩(wěn)定控制在(80±1) ℃變化范圍內(nèi),溫度穩(wěn)定性符合設(shè)計(jì)要求。
[1] 彭飛,王紅英,康宏彬,等. 小型可調(diào)間隙飼料制粒機(jī)設(shè)計(jì)與試驗(yàn)[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2017,48(4):103-110.
PENG Fei, WANG Hongying, KANG Hongbin, et al. Design and experiment on small-scale adjustable clearance pellet feed mill[J]. Transactions of the Chinese Society for Agricultural Machinery, 2017, 48(4): 103-110. (in Chinese with English abstract)
[2] 彭飛,李騰飛,康宏彬,等. 小型制粒機(jī)喂料器參數(shù)優(yōu)化與試驗(yàn)[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2016,47(2):51-58.
PENG Fei, LI Tengfei, KANG Hongbin, et al. Optimization and experiment on feeder for small-scale pellet mill[J]. Transactions of the Chinese Society for Agricultural Machinery, 2016, 47(2): 51-58. (in Chinese with English abstract)
[3] LUNDBLAD K K, ISSA S, HANCOCK J D, et al. Effects of steam conditioning at low and high temperature, expander conditioning and extruder processing prior to pelleting on growth performance and nutrient digestibility in nursery pigs and broiler chickens[J]. Animal Feed Science and Technology, 2011, 169(3/4): 208-217.
[4] 段海濤,李軍國,秦玉昌,等. 調(diào)質(zhì)溫度及??组L徑比對顆粒飼料加工質(zhì)量的影響[J]. 農(nóng)業(yè)工程學(xué)報(bào),2018,34(11):278-283.
DUAN Haitao, LI Junguo, QIN Yuchang, et al. Effects of conditioning temperature and length-diameter ratio of ring die on quality of pelleted feeds[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2018, 34(11): 278-283. (in Chinese with English abstract)
[5] 孔丹丹,方鵬,王紅英,等. 高含量乳清粉的仔豬配合飼料熱特性及調(diào)質(zhì)溫度控制[J]. 農(nóng)業(yè)工程學(xué)報(bào),2017,33(16):299-307.
KONG Dandan, FANG Peng, WANG Hongying, et al. Thermal properties and conditioning temperature control of formula feeds containing high levels of whey powder for weanling pigs[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(16): 299-307.(in Chinese with English abstract)
[6] 李軍國,劉子奇,張嘉琦,等. 緩沉性水產(chǎn)膨化飼料加工工藝參數(shù)優(yōu)化[J]. 農(nóng)業(yè)工程學(xué)報(bào),2022,38(4):308-315.
LI Junguo, LIU Ziqi, ZHANG Jiaqi, et al. Optimization of the process parameters for slow-sinking extruded aquatic feed[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(4): 308-315. (in Chinese with English abstract)
[7] 彭飛. 小型制粒系統(tǒng)優(yōu)化設(shè)計(jì)與試驗(yàn)研究[D]. 北京:中國農(nóng)業(yè)大學(xué),2017.
PENG Fei. Optimization Design and Experimental Research of Small-scale Pelletizing System[D]. Beijing: China Agricultural University, 2017.
[8] RUEDA M, Rubio A A, Starkey C W, et al. Effect of conditioning temperature on pellet quality, performance, nutrient digestibility, and processing yield of broilers[J]. Journal of Applied Poultry Research, 2022, 31(2): 100235.
[9] WANG T X, HUANG Y K, YAO W L, et al. Effect of conditioning temperature on pelleting characteristics, nutrient digestibility and gut microbiota of sorghum-based diets for growing pigs[J]. Animal Feed Science and Technology, 2019, 254: 114227.
[10] BOLTZ T P, WARD N E, AYRES V E, et al. The effect of varying steam conditioning temperature and time on pellet manufacture variables, true amino acid digestibility, and feed enzyme recovery[J]. Journal of Applied Poultry Research, 2020, 29(2): 328-338.
[11] BONEY J W, MORITZ J S. The effects of Spirulina algae inclusion and conditioning temperature on feed manufacture, pellet quality, and true amino acid digestibility[J]. Animal Feed Science and Technology, 2017, 224: 20-29.
[12] 夏尚. 制粒機(jī)溫控系統(tǒng)的控制與實(shí)現(xiàn)[D]. 上海:上海交通大學(xué),2009.
XIA Shang. Control and Implementation of Temperature Control System of Granulator[D]. Shanghai: Shanghai Jiaotong University, 2009.
[13] 吳勇,趙勇,黃堃. 基于模糊免疫PID的飼料加工試驗(yàn)機(jī)溫度控制研究[J]. 飼料工業(yè),2013,34(11):8-10.
WU Yong, ZHAO Yong, HUANG Kun. Research on temperature control of feed processing tester based on fuzzy immune PID[J]. Feed Industry, 2013, 34(11): 8-10. (in Chinese with English abstract)
[14] 錢素娟,張偉,李強(qiáng). 基于模糊PID的電液比例閥流量控制設(shè)計(jì)及分析[J]. 中國工程機(jī)械學(xué)報(bào),2021,19(6):512-517.
QIAN Sujuan, ZHANG Wei, LI Qiang. Flow control design and analysis of electro-hydraulic proportional valve based on fuzzy PID[J]. Chinese Journal of Construction Machinery, 2021, 19(6): 512-517. (in Chinese with English abstract)
[15] 賀剛,蔡曉華,白陽,等. 基于模糊PID的犢牛代乳粉奶液溫度控制系統(tǒng)設(shè)計(jì)與試驗(yàn)[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2022,53(3):266-276.
HE Gang, CAI Xiaohua, BAI Yang, et al. Design and test of temperature control system of calf milk replacer solution based on fuzzy PID[J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(3): 266-276. (in Chinese with English abstract)
[16] GARCIA-MARAVER A, RODRIGUEZ M L, SERRANO-BERNARDO F, et al. Factors affecting the quality of pellets made from residual biomass of olive trees[J]. Fuel Processing Technology, 2015, 129: 1-7.
[17] STERCZEWSKI L A, GRZELCZAK M P, PLINSKI E F. Heating system of pellet samples integrated with terahertz spectrometer[J]. Review of Scientific Instruments, 2016, 87(1): 013106.
[18] ZHANG K, WU J G, ZANG P J, et al. Study on the control system of the hoop standard granulator based on the expert system[J]. Computers and Applied Chemistry, 2012, 29(10): 1249-1252.
[19] MAZZINGHY D B, SCHNEIDER C L, ALVES V K, et al. Vertical agitated media mill scale-up and simulation[J]. Minerals Engineering, 2015, 73: 69-76.
[20] COTABARREN I M, BERTIN D E, BUCALA V, et al. Feedback control strategies for a continuous industrial fluidized-bed granulation process[J]. Powder Technology, 2015, 283: 415-432.
[21] PEREIRA G C, MUDDU S V, ROMAN-OSPINO A D, et al. Combined feedforward/feedback control of an integrated continuous granulation process[J]. Journal of Pharmaceutical Innovation, 2019, 14(3): 259-285.
[22] 于暢暢,李洪文,何進(jìn),等. 基于PID算法的高頻間歇供肥系統(tǒng)設(shè)計(jì)與試驗(yàn)[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2020,51(11):45-53.
YU Changchang, LI Hongwen, HE Jin, et al. Design and experiment of high-frequency intermittent fertilizer supply system based on PID algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(11): 45-53. (in Chinese with English abstract)
[23] 劉曉偉. 基于先進(jìn)PID控制的電加熱爐系統(tǒng)[D]. 杭州:杭州電子科技大學(xué),2021.
LIU Xiaowei. Electric Heating Furnace System Based on Advanced PID Control[D]. Hangzhou: Hangzhou University of Electronic Science and Technology, 2021.
[24] 沈雙,雷靜桃,張悅文. 仿生跳躍機(jī)器人氣動串聯(lián)彈性關(guān)節(jié)的位置/剛度控制[J]. 中國機(jī)械工程,2021,32(12):1486-1493.
SHEN Shuang, LEI Jingtao, Zhang Yuewen. Position and stiffness control of pneumatic series elastic joints for bionic jumping robots[J]. China Mechanical Engineering, 2021, 32(12): 1486-1493. (in Chinese with English abstract)
[25] 孫文峰,劉海洋,王潤濤,等. 基于神經(jīng)網(wǎng)絡(luò)整定的PID控制變量施藥系統(tǒng)設(shè)計(jì)與試驗(yàn)[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2020,51(12):55-64.
SUN Wenfeng, LIU Haiyang, WANG Runtao, et al. Design and experiment of PID control variable application system based on neural network tuning[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(12): 55-64. (in Chinese with English abstract)
[26] 許林云,韓元順,陳青,等. Data-SSI與圖論聚類結(jié)合識別果樹固有頻率[J]. 農(nóng)業(yè)工程學(xué)報(bào),2021,37(15):136-145.
XU Linyun, HAN Yuanshun, CHEN Qing, et al. Natural frequency identification of fruit trees by combination of data-driven stochastic subspace identification and graph theory clustering method[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(15): 136-145. (in Chinese with English abstract)
[27] 宋燦燦,周志艷,王國賓,等. 施肥無人機(jī)槽輪式排肥器槽輪結(jié)構(gòu)參數(shù)優(yōu)選[J]. 農(nóng)業(yè)工程學(xué)報(bào),2021,37(22):1-10.
SONG Cancan, ZHOU Zhiyan, WANG Guobin, et al. Optimization of the groove wheel structural parameters of UAV-based fertilizer apparatus[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(22): 1-10. (in Chinese with English abstract)
Design and test of the temperature control system for the feed pelleting and conditioning based on PID
WANG Hongying, FAN Jiayu, WANG Liangju, WU Junhua, WANG Wei, YANG Chengcai
(National R&D Center for Agro-processing Equipment, College of Engineering, China Agricultural University, Beijing 100083, China)
Conditioning temperature is one of the key factors in the quality of feed pellets during feed processing. It is a high demand to maintain the constant conditioning temperature. Specifically, too high conditioning temperature can lead to the inactivation of heat-sensitive ingredients, such as probiotics, whereas, too low conditioning temperature can be found in the incomplete sterilization of the starch paste. In this study, a Proportion Integration Differentiation (PID)-based control system was developed to control the conditioning temperature of the feed pellets during processing. The whole unit consisted of a control system, steam piping, and a pelletizer. The control system with a Programmable Logic Controller (PLC) and a touch screen was utilized to control the start/stop of the pelletizer and the opening of the electric regulating valve. The process parameters of the pelletizer were also automatically collected, according to the given time interval. A temperature sensor was installed at the outlet of the pelletizer. The PT100 temperature sensor was used to collect the conditioning temperature of the material at the outlet of the temperature in real time. Subsequently, the collected data was fed back to the PLC. The PID closed-loop control algorithm was utilized to calculate the electric actuator again after the appropriate adjustment of the parameters. The stable control of tempering temperature was realized to change the steam flow into the temperature. A systematic analysis was made to obtain the convective heat exchange process between the mixed feed and steam at temperature. A theoretical model of heat transfer was established to obtain the specific parameters using the step response curve method. After that, the data curve was processed (2 = 0.976) to obtain a control model between the electric proportional control valve and the tempering temperature in the control system. As such, a large influence of special points was avoided on the experimental data after processing. Furthermore, the simulation analysis was carried out to determine the optimum parameters for the PID control using the Simulink platform. A comparison was performed on the response curves from three PID parameter regulations, namely the Z-N regulation, the decay curve method, and the critical proportional method. Finally, the critical proportional method was found to present the best control effect, in terms of the overshoot and regulation time in the dynamic performance indicators with the PID parameters (proportionality coefficientK=52.7, integral coefficientT=6.4, and differential coefficientT= 1.6). The response time of the PID controller obtained by the critical proportionality method was 14 s and the overshoot was 3.3 ℃. Taking the lactating sow meal as an example, a series of prototype tests were carried out on the pelletizer. Specifically, the lactating sow meal was first crushed with the 1.5 and 2 mm sieves. The moisture content of the mixture was 10.17%, while the tempering temperature was set at 75, 80, and 85 °C. The tempering temperature was maintained within the set range after stability. Subsequently, the tempering temperature of 80 °C was chosen for the stability test. The tempering temperature was recorded every 1min during the test. The basically stable tempering temperature was achieved in the whole test process, which was controlled within (80±1) ℃, indicating the small average relative error and coefficient of variation of temperature. Therefore, the stable control of system temperature can be expected to automatically collect the pelletizing production data. Anyway, the control system can be expected to serve as the rapid response and real-time control of tempering temperature in the pelletizing process. Furthermore, the processing operation was simplified to improve automation in pelletizing production.
production control; quality; PID; conditioning temperature;pellet feed; small granulator
10.11975/j.issn.1002-6819.202210132
S816.8
A
1002-6819(2023)-01-0001-08
王紅英,范佳宇,王糧局,等. 基于PID的飼料制粒調(diào)質(zhì)溫度控制系統(tǒng)設(shè)計(jì)與試驗(yàn)[J]. 農(nóng)業(yè)工程學(xué)報(bào),2023,39(1):1-8.doi:10.11975/j.issn.1002-6819.202210132 http://www.tcsae.org
WANG Hongying, FAN Jiayu, WANG Liangju, et al. Design and test of the temperature control system for the feed pelleting and conditioning based on PID[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(1): 1-8. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.202210132 http://www.tcsae.org
2022-10-18
2022-11-29
國家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2021YFD1300300)
王紅英,教授,博士生導(dǎo)導(dǎo)師,研究方向?yàn)轱暳霞庸すに嚰夹g(shù)與設(shè)備及畜禽養(yǎng)殖技術(shù)與裝備。Email:hongyingw@cau.edu.cn
中國農(nóng)業(yè)工程學(xué)會會員:王紅英(E041200500S)