臥式馬鈴薯去皮機(jī)設(shè)計【臥式土豆去皮機(jī)設(shè)計】

臥式馬鈴薯去皮機(jī)設(shè)計【臥式土豆去皮機(jī)設(shè)計】,臥式土豆去皮機(jī)設(shè)計,臥式馬鈴薯去皮機(jī)設(shè)計【臥式土豆去皮機(jī)設(shè)計】,臥式,馬鈴薯,土豆,去皮,設(shè)計,洋芋 UNIVERSITY本 科 畢 業(yè) 論 文（設(shè) 計） 題目： 臥式馬鈴薯去皮機(jī)設(shè)計 學(xué) 院： 姓 名： 學(xué) 號： 專 業(yè)： 機(jī)械設(shè)計制造及其自動化年 級： 指導(dǎo)教師： 職 稱： 講師 二一二 年 五 月摘要 目前，常見馬鈴薯去皮機(jī)多采用立式轉(zhuǎn)筒型，立式結(jié)構(gòu)多通過下端輸入動力，上端懸置，這就使轉(zhuǎn)筒存在運動不平穩(wěn)的問題，同時，馬鈴薯主要依靠轉(zhuǎn)筒底部的圓盤來達(dá)到去皮效果，而馬鈴薯依靠自身重力大多堆積在圓盤上，各馬鈴薯與圓盤接觸的不均致使馬鈴薯去皮不均勻，去皮效果不佳。本文論述了解決以上兩大問題的方法，即將轉(zhuǎn)筒制成臥式，采用兩端軸承固定的方法提高轉(zhuǎn)筒運動平穩(wěn)性，同時通過轉(zhuǎn)筒筒壁上的凸起棱部分與馬鈴薯的摩擦來達(dá)到去皮效果，這使得馬鈴薯的去皮效果達(dá)到均勻且較佳。通過對兩種去皮機(jī)各方面性能的綜合對比，采用傳統(tǒng)設(shè)計方法，獲取整機(jī)各零件的參數(shù)，并且通過計算，論證了該設(shè)計方案的可行性，最終結(jié)論是臥式去皮機(jī)綜合性能較立式去皮機(jī)更佳。關(guān)鍵詞：去皮機(jī)；馬鈴薯去皮機(jī)理；臥式馬鈴薯去皮機(jī)Abstract At present, the common potato peeling machine adopts the vertical drum type, vertical structure in the lower end of the input power, the upper suspension, which makes the rotary movement exists unstable problem, at the same time, potato mainly rely on the drum at the bottom of the disk to achieve the peeling effect, and potato on its own gravity mostly accumulates on the disc, the potato contact with the disk does not have led to peel the potatoes peeled uneven, poor effect. This paper discusses the method ,to solve two problems the drum made of horizontal, with both ends of bearing fixing method for improving the rotary motion stability, at the same time through the rotating barrel wall convex edge part and potato friction to achieve the peeling effect, which makes the potato peeling effect to achieve uniform and better. Through to two kind of peeling machine all aspects of the comprehensive comparison, using the traditional design method, acquiring the various parameters of parts, and through calculation, it proves the feasibility of the design, the final conclusion is that the horizontal peeling machine comprehensive performance than vertical peeling machine. Key words : peeling machine for peeling potatoes; mechanism; horizontal potato peeling machine 目錄1 緒論1 1.1 馬鈴薯的主要特點及功用1 1.2 常用薯類去皮方法12 整機(jī)的結(jié)構(gòu)設(shè)計和工作原理23 馬鈴薯去皮機(jī)零部件的設(shè)計3 3.1 機(jī)械傳動系統(tǒng)總體設(shè)計3 3.1.1 傳動方案的擬定3 3.1.2 電動機(jī)的選擇3 3.2 傳動裝置運動和動力參數(shù)的計算4 3.2.1 傳動比分配4 3.2.2 各軸的轉(zhuǎn)速計算5 3.2.3 各軸輸入功率計算5 3.2.4 各軸輸入扭矩計算5 3.3 V 帶傳動的設(shè)計計算5 3.4 齒輪傳動的設(shè)計計算11 3.5 軸系零件的設(shè)計計算11 3.5.1 初算d12 3.5.2 計算軸上載荷12 3.5.3 繪制軸的彎扭矩圖，對危險截面進(jìn)行校核14 3.5.4 軸承的校核15 3.5.5 軸上鍵連接的選擇及校核15 3.5.6 軸上螺母的選擇15 3.6 滾筒及其軸系零件的設(shè)計、選擇與校核15 3.6.1 滾筒的結(jié)構(gòu)設(shè)計16 3.6.2 軸承的選擇、校核18 3.6.3 齒輪連接鍵的選擇及校核18 3.6.4 軸上螺母選擇18 3.7 軸承座、端蓋的結(jié)構(gòu)設(shè)計18 3.7.1 軸承座的選材18 3.7.2 軸承座的固定方式18 3.7.3 軸承座的結(jié)構(gòu)設(shè)計19 3.7.4 軸承座端蓋選材、結(jié)構(gòu)設(shè)計19 3.8 軸承座聯(lián)接用螺栓的設(shè)計計算19 3.9 機(jī)架的結(jié)構(gòu)設(shè)計21設(shè)計小結(jié)22參考文獻(xiàn)2341 緒論1.1 馬鈴薯的主要特點及功用馬鈴薯為植物的塊莖形狀為圓形或橢圓形，其結(jié)構(gòu)由表皮層、形成層、外果肉和內(nèi)果肉四部分。馬鈴薯品種可分兩大類，一類是淀粉含量較高的，適宜于作為生產(chǎn)淀粉的原料，另一類是蛋白質(zhì)含量較高，適宜作為蔬果或制成多種食品。馬鈴薯營養(yǎng)豐富，除直接食用外，還可以加工成食品、全粉、淀粉等經(jīng)濟(jì)價值較高的食品，通過加工可以大幅度提高鮮薯的商品價值。鑒于馬鈴薯的很多特點，馬鈴薯得到了廣泛的利用：a.馬鈴薯可鮮食，鮮食用馬鈴薯主要用作家庭餐館烹調(diào)，我國主要用來制作菜肴、面點小吃等大眾食品。果外除蒸烤鮮馬鈴薯作主食外，還有咖哩飯、燉薯快以及色拉涼拌菜。馬鈴薯可制成方便食品、快餐食品、休閑食品，如馬鈴薯粉、馬鈴薯全粉、脫水馬鈴薯片（條）、速凍薯條（薯泥）、蒸薯條、罐裝和去皮馬鈴薯、馬鈴薯脆片、馬鈴薯膨化小食品等；b，加工成淀粉及相關(guān)產(chǎn)品：由于馬鈴薯淀粉的優(yōu)良特性，不僅是制作高級方便面、面類最為理想的添加淀粉，而且還是肉制品、魚糜制品等的添加劑或原料。馬鈴薯淀粉也是粉條的優(yōu)質(zhì)原料。出馬鈴薯淀粉外，也可得到相關(guān)產(chǎn)品，包括各種變性淀粉、飴糖、葡萄糖、膳食纖維制品等；c，其他制品：馬鈴薯提取淀粉后的殘渣可制成馬鈴薯發(fā)酵飼料、提取蛋白等；1.2 常用薯類去皮方法去皮用于多種水果和蔬菜的加工中以除去不需要或不可食的物質(zhì)，并改善成品的外觀。主要的考慮因素包括通過盡可能減少去掉的部分以及可能降低能源、勞力和物質(zhì)成本來降低總成本。這里，主要介紹以下四種去皮方法： a.機(jī)械切削去皮 是采用鋒利的刀片表面皮層。去皮速度較快，但不完全，且果肉損失較多，一般需用手工加以修整，難以實現(xiàn)完全機(jī)械作業(yè)，適用于果大、皮薄、肉質(zhì)較硬的果蔬。目前，蘋果、梨、柿等常使用機(jī)械切削去皮，常用的形式為旋皮機(jī)。旋皮機(jī)是將待去皮的水果插在能旋轉(zhuǎn)的插軸上，靠近水果一側(cè)安裝（或手持）一把刀口彎曲的刀，使刀口貼在果面上。插軸旋轉(zhuǎn)時，刀就從旋轉(zhuǎn)的水果表面將皮車去。旋皮機(jī)插軸的轉(zhuǎn)動有手搖、腳踏和電動幾種動力形式。在旋車去皮之前應(yīng)有選果工序，以保證水果大小基本一致。b.機(jī)械磨削去皮 是利用覆有磨料的工作面除去表面皮層?？筛咚僮鳂I(yè)，易于實現(xiàn)完全機(jī)械操作，所得碎皮細(xì)小，便于用水或氣流清除，但去皮后表面較粗糙，適用于質(zhì)地堅硬、皮薄、外形整齊的果蔬。胡蘿卜、番茄等塊根類蔬菜原料去皮大多采用機(jī)械磨削去皮機(jī)。c.機(jī)械摩擦去皮 是利用摩擦因數(shù)大、接觸面積大的工作構(gòu)件而產(chǎn)生的摩擦作用使表皮發(fā)生撕裂破壞而被去除。所得產(chǎn)品表面質(zhì)量好，碎皮尺寸大，去皮死角少，但作用強(qiáng)度差，適用于果大、皮薄、皮下組織松散的果蔬，一般需要首先對果蔬進(jìn)行必要的預(yù)處理來弱化皮下組織。常見到的機(jī)械摩擦去皮機(jī)如采用橡膠板作為工作構(gòu)件的干法去皮機(jī)。d.化學(xué)去皮 又稱堿液去皮，即將果蔬在一定溫度的堿液中處理適當(dāng)?shù)臅r間，果皮即被腐蝕，取出后，立即用清水沖洗或搓擦，外皮即脫落，并洗去堿液。此法適用于桃、李、杏、梨、蘋果等的去皮及橘瓣脫囊衣。桃、李、蘋果等的果皮由角質(zhì)、半纖維素等組成，果肉由薄壁細(xì)胞組成，果皮與果肉之間為中膠層，富含原果膠及果膠，將果皮與果肉連接。當(dāng)果蔬與堿液接觸時，果皮的角質(zhì)、半纖維素被堿腐蝕而變薄乃至溶解，果膠被堿水溶解而失去膠凝性，果肉薄壁細(xì)胞膜較能抗堿。因此，用堿液處理后的果實，不僅果皮容易去除，而且果肉的損傷較少，可以提高原料的利用率。但是，化學(xué)去皮用水量較大，去皮過程產(chǎn)生的廢水多，尤其是產(chǎn)生大量含有堿液的廢水。2 整機(jī)的結(jié)構(gòu)設(shè)計和工作原理 圖1 整機(jī)結(jié)構(gòu)設(shè)計圖整機(jī)的機(jī)構(gòu)設(shè)計如上圖所示：1電動機(jī)； 2帶輪傳動； 3齒輪傳動；4滾筒馬鈴薯去皮機(jī)工作原理：如上圖所示，電動機(jī)通過皮帶傳動和齒輪傳動兩級降速，將動力傳至滾筒，滾筒以一定轉(zhuǎn)速旋轉(zhuǎn)，馬鈴薯由進(jìn)料漏斗通過滾筒右側(cè)的空心軸進(jìn)入滾筒，滾筒轉(zhuǎn)度限制在一定范圍內(nèi)，以使馬鈴薯在隨滾筒旋轉(zhuǎn)時在滾筒的最高點以前與筒壁分離，從而達(dá)到去皮效果，同時，滾筒的半徑左大右小，具有一定錐度，馬鈴薯受到向左的軸向分力，在軸向分力的作用下，馬鈴薯在滾筒內(nèi)作翻轉(zhuǎn)運動的同時沿軸向運動至滾筒左側(cè)，從滾筒左側(cè)筒壁上開的小口落下，完成去皮運動。馬鈴薯在滾筒內(nèi)作翻轉(zhuǎn)運動，為了達(dá)到去皮效果，滾筒轉(zhuǎn)速不得大于臨轉(zhuǎn)速否則，馬鈴薯在滾筒內(nèi)隨滾筒一起轉(zhuǎn)動，馬鈴薯與滾筒沒有相對運動速度，起不到去皮效果。 。 圖2 馬鈴薯在滾筒內(nèi)的運動圖 3 馬鈴薯去皮機(jī)零部件的設(shè)計3.1 機(jī)械傳動系統(tǒng)總體設(shè)計3.1.1 傳動方案的擬定：常用傳動機(jī)構(gòu)的一般布置原則如下： （1）帶傳動承載能力較低，但傳動平穩(wěn)，緩沖吸振能力強(qiáng)，宜布置在高速級。 （2）對于開式齒輪的傳動，由于其工作環(huán)境較差，潤滑不良，為減少磨損，宜布置在低速級。3.1.2 電動機(jī)的選擇給定去皮機(jī)的工作條件：滾筒工作功率=3.2kw，直徑D=300mm，稍有震動，在室溫下連續(xù)運轉(zhuǎn)，工作環(huán)境多塵，電源為三相交流，電壓為380V。（1）選擇電動機(jī)類型和結(jié)構(gòu)形式 系統(tǒng)無特殊需求，一般選用Y系列三相交流異步電動機(jī)。選用全封閉自扇冷式籠型，電壓380V。（2）選擇電動機(jī)容量 為電動機(jī)的功率； 為工作及功率； 為傳動裝置的總效率； 為滑動軸承的效率，查表取0.97（一對） 為帶傳動的效率，查表取0.96 為齒輪傳動的效率，查表取0.9求解得：=0.960.9 =0.813 kw ，差電動機(jī)參數(shù)表選取電動機(jī)額定功率=4kw。（3）選擇電動機(jī)轉(zhuǎn)速、確定滾筒轉(zhuǎn)速、總傳動比 （a）根據(jù)動力源和工作條件，電機(jī)的轉(zhuǎn)速選擇常用的兩種同步轉(zhuǎn)速：1500r/min和1000r/min。選用1000r/min。 查表選用Y132M1-6型號的電機(jī)，其參數(shù)如表1： 表1 所選電動機(jī)的相關(guān)參數(shù)電機(jī)型號額定功率 （kw）同步轉(zhuǎn)速(r/min) 滿載轉(zhuǎn)速（r/min）電機(jī)重量 （kw）參考價格（元）Y132M1-6 4 1000 960 73 823 （b）先求取滾筒臨界轉(zhuǎn)速由臨界狀態(tài)得： m為馬鈴薯質(zhì)量，R為滾筒半徑R= 令總傳動比為i，則滾筒轉(zhuǎn)速為n=，因此： V= 化解得i12.39，取i=14。3.2 傳動裝置運動和動力參數(shù)的計算3.2.1 傳動比分配 根據(jù)常用傳動機(jī)構(gòu)的主要特征及適用范圍： 取V帶傳動的傳動比為3.5，則圓柱齒輪傳動比3.2.2 各軸的轉(zhuǎn)速計算： =960r/min r/min r/min3.2.3 各軸輸入功率計算： 3.2.4 各軸輸入扭矩計算 將上述結(jié)果列入表2，以供查用。表2 各軸的的運動參數(shù)軸號轉(zhuǎn)速n/(r/min)功率Pkw扭矩T（Nm）I960439.8II274.33.7248129.68III68.573.25452.643.3 V帶傳動的設(shè)計計算 選用普通V帶傳動，動力機(jī)位Y系列三相異步電動機(jī)，功率P=4kw，轉(zhuǎn)n=960r/min，每天工作16h，中心距小于600mm。計算項目 計算內(nèi)容 計算結(jié)果 定V帶型號和帶輪直徑工作情況系數(shù) 由表 =1.2計算功率 選帶型號 由圖 A型小帶輪直徑 由表 取大帶輪直徑 選 (為滑動率，取=2%)大帶輪轉(zhuǎn)速 以上所選參數(shù)合理 計算帶長求 求 = =109mm初取中心距 a=500mm帶長 L=+2a+=199+2500+ L=1648.6mm基準(zhǔn)長度 由圖 =1800mm 求中心距和包角中心距 = a=577.28mm 600mm小輪包角 = = 求帶根數(shù)帶速 v=4.52m/s傳動比 i= i=3.5帶根數(shù) 由表 =0.78kw；0.94 ；1.01； ； Z= = =3.68 取z=4根 求軸上載荷張緊力 =500+q 500+0.10 =148.9N（由表 q=0.10kg/m）軸上載荷 =2z =26148.9 =1752N帶輪結(jié)構(gòu)設(shè)計 由于帶速v30m/s，帶輪用HT200制造。小帶輪采用整體式結(jié)構(gòu)，大帶輪采用輪輻式結(jié)構(gòu)，且D500mm，輪輻數(shù)目取為4.具體結(jié)構(gòu)參數(shù)見零件圖。綜上整理帶傳動參數(shù)如表3：表3 帶傳動的相關(guān)參數(shù)小帶輪直徑 大帶輪直徑 傳動比i帶基準(zhǔn)長度根數(shù)Z中心距a90mm308mm3.51800mm4577.28mm3.4 齒輪傳動的設(shè)計計算 使用要求：預(yù)期使用壽命10年，每年300個工作日，在使用期限內(nèi)，工作時間占20%。工作有中等振動，傳動不逆轉(zhuǎn)，齒輪對稱布置。傳動尺寸無嚴(yán)格限制，無嚴(yán)重過載。傳動比i=4,。 因傳動尺寸無嚴(yán)格限制，且為開式傳動，故小齒輪用45鋼，調(diào)質(zhì)處理，硬度241HB286HB，平均取為260HB，大齒輪用球墨鑄鐵QT500-7，硬度170HB230HB，平均取為200HB。開式傳動的齒輪，主要失效形式是彎曲疲勞折斷和磨粒磨損，磨損尚無完善的計算方法，故只進(jìn)行彎曲疲勞強(qiáng)度計算。計算項目 計算內(nèi)容 計算結(jié)果1.初步計算轉(zhuǎn)矩 由前表查得 =129.68齒寬系數(shù) 由表，取=1.0 =1.0彎曲疲勞極限 由圖 =500Mpa =350Mpa初步計算的許用彎曲應(yīng)力 =0.7 =0.7500 =350Mpa =0.7 =0.7350 =245Mpa 值 由表，取=1.45 =1.45初取齒輪齒數(shù) 取小齒輪齒數(shù)=25 =25齒形系數(shù) 由圖 =2.63 =2.18應(yīng)力修正系數(shù) 由圖 =1.58 =1.81初步計算的齒輪模數(shù)m m =1.96 m=3初步寬度b b= =75mm =65mm2.校核計算圓周速度v v= v=1.08m/s精度等級 由表 選9級等級齒數(shù)z和模數(shù)m 由前計算，m=3； =25，=i=100 =25 =100使用系數(shù) 由表 =1.25動載系數(shù) 由表 =1.1重合度 = =1.88-3.2（）=1.72 =1.72重合度系數(shù) =0.25+=0.25+ =0.69齒間載荷分配系數(shù) 由表，= =1.4齒向載荷分配系數(shù) =9.63 由圖 =1.25載荷系數(shù)K =1.251.11.41.25 K=2.4彎曲最小安全系數(shù) 由表 =1.2應(yīng)力循環(huán)次數(shù) =60=601274.3 14400 = =60=60168.57 14400 =0.6彎曲壽命系數(shù) 由圖 =0.92 =0.98尺寸系數(shù) 由圖 =1.0許用彎曲應(yīng)力 = =368Mpa = =274.4Mpa驗算 = =158.6Mpa =158.6 150.60Mpa 因傳動無嚴(yán)重過載，故不作靜強(qiáng)度校核齒輪的結(jié)構(gòu)的設(shè)計：小齒輪制成實心式，大齒輪制成圓盤式，具體結(jié)構(gòu)參數(shù)見零件圖。綜上整理齒輪傳動的參數(shù)如表4：表4 齒輪傳動的相關(guān)參數(shù)模數(shù)m小齒輪齒數(shù)壓力角大齒輪齒數(shù)傳動比32510043.5 軸系零件的設(shè)計計算軸材料選用45鋼調(diào)質(zhì)，=650Mpa，=360Mpa。軸的設(shè)計計算步驟如下：計算項目 計算內(nèi)容 計算結(jié)果3.5.1 初算軸徑d 由表，C=112 =112 =26.72mm 取d=40mm3.5.2 初步計算軸上各段長度 軸承選6208，寬度B=18mm； 小齒輪齒寬b=75mm； 由表： 大帶輪寬度B=（Z-1）e+2f =（6-1）15+ 210=95mm軸的結(jié)構(gòu)設(shè)計如圖3：圖3 軸II的結(jié)構(gòu)設(shè)計圖計算軸上載荷：由前計算：帶輪作用軸上載荷=1752N，T=129.68Nm齒輪作用在軸上載荷： =3458N，=129.68Nm3.5.3 繪制軸的彎扭矩圖，對危險截面進(jìn)行校核簡化軸上載荷如圖4：圖4 軸II所受的載荷圖其中， =1752N，T=129.68Nm， =3458cos=3249.5N =3458=1182.7N畫軸的彎矩圖，扭矩圖圖5 軸II的彎矩圖、扭矩圖由彎矩圖、扭矩圖可知B點為危險截面。對B點進(jìn)行校核計算：M=276.64Nm查表得：=215Mpa，=102.5Mpa，=60Mpa 對于不變的轉(zhuǎn)矩，取 =278N.m所以： =43.43Mpa=60Mpa滿足強(qiáng)度要求。軸承選用6208，帶輪和齒輪結(jié)構(gòu)見零件圖。3.5.4 軸承的校核（1）計算軸承的當(dāng)量動載荷P： 由式：P=X+Y知， 對不承受軸向載荷的深溝球軸承，X=1，Y=0 由力學(xué)相關(guān)知識解得：=2599.6N； ；=728.46N =3409.6N =5894.3N 得：=3409.6N；=5894.3N （2）校核計算 軸承的計算額定動載荷，它與所選用軸承型號的基本額定載荷C值必須滿足下式要求： C； 為軸承的預(yù)期使用壽命， 查表，取=6000h 解得=3409.6=15.76KwC=29.5Kw =5894.3=27.24KwC=29.5Kw 綜上：軸承滿足使用要求，選用合理3.5.5 軸上鍵連接的選擇及校核 因無特殊要求，選用圓頭普通平鍵，鍵108，通常（1.61.8）d因此，L（1.61.8）34=54.461.2mm，取L=50mm； 校核計算如下：鍵的接觸長度=L-b=50-10=40mm。鍵與縠的接觸高度=4mm；許用擠壓應(yīng)力查表取=150Mpa；所以鍵連接所能傳遞的轉(zhuǎn)矩為：T=0.0040.040.034150=408Nm=129.68Nm。所以，以上選擇的參數(shù)滿足強(qiáng)度要求。合理。3.5.6 軸上螺母的選擇因螺母只需一般的固定作用，并無特殊要求，所以選用普通六角螺母M30。3.6 滾筒及其軸系零件的設(shè)計、選擇與校核。3.6.1 滾筒的結(jié)構(gòu)設(shè)計考慮到系統(tǒng)結(jié)構(gòu)的簡單，及方便安裝，將滾筒與其上的軸制成整體式。軸選用45鋼，調(diào)質(zhì)處理。滾筒可以采用由圓鋼焊接框架并用細(xì)薄鐵皮包裹。軸與滾筒焊接成一體。其結(jié)構(gòu)如圖6：圖6 滾筒及相連軸的結(jié)構(gòu)設(shè)計圖具體參數(shù)見零件圖。滾筒的內(nèi)壁制成內(nèi)徑左大右小的圓錐形，馬鈴薯由右端入口放入，在滾筒內(nèi)隨滾筒翻轉(zhuǎn)的同時，沿滾筒軸向運動，在滾筒內(nèi)去皮后，由滾筒左端筒壁上的開口落下。即完成馬鈴薯的去皮過程。其內(nèi)壁剖面結(jié)構(gòu)如圖7： 圖7 滾筒剖視圖3.6.2 軸承的選擇、校核考慮到滾筒的體積、質(zhì)量較大，并且不受軸向載荷，選用滾動軸承6218，其內(nèi)徑d=90mm。（1） 求解各軸承受力圖8 滾筒軸所受載荷圖其中，3017.6N；=3017.6=1098.3N由力學(xué)相關(guān)知識解得：=3436.13N；=418.53N； =1202.9N； =104.6N；（2）計算軸承的當(dāng)量動載荷P： 由式：知：對不承受軸向載荷的深溝球軸承，X=1，Y=0 =3640.6N =431.4N 得： =3640.6N； =431.4N （3）校核計算 軸承的計算額定動載荷，它與所選用軸承型號的基本額定載荷C值必須滿足下式要求： C=； 為軸承的預(yù)期使用壽命， 查表，取=6000h 解得=3640.6=10.6KwC=95.8Kw =431.4=1.256Kw=452.64Nm。所以，以上選擇的參數(shù)滿足強(qiáng)度要求。合理。3.6.4 軸上螺母選擇因螺母只需一般的固定作用，并無特殊要求，所以選用普通六角螺母M42。3.7 軸承座、端蓋的結(jié)構(gòu)設(shè)計3.7.1 軸承座的選材 由于機(jī)構(gòu)運轉(zhuǎn)過程中并無較大沖擊載荷，且軸承外徑較大，考慮到節(jié)約成本，故選用灰鑄鐵HT300，=290Mpa，硬度190240HB。3.7.2 軸承座的固定方式 軸承座與機(jī)架用螺栓聯(lián)接。3.7.3 軸承座的結(jié)構(gòu)設(shè)計 具體結(jié)構(gòu)參數(shù)見零件圖。3.7.4 軸承座端蓋選材、結(jié)構(gòu)設(shè)計 端蓋選用灰鑄鐵HT300，=290Mpa，硬度190240HB。用螺栓與軸承座聯(lián)接。端蓋用于限制軸承在軸承座內(nèi)的軸向位移，且在端蓋與軸承座之間加用墊圈，通過換用不同厚度的墊圈即可調(diào)整軸承在軸承座內(nèi)的軸向位置，如圖9所示： 圖9 軸承與內(nèi)孔及端蓋的轉(zhuǎn)配關(guān)系圖具體結(jié)構(gòu)參數(shù)見零件圖。3.8 軸承座聯(lián)接用螺栓的設(shè)計計算 螺栓材料選用45鋼，材料的許用拉應(yīng)力=350Mpa。螺栓直徑d的設(shè)計計算：（1） 軸左右兩軸承座受力如圖10所示； 圖10 軸II上的兩軸承座的受力分析圖 對于固定左軸承座的螺栓，預(yù)緊力只須滿足： ； z螺栓個數(shù)，z=2； 螺栓預(yù)緊力； 接觸面間的摩擦系數(shù)，查表取=0.135 ； m接合面數(shù)目 ，m=1； 考慮摩擦傳力的可靠系數(shù)，取=1.3 =8023.4N 螺栓直徑d=6.16mm 對于固定右軸承座得螺栓，預(yù)緊力必須滿足： ; 殘余預(yù)緊力；其余符號含意同上； =3507.4N 同時螺栓所受總拉力F=+=3507.4+5849.1=9356.5N 螺栓直徑d=6.65mm綜上，軸上軸承座選用螺栓M8. （2）滾筒左右兩軸承座受力如圖11所示： 圖11 滾筒軸上兩軸承座的受力分析圖 對于固定左軸承座的螺栓，預(yù)緊力只須滿足： ； z螺栓個數(shù)，z=2； 螺栓預(yù)緊力； 接觸面間的摩擦系數(shù)，查表取=0.135 m接合面數(shù)目 ，m=1； 考慮摩擦傳力的可靠系數(shù)，取=1.3 =2355.6N 螺栓直徑d=3.34mm 對于固定右軸承座得螺栓，預(yù)緊力必須滿足： ； 殘余預(yù)緊力；其余符號含意同上； =503.6N 同時螺栓所受總拉力F=503.6+5849.1=6352.7N 螺栓直徑d=6.5mm綜上，滾筒軸上軸承座選用螺栓M8.3.9 機(jī)架的結(jié)構(gòu)設(shè)計 機(jī)架材料選用型鋼，由型鋼焊接成機(jī)架。在機(jī)架的結(jié)構(gòu)設(shè)計中，主要考慮便于軸承座的安裝，以及方便機(jī)架上零件間相對距離的調(diào)整，具體結(jié)構(gòu)參數(shù)見零件圖。參考文獻(xiàn) 1邱宣懷、郭可謙、吳宗澤等.機(jī)械設(shè)計M.4版.北京：高等教育出版社.2010.2劉混舉、趙河明、王春燕.機(jī)械可靠性設(shè)計M.北京：國防工業(yè)出版社.2010.3楊光、席偉光、李波、陳曉岑.機(jī)械設(shè)計課程設(shè)計M.2版.北京：高等教育出版社.2010.4金清肅、范順成、范曉珂.機(jī)械設(shè)計課程設(shè)計M.武漢：華中科技大學(xué)出版社.2006.5王慧、呂宏、王連明.機(jī)械設(shè)計課程設(shè)計M.北京：北京大學(xué)出版社.2011.6于永泗、齊民.機(jī)械工程材料M.8版.大連：大連理工大學(xué)出版社.2010.7鄭文緯、吳克堅.機(jī)械原理M.7版.北京：高等教育出版社.2010.8劉鴻文.材料力學(xué)M.4版.北京：高等教育出版社.2010.9哈爾濱工業(yè)大學(xué)理論力學(xué)教研室.理論力學(xué)M.6版.北京：高等教育出版社.2004.10陳于萍、周兆元.互換性與測量技術(shù)基礎(chǔ)M.2版.北京：機(jī)械工業(yè)出版社.2009.11何銘新、錢可強(qiáng).機(jī)械制圖M.5版.北京：高等教育出版社.2008.12蔣曉、沈培玉、苗青.AutoCAD2008中文版機(jī)械設(shè)計標(biāo)準(zhǔn)實例教程M.北京：清華大學(xué)出版社.2008.設(shè)計小結(jié)畢業(yè)設(shè)計是我們專業(yè)課程知識綜合應(yīng)用的實踐訓(xùn)練，是我們邁向社會，從事職業(yè)工作前一個必不少的過程”千里之行始于足下”，通過這次畢業(yè)設(shè)計，我深深體會到這句千古名言的真正含義我今天認(rèn)真的進(jìn)行畢業(yè)設(shè)計，學(xué)會腳踏實地邁開這一步，就是為明天能穩(wěn)健地在社會大潮中奔跑打下堅實的基礎(chǔ) 說實話，畢業(yè)設(shè)計真的有點累然而，當(dāng)我一著手清理自己的設(shè)計成果，漫漫回味這10周的心路歷程，一種少有的成功喜悅即刻使倦意頓消雖然這是我剛學(xué)會走完的第一步，也是人生的一點小小的勝利，然而它令我感到自己成熟的許多，另我有了一中”春眠不知曉”的感悟。通過畢業(yè)設(shè)計，使我深深體會到，干任何事都必須耐心，細(xì)致。畢業(yè)設(shè)計過程中，許多計算有時不免令我感到有些心煩意亂：有2次因為不小心我計算出錯，只能毫不情意地重來但想到今后自己應(yīng)當(dāng)承擔(dān)的社會責(zé)任，想到世界上因為某些細(xì)小失誤而出現(xiàn)的令世人無比震驚的事故，我不禁時刻提示自己，一定要養(yǎng)成一種高度負(fù)責(zé)，認(rèn)真對待的良好習(xí)慣。這次畢業(yè)設(shè)計使我在工作作風(fēng)上得到了一次難得的磨練短短10周是畢業(yè)設(shè)計，使我發(fā)現(xiàn)了自己所掌握的知識是真正如此的缺乏，自己綜合應(yīng)用所學(xué)的專業(yè)知識能力是如此的不足，幾年來的學(xué)習(xí)了那么多的課程，今天才知道自己并不會用。 最后，我要感謝我的老師們，是您嚴(yán)厲批評喚醒了我，是您的敬業(yè)精神感動了我，是您的教誨啟發(fā)了我，是您的期望鼓勵了我，我感謝老師您今天又為我增添了一幅堅硬的翅膀由于本人的設(shè)計能力有限，在設(shè)計過程中難免出現(xiàn)錯誤，懇請老師們多多指教,我十分樂意接受你們的批評與指正，本人將萬分感謝。23systems. assessing the example of three tractors of the same category, which are exploited in climatic and soil conditions 1. Introduction for agricultural agricultural recognized careful technical, predicting ofcropproduction.Nowadays,theexistingmathematicaloptimiza- tion methods, supported by the high-performance computers, can efficiently resolve the optimization problems (Dette Duffy et al., 1994; Mileusnic, 2007; etc.). The formation of an optimal technical system in order to produce cheaper food, highly impacted reliability of tractors, its maintainability, and the functionality of the system. rounding conditions. Although in the same spirit, some authors have defined effectiveness somewhat differently. In (Ebramhimipour maintainabilityascapacityofthe systemforpreventionandfindingfailuresanddamages,forrenewing operating ability and functionality through technical attending and repairs; and functionality as the degree of fulfilling the functional requirements, namely the adjustment to environment, or more pre- cisely to the conditions in which the system operates. In the case of monitoring reliability and maintainability it is common to monitor the time picture of state (Fig. 1) according to their working conditions is obtained. The model can be used as cri- teria for decision making related to any procedure in purchasing, operation or maintenance of the system, for prediction of repair and maintenance costs. Quality and functionality of the proposed model is shown in effectiveness determination of agricultural machinery, precisely tractors. R. Miodragovic et al./Expert Systems with Applications 39 (2012) 89408946 8941 which the functions of reliability and maintainability can be deter- mined, as well as the mean time in operation and the mean time in failure. The main problem that occurs in forming the time picture of state is data monitoring and recording. In real conditions the ma- chines should be connected to information system which would precisely record each failure, duration and procedure of repair. This is usually expensive and improvised monitoring of the machine performance, namely of its shut downs, is imprecise. Moreover, statistical data processing provided by the time picture of the state requires that all machines work under equal conditions, which is difficult to achieve. As for the functionality of the technical system, there is no common way for its measuring and quantification. This is the reason why in this paper, in order to assess the effectiveness, expertise judgments of the employed in the working process of the analyzed machines will be used. Application of expertise judgments has been largely used in literature, primarily for data processing and the assessment of the technical systems in terms of: risk (Li Wang, Yang, Tanasijevic, Ivezic, Ignjatovic, Zadeh, 1996). Application of fuzzy sets today represents one of the most frequently used tools for solving the problems in various areas of optimization (Huang, Gu, Liebowitz, 1988) in general is also used for solving the optimizations problems from area of agro machinery. In article (Rohani, Abbaspour-Fard, and fuzzy composition of men- tioned indicators into one synthesized. Fuzzy proposition is pro- cedure for representing the statement that includes linguistic variables based on available information about considered techni- cal system. In that sense it is necessary to define the names of lin- guistic variables that represent different grades of effectiveness of considered technical system and define the fuzzy sets that describe the mentioned variables. Composition is a model that provides structure of indicators influences to the effectiveness performance. 2.1. Fuzzy model of problem solving The first step in the creation of fuzzy model for effectiveness (E) assessment is defining linguistic variables related to itself and to reliability (R), maintainability (M) and functionality (F). Regarding number of linguistic variables, it can be found that seven is the maximal number of rationally recognizable expressions that hu- man can simultaneously identify (Wang et al., 1995). However, for identification of considered characteristics even the smaller number of variables can be useful because flexibility of fuzzy sets to include transition phenomena as experts judgments commonly is (Ivezic et al., 2008). According to the above, five linguistic vari- ables for representing effectiveness performances are included: poor, adequate, average, good and excellent. Form of these linguis- tic variables is given as appropriate triangular fuzzy sets (Klir .;l 5 R ; l M l 1 M ; .;l 5 M ; l F l 1 F ; .;l 5 F 1 In the next step, maxmin composition is performed on them. Max min composition, also called pessimistic, is often used in fuzzy alge- bra as a synthesis model (Ivezic et al., 2008; Tanasijevic et al., 2011; Wang et al., 1995; Wang 2000). The idea is to make overall assess- ment (E) equal to the partial virtual representative assessment. This assessment is identified as the best possible one between the worst partial grades expected (R, M or F). It can be concluded that all elements of (R, M and F) that make the E have equal influence on E, so that maxmin composition will be used, which in parallel way treats the partial ones onto the h time of planned shut down due to preventive maintenance. 1995) and OR R M F If we tions that is (according to Fig. 2): with 39 (2012) 89408946 Further, for each outcome its values are calculated (X c ). The outcome which would suit the combination c, it would be calcu- lated following the equations: X c P R;M;E j hi c 3 3 Finally, all of these outcomes are treated with maxmin composi- tion, as follows: (i) For each outcome search for the MINimum value of l R,M,F in vector E c (2). The minimum which would suit the combina- tion o, it would be calculated following the equations: MIN 0 minfl j1;.;5 R ;l j1;.;5 M .;l j1;.;5 F g;for all o 1toO 4 (ii) Outcomes are grouped according to their values X c (3), namely the size of j. (iii) Find the MAXimum between previously identified mini- mums (i) for each group (ii) of outcomes. The maximum which would suit value of j, would be calculated following the equations: MAX j maxfMIN o g; for every j 5 E assessment of technical system is obtained in the form: l E This expression (Fig. 2 tion of to fuzzy cedure (d) between the E which d i E j ;H take into account only values if l j1;.;5 R;M;F 0, we get combina- are named outcomes (o =1toO, where O # C). in the process of synthesis, are also used. Precisely, if we look at three partial indicators, namely their membership function (1), it is possible to make C = j 3 =5 3 combina- tions of their membership functions. Each of these combinations represents one possible synthesis effectiveness assessment (E). E l j1;.;5 ;l j1;.;5 ; .;l j1;2;.5 hi ; for all c 1toC 2 maxmin compositions which by using operators AND provide an advantage to certain elements over the others synthetic indicator. In literature (Ivezic et al., 2008; Wang et al., Fig. 2. Effectiveness fuzzy sets. 8942 R. Miodragovic et al./Expert Systems MAX j1 ; .;MAX j5 l 1 E ; .;l 5 E 6 (6) is necessary to map back to the E fuzzy sets ). Best-fit (Wang et al., 1995), method is used for transforma- E description (6) to form that defines grade of membership sets: poor, adequate, average, good and excellent. This pro- is recognized as identification. Best-fit method uses distance E obtained by maxmin composition (6) and each of expressions (according to Fig. 2), to represent the degree to E is confirmed to each of fuzzy sets of effectiveness (Fig. 2). i X 5 j1 l j E C0l j H j 2 v u u t ; j 1; .;5;H i fexcellent;goodaverage;adequate;poorg7 E i fb i1 ;poor;b i2 ;adequate;b i3 ;good; b i4 ;average;b i5 ;excellentg 10 3. An illustrative example As an illustrative example of evaluation of agriculture machin- ery effectiveness, the comparative analysis of three tractors A 1 B 2 , and C 2 is given in this article. In tractor A a 7.146 l engine LO4V TCD 2013 is installed. Thanks to the reserves of torque from 35%, the tractor is able to meet all the requirements expected in the worst performing farming oper- ations in agriculture. Total tractor mass is 16,000 kg. According to OECD (CODE II) report maximum power measured at the PTO shaft is 243 kW at 2200 rpm with specific fuel consumption of 198 g/kW h (ECE-R24). Maximum engine torque is 1482 Nm at en- gine regime of 1450 rpm. Transmission gear is vario continious transmision. Linkage mechanism is a Category II/III with lifting force of 11,800 daN. In tractors B 2 and C 2 8.134 l engine 6081HRW37 JD is installed, with reserve torque of 40%, and this tractor was able to meet all the requirements expected in the worst performance of the farming operations in agriculture. Total tractor weight is 14,000 kg. Accord- ing to OECD (CODE II) report maximum power measured at the PTO shaft is 217 kW at 2002 rpm with specific fuel consumption of 193 g/kW h (ECE-R24). Maximum torque is 1320 Nm at engine revs of 1400 rpm. Transmission is AutoPower. Linkage mechanism is a Category II/III with lifting force of 10,790 daN. Both models have electronically controlled tractor engine and fuel supply system that meets the regulations on emissions. From the submitted technical characteristics of the tractor A, B and C it is seen that all three tractors are fully functional for l exc. = (0,0,0,0.25,1); l good = (0,0,0.25,1,0.25); l aver. = (0,0.25,1,0.25,0); l adeq. = (0.25,1,0.25,0,0); l poor = (1,0.25,0,0,0). The closer l E (6) is to the ith linguistic variable, the smaller d i is. Distance d i is equal to zero, if l E (6) is just the same as the ith expression in terms of the membership functions. In such a case, E should not be evaluated to other expressions at all, due to the exclusiveness of these expressions. Suppose d imin (i =1,.,5) is the smallest among the obtained distances for E j and leta 1 ,.,a 5 represent the reciprocals of the rel- ative distances (which is calculated as the ratio between corres- ponding distance d i (7) and the mentioned values d imin ). Then, a i can be defined as follows: a i 1 d i =d imin ; i 1; .;5 8 If d i = 0 it follows that a i = 1 and the others are equal to zero. Then, a i can be normalized by: b i a j P 5 m1 a im ; i 1; .;5 X 5 i1 b i 1 9 Each b i represents the extent to which E belongs to the ith defined E expressions. It can be noted that if E i completely belongs to the ith expression then b i is equal to 1 and the others are equal to 0. Thus b j could be viewed as a degree of confidence that E i belongs to the ith E expressions. Final expression for E performance at the level of tech- nical system, have been obtained in the form (10) where Applications 1 Tractor Fendt Vario 936. 2 Tractor John Deere 8520. performing difficult operations for different technologies of agri- cultural production. Tractors B and C have the same technical char- acteristics, and practice is the same type and model, except that the tractor B entered into operation in May 2007, a tractor C in June 2007. A tractor on the experimental farm, which is the technical documentation for the base model, comes into operation in July 2009. The main task of maintaining agricultural techniques is to provide functionality and reliability of machines. Maintenance of all three tractors is done by machine shop owned by the user up- grade option. Ten engineers (analysts) working on maintenance and opera- tion of tractors were interviewed. Their evaluation of R, D and F are given in Table 1. First, the effectiveness of tractor A is calculated. It can be seen that the reliability was assessed as excellent by six out of ten ana- lysts (6/10 = 0.6), as average by three (0.3) and as good by one (0.1). In this way the assessment R is obtained in the form (11): R 0:6=exc; 0:3=good; 0:1=aver; 0=adeq; 0=poor11 In the same way the assessments for M and F are obtained: M 0:4=exc; 0:4=good; 0:2=aver; 0=adeq; 0=poor F 0:5=exc; 0:5=good; 0=aver; 0=adeq; 0=poor In the next step, these assessments are mapped on fuzzy sets (Fig. 1) in order to obtain assessment in the form (1). For example, Reliabil- ity in this example is determined as (11), where it is to linguistic variable excellent joined weight 0.6. Thereby, fuzzy set excellent is defined as: R exc = (1/0, 2/0, 3/0, 4/0.25, 5/1.0) (according to Fig. 1). In this way the specific values of fuzzy set excellent R exc0.6 = (1/(0 C2 0.6), 2/(0 C2 0.6), 3/(0 C2 0.6), 4/(0.25 C2 0.6), 5/(1.0 C2 0.6) are obtained. The remaining four linguistic variables are treated in the same way. In the end for each j =1,.,5 specific membership functions (last row, Table 2) are added into the final fuzzy form (1) of tractor A reliability: l RA 0;0:025;0:175;0:475;0:675 In the same way, based on the questionnaire (Table 1) values for maintainability and functionality are obtained: l MA 0;0:05;0:3;0:55;0:5; l FA 0;0;0:125;0:625;0:62512 These fuzzificated assessments (11) and (12) are necessary to syn- thesize into assessment of effectiveness, using maxmin logics. In this case it is possible to make C =5 3 = 125 combinations, out of which the 48 outcomes. First outcome would be for combination 2-2-3: E 2-2-3 = 0.025,0.05,0.125, where is X 2-2-3 = (2 + 2 + 3)/3 = 2 (rounded as integer). Smallest value among the membership func- tions of this outcome is 0.025. Other outcomes and corresponding values of X c are shown in Table 3. All these outcomes can be grouped around sizes X = 2, 3, 4 and 5. For example, for outcome X = 5 it can be written: E 4C05C05 0:475;0:5;0:625C138;E 5C04C05 0:675;0:55;0:625C138;E 5C05C04 0:675;0:5;0:625C138;E 5C05C05 0:675;0:5;0:625C138 Further, for each of them, minimum between membership function is sought: Table 1 Results of questionnaire. Average x x xx x xx x R. Miodragovic et al./Expert Systems with Applications 39 (2012) 89408946 8943 Analyst Linguistic variables Tractor A Tractor B Excellent Good Average Adequate Poor Excellent Good 1R x x Mx x Fxxx 2R x Mx x Fx 3R x x Mx Fx 4R x x Mx Fx x 5R x x Mx Fxxx 6R x x Mx Fx x 7R x Mx Fx 8R x x Mx x Fx x 9R x x Mx x Fx x 10 R x x Mx x Fx x Tractor C Adequate Poor Excellent Good Average Adequate Poor x x x x x x x x x x x xx x x x x x x x x x with Table 2 Calculation of specific values of fuzzy sets. 12345 0.6/exc. 0 C2 0.6 0 C2 0.6 0 C2 0.6 0.25 C2 0.6 1.0 C2 0.6 0.3/good 0 C2 0.3 0 C2 0.3 0.25 C2 0.3 1.0 C2 0.3 0.25 C2 0.3 8944 R. Miodragovic et al./Expert Systems MINE 4C05C05 minf0:475;0:5;0:625g0:475;MINE 5C04C05 0:55;MINE 5C05C04 0:5;MINE 5C05C05 0:5 Between these minimums, in the end it seeks maximum: MAXX d5 maxf0:475;0:55;0:5;0:5g0:55 Also for other values: X: MAX X =2 = 0.025; MAX X =3 = 0.175; MAX X =4 = 0.55 (Table 1.) 0.1/aver. 0 C2 0.1 0.25 C2 0.1 1.0 C2 0.1 0.25 C2 0.1 0 C2 0.1 0/adeq. 0.25 C2 0 1.0 C2 0 0.25 C2 00C2 00C2 0 0/poor 1.0 C2 0 0.25 C2 00C2 C2 C2 0 P R 0 0.025 0.175 0.475 0.675 Table 3 Structure of MAXMIN composition. Comb. X l MIN 2345 2-2-3 2 0.025,0.05,0.125 0.025 2-2-4 3 0.025,0.05,0.625 0.025 2-2-5 3 0.025,0.05,0.625 0.025 2-3-3 3 0.025,0.3,0.125 0.025 2-3-4 3 0.025,0.3,0.625 0.025 2-3-5 3 0.025,0.3,0.625 0.025 2-4-3 3 0.025,0.55,0.125 0.025 2-4-4 3 0.025,0.55,0.625 0.025 2-4-5 4 0.025,0.55,0.625 0.025 2-5-3 3 0.025,0.5,0.125 0.025 2-5-4 4 0.025,0.5,0.625 0.025 2-5-5 4 0.025,0.5,0.625 0.025 3-2-3 3 0.175,0.05,0.125 0.05 3-2-4 3 0.175,0.05,0.625 0.05 3-2-5 3 0.175,0.05,0.625 0.05 3-3-3 3 0.175,0.3,0.125 0.125 3-3-4 3 0.175,0.3,0.625 0.175 3-3-5 4 0.175,0.3,0.625 0 0.175 3-4-3 3 0.175,0.55,0.125 0.125 3-4-4 4 0.175,0.55,0.625 0.175 3-4-5 4 0.175,0.55,0.625 0.175 3-5-3 4 0.175,0.5,0.125 0.125 3-5-4 4 0.175,0.5,0.625 0.175 3-5-5 4 0.175,0.5,0.625 0.175 4-2-3 3 0.475,0.05,0.125 0.05 4-2-4 3 0.475,0.05,0.625 0.05 4-2-5 4 0.475,0.05,0.625 0.05 4-3-3 3 0.475,0.3,0.125 0.125 4-3-4 4 0.475,0.3,0.625 0.3 4-3-5 4 0.475,0.3,0.625 0.3 4-4-3 4 0.475,0.55,0.125 0.125 4-4-4 4 0.475,0.55,0.625 0.475 4-4-5 4 0.475,0.55,0.625 0.475 4-5-3 4 0.475,0.5,0.125 0.125 4-5-4 4 0.475,0.5,0.625 0.475 4-5-5 5 0.475,0.5,0.625 0.475 5-2-3 3 0.675,0.05,0.125 0.05 5-2-4 4 0.675,0.05,0.625 0.05 5-2-5 4 0.675,0.05,0.625 0.05 5-3-3 4 0.675,0.3,0.125 0.125 5-3-4 4 0.675,0.3,0.625 0.3 5-3-5 4 0.675,0.3,0.625 0.3 5-4-3 4 0.675,0.55,0.125 0.125 5-4-4 4 0.675,0.55,0.625 0.55 5-4-5 5 0.675,0.55,0.625 0.55 5-5-3 4 0.675,0.5,0.125 0.125 5-5-4 5 0.675,0.5,0.625 0.5 5-5-5 5 0.675,0.5,0.625 0.5 MAX 0.025 0.175 0.55 0.55 Finally, we get expression for membership function of effective- ness of tractor A: l EA 0;0:025;0:175;0:55;0:55 Best-fit method (79) and proposed E fuzzy set (Fig. 1) give the final effectiveness assessment for the tractor A: d 1 E;exc X 5 j1 l j E C0l j exc 2 v u u t 0C00 2 0:025C00 2 0:175C00 2 0:55C00:25 2 0:55C01 2 q 0:56899 where is : l E 0;0:025;0:175;0:55;0:55 l exc 0;0;0;0:25;1 For other fuzzy sets: d 2 (E, good) = 0.54658, d 3 (E, aver) = 1.06007, d 4 (E, adeq) = 1.27426, d 5 (E, poor) = 1.29856. for d min d 2 : a 1 1 d 1 =d 2 1 0:56899=0:54658 0:96061; a 2 1:00000;a 3 0:51561;a 4 0:42894;a 5 0:42091: b 1 a 1 P 5 i1 a i 0:96901 0:96901 1 0:51561 0:42894 0:42091 0:28881; b 2 0:30065;b 3 0:15502;b 4 0:12896;b 5 0:12655: Finally, we get the assessment of effectiveness of tractor A, in form (10): E A =(b 1 , excellent), (b 2 , good), (b 3 , average), (b 4 , ade- quate), (b 5 , poor) = (0.28881, excellent), (0.30065, good), (0.15502, average), (0.12896, adequate), (0.12655, poor) In the same way, we get the assessments for other two tractors B and C: E B = (0.23793, excellent), (0.27538, good), (0.20635, aver- age), (0.14693, adequate), (0.13342, poor) E C = (0.17507, excellent), (0.25092, good), (0.25468, aver- age), (0.17633, adequate), (0.14300, poor). Tractor A is in great extent of 0.30065 (in relation to 30 %) as- sessed as good, tractor B in great extent of 0.27538 (27.5%) as- Applications 39 (2012) 89408946 sessed as good, while tractor C is in great extent of 0.25468 (25.5%) assessed as average. It can be concluded that C is the worst, while tractor A is only somewhat better than B, especially if we see with that A is assessed as excellent in the extent of 28.8% while B in the extent of 23.8%. Effectiveness of analyzed tractors can be presented as in Fig. 3., where it can be more clearly seen that tractor A has the biggest effectiveness. If this assessment (E A , E B , E C ) is defuzzificated by center of mass point calculation Z (Bowles if calculated on 10,000 moto-hours, Fig. 3. Relationship of effectiveness of observed tractors. R. Miodragovic et al./Expert Systems it would spend in work 9244 moto-hours. As of the tractor B, out of 10,004 available moto-hours, it spent 9069 moto-hours in work, and tractor C out of 9981 available moto-hours spent 9045 in work. The experiment showed that the more reliable and efficient tractors are the less frequent are delays. In part, this initial advan- tage wiped out worse logistics of delivery of spare parts when it comes to tractor A. in 1100 moto-hours work of the tractor, due to poor logistics in maintaining hoped to eight working days, and it greatly influenced the decline in benefits of maintainability of a given tractor and thus the decline in total exploitation of the same efficiency (Internal technical documentation PKB). 4. Conclusion This paper presents a model for effectiveness assessment of technical systems, precisely agricultural machinery, based on fuzzy sets theory. Effectiveness performance has been adopted as overall indicator of systems quality of service, i.e. as entire measure of technical system availability. Reliability, maintainability and func- tionality performances have been recognized as effectiveness parameters or indicators. Linguistic form can be appointed as the References Bowles, J. B., & Pelaez, C. E. (1995). Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliability Engineering and System Safety, 50(2), 203213. Cai, K. Y. (1996).