軸流式脫揚(yáng)機(jī)的總體及脫粒裝置設(shè)計(jì)【脫粒清選稻、麥】【脫粒機(jī)】

軸流式脫揚(yáng)機(jī)的總體及脫粒裝置設(shè)計(jì)【脫粒清選稻、麥】【脫粒機(jī)】,脫粒清選稻、麥,脫粒機(jī),軸流式脫揚(yáng)機(jī)的總體及脫粒裝置設(shè)計(jì)【脫粒清選稻、麥】【脫粒機(jī)】,軸流,式脫揚(yáng)機(jī),總體,整體,脫粒,裝置,設(shè)計(jì),清選稻 UNIVERSITY設(shè) 計(jì)題目： 軸流式脫揚(yáng)機(jī)的總體及脫粒裝置畢業(yè)設(shè)計(jì) 學(xué) 院： 姓 名： 學(xué) 號(hào)： 專 業(yè)： 機(jī)械設(shè)計(jì)制造及其自動(dòng)化 年 級(jí)： 指導(dǎo)教師：= 職 稱： 二一二 年 五 月13摘要本設(shè)計(jì)是關(guān)于軸流式脫揚(yáng)機(jī)的總體設(shè)計(jì)，主要對(duì)軸流式脫揚(yáng)機(jī)的脫粒裝置總體進(jìn)行計(jì)算和分析設(shè)計(jì)。軸流式脫揚(yáng)機(jī)脫粒部分主要由滾筒、主軸、釘齒、機(jī)架等組成，通過(guò)對(duì)進(jìn)入脫粒室的谷物進(jìn)行沖擊和揉搓作用，分離莖稈和谷粒，并直接將谷粒拋出。它能有效提高脫粒效率，有利于脫粒干凈，減低對(duì)稻穗的破碎率，并能很好的分離莖稈和谷粒，從而有效提高農(nóng)業(yè)生產(chǎn)率，大大減輕農(nóng)民勞動(dòng)強(qiáng)度。關(guān)鍵字：脫揚(yáng)機(jī)；分離；滾筒Abstract This project ,which focused on the total calculation and analysis of Axial de-Yang machines Threshing devices ,is about the total design of Axial de-Yang machine . The Axial de-Yang machines threshing part is constitute of roller,spindle,frame and nail tooth.When grain get into the threshing room,through to the impact of the grain and knead role,the stem and the grain will separate,and the grain will been throw away.this machine can effectively improve the efficiency of threshing,make threshing more clearer, and reduce the grains broken rate,whats more,it can be well to separate stem and grain,then effectively improve agricultural productivity,reduce farmers labor intensity.Key words :Axial de-Yang machine;separate;roller 目 錄1. 緒論11.1設(shè)計(jì)的目的與意義11.2國(guó)內(nèi)外發(fā)展現(xiàn)狀12. 軸流式脫揚(yáng)機(jī)的總體方案設(shè)計(jì)及工作原理22.1總體方案的選擇22.2工作原理23. 電動(dòng)機(jī)的選擇33.1電動(dòng)機(jī)的類型和結(jié)構(gòu)33.2電動(dòng)機(jī)容量的選擇33.3.電動(dòng)機(jī)型號(hào)的選擇44. 滾筒的設(shè)計(jì)44.1.滾筒的型式44.2.滾筒的直徑和轉(zhuǎn)速44.3滾筒齒的形狀和排列54.4滾筒長(zhǎng)度55. 滾筒釘齒的設(shè)計(jì)55.1滾筒釘齒的形狀55.2滾筒釘齒的排列66. 凹板篩的設(shè)計(jì)76.1凹板篩型式選擇76.2凹板篩包角選擇76.3凹板篩間隙確定77. 滾筒主軸的設(shè)計(jì)與校核77.1.滾筒主軸的形狀77.2.選擇軸的材料77.3初步確定軸的直徑87.4軸的結(jié)構(gòu)設(shè)計(jì)87.5軸上零件的周向定位87.6滾筒主軸的強(qiáng)度校核97.6.1.對(duì)軸進(jìn)行受力分析并簡(jiǎn)化軸的受力97.6.2.計(jì)算水平面上的剪切力和彎矩，找出危險(xiǎn)截面97.6.3.計(jì)算垂直面上的剪切力和彎矩，并找出危險(xiǎn)截面97.6.4.計(jì)算轉(zhuǎn)矩107.7鍵聯(lián)接的強(qiáng)度強(qiáng)度校核108. 軸承的選用11參考文獻(xiàn)12致謝131. 緒論1.1 設(shè)計(jì)的目的與意義隨著我國(guó)農(nóng)業(yè)的不斷發(fā)展，我國(guó)對(duì)農(nóng)村的問題越來(lái)越關(guān)注，農(nóng)業(yè)是國(guó)民經(jīng)濟(jì)的基礎(chǔ), 這是不以人們意志為轉(zhuǎn)移的客觀經(jīng)濟(jì)規(guī)律。農(nóng)業(yè)生產(chǎn)力發(fā)展的水平和農(nóng)業(yè)勞動(dòng)生產(chǎn)率的高低, 決定了農(nóng)業(yè)為其他部門提供剩余產(chǎn)品和勞動(dòng)力的數(shù)量, 進(jìn)而制約著這些部門的發(fā)展規(guī)模和速度。只有農(nóng)業(yè)發(fā)展了, 國(guó)民經(jīng)濟(jì)其他部門才能得以進(jìn)一步的發(fā)展。而農(nóng)業(yè)機(jī)械化是農(nóng)業(yè)現(xiàn)代化的中心環(huán)節(jié), 它凝聚著現(xiàn)代科學(xué)技術(shù)的最新成果, 并配合農(nóng)業(yè)生物等農(nóng)業(yè)技術(shù), 成為發(fā)揮增產(chǎn)作用的基本手段和提高勞動(dòng)生產(chǎn)率、減輕繁重體力勞動(dòng)的必要條件和根本途徑, 從而帶來(lái)生產(chǎn)力的質(zhì)的飛躍，面對(duì)我過(guò)十幾億的人口壓力，發(fā)展農(nóng)業(yè)的機(jī)械化顯得尤其重要，由機(jī)械化代替人力畜力作業(yè)不只是我國(guó)農(nóng)業(yè)的未來(lái)發(fā)展趨勢(shì)，也是整個(gè)世界農(nóng)業(yè)的發(fā)展趨勢(shì)。我國(guó)是一個(gè)以農(nóng)業(yè)生產(chǎn)為主的發(fā)展中大國(guó)，20世紀(jì)后半期我國(guó)用占世界7%的耕地,卻為世界22%的人口提供了基本充足的食品。農(nóng)業(yè)的快速穩(wěn)步的發(fā)展離不開農(nóng)業(yè)機(jī)械化。中國(guó)農(nóng)業(yè)機(jī)械化經(jīng)過(guò)多年的努力發(fā)展，已經(jīng)取得了一定的成就，但是仍然存在一些不足，如何讓在日常的生產(chǎn)影響中有限的提高生產(chǎn)率，實(shí)現(xiàn)一機(jī)多用是擺在人們面前的一個(gè)棘手的問題，實(shí)現(xiàn)農(nóng)業(yè)的現(xiàn)代化、智能化是今后農(nóng)業(yè)的必然選擇。通過(guò)采用現(xiàn)代化農(nóng)業(yè)工程和機(jī)械技術(shù)，適應(yīng)自然環(huán)境，為植物生產(chǎn)收獲提供相對(duì)更為有利條件，從而在一定程度上擺脫對(duì)自然環(huán)境的依賴而進(jìn)行有效生產(chǎn)的農(nóng)業(yè)，它是在人們生活需求不斷增長(zhǎng)的同時(shí)發(fā)展起來(lái)的，是在人為可控設(shè)施下得農(nóng)業(yè)生產(chǎn)，具有高投入、高技術(shù)含量、高品質(zhì)、高產(chǎn)量和高效益等特點(diǎn)，是最具活力的現(xiàn)代新農(nóng)業(yè)。全喂入式軸流式脫揚(yáng)機(jī)，要求體積的質(zhì)量小、動(dòng)力足，操作舒適，符合人機(jī)工程學(xué)的設(shè)計(jì)原理，減輕作業(yè)者勞動(dòng)強(qiáng)度，盡量減少發(fā)動(dòng)機(jī)對(duì)設(shè)施環(huán)境的污染。我國(guó)是農(nóng)業(yè)大國(guó)，農(nóng)村市場(chǎng)巨大，要發(fā)展農(nóng)村經(jīng)濟(jì)，就需要轉(zhuǎn)移農(nóng)村勞動(dòng)力，提高勞動(dòng)土地面積，可以預(yù)料，在未來(lái)的一段時(shí)間里，中國(guó)將成為世界上最大的脫揚(yáng)機(jī)市場(chǎng)之一。1.2國(guó)內(nèi)外發(fā)展現(xiàn)狀1949年,全國(guó)農(nóng)業(yè)機(jī)械化裝備總動(dòng)力只有8101萬(wàn)千瓦, 農(nóng)用拖拉機(jī)只有117臺(tái),一些大型農(nóng)業(yè)機(jī)械如聯(lián)合收割機(jī)、農(nóng)用載重汽車基本上是空白。經(jīng)過(guò)半個(gè)多世紀(jì)的發(fā)展, 農(nóng)業(yè)機(jī)械擁有量增長(zhǎng)了上千倍, 有的品種甚至數(shù)萬(wàn)倍，截至2003年底,全國(guó)農(nóng)業(yè)機(jī)械總動(dòng)力達(dá)到6億kW以上,農(nóng)機(jī)原值達(dá)3362億美元。農(nóng)用拖拉機(jī)保有量達(dá)1494萬(wàn)臺(tái),拖拉機(jī)配套農(nóng)機(jī)具2292萬(wàn)部, 聯(lián)合收獲機(jī)械36萬(wàn)臺(tái)，農(nóng)田作業(yè)機(jī)械化水平顯著提高,機(jī)械耕地、播種、收獲水平分別達(dá)到46.8 %、26.7 %、19 %；2004年小麥機(jī)收比1995年提高了47%，農(nóng)業(yè)機(jī)構(gòu)服務(wù)領(lǐng)域由原來(lái)的農(nóng)田作業(yè),逐步向產(chǎn)前和產(chǎn)后延伸,向其他領(lǐng)域擴(kuò)展。一大批設(shè)施農(nóng)業(yè)設(shè)備、農(nóng)副產(chǎn)品加工機(jī)械、畜牧業(yè)機(jī)械、林業(yè)機(jī)械、植保機(jī)械、運(yùn)輸機(jī)械、農(nóng)田基本建設(shè)機(jī)械等迅速增長(zhǎng)。溫室面積達(dá)到69 億平方米, 田園管理機(jī)達(dá)到4 萬(wàn)臺(tái)。1近年來(lái), 國(guó)際上不少大型農(nóng)機(jī)企業(yè)看準(zhǔn)中國(guó)巨大的農(nóng)機(jī)市場(chǎng), 與中國(guó)有關(guān)部門和企業(yè)合作,在中國(guó)開拓事業(yè), 取得了雙贏的佳績(jī)。國(guó)內(nèi)一些大型企業(yè), 不斷學(xué)習(xí)國(guó)外的先進(jìn)經(jīng)驗(yàn)和技術(shù), 加大技術(shù)改造和升級(jí)換代力度, 推進(jìn)了國(guó)產(chǎn)農(nóng)業(yè)機(jī)械化產(chǎn)品質(zhì)量的提高。為鼓勵(lì)大型農(nóng)業(yè)機(jī)械的進(jìn)口, 國(guó)家還制定了優(yōu)惠進(jìn)口稅收政策。在中國(guó)舉辦類似于今天的展覽會(huì), 也是農(nóng)機(jī)界加強(qiáng)國(guó)際交流與合作的重要形式, 我們積極支持這類活動(dòng)在中國(guó)開展。國(guó)外軸流式脫揚(yáng)機(jī)的發(fā)展，基本上分為歐美和日本兩大類型，歐美國(guó)家以旱地為主，地塊大，各類作物以小麥為主；日本以水田為主，田塊小，以水稻為主。因此，前者用的脫揚(yáng)機(jī)是大型的，大功率的，而后者用的機(jī)型都是小型的或中型的。2. 軸流式脫揚(yáng)機(jī)的總體方案設(shè)計(jì)及工作原理2.1總體方案的選擇脫粒機(jī)械的農(nóng)業(yè)技術(shù)要求是：脫的干凈、損失少、沒有碎粒和脫殼現(xiàn)象，并且盡可能避免谷粒的機(jī)械損傷，這對(duì)于作為留種的谷粒來(lái)說(shuō)更為重要，因?yàn)榧词故艿捷p微的損傷也會(huì)影響發(fā)芽率。此外由于谷物的莖桿有著很高的經(jīng)濟(jì)價(jià)值，要盡量減少其損失和損壞。脫粒機(jī)應(yīng)具有一定的生產(chǎn)率。脫粒的本質(zhì)在于使谷粒和作物本身分離，欲達(dá)到這個(gè)目的就得借助某一形式的脫粒裝置。本設(shè)計(jì)采用的是全喂入型脫粒機(jī)構(gòu)，脫粒裝置是滾筒式的，滾筒為一高速旋轉(zhuǎn)的圓柱體，在滾筒表面上裝有脫粒元件，而在滾筒下面裝有不動(dòng)的圓弧形凹板，凹板和滾筒之間保持一定的間隙，稱為脫粒間隙。脫粒時(shí)滾筒將谷物從脫粒間隙中通過(guò)進(jìn)行脫粒，滾筒上采用釘齒式脫粒元件。2.2工作原理一、沖擊脫粒這種脫粒方法目前應(yīng)用最廣，靠脫粒原件與谷穗的相互沖擊作用而達(dá)到脫粒目的。能增強(qiáng)沖擊作用，提高生產(chǎn)率和脫凈率，但沖擊過(guò)強(qiáng)會(huì)使谷粒破碎和損傷。沖擊強(qiáng)度一般是用沖擊速度來(lái)衡量的。二、揉擦脫粒它是靠谷穗與脫粒原件之間的揉擦以及谷物之間的相互摩擦而使谷粒脫下來(lái)的。揉擦力越大脫得越干凈，但這種方法易使谷粒損傷，用它脫水稻最不適宜。本設(shè)計(jì)的工作原理是：將谷物連同莖稈由進(jìn)料口進(jìn)入脫粒室，經(jīng)滾筒的沖擊揉搓作用，莖稈伴隨滾筒旋轉(zhuǎn)到出料口，谷物直接掉落在凹板篩上，并落入螺旋輸送器，這樣莖稈自另一側(cè)出料口排出，谷粒由螺旋輸送器從出料口一側(cè)又重新到達(dá)進(jìn)料口一側(cè)，并落入拋揚(yáng)器，谷粒由拋揚(yáng)器拋出，從而達(dá)到谷物的全喂入脫揚(yáng)目的。3. 電動(dòng)機(jī)的選擇3.1電動(dòng)機(jī)的類型和結(jié)構(gòu)電動(dòng)機(jī)類型和結(jié)構(gòu)形式要根據(jù)工作條件、電源、載荷特點(diǎn)和轉(zhuǎn)速來(lái)確定。對(duì)于本設(shè)計(jì)的電動(dòng)機(jī)沒有特殊要求，而Y系列電動(dòng)機(jī)適用于不易燃易爆，無(wú)腐蝕性場(chǎng)合，故選用Y系列三相異步電動(dòng)機(jī)。3.2電動(dòng)機(jī)容量的選擇所選電動(dòng)機(jī)的額定功率應(yīng)大于實(shí)際工作的功率以防止過(guò)載損壞電動(dòng)機(jī)，更不能小于實(shí)際的功率以免造成機(jī)器無(wú)法正常工作。電動(dòng)機(jī)所需功率計(jì)算公式為： （31） 其中一一電動(dòng)機(jī)工作時(shí)的實(shí)際輸出功率 一一工作所需額定功率 一一總傳動(dòng)效率的確定： （32） 其中F一一工作機(jī)阻力 V一一工作機(jī)線速度 一一工作機(jī)效率由于傳動(dòng)效率大于97%，可得工作所需輸入功率為3.3. 電動(dòng)機(jī)型號(hào)的選擇綜合電動(dòng)機(jī)與傳動(dòng)裝置的尺寸、重量、價(jià)格以及傳動(dòng)比的特點(diǎn)和大小，選用1500r/min的電動(dòng)機(jī)比較方便，額定功率13KW，滿載功率因素0.88。4. 滾筒的設(shè)計(jì)4.1.滾筒的型式圖41 滾筒4.2.滾筒的直徑和轉(zhuǎn)速滾筒的直徑不可過(guò)大，以免工作阻力增大，但滾筒直徑過(guò)小則易于纏草。故其最小齒根圓直徑應(yīng)保證齒根圓的周長(zhǎng)大于該地區(qū)割下最高桿的桿長(zhǎng)?；?（41）式中： 滾筒最小的齒根圓直徑 L 割下作物最高桿的桿長(zhǎng)本設(shè)計(jì)過(guò)程中為320毫米，由公式得周長(zhǎng)1005毫米，符合要求。再根據(jù)釘齒高度，確定頂圓直徑 （42） 釘齒高度取85毫米，所以頂圓直徑為490毫米。滾筒的速度是影響工作質(zhì)量的重要參數(shù)，當(dāng)滾筒的圓周速度太小時(shí)，鋼絲齒對(duì)稻穗的沖擊力減弱，需要增長(zhǎng)脫粒時(shí)間而降低生產(chǎn)率。但如果圓周速度過(guò)大，脫粒效率的提高并不明顯，僅使谷粒在滾筒上的跳動(dòng)加劇，增加谷粒的拋散損失。目前已有的機(jī)器上多為8.89.4米/秒（齒頂端線速度），電機(jī)帶動(dòng)的機(jī)具為1112.6米/秒。脫粒秈稻時(shí)由于秈稻比較容易脫粒，滾筒速度對(duì)脫粒效率影響不大顯著。4.3滾筒齒的形狀和排列滾筒上的齒用長(zhǎng)度為85mm的釘齒，經(jīng)熱處理后表面硬度為HRC55，以提高耐磨性。隨著齒的增長(zhǎng)，可以提高脫粒能力，但易帶草，并且消耗的動(dòng)力多。各種齒都采用交錯(cuò)排列，每根齒板條上的齒距一般取5060毫米。安裝時(shí)相鄰兩齒板條上的齒錯(cuò)開半個(gè)齒距。簡(jiǎn)易脫粒機(jī)的滾筒都制成開式，即滾筒齒固定在齒板上，然后與滾筒的左右幅板連接，齒板條多為612根，本設(shè)計(jì)選用6根。4.4滾筒長(zhǎng)度滾筒長(zhǎng)度主要取決于滾筒的傳動(dòng)動(dòng)力，單人腳踏板齒輪驅(qū)動(dòng)的脫粒機(jī)滾筒長(zhǎng)10001100毫米，電動(dòng)機(jī)帶動(dòng)的脫粒滾筒，考慮到滾筒的結(jié)構(gòu)強(qiáng)度，一般取2000毫米以內(nèi)。本設(shè)計(jì)軸流式脫揚(yáng)機(jī)的滾筒長(zhǎng)度采用1000毫米。5. 滾筒釘齒的設(shè)計(jì)5.1滾筒釘齒的形狀圖51 釘齒釘齒是滾筒的主要脫粒元件，特別是對(duì)全喂入式脫粒機(jī)構(gòu)來(lái)說(shuō)，谷物進(jìn)入脫谷室是靠釘齒抓取，谷物進(jìn)入脫谷室后又是靠釘齒打擊脫粒，莖稈在脫谷室內(nèi)做螺旋軸向轉(zhuǎn)動(dòng)還是靠釘齒對(duì)它施加很高的圓周速度使它沿著蓋板上的螺旋導(dǎo)板運(yùn)動(dòng)，直到最后把莖稈逐出機(jī)外還是由釘齒完成。全喂入式脫粒機(jī)的釘齒常用的有楔形釘齒、板形釘齒、指形釘齒三種。前兩種脫粒能力較強(qiáng)，適用于切流型脫粒機(jī)構(gòu)，指形釘齒脫粒能力弱，適用于全喂入軸流型脫粒機(jī)構(gòu)，因?yàn)檩S流型脫粒流程長(zhǎng)，為了減少碎草，采用脫粒能力較弱的指形釘齒。為了避免帶草和提高釘齒在排草口的排草能力，通常釘齒的工作面都有1015的后傾角。5.2滾筒釘齒的排列釘齒在滾筒上的排列方式對(duì)滾筒的脫粒性能都是有一定的影響的，釘齒的排列應(yīng)考慮到充分發(fā)揮每個(gè)釘齒的作用。對(duì)于軸流式全喂入脫粒機(jī)滾筒，其釘齒排列方式按螺旋線排列比較好這樣即可以充分發(fā)揮每個(gè)釘齒的抓取能力有利于連續(xù)均勻喂入，有利于脫粒，又可以在滾筒全長(zhǎng)上有較多的齒跡。滾筒上的釘齒均勻的配置在數(shù)排齒桿上，齒桿的數(shù)量最好是雙數(shù)的，有利于滾筒的平衡，考慮整體的重量、經(jīng)濟(jì)性等通常采用六排排列。相鄰兩個(gè)齒跡的距離叫做齒跡距，通常為2040毫米，齒跡距過(guò)小雖然脫粒作用強(qiáng)但是碎矸顯著增多，消耗功率加大。由于本設(shè)計(jì)是全喂入式，取偏低值，可取齒跡距為28毫米。相鄰釘齒的距離也不能過(guò)大或者過(guò)小，過(guò)大脫粒難以干凈，過(guò)小消耗功率大，容易纏草，易打碎稻穗，故本設(shè)計(jì)選擇65毫米。6. 凹板篩的設(shè)計(jì)6.1凹板篩型式選擇對(duì)于比較容易脫粒的秈稻，可以不用滾筒凹板，而對(duì)難以脫粒的粳稻或脫小麥時(shí)，一般都采用滾筒篩式凹板，本設(shè)計(jì)采用柵格式凹板篩，這種凹板篩目前應(yīng)用最廣，其優(yōu)點(diǎn)明顯，利于脫粒，分離谷粒能力強(qiáng)，堅(jiān)固耐用。柵格篩孔用鋼絲和扁鋼組成，篩孔常見的是2015毫米，長(zhǎng)為扁鋼距離寬為鋼絲的間距，本設(shè)計(jì)材料采用23.5鋼絲及203、204或205扁鋼。6.2凹板篩包角選擇包角的大小對(duì)谷粒分離效果影響很大，適當(dāng)增加包角可以適當(dāng)縮短滾筒長(zhǎng)度，本設(shè)計(jì)采用202包角，這樣可以最好的增加作物揉搓時(shí)間，使脫粒更加干凈。6.3凹板篩間隙確定全喂入式脫揚(yáng)機(jī)考慮到較好的脫粒和分離能力，凹板篩間隙一般在1025毫米之間，本設(shè)計(jì)選擇20毫米。7. 滾筒主軸的設(shè)計(jì)與校核7.1.滾筒主軸的形狀圖71 滾筒主軸7.2.選擇軸的材料 軸的材料主要是碳素鋼和合金鋼，根據(jù)傳動(dòng)的功率和一些參數(shù)選擇材料，最常用45#鋼，經(jīng)調(diào)質(zhì)處理得到的組織具有良好的綜合力學(xué)性能，有較好的強(qiáng)度，同時(shí)兼具較好的塑性和韌性，查表得毛坯直徑200毫米，硬度217-255HBS，抗拉強(qiáng)度極限為640MPa,屈服強(qiáng)度極限為355MPa,彎曲疲勞極限為275MPa,剪切疲勞極限為155MPa。7.3初步確定軸的直徑軸是機(jī)械傳動(dòng)的重要零件，必須達(dá)到足夠的強(qiáng)度，保持良好的穩(wěn)定性，并具有良好的工藝性，根據(jù)軸上零件的定位和固定要求以及加工裝配要求，合理的定出軸的結(jié)構(gòu)外形和全部尺寸。對(duì)于軸流式脫揚(yáng)機(jī)的主軸主要是承受扭矩作用，故只需按軸所受的轉(zhuǎn)矩來(lái)進(jìn)行計(jì)算。扭矩強(qiáng)度條件： （71）式中： 軸的扭轉(zhuǎn)切應(yīng)力 T 軸所受的扭矩 n 軸的轉(zhuǎn)速 軸的許用扭轉(zhuǎn)切應(yīng)力 軸的抗扭截面系數(shù)由于本設(shè)計(jì)的軸采用的是實(shí)心軸，由 （72）可得軸的直徑： （73） C取決于的大小，C取較小值時(shí)取較大值，反之取較小值。根據(jù)軸的材料以及估算結(jié)果，軸直徑取48毫米。7.4軸的結(jié)構(gòu)設(shè)計(jì) 軸主要有軸頸、軸頭、軸身三部分組成，考慮到滾筒主軸主要承受扭矩，故采用圓截面的實(shí)心傳動(dòng)軸，以保持良好的強(qiáng)度，軸長(zhǎng)設(shè)計(jì)為1400毫米。7.5軸上零件的周向定位 本設(shè)計(jì)主要使用皮帶輪傳動(dòng)，軸上皮帶輪的周向定位采用平鍵連接，由手冊(cè)并根據(jù)輪轂寬度選用14970的平鍵，軸肩高度為0.0848=3.84毫米。7.6滾筒主軸的強(qiáng)度校核7.6.1.對(duì)軸進(jìn)行受力分析并簡(jiǎn)化軸的受力 根據(jù)對(duì)滾筒主軸上零件的作用力分析，將其上各受力簡(jiǎn)化為集中力，其所受力主要為電機(jī)的轉(zhuǎn)矩、軸的徑向力以及滾筒的作用力。其受力如圖所示：圖72 滾筒主軸的受力分析圖7.6.2.計(jì)算水平面上的剪切力和彎矩，找出危險(xiǎn)截面剪切力： 彎矩： 剪切圖彎矩圖分別為： 圖73 滾筒主軸水平面上的剪切與彎矩圖7.6.3.計(jì)算垂直面上的剪切力和彎矩，并找出危險(xiǎn)截面 剪切力： 彎矩： 剪切圖彎矩圖分別為：圖74 滾筒主軸垂直面上的剪切與彎矩圖7.6.4.計(jì)算轉(zhuǎn)矩 由,運(yùn)用第四強(qiáng)度理論校核滾筒主軸強(qiáng)度，則有： （74）校核結(jié)果： （75） 故所受最大力截面安全，該軸符合強(qiáng)度的安全要求。7.7鍵聯(lián)接的強(qiáng)度強(qiáng)度校核對(duì)于平鍵聯(lián)接，如忽略摩擦，則當(dāng)聯(lián)接傳遞扭矩時(shí)鍵軸一體受力較大，可能的失效有：軟弱零件的工作面被壓潰或磨損和鍵的剪斷等。對(duì)于實(shí)際采用的材料組合和標(biāo)準(zhǔn)尺寸來(lái)說(shuō)，壓潰或磨損常是主要失效形式。因此，通常只作聯(lián)接的擠壓強(qiáng)度或耐磨性計(jì)算，但在重要的場(chǎng)合也要驗(yàn)算鍵的強(qiáng)度。根據(jù)軸徑查表得bh=149,取L=70，聯(lián)接所能傳遞轉(zhuǎn)矩 （76）其中：許用擠壓應(yīng)力 T傳遞的扭矩 h鍵的高度 l鍵的接觸長(zhǎng)度 d軸的直徑 （77）其中： 鍵的許用剪切應(yīng)力 剪切應(yīng)力經(jīng)校核=4.532MPa;=14.08MPa,故滿足強(qiáng)度要求。8. 軸承的選用軸承的作用是支撐軸及軸上的零件，保持軸的旋轉(zhuǎn)精度，減少軸與支撐之間的摩擦和磨損。本設(shè)計(jì)因?yàn)檩S主要是受軸向和徑向載荷，故選用滾動(dòng)軸承，相比于滑動(dòng)軸承，采用滾動(dòng)軸承的機(jī)器起動(dòng)力矩小，有利于在負(fù)載下起動(dòng)；徑向游隙比較小，運(yùn)轉(zhuǎn)精度高；可使機(jī)器軸向結(jié)構(gòu)緊湊；對(duì)于大多數(shù)滾動(dòng)軸承，軸承組合結(jié)構(gòu)較為簡(jiǎn)單；消耗潤(rùn)滑劑少，便于密封和維護(hù)；不需要要用有色金屬；標(biāo)準(zhǔn)化程度高，能成批生產(chǎn)，使用成本低。因此本設(shè)計(jì)直接選擇深溝球軸承6000系列。查手冊(cè)可得，選軸承尺寸如下：，極限轉(zhuǎn)速12000，軸承代號(hào)61908. 參考文獻(xiàn)1宋宜清.我國(guó)農(nóng)業(yè)機(jī)械化現(xiàn)狀及發(fā)展趨勢(shì)J.農(nóng)業(yè)與技術(shù).2007.2.25282李陸俊.中國(guó)農(nóng)業(yè)機(jī)械化的現(xiàn)狀與發(fā)展趨勢(shì)M北京：西北農(nóng)林科技大學(xué)，20013倫冠德.我國(guó)農(nóng)業(yè)機(jī)械化現(xiàn)狀及發(fā)展趨勢(shì)J. 農(nóng)機(jī)化研究,2006. 6.17194萬(wàn)鶴群.農(nóng)業(yè)經(jīng)濟(jì)結(jié)構(gòu)調(diào)整與農(nóng)業(yè)機(jī)械化優(yōu)化M.北京:科學(xué)技術(shù)出版社.5邱宣懷.機(jī)械設(shè)計(jì)M.高等教育出版社.6劉鴻文.材料力學(xué)M.高等教育出版社.7實(shí)用機(jī)械設(shè)計(jì)手冊(cè)M.中國(guó)農(nóng)業(yè)機(jī)械出版社.8何銘新,錢可強(qiáng).機(jī)械制圖M.高等教育出版社.9于永泗,齊民,等.機(jī)械工程材料M.大連理工大學(xué)出版社.10牛淑卿.我國(guó)農(nóng)業(yè)機(jī)械化發(fā)展的研究J.農(nóng)機(jī)化研究.2006.11劉曉娟.我國(guó)農(nóng)業(yè)機(jī)械化發(fā)展的現(xiàn)狀與對(duì)策J. 農(nóng)業(yè)科技與裝備.2008. 8.116118 致謝 本設(shè)計(jì)是在嚴(yán)霖元教授、吳彥紅教授的悉心指導(dǎo)下，與周鵬坤同學(xué)共同完成的，經(jīng)過(guò)接近兩個(gè)月的準(zhǔn)備及對(duì)實(shí)際脫揚(yáng)機(jī)的測(cè)繪分析，順利完成了本次設(shè)計(jì)。通過(guò)此次畢業(yè)設(shè)計(jì)，對(duì)大學(xué)四年的課程做了一個(gè)系統(tǒng)全面的回顧和深化，并使我更加熟練了對(duì)AutoCAD的運(yùn)用，為以后的工作打下更好的基礎(chǔ)。本設(shè)計(jì)總體上還是合理的，但是由于自身的知識(shí)、實(shí)踐等有限，還有一些地方有疏漏不足之處，請(qǐng)指導(dǎo)老師不吝指正。在這次設(shè)計(jì)的過(guò)程中，我們有幸得到嚴(yán)霖元教授和吳彥紅教授的耐心幫助和支持，為我們豐富了設(shè)計(jì)的方法，在此對(duì)兩位老師表示衷心的感謝，同時(shí)在設(shè)計(jì)的過(guò)程中班里同學(xué)的幫助讓我們能更快更好的完成設(shè)計(jì)，在此也一并表示感謝！ 工學(xué)院 王晨 2012年5月13日systems. 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).