手扶插秧機傳動部分設(shè)計
手扶插秧機傳動部分設(shè)計,手扶插秧機傳動部分設(shè)計,手扶,插秧機,傳動,部分,部份,設(shè)計
手扶插秧機傳動部分設(shè)計
UNIVERSITY
本 科 畢 業(yè) 論 文(設(shè) 計)
題目: 手扶插秧機傳動部分設(shè)計
學(xué) 院:
姓 名:
學(xué) 號:
專 業(yè): 機械設(shè)計制造及其自動化
年 級:
指導(dǎo)教師: XX 職 稱: 講師
二○一二 年 五 月
摘 要
眾所周知,高性能插秧機是與當今世界插秧機設(shè)計,制造技術(shù)接軌的高新技術(shù)。在當前低碳經(jīng)濟環(huán)境下,步行成為一種時尚,步行與插秧機結(jié)合起來,具有著許多的科技含量。本設(shè)計是基于洋馬步行式插秧機為原型,設(shè)計插秧機的傳動部分。為保證水稻栽植的順利進行,栽植運動的傳動部分系統(tǒng)設(shè)計至關(guān)重要。本文對傳動系統(tǒng)進行分析和計算,得到合理的機構(gòu)參數(shù),為插秧機的傳動系統(tǒng)設(shè)計提供依據(jù)。
關(guān)鍵詞:插秧機;傳動系統(tǒng);設(shè)計;機構(gòu)
The hand transplanter drive part design
Abstract:As everyone know,high performance rice transplanter transplanting machine is with the word,manufacturing technology of new and high technology standards.In the current low carbon economy environment,walking becomes a kind of fashion,walking and transplanting machine together,have a lot of content of science and technology. The design is based on the race walking type rice transplanter for prototype,design of rice transplanter drive part.In order to ensure the smooth rice planting,planting motion transmission part of the system design is very important.In this paper,the transmission system analysis and calculation,a reasonable structure parameters for rice transplanter,the transmission system design basis.
Key words: Rice transplanter;transmission system;design;mechannism
目 錄
1 緒論......................................................5
2 手扶插秧機的整體設(shè)計......................................7
2.1 插秧機的基本結(jié)構(gòu)及分類................................7
2.2 洋馬步行式插秧機工作原理...............................8
2.3 洋馬步行式插秧機的傳動原理.............................9
3 機械零部件選擇及設(shè)計......................................10
3.1 發(fā)動機的選擇.......................................... 11
3.2 減速器中各主要參數(shù)的確定...............................11
3.3 減速器中軸設(shè)計計算.....................................12
3.3.1 軸的主要參數(shù)........................................12
3.3.2 軸的輸入扭矩計算....................................13
3.4 平帶輪傳動參數(shù)設(shè)計.....................................13
3.5 齒輪傳動的設(shè)計計算.....................................14
3.6 主軸的設(shè)計計算.........................................16
3.7 軸承的校核.............................................18
4 操縱部分設(shè)計...............................................18
4.1 速度及株距操縱系統(tǒng).....................................18
4.2 轉(zhuǎn)向離合操縱系統(tǒng).......................................19
5 結(jié)束語.....................................................20
6 參考文獻...................................................20
1 緒論
我國是農(nóng)業(yè)大國,水稻是我國的主要糧食作物,種植面積為 0.29 億公頃.各級技術(shù)人員通過多年的探索總結(jié)出群體質(zhì)量栽培模式。高性能插秧機是與當今世界插秧機設(shè)計、制造技術(shù)接軌的高新技術(shù),他與過去的插秧機有關(guān)很大的區(qū)別,首先他的性能依據(jù)于現(xiàn)代水道群體質(zhì)量栽培管理理論,促進水稻高產(chǎn)穩(wěn)定。高性能插秧機所插的秧苗是通過表準化育秧規(guī)范培育而成的,插秧機所用的秧苗規(guī)格基本一致,插秧機就是為這樣的秧苗而設(shè)計的所以插秧質(zhì)量比過去高的多,這也符合現(xiàn)代前后工序的銜接的工業(yè)化原理,這顯然與形態(tài)千差萬別的手撥有著本質(zhì)的區(qū)別,可以說是先帶農(nóng)業(yè)發(fā)展的必然結(jié)果。
近兩年,農(nóng)場引進新技術(shù),引進了各種品牌的插秧機,其中有久保田、洋馬、井關(guān)這三種。提高水稻的質(zhì)量、產(chǎn)量,插秧環(huán)節(jié)是一個不可不在乎的問題。水稻種植機械化的發(fā)展模式主要取決于水稻種植栽培技術(shù)。縱觀世界水稻發(fā)展,水稻種植技術(shù)主要有2種模式,即水稻直播種植技術(shù)和水稻育秧移栽種植技術(shù)。我國水稻移栽種植模式主要是人工插秧種稻,生產(chǎn)工藝落后,作業(yè)條件艱苦,勞動強度大,作業(yè)效率低。所以,改進生產(chǎn)工藝,改善作業(yè)條件,提高作業(yè)效率是農(nóng)民急需解決的一大難題。
本人的畢業(yè)設(shè)計題目是《手扶插秧機傳動部分設(shè)計》,在大四上學(xué)期跟隨XX老師的設(shè)計小組一起的學(xué)習(xí)專研中,已對洋馬步行式AP4插秧機的工作原理及其特點有了深入的了解,在此基礎(chǔ)上,我開始完成我的畢業(yè)設(shè)計,便以該類型插秧機為原型。我先熟悉產(chǎn)品的工作原理,熟悉各零件的加工工藝,在充分了解產(chǎn)品的基礎(chǔ)上,我確定了設(shè)計思路和總體的方案。先設(shè)計尺寸,對材料的校核計算,但因為時間的關(guān)系,我只是對其傳動部分整體設(shè)計改善。在設(shè)計過程中,我把整個產(chǎn)品每一個部分進行了較為深刻了解,然后分別根據(jù)各自的組成原理,初步設(shè)計零件以及機構(gòu)傳動特點,然后考慮其裝配的要求,力爭小巧,美觀;在鏈輪的設(shè)計中我主要考慮其以前出現(xiàn)的問題點,以及重要部件的加工工藝,熱處理工藝,裝配關(guān)系。此外,還提供了一些和計算相關(guān)的主要的零件圖和洋馬步行式插秧機總裝圖,以保持設(shè)計的完整。
本文所用公式引用及文獻的引用,均來自參考文獻資料,見參考文獻。
洋馬步行式AP4插秧機是雙輪驅(qū)動步行式插秧機,人在機后步行操作,其主要操作系統(tǒng)都在機器后部,用剛絲與各控制部分相連,便于操作,控制機器。苗箱與插植臂也在機器后部,便于機手查看并添加秧苗。為了提高機器的機動性能,減輕重量,洋馬步行式AP4插秧機大大采用了工程塑料(浮板、秧箱、罩蓋等)和鋁合金鑄件(主變速箱、插枝傳動箱、導(dǎo)軌等)。插秧機的發(fā)動機在前部,使機器前后平衡。插秧機的主要技術(shù)特點:一是基本苗、栽插深度、株距等指標可以量化調(diào)節(jié),通過調(diào)節(jié)橫向移動手柄與縱向送秧調(diào)節(jié)手柄來調(diào)整所取小秧塊面積,達到適宜基本苗要求,同時插深也可以通過手柄方便地調(diào)節(jié),能充分滿足農(nóng)藝技術(shù)要求。二是具有液壓仿形系統(tǒng),提高水田作業(yè)穩(wěn)定性。它可以隨著大田表面及硬度層的起伏,不斷調(diào)整機器狀態(tài)保證機器平衡和插深一致。
洋馬步行式AP4插秧機是一種適合于我國水稻產(chǎn)區(qū)廣大經(jīng)濟條件使用的步行式水稻插秧機,洋馬步行式AP4插秧機設(shè)計結(jié)構(gòu)簡單、輕巧,操作簡便,使用安全可靠,工作效率高,油耗低等優(yōu)點,能夠有效地解決傳統(tǒng)手工栽插勞動強度大、栽插時間長、生產(chǎn)成本高,產(chǎn)出效率低等問題。它主要由發(fā)動機、傳動系統(tǒng)、機架及行走系統(tǒng)、液壓仿行及插深控制系統(tǒng)等組成。見圖(1-1)
圖(1-1)
插秧機的技術(shù)參數(shù)如下:
洋馬AP4步行式插秧機
型號名稱
2ZQS-4(AP4型)
機器尺寸
總長(mm)
2190
總寬(mm)
1500
總高(mm)
1034
機身重量(kg)
145
發(fā)動機
型號名稱
MZ175
種類
空氣冷卻OHV四沖程單缸汽油發(fā)動機
排氣量(cc)
171
輸出/轉(zhuǎn)速 kW(PS)min-1
2.6Kw(3.5PS)/3000[最大3.2kW(4.3PS)]
使用燃料
汽車用無鉛汽油
燃料油箱容量(L)
4
啟動方式
手拉式啟動
行走部
機體上下調(diào)節(jié)
液壓式調(diào)節(jié)(手動、自動、連動)
車輪(mm)
橡膠凸緣車輪外徑660
變速檔數(shù)(檔)
前進2(插植1)后退1
插植部
插植方式
曲柄搖桿式
插植行數(shù)(行)
4
插植行距(cm)
30
插植株距(cm)
22、15、12
插植株數(shù)(株/3.3m2)
50.65.75.90(簡易手柄調(diào)節(jié))
插植深度(mm)
15-40(6段調(diào)節(jié))
苗數(shù)
調(diào)節(jié)量
橫向進給(mm)
11(26回),14(20回)
縱向抓?。╩m)
8-17(10段手柄調(diào)節(jié))
秧苗條件
秧苗的種類
幼苗、中苗
葉齡·苗高 (葉)·(cm)
(2.0-4.5)·8-25
預(yù)備用秧苗搭載數(shù)(箱)
3
作業(yè)速度(m/s)
載插:0.38-0.76(0.34-0.68)
道路上:0.72-1.54
后退:0.18-0.36(0.16-0.32)
作業(yè)效率(畝/小時)
—2.09(最大)
2 傳動裝置的整體設(shè)計
2.1 插秧機的基本結(jié)構(gòu)及分類
圖2-1 組織結(jié)構(gòu)圖
上圖是一般插秧機的系統(tǒng)分布圖,而洋馬步行式插秧機是上圖大同小異。
目前,國內(nèi)外較為成熟并普遍使用的插秧機,其工作原理大體相同。發(fā)動機分別將動力傳遞給插秧機和送秧機構(gòu),在兩大機構(gòu)的相互配合下,插秧機機構(gòu)的秧針插入秧塊抓取秧苗,并將其取出下移,當移到設(shè)定的插秧深度時,由插秧機構(gòu)中的插植叉將秧苗從秧針上壓下,完成一個插秧過程。同時,通過浮板和液壓系統(tǒng),控制行走輪與機體的相對位置和浮板與秧針的相對位置,使得插秧深度基本一致。
插秧機通常按操作方式和插秧速度進行分類。按操作方式可分為步行式插秧機和乘坐式插秧機。而步行式插秧機均為普通插秧機;乘坐式插秧機有普通插秧機,也有高速插秧機。
洋馬步行插秧機主要部件具有以下特點:
動力部分:采用MZ175發(fā)動機,性能穩(wěn)定,啟動方便。
插植系統(tǒng):能調(diào)整不同的株距,操作簡單。
行走部分:采用三條船行浮板,可以有效的防止或減少水田行走時產(chǎn)生的
泥巴而沖起已插好的秧苗的弊端。采用鋼圈式包叫膠驅(qū)動輪,在水田行
走時,附著效果好,打滑率低,同時由于輪子很窄,所留輪痕輕微。
2.2 洋馬步行式插秧機工作原理
不同的檔位是依靠主變速箱內(nèi)的不同齒輪相互嚙合來實現(xiàn)的。發(fā)動機輸出的動力經(jīng)過兩級皮帶輪傳入輸入軸--主軸。通過變速桿撥叉帶動雙聯(lián)滑移齒輪 25-32 左右滑移來實現(xiàn)檔位選擇。在道路行走檔時齒輪 25T 和主軸齒輪 10T 相互嚙合,且同時與轉(zhuǎn)向離合器齒輪53T相嚙合;栽插檔時,雙聯(lián)齒輪 22 與 轉(zhuǎn)向離合器齒輪53T相互嚙合,雙聯(lián)齒輪32與主軸齒輪10T嚙合;后退檔時雙聯(lián)齒輪 22 與轉(zhuǎn)向離合器齒輪 53脫合再與退檔齒輪16T 嚙合,而雙聯(lián)齒輪32繼續(xù)與主軸齒輪11嚙合。轉(zhuǎn)向離合軸上的鏈輪10T通過鏈條把傳動傳給車輪上的鏈輪24T,從而帶動車輪前進。
圖 2-2
插秧機能得到不同的株距,是由株距撥叉對株距齒輪撥動產(chǎn)生不同的傳動比,具體是:當撥叉撥動28T使之與株距齒輪25T靠合時,主軸通過齒輪主軸齒輪15T與株距齒輪嚙合帶動株距變速軸轉(zhuǎn)動,株距齒輪14T與插植離合器齒輪33T嚙合,產(chǎn)生220mm的株距;同樣當28T與株距齒輪30T靠合時,產(chǎn)生120mm的株距;而28T撥在中間時,28T便與主軸齒輪12T嚙合,主軸動力傳動株距變速軸,產(chǎn)生150mm的株距。插植離合器軸帶動傳動軸轉(zhuǎn)動并通過錐齒輪使秧爪作插植運動,同時,插植離合器上的錐齒輪把轉(zhuǎn)動傳給動力輸入軸,擺動箱使放秧板做左右的擺動,配合著秧爪的插植運動。
圖 2-3
2.3 洋馬步行式插秧機的傳動原理
洋馬步行式AP4插秧機的動力傳遞如下傳動簡圖: 圖(2-4)
看出插秧機的動力傳遞大致可分為三條路線:一是車輪驅(qū)動和轉(zhuǎn)向路線;二是插植驅(qū)動及株距調(diào)整傳動路線;三是苗箱移動和送秧量調(diào)節(jié)傳動路線。這三條動力傳遞路線想互協(xié)作共同完成插植部插秧機的動作。
3 機械零部件選擇及設(shè)計
3.1 發(fā)動機的選擇
發(fā)動機是一種能量個轉(zhuǎn)換工具,它把燃料燃燒產(chǎn)生的熱能轉(zhuǎn)化成機械能。洋馬步行式AP4插秧機中,它可以說是整個插秧機的心臟,是產(chǎn)生并輸出動力的部件。AP4插秧機采用的是四沖程汽油機。它主要由發(fā)動機缸體、反沖式啟動器、燃油過濾器、空氣濾清器、汽化器、消音器等組成。
插秧機發(fā)動機原始數(shù)據(jù):
發(fā)動機(型號MZ175) 輸出轉(zhuǎn)速3000 r/min
→主軸角速度 ω發(fā) =100πrad/s
類型 4沖程汽油空冷OHV
孔徑x沖程 66x55mm
排量 171cm3
額定功率 3.3/3600 kw/rpm
最大扭矩 9.2/2400 Nm/rpm
燃油箱容量 4.5L
啟動方式 手動
火花塞 NGK BPR4ES
尺寸(長x寬x高) 315x352x370
凈重 16 kg
發(fā)動機主軸經(jīng)皮帶傳動至變速箱主軸,查《機械設(shè)計》課本第176頁表11.1,傳動形式設(shè)為兩級開口平帶傳動,即傳動比 i≤5,取i1=i2=5。
ω發(fā)經(jīng)兩級開口平帶至主軸,有如下:
ω發(fā)=i1i2ω主=100πrad/s
即解得 :ω主=4πrad/s≈12.168 rad/s
(注 :ω主是變速箱主軸的角速度,i1,i2分別是兩級皮帶傳動比。)
3.2 減速器中各主要參數(shù)的確定
設(shè)計傳動齒輪模長:
查閱《機械 設(shè)計》課本第206表12.2,表12.3,表12.4取模長m=2 mm,齒頂高 ha=m=2 mm, 齒根高 hf=1.25m=2.5 mm。
作業(yè)速度(m/s):
道路速度:0.38~0.76 m/s,則車輪角速度ω=0.5758~1.1516rad/s。取栽插固定速度0.5m/s,ω≈0.7576 rad/s。
栽插速度:0.72~1.54 m/s,則車輪角速度ω=1.0909~2.333rad/s。取栽插固定速度1.2m/s,ω≈1.818 rad/s。
后退速度:0.18~0.36 m/s,則車輪角速度ω=0.2727~0.5454rad/s。取栽插固定速度0.2m/s,ω≈0.303 rad/s。
3.2.1 傳動比的分配
ω主變速箱主軸的角速度 :ω主=4πrad/s≈12.168 rad/s。
變速(車輪)機構(gòu):
道路運動 ω主: ω輪=53:19≈2.789 rad/s
栽插運動 ω主: ω輪=x≈5.65 rad/s
后退運動 ω主: ω輪=≈13.8 rad/s
株距變速機構(gòu):
株距(mm)
插植離合器軸角速度(rad/s)
備注(當車輪轉(zhuǎn)1圈)
220
2.2725
3
150
3.002
4.4
120
4.1663
5.5
3.3 減速器中各軸設(shè)計計算
3.3.1 各軸的主要參數(shù)設(shè)計
因為主軸、變速軸和株距變速軸上配合滑移齒輪,所以采用花鍵軸設(shè)計。相對應(yīng)軸如下:
主軸:接皮帶輪
變速軸:
轉(zhuǎn)向離合軸:
株距變速軸:
插植離合軸:
3.3.2 各軸輸入扭矩計算
主軸的轉(zhuǎn)速計算
n主=120r/min
各軸輸入功率計算
P主=Pη1 =2.6x0.8=2.08kw
P變速軸=P主η2=2.08x0.95=1.976kw
P車輪軸=P變速軸η2=1.976x0.95=1.8772kw
主軸輸入扭矩計算
T主=9550P主∕n主=9550×2.08∕120N·m=165.5N·m
3.4 平帶輪傳動參數(shù)設(shè)計
于帶速v30,平帶輪用HT200制造。小帶輪采用整體式結(jié)構(gòu)。
整理帶傳動參數(shù)如表:
小帶輪直徑D1
(mm)
大帶輪直徑D2、
(mm)
傳動比i
50
250
5
平帶設(shè)計
帶輪直徑: D1=50mm ,D2=250mm , Dm===150mm, Δ==100mm
中心距: 取a=1.5(D1+D2) =1.5x300=450mm
帶長: L= πDm+2a+=150π+900+=1393mm
包角: =1800-x600=1800-=153.30 >1500
帶厚: θ≤(1/40~1/30)D1 , θ =0.005D+3=3.25mm
帶截面面積:A===114.3mm2
帶寬: b==35.1mm
軸上載荷: FQ=2x1.8MPa x 114.3x10-6x106sin=399 N
3.5 齒輪傳動的設(shè)計計算
因傳動尺寸無嚴格限制,且為開式傳動,故小齒輪用40Cr鋼,熱處理調(diào)質(zhì)表面淬火,40-50HRC,平均取為45HRC,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,故只進行彎曲疲勞強度計算。
計算步驟如下:
轉(zhuǎn)矩T主 由前計算得 T主 =165.5N.m
齒寬系數(shù)ψd 取ψd =1.0 ψd=1.0
彎曲疲勞極限 由圖 σflim1=735Mpa
σflim2=500Mpa
初步計算的許用彎曲應(yīng)力 [σF1]
[σF1]≈0.7σflim1=0.7×735 [σF1]=514.5Mpa
[σF2]≈0.7σflim2=0.7×500 [σF2] =350Mpa
Am值 取Am=1.45 Am=1.45
初取齒輪齒數(shù) 取小齒輪齒數(shù)z1=10 z1 =10
齒形系數(shù)YFa YFa1 =2.63 YFa2 =2.18
應(yīng)力修正系數(shù)YSA YSA1=1.58
YSA1 =1.81
初步計算的齒輪模數(shù)m m≧Am
=1.96 m=2
校核計算
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=2;
z1=10
z2=25
使用系數(shù)KA 由表 KA=1.25
動載系數(shù)KV 由表 KV=1.1
重合度εɑ εɑ=[1.88-3.2(1/10+1/25)]cosβ
=1.88-3.2()=1.72 εɑ =1.72
重合度系數(shù) Yε Yε=0.25+0.75/εɑ=0.25+ Yε=0.69
齒間載荷分配系數(shù)KFɑ 由表,KFɑ=1/Yε=1/0.69
KFɑ=1.4
齒向載荷分配系數(shù) KFβ b/h=65/(2.25x3)=9.63
KFβ =1.25
載荷系數(shù)K K= KAKVKFβKFa
=1.25×1.1×1.4×1.25 K=2.4
彎曲最小安全系數(shù) SFmin 由表
SFmin=1.2
彎曲壽命系數(shù)YN YN1 =0.92
YN2=0.98
許用彎曲應(yīng)力 [σF] [σF1]==
[σF1]=563Mpa
[σF2]==
[σF2]=475.34Mpa
驗算 σF1=
σF1=452Mpa <[σF1]
σF2=
σF2=367.3Mpa <[σF2]
3.6 主軸的設(shè)計計算
軸材料選用20CrMnMo.主軸的設(shè)計計算步驟如下:
計算項目 計算內(nèi)容 計算結(jié)果
計算軸上載荷:
主軸上載荷,T主=165.5N.m
齒輪作用在軸上載荷:
FT ==22066N
繪制軸的彎扭矩圖,對危險截面進行校核
簡化軸上載荷如圖:
畫軸的彎矩圖,扭矩圖
由彎矩圖、扭矩圖可知B點為危險截面。對B點進行校核計算:
M===675.43Nm
查表得:[σ1b]=215Mpa,[σ01b]=322.2Mpa,[σ-1b]=90Mpa
對于不變的轉(zhuǎn)矩,取 ɑ ==0.27
M,= ==478N·m
所以:
σb===83.43Mpa≤[σ-1b]=90Mpa
滿足強度要求。
3.7 軸承的校核
初選用深溝球軸承,其型號1為6202,其尺寸為d x D x T=15 x 35 x 11。型號2為6004,其尺寸為d x D x T=20 x 42 x 12。
計算軸承的當量動載荷P:
由式:P=XFr+YFa知, 對不承受軸向載荷的深溝球軸承,X=1,Y=0
Fr=
由材料力學(xué)相關(guān)知識:FZ1=3949.2N;FZ2=6753.3N
FY1=2206.4 ;FY2=7218.46N
Fr1= = = 7493.58
Fr2= = = 8952.13
得:P1=Fr1 =7493.58; P2=Fr2 =8952.13
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≥C,=P ; ε為壽命指數(shù)
Lh,為軸承的預(yù)期使用壽命,
查表,取Lh,=6000h
解得 C1,=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。
4 操縱部分設(shè)計
4.1 速度及株距操縱系統(tǒng)
速度和株距的操縱是通過同一根操縱桿的控制來實現(xiàn),如下圖:
原理都是通過操縱桿帶動撥叉撥動滑移齒輪來改變不同的傳動比。
變速撥叉軸焊合由鋼珠、撥叉彈簧定位。作用是撥動變速齒輪Z=25-32滑移,實現(xiàn)不同工作檔位的選擇。
變速撥叉軸焊合
株距變速焊合也是通過鋼珠、撥叉彈簧定位。作用是撥動株距齒輪19T滑移,實現(xiàn)不同株距檔位的選擇。
4.2 轉(zhuǎn)向離合操縱系統(tǒng)
轉(zhuǎn)向撥叉組合:
轉(zhuǎn)向撥叉組合由左、右側(cè)離合器臂焊合、側(cè)離合器撥叉、開口銷、油封組成。作用是通過控制側(cè)離合器的離合,實現(xiàn)插秧機的轉(zhuǎn)向。在直線行駛時左、右側(cè)離合器在彈簧的壓力作用下各自是閉合的,左右車輪按相等的速度前進或后退,轉(zhuǎn)向時通過收緊側(cè)離合器拉線,帶動側(cè)離合器臂焊合轉(zhuǎn)動側(cè)離合器撥叉迫使相應(yīng)的側(cè)離合器牙嵌分離,使一側(cè)的車輪失去動力,停止轉(zhuǎn)動,另一側(cè)車輪繼續(xù)轉(zhuǎn)動實現(xiàn)插秧機的轉(zhuǎn)向。
5 結(jié)束語
本設(shè)計說明書編到這里,心中充滿了無比激動的心情?;叵腴_始選課題時,面對一個個陌生而又充滿了誘惑的課題名,心中是有許多的擔(dān)心。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.我認真的進行畢業(yè)設(shè)計,同樣也是對大學(xué)四年學(xué)業(yè)的有力檢驗。
萬事開頭難。設(shè)計最難的就是跨出的第一步,然而,當工作過程中回望著手準備的材料時,確實是件很鼓勵人的事。設(shè)計最難的地方是各種尺寸的確定,沒有數(shù)據(jù)去畫圖是最費心的事。當沒有具體的標準可尋時,這時便需要加入自己的設(shè)計理念。漫漫回味這一個學(xué)期的心路歷程,一種強大的成就感涌上心頭。這是我準備踏入社會的第一步,或許也是人生的一次勝利。這次難忘的經(jīng)練讓我明白:世上無難事,只怕有心人。同時也鍛煉了我耐心,仔細的能力.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。有時甚至是碰到的一些技術(shù)難題,讓我大費精力去專研,每次通過自己的能力攻破的時候,心中無比爽朗。
最后,我要感謝我的導(dǎo)師--XX老師。是您不斷的教導(dǎo)鼓勵支持我,是您的耐心感動了我。同時,還有給予我?guī)椭睦蠋焸?,本人在此萬分感謝。
6 參考文獻
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手扶插秧機傳動部分設(shè)計劉昆亮,來自機制081班學(xué)號:20080948性格:樂觀,開朗興趣:踢足球座右銘:世界上充滿了美,只是 我們?nèi)鄙侔l(fā)現(xiàn)美的眼睛。設(shè)計課題:手扶插秧機傳動部分設(shè)計指導(dǎo)老師:肖麗萍洋馬步行式插秧機工作原理 不同的檔位是依靠主變速箱內(nèi)的不同齒輪相互嚙合來實現(xiàn)的。發(fā)動機輸出的動力經(jīng)過兩級皮帶輪傳入輸入軸-主軸。通過變速桿撥叉帶動雙聯(lián)滑移齒輪 25-32 左右滑移來實現(xiàn)檔位選擇。在道路行走檔時齒輪 25T 和主軸齒輪 10T 相互嚙合,且同時與轉(zhuǎn)向離合器齒輪53T相嚙合;栽插檔時,雙聯(lián)齒輪 22 與 轉(zhuǎn)向離合器齒輪53T相互嚙合,雙聯(lián)齒輪32與主軸齒輪10T嚙合;后退檔時雙聯(lián)齒輪 22 與轉(zhuǎn)向離合器齒輪 53脫合再與退檔齒輪16T 嚙合,而雙聯(lián)齒輪32繼續(xù)與主軸齒輪11嚙合。轉(zhuǎn)向離合軸上的鏈輪10T通過鏈條把傳動傳給車輪上的鏈輪24T,從而帶動車輪前進。插秧機能得到不同的株距,是由株距撥叉對株距齒輪撥動產(chǎn)生不同的傳動比,具體是:當撥叉撥動28T使之與株距齒輪25T靠合時,主軸通過齒輪主軸齒輪15T與株距齒輪嚙合帶動株距變速軸轉(zhuǎn)動,株距齒輪14T與插植離合器齒輪33T嚙合,產(chǎn)生220mm的株距;同樣當28T與株距齒輪30T靠合時,產(chǎn)生120mm的株距;而28T撥在中間時,28T便與主軸齒輪12T嚙合,主軸動力傳動株距變速軸,產(chǎn)生150mm的株距。插植離合器軸帶動傳動軸轉(zhuǎn)動并通過錐齒輪使秧爪作插植運動,同時,插植離合器上的錐齒輪把轉(zhuǎn)動傳給動力輸入軸,擺動箱使放秧板做左右的擺動,配合著秧爪的插植運動。株距變速操縱和速度操縱都是通過鋼珠、撥叉彈簧定位。作用是撥動株距齒輪19T滑移,實現(xiàn)不同株距檔位的選擇。設(shè)計總結(jié)萬事開頭難。設(shè)計最難的就是跨出的第一步,然而,當工作過程中回望著手準備的材料時,確實是件很鼓勵人的事。設(shè)計最難的地方是各種尺寸的確定,沒有數(shù)據(jù)去畫圖是最費心的事。當沒有具體的標準可尋時,這時便需要加入自己的設(shè)計理念。漫漫回味這一個學(xué)期的心路歷程,一種強大的成就感涌上心頭。這是我準備踏入社會的第一步,或許也是人生的一次勝利。這次難忘的經(jīng)練讓我明白:世上無難事,只怕有心人。同時也鍛煉了我耐心,仔細的能力畢業(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。有時甚至是碰到的一些技術(shù)難題,讓我大費精力去專研,每次通過自己的能力攻破的時候,心中無比爽朗。最后,我要感謝我的導(dǎo)師-肖麗萍老師。是您不斷的教導(dǎo)鼓勵支持我,是您的耐心感動了我。同時,還有給予我?guī)椭睦蠋焸?,本人在此萬分感謝。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).
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