手扶插秧機插植部分設(shè)計
手扶插秧機插植部分設(shè)計,手扶插秧機插植部分設(shè)計,手扶,插秧機,部分,部份,設(shè)計
XX大學(xué)畢業(yè)設(shè)計(論文)任務(wù)書
設(shè)計(論文)
課題名稱
手扶插秧機插植部分設(shè)計
學(xué)生姓名
XX
院(系)
工學(xué)院
專 業(yè)
機械設(shè)計制造及其自動化
指導(dǎo)教師
XX
職 稱
講師
學(xué) 歷
博士
畢業(yè)設(shè)計(論文)要求:
本設(shè)計以洋馬步行式插秧機為原型,設(shè)計插秧機的插植部分,對插秧機的插植臂和送秧箱的整體設(shè)計,傳動齒輪和軸進行設(shè)計計算。
圖紙不少于1.5個A0,設(shè)計說明書字數(shù)不少于4000字。
畢業(yè)設(shè)計(論文)內(nèi)容與技術(shù)參數(shù):
發(fā)動機輸出/轉(zhuǎn)數(shù) KW(PS)min-1 2.6KW (3.5PS)/3000 [最大3.2KW (4.3PS)]
作業(yè)速度:道路速度:0.38~0.76 m/s
栽插速度:0.72~1.54 m/s
后退速度:0.18~0.36 m/s
株距檔位:220mm 、150mm 、120mm
畢業(yè)設(shè)計(論文)工作計劃:
工作時長(9周):
插植系統(tǒng)設(shè)計 1周 確定具體設(shè)計方案以及確定插植臂主軸尺寸 2周
機械制圖 3周 編寫設(shè)計說明書 2周
改進設(shè)計 1周 檢查錯誤 1周
接受任務(wù)日期 20011 年 11月 9日 要求完成日期2012 年 5 月 9 日
學(xué) 生 簽 名 年 月 日
指導(dǎo)教師簽名 年 月 日
院長(主任)簽名 年 月 日
UNIVERSITY
本 科 畢 業(yè) 論 文(設(shè) 計)
題目: 手扶插秧機插植部分設(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: 職 稱:講師
二O一二年 五 月
XX大學(xué)畢業(yè)設(shè)計(論文)任務(wù)書
設(shè)計(論文)
課題名稱
手扶插秧機插植部分設(shè)計
學(xué)生姓名
XX
院(系)
工學(xué)院
專 業(yè)
機械設(shè)計制造及其自動化
指導(dǎo)教師
XX
職 稱
講師
學(xué) 歷
博士
畢業(yè)設(shè)計(論文)要求:
本設(shè)計以洋馬步行式插秧機為原型,設(shè)計插秧機的插植部分,對插秧機的插植臂和送秧箱的整體設(shè)計,傳動齒輪和軸進行設(shè)計計算。
圖紙不少于1.5個A0,設(shè)計說明書字數(shù)不少于4000字。
畢業(yè)設(shè)計(論文)內(nèi)容與技術(shù)參數(shù):
發(fā)動機輸出/轉(zhuǎn)數(shù) KW(PS)min-1 2.6KW (3.5PS)/3000 [最大3.2KW (4.3PS)]
作業(yè)速度:道路速度:0.38~0.76 m/s
栽插速度:0.72~1.54 m/s
后退速度:0.18~0.36 m/s
株距檔位:220mm 、150mm 、120mm
畢業(yè)設(shè)計(論文)工作計劃:
工作時長(9周):
插植系統(tǒng)設(shè)計 1周 確定具體設(shè)計方案以及確定插植臂主軸尺寸 2周
機械制圖 3周 編寫設(shè)計說明書 2周
改進設(shè)計 1周 檢查錯誤 1周
接受任務(wù)日期 20011 年 11月 9日 要求完成日期2012 年 5 月 9 日
學(xué) 生 簽 名 年 月 日
指導(dǎo)教師簽名 年 月 日
院長(主任)簽名 年 月 日
畢業(yè)論文題目
摘 要
隨著農(nóng)業(yè)種植規(guī)?;?,機械化,水稻插秧機在農(nóng)業(yè)機械中占有極為重要的地位,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)。本設(shè)計是基于洋馬AP4步行式插秧機為原型,設(shè)計插秧機的插植部分。為保證水稻栽植的順利進行,栽植運動的插植部分系統(tǒng)設(shè)計至關(guān)重要。本文對插植結(jié)構(gòu)進行結(jié)構(gòu)分析設(shè)計和計算,得到合理的機構(gòu)參數(shù),為插秧機的精確插植設(shè)計提供依據(jù)。
關(guān)鍵詞:插秧機,插植部,設(shè)計,機構(gòu)
The hand transplanter planting design
Abstract:Along with the agriculture planting scale, mechanization, rice transplanting machine in agricultural machinery occupies a very important position, high performance rice transplanter is with the current world rice transplanter design, manufacturing technology integration of high-tech. The design is based on AP4race walking type rice transplanter for prototype, design of rice transplanter transplanting part. In order to ensure the smooth rice planting, planting movement of the planting system design is very important. This paper analyses the structure of planting structure design and the computation, obtains the reasonable parameters for rice transplanter, the precise planting design basis
Keywords:rice transplanter, transplanting, design, mechanism
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目錄
1緒論 - 2 -
1.1插秧機發(fā)展歷史 - 2 -
1.2發(fā)展趨勢 - 2 -
2 插秧機總體介紹 - 3 -
2.1 插秧機總體結(jié)構(gòu)和設(shè)計原理 - 3 -
2.2手扶插秧機的各類參數(shù) - 4 -
2.3 插秧機動力傳送路線 - 7 -
3 插植臂結(jié)構(gòu)設(shè)計與運動原理 - 8 -
3.1 分插運動軌跡和結(jié)構(gòu)參數(shù) - 8 -
3.2插植臂結(jié)構(gòu) - 9 -
4 插植部送秧結(jié)構(gòu) - 11 -
5 校核計算 - 12 -
5.1主軸的設(shè)計計算 - 12 -
5.2 錐齒輪的校核 - 15 -
參考文獻 - 19 -
致謝 - 20 -
1緒論
1.1插秧機發(fā)展歷史
中國傳統(tǒng)的插秧工具秧馬和蒔扶,已有近千年的使用歷史。宋代蘇軾曾作“秧馬歌”,敘說了湖北農(nóng)民使用秧馬的情景。使用蒔扶可以代替手工分秧,并將秧苗梳入泥中定植,直至20世紀50年代,某些地區(qū)仍在使用。中國水稻插秧機的研制工作始于1953年。1956年在蒔扶分秧方式的啟發(fā)下,首次提出群體逐次分格取秧、直接栽插的秧苗分插原理,從而在水稻插秧機的研制上取得了突破,研制出水稻拔取苗移栽的第一代樣機。到1960年,各地推薦生產(chǎn)上使用的人力、畜力插秧機已達21種。1967年,第一臺自走式機動插秧機“東風(fēng)-2S”型通過鑒定定型并投入生產(chǎn),每天可插秧15~20畝。
日本于1898年,發(fā)表第一個水稻插秧機專利;意大利于1915年開始研究拔秧苗的水稻插秧機,至50年代已有拖拉機配套的商品出售,但都由于結(jié)構(gòu)復(fù)雜、造價高,作業(yè)時需用輔助勞力多而未能推廣。日本于60年代研制帶土小苗的栽植技術(shù)和相應(yīng)的水稻插秧機。1966年后,工廠化水稻育秧設(shè)備研制成功,促進了插秧機械化的迅速發(fā)展。
1.2發(fā)展趨勢
插秧機的研究應(yīng)該根據(jù)各國土質(zhì)和人口等地區(qū)因素,因地制宜,發(fā)展適合當?shù)厍闆r的插秧機,此外,插秧機也要向提高作業(yè)效率,提高對秧苗的適應(yīng)性,提高使用操作性能方向發(fā)展。為了克服漏插、漂秧和鉤傷秧等缺陷,今后將通過對送秧、分秧、插秧等工作機構(gòu)的改進與創(chuàng)新,繼續(xù)提高插秧質(zhì)量和對各種秧苗的適應(yīng)性,同時要研制適用于每穴一株雜交水稻秧苗的新型插秧機;研究提高工作裝置的自動化程度,如實現(xiàn)自動裝秧及故障自動停機等的途徑;進一步完善包括育秧在內(nèi)的水稻全套種植機械化體系,提高非插秧季節(jié)水稻插秧機的綜合利用程度。
2 插秧機總體介紹
2.1 插秧機總體結(jié)構(gòu)和設(shè)計原理
類型
水稻插秧機按適應(yīng)秧苗的狀態(tài)分拔洗苗型、帶土苗型和兩用型。按動力分為人力插秧機和機動插秧機兩類。人力插秧機采用間歇插秧方式,插秧動作在機器停歇狀態(tài)下進行,插秧動作結(jié)束后,手拉機器移動一個株距,再次進行插秧動作。機動插秧機采用連續(xù)插秧方式,在機器行進過程中完成分秧、插秧動作。機動插秧機又分手扶自走式、乘坐自走式和拖拉機懸掛式等類型。按分秧和插秧機構(gòu)的運動特征可分為縱分滾動直插式、縱分擺動直插式和橫分擺動直插式。滾動直插和擺動直插是指取秧器定位桿件分別由作圓周運動和作往復(fù)運動的機構(gòu)驅(qū)動,并在軌跡控制機構(gòu)的控制下完成分秧、插秧動作,取秧器在插秧段的運動軌跡接近與地面垂直,使形成的插孔較小,秧苗直立性和穩(wěn)定性好。滾動直插只用于機動插秧機。
原理和構(gòu)造
插秧機的工作過程,因結(jié)構(gòu)不同而各有差異,但基本流程大致相同。其“群體逐次分格取秧直接栽插”原理為:秧苗以群體狀態(tài)整齊放入秧箱,隨秧箱作橫向移動,使取秧器逐次分格取走一定數(shù)量的秧苗,在插秧軌跡控制機構(gòu)作用下,按農(nóng)藝要求將秧苗插入泥土中,取秧器再按一定軌跡回至秧箱取秧。
各種插秧機栽插部分的組成基本相同:人力插秧機由秧箱、分插秧機構(gòu)、機架和浮體(船板)等組成,自走式機動插秧機還設(shè)有動力驅(qū)動、行走裝置、送秧機構(gòu)等部分。
秧箱
主要功能是承載秧苗,并與送秧機構(gòu)、分插秧機構(gòu)配合,完成送秧和分秧作業(yè)。主要有箱體、箱架、秧門(包括秧簾)和秧刷等組成。在橫向移箱機構(gòu)作用下,使秧箱橫向移動,從而使秧苗移向秧門,以配合取秧器有規(guī)律的取秧栽插。
分插秧機構(gòu)
是水稻插秧機的主要工作部件,由取秧器及其驅(qū)動機構(gòu)和軌跡控制機構(gòu)組成。取秧器在驅(qū)動機構(gòu)的驅(qū)動和軌跡控制機構(gòu)的控制下,按照一定的軌跡從秧箱中分取一定數(shù)量的秧苗并將其插入土中,然后返回原始位置開始下一次循環(huán)動作。按分秧動作,有橫分和縱分兩種。①橫分取秧器有適于拔取苗栽插的秧夾和適于帶土苗栽插的切扒式秧爪,兩者根據(jù)需要可互換使用。秧夾由活動夾片和固定夾片構(gòu)成,其張開度根據(jù)秧苗的粗細和秧苗數(shù)量進行調(diào)節(jié);切扒式秧爪帶有脫秧片,使帶土秧苗從秧爪上順利脫出。②縱分取秧器有適于拔取苗栽插的梳式秧爪,適于帶土苗栽插的有裝上脫秧器的梳式秧爪,或采用筷子式秧爪。梳式秧爪在分秧過程中對秧苗有分理作用;筷子式秧爪在插入帶土秧苗中取秧時,由推秧片把帶土苗強制推出。
一定數(shù)量的秧夾或秧爪按規(guī)定行距配置在秧夾(或秧爪)排上。在滾動直插式插秧機上,一般有2~4個秧爪排與作圓周運動的分插輪轉(zhuǎn)臂鉸接相連;在擺動直插式插秧機上。一般是一個秧爪排同作往復(fù)擺動的搖臂鉸接相連,也可將一個取秧器直接裝在一組曲柄連桿機構(gòu)的連桿上,進行分組驅(qū)動。在多數(shù)插秧機上,取秧器的運動軌跡除由驅(qū)動機構(gòu)控制外,還受軌跡控制機構(gòu)的控制。常用的軌跡控制機構(gòu)有導(dǎo)槽、滑道、凸輪、行星齒輪和四桿機構(gòu)等,與各種驅(qū)動機構(gòu)配合組成各種類型的分插秧機構(gòu)。
送秧機構(gòu)
包括縱向送秧機構(gòu)和橫向送秧機構(gòu),其作用是按時、定量地把秧苗送到秧門處,使秧爪每次獲得需要的秧苗。①縱向送秧機構(gòu)的送秧方向同機器行進方向一致,有重力送秧和強制送秧兩種。重力送秧是利用壓秧板和秧苗自身的重量,使秧苗隨時貼靠在秧門處,常用于人力插秧機,其送秧能力隨秧箱形式及秧箱內(nèi)秧苗數(shù)量多少而變化,因而送秧均勻度較差。強制送秧是由縱向送秧機構(gòu)定期推送秧苗,其送秧能力強,又分整體送秧和對準送秧兩種。前者主要用于帶土苗。當秧箱橫向移動至兩端極限位置時,將整體秧苗往秧門推送一次;后者主要用于拔取苗,取秧器每取秧一次,即相應(yīng)的送秧一次,送秧寬度等于取秧器的取秧寬度。②橫向送秧機構(gòu)的送秧方向同機器行進方向垂直,都采用移動秧箱法,因而又稱移箱機構(gòu)。按其移動方式又分為間歇移箱和連續(xù)移箱:間歇移箱機構(gòu)用于拔取苗和帶土苗,其特點是在秧爪分取秧苗時停止移箱,以利于秧爪梳理分秧。連續(xù)式移箱機構(gòu)是在作業(yè)中使秧箱作橫向連續(xù)等速運動,移至兩端極限位置后自動換向,因而在分秧階段,秧爪和秧箱相對移動,適用于帶土苗。
機架
是插秧機各部件和機構(gòu)安裝的基礎(chǔ),要求剛性好、重量輕。按機架與船板連接方式可分為整體式和鉸接式兩種:整體式是用插深調(diào)節(jié)器調(diào)整插深后,把機架和船板鎖定;鉸接式是機架和船板僅靠插鎖連接,在作業(yè)過程中插秧深度隨泥腳深淺而變化。
行走裝置和承載浮體
人力插秧機以船板為承載浮體,支承機器的全部重量,一般不設(shè)行走裝置,作業(yè)時由人力牽引,使船板在泥面滑行。自走式機動插秧機的行走裝置包括驅(qū)動輪、導(dǎo)向輪和陸地運輸輪等。驅(qū)動輪多采用葉片式鐵輪,并有獨輪驅(qū)動、兩輪驅(qū)動和四輪驅(qū)動等類型,其承載浮體有整式船板和間隔配置的浮板兩種類型,支承機器的部分重量。中國的乘坐自走式機動插秧機多采用前面一個驅(qū)動輪、后面為整體式船板的獨輪驅(qū)動方式,陸地運輸時加裝2個尾輪,具有結(jié)構(gòu)簡單、行駛阻力小、操縱輕便、行駛直線性和轉(zhuǎn)彎靠行性能好等特點。日本則采用前面兩個導(dǎo)向輪、后面兩個驅(qū)動輪加3~4塊浮板的驅(qū)動方式,或前、后4個驅(qū)動輪加浮板的驅(qū)動方式。日本的手扶自走式機動插秧機多采用兩個驅(qū)動輪加浮板的驅(qū)動方式。 動力驅(qū)動部分及其他 自走式機動插秧機的動力驅(qū)動部分包括發(fā)動機、 變速傳動裝置,以及轉(zhuǎn)向、換檔、離合等操縱機構(gòu)。此外還有各種調(diào)節(jié)裝置、監(jiān)測訊號裝置、牽引架、插秧手座位、秧籃及遮陽裝置等輔助部分。
2.2手扶插秧機的各類參數(shù)
洋馬AP4步行式插秧機是雙輪驅(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。
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,操作靈便,使用安全可靠,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(2-1)
洋馬AP4步行式插秧機各類參數(shù)
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)
表2-1
2.3 插秧機動力傳送路線
1-2
圖2-2
3 插植臂結(jié)構(gòu)設(shè)計與運動原理
3.1 分插運動軌跡和結(jié)構(gòu)參數(shù)
(1)分插結(jié)構(gòu):用以完成分秧和插秧的工作部件稱為秧爪,而控制秧爪運動軌跡的機構(gòu)稱為分插結(jié)構(gòu)。插秧機工作時秧爪尖相對于插秧機機架的軌跡稱為秧爪靜軌跡(即機器不前進時的軌跡)或者稱為相對運動軌跡,而秧爪相對于地面的軌跡稱為秧爪動軌跡(即秧爪正常前進時的軌跡)或者稱為絕對運動軌跡。秧爪運動軌跡可以分為分秧、運秧、插秧、出土、回程段5個階段。如圖2-1所示(圖中主要參數(shù)見表2-1),秧爪進入秧箱取秧走過的軌跡D1D2稱分秧段,分秧之后到插秧之前的軌跡D2D3稱運秧段,插秧時秧爪尖的動軌跡D3`D4`稱插秧段,插秧之后秧爪尖到離開地面的運動軌跡D4`D5`稱為出土段,出土之后回到取秧之前的靜軌跡D5D1稱為回程段。
圖3-1 插秧機插秧軌跡
名稱
代號
參數(shù)
名稱
代號
參數(shù)
曲柄(OA)
R2
35mm
B點調(diào)節(jié)長槽長度
BL
30 mm
連桿(AC)
R4
90mm
調(diào)節(jié)長槽與X軸夾角
RB
16°
搖桿(BC)
R5
90mm
秧門角點M坐標值
XM
YM
-202 mm
30 mm
秧爪尖與A點距離(AD)
L
190 mm
秧門與X軸夾角
RM
138°
AD與連桿夾角
R
163.17°
秧爪與連桿夾角
RD
50°
最大取秧量B點坐標值
X0
Y0
72 mm
80 mm
推秧時曲柄與連桿夾角
RT
50.87°
曲柄中心安裝高度
H0
120 mm
3寸穴距機器前進速度
V0
-0.36m/s
表2-1
3.2插植臂結(jié)構(gòu)
插秧機共設(shè)有四個插植臂,插植臂間隔距離相等,呈左右對稱狀態(tài)。插植臂主要由曲軸臂、插植臂殼體、推桿、秧爪、彈簧、插植臂上蓋、凸輪等組成(如圖3-2所示)。作用是從苗箱上切取一定面積的秧塊并栽插到田里。
如圖所示,由曲柄臂、從動臂、插植臂殼體和機架組成四連桿機構(gòu),相互鉸接處都安裝有軸承,保證轉(zhuǎn)動靈活,工作平穩(wěn),運動軌跡準確。曲軸臂固定在插植臂軸上,當動力通過插植臂軸傳入時,曲軸臂做圓周運動,從動臂做往復(fù)運動,而插植臂殼體(即連桿)做平面內(nèi)的復(fù)雜運動,與插植臂殼體固定為一個構(gòu)件的秧爪按預(yù)訂的軌跡(連桿曲線)進入秧門取秧后插入地面,當秧爪插入地面的時由凸輪和推桿手柄脫離接觸,在彈簧的壓力下推桿使秧苗脫離秧爪而栽植于農(nóng)田。
分析插植臂結(jié)構(gòu)的工作過程,主要是看分秧段和插秧段。分秧段影響分秧的質(zhì)與量,分秧時秧爪與秧苗間夾角一般較小,均在30°以內(nèi),進入秧門D1點距秧門口的高度稱為取秧高度,應(yīng)大于苗根土厚10mm;在D2點秧爪分秧速度一般在1.0m/s以上,最佳范圍為1.5~2m/s便于利索分秧;擰動調(diào)節(jié)按鈕可以改變從動臂B點連接在鏈箱后蓋長槽中的位置可改變分秧段軌跡而調(diào)整取秧量大小,插秧段主要討論運動軌跡,由于D3D5插孔大小,時有利于提高插秧的穩(wěn)定性,而推秧的相位與軌跡影響秧苗插秧時的直立性。在插秧段秧爪速度應(yīng)急劇減小,依靠慣性作用(此時秧爪加速度最大)而提高插秧直立性與穩(wěn)定性。
圖3-2 插植臂結(jié)構(gòu)
4 插植部送秧結(jié)構(gòu)
插植部送秧箱:把秧苗定時輸送到秧爪取秧部位的結(jié)構(gòu)稱為送秧結(jié)構(gòu)。它由橫向送秧結(jié)構(gòu)和縱向送秧結(jié)構(gòu)組成。它的主要作用是將由齒輪箱傳遞過來的動力傳遞給送秧機構(gòu),實現(xiàn)橫、縱向送秧。
圖4-1
橫向送秧結(jié)構(gòu)的作用是使秧爪能在秧箱的工作幅度內(nèi)依次均勻取秧,使秧箱連同秧苗做整體移動,它主要由插植動力輸入軸、輸入鏈輪、導(dǎo)向螺桿,橫送軸,縱送軸,端蓋等構(gòu)成(圖3-1)。插植臂軸通過鏈條帶動輸入鏈輪轉(zhuǎn)動,鏈輪通過一對直齒輪將動力傳動給導(dǎo)向螺桿,插入導(dǎo)向螺桿內(nèi)的螺旋槽的導(dǎo)塊沿著螺旋槽斜面移動從而帶動橫送軸左右運動,隨之完成了橫向送秧運動。
縱向送秧結(jié)構(gòu):一般縱向送秧結(jié)構(gòu)安裝在秧箱底部。主動凸輪安裝在導(dǎo)向螺桿上,主動凸輪間歇性地帶動從動凸輪,使固定在送秧軸上的抬把隨軸轉(zhuǎn)動秧箱下的棘爪而推動棘輪帶動送秧星輪轉(zhuǎn)動一定的角度完成縱向整體送秧,送秧完畢,棘爪與抬把依靠扭簧復(fù)位。
5 校核計算
5.1主軸的設(shè)計計算
軸的結(jié)構(gòu)設(shè)計:(圖5-1)
圖5-1
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
初算軸徑d 由表,C=112
=112×
=16.72mm 取d=20mm
初步計算軸上各段長度 軸承選6001,寬度B=12mm
計算軸上載荷:
由前計算:
鏈輪作用軸上載荷=1552N,T=110N·m
齒輪作用在軸上載荷:
=1100N,=110N·m
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:
其中, =1552N,T==110N·m, ==1100×cos=1033.6N
==3458×=376.3N
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===78.6Nm
查表得:=215Mpa,=102.5Mpa,=60Mpa
對于不變的轉(zhuǎn)矩,取
=114.4N.m
所以:
=14.3Mpa=60Mpa
滿足強度要求。
。
5.2 錐齒輪的校核
(1)選用直齒錐齒輪傳動,7級精度。
已知輸入功率P1=1.4 kw ;
錐齒輪轉(zhuǎn)速n=80r/min ;
齒數(shù)比u=i1=1
條件:動力機為電動機,工作平穩(wěn),傳動不逆向。
(2)材料選擇
1軸上的小齒輪材料為40cr(調(diào)質(zhì)),硬度為241~286HB,取硬度為260HB,嚙合的中齒輪材料為45#鋼(調(diào)質(zhì)),硬度229~286HB,硬度取為240HB。
(3) 計算
(I) 按齒面接觸強度設(shè)計
轉(zhuǎn)矩 T1=257040 n/mm
齒寬系數(shù) Ψd=1.0
解除疲勞強度 σHlim1= 710 MPa
σHlim2= 580 Mpa
初步計算的許用接觸應(yīng)力 [σH1]=0.9σHlim1=639
[σH2]=0.9σHlim2=522
取Ad=83
初步計算齒輪直徑 d1≥83=35.7
取d=40
齒寬b b=Ψdd1=3.63 mm
計算圓周速度
V =πdn1/(60×1000)
= 3.14×40×80/(60×1000)
=1.79 m/s
齒數(shù)與模數(shù) 初取齒數(shù)z=11 m=d1/z1=2
載荷系數(shù)
根據(jù)v=1.79 m/s , 選擇齒輪為7級精度,
由機械設(shè)計查得動載系數(shù) KV =1.25.
使用系數(shù) KA=1.5
Ft=2T1/d1=6112 N
=79.6 n/mm <100 n/mm
由表查得:KHα=KFα=1.3 ;
載荷系數(shù)K=1.5*1.25*1.2*1.2=2.7
ε=[1.88-3.2(1/z1+1/z2)]
=1.68
Zε==0.88
彈性系數(shù)ZE1=189
節(jié)點區(qū)域系數(shù)ZH=2.5
接觸最小安全系數(shù) SHmin=1.05
由公式計算應(yīng)力循環(huán)次數(shù)
N1 = 60 n1jLh
= 60×80×1×4000= 1.92×107
N2 =0.24×108
接觸壽命系數(shù) ZN ZN1=1.15 ZN2=1.25
許用接觸應(yīng)力[σH] : [σH1] =777.6MPa
[σH2]= 690MPa
驗算σH=ZEZHZε=570 MPa <[σH2]
計算結(jié)果表明,接觸疲勞強度較為合適,齒輪尺寸無需調(diào)整
確定傳動主要尺寸
d=m*z=2*11=22
(II)按齒根彎曲強度設(shè)計
重合度Yε=0.25+0.75/ε=0.7
齒向載荷分配系數(shù) KFα=1/Yε=1.43 KFβ=1.35
載荷系數(shù) K=KAKVKFαKFβ=3.62
[σF]1= Mpa
[σF]2= Mpa
查取齒形系數(shù)
YFa1=2.4 YFa2=2.1
應(yīng)力修正系數(shù) YSa1=1.63 YSa2=1.75
彎曲疲勞極限 σFmin1=600 MPa σFmin2=450 MPa
最小安全系數(shù) SFmin=1.25
由公式計算應(yīng)力循環(huán)次數(shù)
N1 = 60 n1jLh
= 60×485×1×4000= 1.2×108
N2 =0.24×108
彎曲壽命系數(shù) YN1=0.85 YN2=0.92
尺寸系數(shù) FX=1.0
許用彎曲應(yīng)力[σF] [σF1]==408 MPa
[σF2]==331.2 MPa
驗算 σF1==102.6 MPa <[σF1]
σF2=σF1=98.5 MPa <[σF2]
所以滿足要求
(III)確定齒輪的齒形參數(shù)
標準錐齒輪幾何尺寸:
① 分度圓直徑d :
d=mz=2×11=22 mm
② 齒頂高ha
ha=ha*m=1×2=2mm
③ 齒根高 hf=(ha*+c*)m=(1+0.25)×2=2.5 mm
④ 齒全高 h=ha+hf =(2ha*+c*)m=2+2.5=4.5 mm
(IV)齒輪結(jié)構(gòu)
對于小齒輪,其齒數(shù)較少,分度圓直徑與軸的直徑相差不是很大,可以采用整體式設(shè)計。
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12.李寶筏.農(nóng)業(yè)機械學(xué).北京.中國農(nóng)業(yè)出版社.2003年
致謝
本次畢業(yè)設(shè)計,是在XX老師導(dǎo)下完成的,通過本次設(shè)計,不僅檢驗了我大學(xué)四年來知識積累的程度,而且豐富了我在實際設(shè)計中經(jīng)驗的累積,更是對我設(shè)計思想的一次全面升華。在設(shè)計過程中,本著認真刻苦的態(tài)度去學(xué)習(xí)設(shè)計的步驟、方法、以及經(jīng)驗,但是由于該設(shè)計許多方面的細節(jié)問題涉及面太廣,而本人知識面和能力都極其有限,同時由于時間倉促,因而不能科學(xué)詳盡地做出正確的選擇與判斷。所以設(shè)計中難免出現(xiàn)很多錯誤。雖然有這些不足和遺憾,但是總的來說,基本上完成了插秧機的插植部設(shè)計和一些零部件設(shè)計,成功的完成了老師布置的任務(wù)。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。
在這一個學(xué)期的設(shè)計過程中,我們得到了有豐富工作經(jīng)驗的指導(dǎo)老師肖老師的大力支持和幫助,在設(shè)計過程中他們不知疲倦、不厭其煩的給我們分析和講解,而且也給我灌輸了一些先進的設(shè)計方法和設(shè)計理念,使我大受裨益。在此,我忠心地向XX老師表示感謝。同時,在設(shè)計過程中,我也得到很多同學(xué)的支持和幫助,在此,我一同表示最忠誠的感謝。
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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