環(huán)保型剪草機設計-手推式草坪除草機設計【三維SW模型】,三維SW模型,環(huán)保,剪草機,設計,手推式,草坪,除草機,三維,SW,模型 環(huán)保型剪草機設計說明書 目 錄 目錄……………………………………………………………………………………………………1 中文摘要………………………………………………………………………………………………3 ABSTRACT………………………………………………………………………………………………3 第1章 緒論………………………………………………………………………………………… 3 第2章 環(huán)保型剪草機的概述 2 2.1 環(huán)保型剪草機的組成 2 2.2 環(huán)保型剪草機的主要機構及其功能 3 第3章 環(huán)保型剪草機方案………………………………………………………………………… 7 3.1環(huán)保剪草機方案布局圖………………………………………………………………………7 3.2環(huán)保剪草機方案的比較與選取………………………………………………………………7 第4章 傳動系統(tǒng)的設計…………………………………………………………………………… 7 4.1齒輪傳動的設計……………………………………………………………………………8 4.2選擇材料，確定和及精度等級……………………………………………11 4.3按接觸強度進行初步設計……………………………………………………………… 11 4.3. 1確定中心距…………………………………………………………………………11 4.3. 2 確定模數(shù)……………………………………………………………………………11 4.3. 3確定齒數(shù)……………………………………………………………………………11 4.3. 4計算主要的幾何尺寸………………………………………………………………12 4.3.5校核齒面接觸強度……………………………………………………………………12 4.3.6校核齒根的強度………………………………………………………………………13 4.3.7齒輪及齒輪副精度的檢驗項目計算……………………………………………………15 4.3.8確定齒厚偏差代號…………………………………………………………………15 4.3.9確定齒輪的三個公差組的檢驗項目及公差值……………………………………15 4.3.10確定齒輪副的檢驗項目與公差值…………………………………………………15 4.3.11 確定齒坯的精度……………………………………………………………………16 4.4軸的設計 …………………………………………………………………………………… 17 4.4.1按扭轉(zhuǎn)強度計算………………………………………………………………………… 17 第5章 滾刀的設計………………………………………………………………………………… 18 5.1滾刀的設計………………………………………………………………………………… 18 5.1.1刀刃的起訖位置…………………………………………………………………………19 5.1.2刀刃的前角………………………………………………………………………………19 5.1.3刀刃的后角……………………………………………………………………………… 21 5.1.4刀刃的刃傾角 …………………………………………………………………………21 5.1.5刀刃上任一點位量上攪碎速度…………………………………………………………23 5.1.6滾刀片的結構……………………………………………………………………………24 第6章 生產(chǎn)能力分析……………………………………………………………………………… 25 6.1滾刀的切割能力…………………………………………………………………………… 25 6.2 環(huán)保型剪草機的生產(chǎn)能力…………………………………………………… 25 6.3功率消耗………………………………………………………………………………………25 第7章 環(huán)保剪草機的三維建?！?….26 設計總結………………………………………………………………………………………………26 鳴謝……………………………………………………………………………………………………26 參考文獻………………………………………………………………………………………………26  摘要 本文論述了草坪機械—環(huán)保型剪草機設計說明書的工作原理、主要技術參數(shù)、傳動系統(tǒng)、典型零件的結構設計及生產(chǎn)能力分析。 課題設計的環(huán)保型剪草機，不僅可以用來剪切公園草坪里的，還可以用來剪切球場，荒地等地方的草，該設備采用無動力驅(qū)動，結構設計合理，能滿足指定場所的剪草需求。。 關鍵詞：環(huán)保型剪草機設計說明書，剪草，無動力驅(qū)動。 ABSTRACT The principle, technical pare-maters, transmiting system and main parts structure of mincing ma-chine were introduced. The productingcapacity was analysed.Keywords Mincing machine Holds plate Cutting blade Transfer auger This paper discusses the meat processing machinery - crusher working principle, main technical parameters, transmission system, the typical parts of the structure design and production capacity analysis. Small twisted paper broken machine for ordinary home, not only can be used for minced meat, can also be used with crushed peanuts, crushed ice, spices and other food, small power requirements, powered by the motor drive, reasonable structure design, can meet the family kitchen generally meat food consisting mainly of minced required. Key words: meat chopper ，reamer 緒 論 中國草坪的發(fā)展最初是從秦漢開始的，據(jù)《史記》記載，司馬相如寫的《上林賦》一文中“布結縷，攢淚荷”就是種植結縷草的意思。據(jù)記載，我國古代大面積使用（建植）草地，是清朝在河北承德“避暑山莊”熱河泉以北的“萬樹園”。歐美等國家的草坪歷史晚于中國， 但發(fā)展較快。二戰(zhàn)后，美國經(jīng)濟發(fā)展迅速，草坪用途進一步擴大，栽培面積急劇上升，揭開了草坪發(fā)展業(yè)的新篇章，許多大學和科研單位開展草坪的研究和育種工作，發(fā)展突飛猛進。國內(nèi)外草坪發(fā)展趨勢及存在問題 目前的草坪品種對管理要求非常嚴格，美國、英國等國家正在培育耐修剪、低矮和抗病性強的品種，至今我們國家還沒有自己生產(chǎn)的較優(yōu)良的冷暖季型草坪種子。由于混播能發(fā)揮草種各自的優(yōu)勢，抵抗各種不利因素，增強抗逆性，因此不同草坪品種混播建植仍是草坪建植的發(fā)展趨勢。近年來，草坪混播的情況越來越多，也出現(xiàn)了很多問題，多數(shù)情況下不能達到所期望的目的。如習慣上采用早熟禾、紫羊茅和多年生黑麥草混播，在強光照地區(qū)以早熟禾為主，遮陰區(qū)以紫羊茅為主。多年生黑麥草可迅速覆蓋地面，起保護作用。但最后結果，常常是以黑麥草為主的草坪，有時草坪中幾乎看不到早熟禾的存在。根據(jù)其工作原理和形式可分為滾刀式、懸刀式和掃雷式三種類型。我國生產(chǎn)剪草機起步較晚,生產(chǎn)企業(yè)規(guī)模普遍較小,產(chǎn)品用途較為單一,均沒有形成規(guī)模批量,所以長期以來,草坪剪草機均以進口為主。據(jù)統(tǒng)計,到1999 年底我國有各種園林機械保有量達10 萬臺,1999 年的剪草機銷售量在3 萬臺左右,其中80 %為進口。 冷季型草夏季病蟲害發(fā)生嚴重，越冬困難，養(yǎng)護管理壓力大，而馬尼拉、結縷草、狗牙根等暖季型草坪具有綠色期短、冬季枯黃等缺點。上海市園林科學研究所提出，采取在暖季型草坪矮生百慕達中追播冷季型草坪一年生黑麥草，充分利用矮生百慕達夏季生長良好和一年生黑麥草冬季生長良好的特點，達到四季長綠的目的。但冷季型草坪一般難與暖季型草坪混播。夏季暖季型草生長良好，并要求施用足夠氮肥，此時冷季型草則處于不適期，一般不可施用過量氮肥。即冷暖季型草坪草從生理上要求有很大差異。多數(shù)情況下，會出現(xiàn)斑塊分離現(xiàn)象。因此，目前許多國家已經(jīng)開始研究以結縷草為主的暖季型草坪，試圖從中培育出綠期長的品種。 我國草坪業(yè)發(fā)展的對策 第一，加強科研投入，制定發(fā)展計劃。目前，我們應用的冷暖季型草種大部分靠進口，這需要大量的資金，因此我們要投入大量資金，有計劃地在某些農(nóng)業(yè)院校和科研機構進行草坪新品種的培育和開發(fā)，生產(chǎn)出自己的優(yōu)良草坪品種。 第二，在發(fā)展不同草種混播的同時，推廣同類草坪草不同品種之間的混播建植草坪形式。對于單一種植，人們所關心的是它的環(huán)境適應性。在同一草坪上，不同位置光照、濕度、溫度、施肥、土壤通氣性和耐踐踏性等變化很大，任何一種草坪草在某一地方超過了適應范圍，草坪的質(zhì)量就會不可避免的下降。由于草種的遺傳特性是異質(zhì)的，因而疾病對單一草坪質(zhì)量有嚴重的影響。為了解決這一問題，最好用草坪種內(nèi)不同品種之間的混播。單一草種不同品種混播時應注意：選擇品種之間在發(fā)病率、潛在發(fā)生病害和對環(huán)境的適應性上要有較大差異的品種；不同品種比例適當；至少要選擇一個適用于當?shù)貤l件的品種，至少要有三種以上的品種參與混合。 第三，加強草坪管理，定期修剪，提高肥水管理質(zhì)量，提高病蟲草害綜合治理水平，使用腐熟有機肥，創(chuàng)造一個有利于草坪草生長而不利于草坪重要有害生物生長發(fā)育的環(huán)境。草坪修剪高度3－5厘米，可以提高草坪的生長勢及其品質(zhì)，以及抗蟲性、抗病性、抗熱性。草坪中的重要雜草，一般較草坪植株高，每次修剪，均可剪除其生長點部分，致使雜草不能正常生長和抽穗結實，雜草的生長力和繁殖率均可明顯下降。修剪是草坪區(qū)別于其它一些植物的特殊要求，草坪業(yè)的迅猛發(fā)展，意味著草坪剪草機械的大量需求。我國綠化環(huán)境使剪草機行業(yè)的迅速發(fā)展勢在必行,為此必須防止為爭奪這一市場一哄而起、在低水平低質(zhì)量上重復建廠生產(chǎn)的不良局面,建議有志于開發(fā)這類產(chǎn)品的企業(yè)聯(lián)合起來開發(fā)產(chǎn)銷對路的產(chǎn)品。在創(chuàng)名牌,上規(guī)模,上品種,上檔次等方面進行有益的競爭,抓住這個商機,充分利用原有的廠房設備,適當?shù)剡M行技術改造進行一定規(guī)模的生產(chǎn)。根據(jù)市場調(diào)查發(fā)現(xiàn)，剪草機必須符合當今人類對環(huán)境保護方面的需求,目前市面上的剪草機大多都是動力引擎這會產(chǎn)生較大的噪音，帶來環(huán)境污染，在辦公和學習的地方，這種動力引擎的剪草機非常不受歡迎。由于動力引擎剪草機有動力裝置，保養(yǎng)維護費用較高;同時動力引擎剪草機主要依靠刀片的高速旋轉(zhuǎn)把草割斷，通過旋轉(zhuǎn)氣流把草排出，因此，對整機的安全性要求較高，操作時也會給工作人員帶來強烈的震動，使得操作很不舒服。雖然動力引擎剪草機剪草效率較高，剪草效果較好，但是價格也較昂貴，對于一般的用戶難以接受。所以研究一種無引擎驅(qū)動且造價較低的剪草機勢在必行！ 第二章環(huán)保型剪草機概述 2.1環(huán)保型剪草機的組成 環(huán)保型剪草機主要由兩兩相互嚙合的齒輪傳動機構、切割機構等組成，如圖2－1所示。 圖2－1 環(huán)保型剪草機設計說明書結構 1.大齒輪 2.小齒輪 3.中間齒輪 4.后小齒輪 5.滾刀 2.2 環(huán)保型剪草機的主要機構及其功能 2.2.1齒輪傳動機構 包括大齒輪1、小齒輪2和傳動軸1。其作用通過后面大輪的轉(zhuǎn)動傳遞動力給前面的滾刀，并使剪草機在人力的作用下能夠向前行駛。 2.2.2切割機構 包括滾刀5,傳動軸3，其作用是整個設備的核心部件，剪草的功能就是靠滾刀來實現(xiàn)的， 滾刀部分設計成上下可調(diào)型，通過絲桿來調(diào)節(jié)滾刀和高低。 第3章 環(huán)保型剪草機方案 3.1環(huán)保剪草機方案布局圖 3.1.1方案布局圖一 圖3－1 環(huán)保型剪草機方案一 1.大齒輪 2.小齒輪 3.中間齒輪 4.小V帶輪 5.滾刀 3.1.2方案布局圖二 1.大齒輪 2.小齒輪 3.中間齒輪 4.后小齒輪 5.滾刀 3.2環(huán)保剪草機方案的比較與選取 綜觀以上兩個方案，我們發(fā)現(xiàn)兩個方案有著彼此的共同點，都是通過人力推動橡膠輪子轉(zhuǎn)動，從而使兩兩互相嚙合的齒輪轉(zhuǎn)動，進而使?jié)L刀轉(zhuǎn)動，但兩個方案也有著彼此的不同，從而剪草精度與平穩(wěn)性方面考利，帶傳動沒有齒輪傳動的傳動效率高，精度好，例外，V帶會嚴重影響經(jīng)過修剪后的草的排除，而用齒輪傳動，就可以很好地避免那些要求，保證設備運轉(zhuǎn)時的平穩(wěn)性。所以，綜上所述，我們選擇方案二為最優(yōu)方案。以下都是圍繞著方案二進行的設計。 第4章 傳動系統(tǒng)的設計 4.1齒輪傳動的設計 由于滾刀只有一種工作轉(zhuǎn)速，則從大齒輪至滾刀的運動路線為定比傳動，其總的傳動比可通過核算各級傳動的速比來得到。 滾刀的轉(zhuǎn)速不易太高，因為人的行走能力有限，況且滾刀剪草也需要一定的時間。當速度達到一定值以后，效率反而下降，且速度過高，滾刀容易磨損，導致剪草的質(zhì)量不高，這樣就容易發(fā)生漏剪現(xiàn)象，因此滾刀的轉(zhuǎn)速一般在10-20r/min比較適宜。在本機選用15r/min。 4.1.1選擇材料，確定和及精度等級。 參考B1表8－3－24和表8－3－25選擇兩齒輪材料為：大、小齒輪均為45#鋼，并經(jīng)調(diào)質(zhì)及表面淬火，齒面硬度為45－50HRc；精度等級為6級。 按硬度下限值，由BI圖8－3－8（d）中的MQ級質(zhì)量指標查得；由B1圖8－3－9（d）中的MQ級質(zhì)量指標查得；。 4.1.2按接觸強度進行初步設計 4.1.3確定中心距a（按B1表8－3－27公式進行設計） 式中：配對材料修正系數(shù)Cm＝1（由B1表8－3－28查?。? 螺旋角系數(shù)Aa＝476（由B1表8－3－29查?。? 載荷系數(shù)K＝1.6（參考B1表8－3－27推薦值） 小齒輪額定轉(zhuǎn)矩 齒寬系數(shù)＝0.4（參考B1表8－3－4推薦值） 齒數(shù)比u=i=2.5 許用接觸應力（參考B1表8－3－27推薦值） 則取a＝80mm 4.1.4 確定模數(shù)m(參考B1表8—3—4推薦表) m=(0.007~4)a=3~10, 取m=5mm 4.1.5確定齒數(shù)z,z 初取螺旋角＝13 z===29.4 取z=72 z=μz=218=36 取z=36 重新確定螺旋角 4.1.6計算主要的幾何尺寸（按B1表8—3—5進行計算） 分度圓的直徑 d=m z/cos=572/cos=360mm d=m z/cos=5*36/cos=180mm 齒頂圓直徑 d= d+2h=45.7+21.5=370mm d= d+2h=114.3+21.5=190mm 端面壓力角 (查B1表8－3－4) 基圓直徑 d= dcos=cos20.292=350mm d= dcos=348cos20.292=165mm 齒頂圓壓力角 =arccos=34.365 = arccos=23.951 端面重合度 =[ z（tg-tg）+ z(tg-tg)] =1.9 齒寬 b=.a＝0.4*80＝32 取b＝50mm；b＝50mm 齒寬系數(shù) ===0.7 縱向重合度 =1.2 當量齒數(shù) ＝31.45 ＝78.628 4.1.7校核齒面接觸強度（按B1表8—3—10校核） 強度條件：[] 計算應力：=ZZZZZ = 式中：名義切向力F===2044N 使用系數(shù) K=1（由B1表8—3—31查?。? 動載系數(shù) =（） 式中 V= A=83.6 B=0.4 C=6.57 =1.2 齒向載荷分布系數(shù) K=1.35（由B1表8—3—32按硬齒面齒輪，裝配時檢修調(diào)整，6級精度K非對稱支稱公式計算） 齒間載荷分配系數(shù) （由B1表8—3—33查取） 節(jié)點區(qū)域系數(shù) =1.5（由B1圖8—3—11查?。? 重合度的系數(shù) （由B1圖8—3—12查?。? 螺旋角系數(shù) （由B1圖8—3—13查?。? 彈性系數(shù) （由B1表8—3—34查?。? 單對齒齒合系數(shù) Z=1 = ＝ ＝245.5MPa 許用應力：[]= 式中：極限應力=1120MPa 最小安全系數(shù)=1.1（由B1表8—3—35查?。? 壽命系數(shù)=0.92（由B1圖8—3—17查?。? 潤滑劑系數(shù)=1.05（由B1圖8—3—19查取，按油粘度等于350） 速度系數(shù)=0.96（按由B1圖8—3—20查取） 粗糙度系數(shù)=0.9（由B1圖8—3—21查?。? 齒面工作硬化系數(shù)=1.03（按齒面硬度45HRC，由B1圖8—3—22查取） 尺寸系數(shù)=1（由B1圖8—3—23查?。? 則： []==826MPa 滿足[] 4.1.8校核齒根的強度（按B1表8—3—30校核） 強度條件：[] 許用應力： =； 式中：齒形系數(shù)=2.61， =2.2（由B1圖8—3—15（a）查取） 應力修正系數(shù)，（由B1圖8—3—16（a）查?。? 重合度系數(shù) =1.9 螺旋角系數(shù)=1.0（由B1圖8—3—14查取） 齒向載荷分布系數(shù)==1.3（其中N=0.94，按B1表8—3—30計算） 齒間載荷分配系數(shù)=1.0（由B1表8—3—33查?。? 則 =94.8MPa ==88.3MPa 許用應力：[]= （按值較小齒輪校核） 式中：極限應力=350MPa 安全系數(shù)=1.25（按B1表8—3—35查?。? 應力修正系數(shù)=2（按B1表8—3—30查取） 壽命系數(shù)=0.9（按B1圖8—3—18查?。? 齒根圓角敏感系數(shù)=0.97（按B1圖8—3—25查?。? 齒根表面狀況系數(shù)=1（按B1圖8—3—26查取） 尺寸系數(shù)=1（按B1圖8—3—24查?。? 則 []= 滿足，〈〈[] 驗算結果安全 4.1.9齒輪及齒輪副精度的檢驗項目計算（大齒輪） 4.1.10確定齒厚偏差代號 確定齒厚偏差代號為：6KL GB10095—88（參考B1表8—3—54查?。? 4.1.11確定齒輪的三個公差組的檢驗項目及公差值（參考B1表8—3—58查?。? 第Ⅰ公差組檢驗切向綜合公差，==0.063+0.009=0.072mm,(按B1表8—3—69計算，由B1表8—3—60，表8—3—59查取)； 第Ⅱ公差組檢驗齒切向綜合公差，=0.6（）=0.6（0.009+0.011）=0.012mm，（按B1表8—3—69計算，由B1表8—3—59查?。?； 第Ⅲ公差組檢驗齒向公差=0.012（由B1表8—3—61查取）。 4.1.12確定齒輪副的檢驗項目與公差值（參考B1表8—3—58選擇） 對齒輪，檢驗公法線長度的偏差。按齒厚偏差的代號KL，根據(jù)表8—3—53的計算式求得齒厚的上偏差=-12=-120.009=-0.108mm，齒厚下偏差=-16=-160.009=-0.144mm；公法線的平均長度上偏差=*cos-0.72sin=-0.108cos-0.72 =-0.110mm,下偏差=cos+0.72sin=-0.144cos+0.720.036sin=-0.126mm；按表8—3—19及其表注說明求得公法線長度=87.652，跨齒數(shù)K=10，則公法線長度偏差可表示為： 對齒輪傳動，檢驗中心距極限偏差，根據(jù)中心距a=80mm，由表查得8—3—65查得=；檢驗接觸斑點，由表8—3—64查得接觸斑點沿齒高不小于40%，沿齒長不小于70%；檢驗齒輪副的切向綜合公差=0.05+0.072=0.125mm（根據(jù)B1表8—3—58的表注3，由B1表8—3—69，B1表8—3—59及B1表8—3—60計算與查?。?；檢驗齒切向綜合公差=0.0228mm （根據(jù)B1表8—3—58的表注3，由B1表8—3—69，B1表8—3—59計算與查取）。 對箱體，檢驗軸線的平行度公差，=0.012mm，=0.006mm（由B1表8—3—63查?。? 4.1.13 確定齒坯的精度要求按B1表8—3—66和8—3—67查取。 根據(jù)大齒輪的功率，確定大輪的孔徑為33mm，其尺寸和形狀公差均為6級，即0.016mm，齒輪的徑向和端面跳動公差為0.014mm。（如圖4-4） 圖4-4 大齒輪簡圖 4.2軸的設計 4.2.1按扭轉(zhuǎn)強度的計算 用實心軸 式中:d－軸的直徑，mm T－軸傳遞的轉(zhuǎn)矩，N.mm P－軸傳遞的額定功率，kw n－軸的轉(zhuǎn)速，r/min []－軸材料的許用切應力，Mpa30 A－系數(shù)，見【1】表4－1－8，這里取120 根據(jù)上面公式計算，齒輪軸的最小直徑d＝30mm；大齒輪軸的最小直徑d＝30mm 依據(jù)結構，設計如圖 圖4－5齒輪軸 第5章 滾刀設計 滾刀的作用是切割草料。它的內(nèi)邊為圓柱狀，刀刃的安裝方向應與滾動旋向相同。滾刀的規(guī)格有2刃、3刃、4刃、6刃、8刃。 滾刀用ZG65 Mn材料制造，淬火硬度為HRC55 - 60，刃口要鋒利，與樣板配合平面應平整、光滑。 5.1滾刀的設計 滾刀的幾何參數(shù)對所絞出草的顆粒度以及產(chǎn)品質(zhì)量有著很大的影響，現(xiàn)對十字刀片的各主要幾何參數(shù)進行設計。 十字刀片如圖(5－1)所示。其每一刃部的攪碎(指切割草的)線速度 分布亦如該圖所示。從圖上可以看出其刃部任一點位置上只有法向速度。 圖5-1 滾刀片示意圖及每一葉刀片上速度分布 其值為： （） 式中：－刀片刃部任一點的線速度m／s； n－刀片的旋轉(zhuǎn)速度rpm； －刀片刃部任一點至旋轉(zhuǎn)中心的距離mm； r－刀刃起始點半徑m m ； R—刀刃終止點半徑mm； 再從任一葉刀片的橫截面上來看 [圖(5-1)A—A截面]，其刃部后角較大，而前角及刃傾角都為零。 因此，該刀片的幾何參數(shù)(角度)不盡合理。故再將以一葉刀片的與網(wǎng)眼扳相接觸的一條刀刃為對象，分析刀片上各參數(shù)的作用及其影響，設計各參數(shù)。 5.1.1刀刃的起訖位置 攪碎時，環(huán)保型剪草機設計說明書的十字刀片作旋轉(zhuǎn)運動。從式[I]可以看出，在轉(zhuǎn)速一定的條件下，刀刃離旋轉(zhuǎn)中心點越遠，則攪碎(指切割草的)線速度越快。并且在螺桿進科速度也一定的條件下，假定攪碎時刀片所消耗的功全部轉(zhuǎn)化為熱能，則任一與網(wǎng)眼板相接觸的刀刃，在單位時間內(nèi)產(chǎn)生的熱量為： 式中：Q－單位時間內(nèi)任一與網(wǎng)眼板相接觸的刀刃切割草所產(chǎn)生的熱量（J／s） F－鉸草時任一與網(wǎng)眼板相接觸的刀刃上的切割力（N）（參見第二部分刀刃的前角式[4]) －任一刀刃切割草的線速度（m／s） 所以，攪碎(切割草)的線速度越快，則所產(chǎn)生的熱量也越大，因此攪碎的線速度不能很高。 根據(jù)經(jīng)驗，我們知道一般攪碎時刀刃切割草的錢速度處在30一90m／min之間最為理想，因此由這些數(shù)據(jù)可估算出刀刃的起訖位置，即刃的起點半徑和終點半徑R。 根據(jù)式[1]得： [3] 我們已知十字刀片得轉(zhuǎn)速n＝326r/min 當時，， ＝30m/min=0.5m/s 當時，， R＝ 圓整后取:r=15mm R=45mm 5.1.2刀刃的前角 當十字刀片攪碎時，其任一與網(wǎng)限板相接觸的刀刃上的受力情況如圖(5-2)所示。 圖5-2 與網(wǎng)眼板相接觸的刀刃的受力分析 根據(jù)圖5-2可知： 其值為： 因為刀刃與網(wǎng)眼板的摩擦力為： 草與前刀面的摩擦力為： 整理得： [4] 式中：F－鉸草時任一與網(wǎng)眼板相接觸的刀刃上的切割力（N） —刀片攪碎時草的剪切抗力（N） －刀刃與網(wǎng)眼板的摩擦系數(shù) －草被剪切時與前刀面的摩擦系數(shù) －刀片的前角（） －網(wǎng)眼板作用于刀刃上的壓力（N） －草被切割時作用于前刀面的壓力（N） 由于 式中：－草的抗剪應力，與草的質(zhì)地有關 －草被剪切的面積，與網(wǎng)眼板的網(wǎng)眼直徑有關 所以與草的質(zhì)地及網(wǎng)眼的直徑有關，故選定網(wǎng)眼板之后，可以看成為常量，故令 。 由于是網(wǎng)眼板作用于刀刃上的壓力，可以看為刀片的預緊壓力，是常量，故令。是刀片切割草時，草對前刀面的壓力與速度v有關，故令。 簡化式[4]得： [5] 從式[5]和式[2]可知，刀刃前角的大小，直接影響著攪碎過程中的切割力，以及切割草時所產(chǎn)生的溫度。 在刀片旋轉(zhuǎn)速度以及螺桿進料速度都一定的情況下，前角大，切割草所需的力和切割草所產(chǎn)生的熱都小；反之，則大。但前角很大時，則因刀具散熱體積小而使切割草時所產(chǎn)生的溫度不能很快冷卻。因此，在一定的條件下，前角有一合理的數(shù)值范圍： 一般?。?草質(zhì)軟取大值，反之取小值) 5.1.3刀刃的后角 刀刃后角的目的：一是減小后刀面與網(wǎng)眼板(包括三眼板)表面的摩擦；二是在前角不變的情況下，增大后角能使刀刃鋒利。 刀片磨損后將使刀刃變鈍，使草在攪碎(切割)過程中變形能增加，同時由于磨損后刀片的后角基本為零，加大了刀片與網(wǎng)眼扳的摩擦，兩者都使攪碎過程中產(chǎn)生的熱量增多。 另外，在同樣的磨鈍標準V B下，后角大的刀片由新用到鈍所磨去的金屬體積較大[如圖5-3所示]。這說明增大后角可提高刀片的耐用度，但同時也帶來的問題是刀片的N B磨損值大(反映在刀體材料的磨損過大這一方面)，并且刀刃極度也有所削弱，故后角也有一合理的數(shù)值范圍： 一般取：(草質(zhì)軟取大值反之取小值) 圖5-3 后角與VB、NB的關系 5.1.4刀刃的刃傾角 從分析由前刀面和后刀面所形成的刀刃來得知刀傾角對刀片性能的影響情況。 在任一葉刀片的法剖面內(nèi)，當把刀刃放大看時，可以把刀刃看成是一段半徑為的圓弧[圖5－4]，由于刀刃有刃傾角，故在線速度方向剖面內(nèi)的刀刃將變成橢圓弧(斜剖刀刃圓柱所得) 圖5-4 刃傾角與刀刃鋒利度 橢圓的長半徑處的曲率半徑，即為刀刃實際純圓半徑。 其關系為： [6] 由此可見，增大刀傾角的絕對值，可減小刀刃的實際鈍圓半徑，這就說明增大刃傾角就可使刀刃變得較為鋒利。 一旦刀刃的起訖半徑r及R確定后，其最大初始刃傾角就可確定了[參見圖5-5]： 圖5-5 [7] 初始刃傾角按下式計算： [見圖5-6] 圖5-6 初始刃傾角計算用示意圖 [8] 式中：r－刀刃起始點半徑(mm)； R－刀刃終止點半徑(mm)； b－葉刀片外端寬度（mm）; －初始刃傾角； 5.1.5刀刃上任一點位量上攪碎速度 由于有了刃傾角，故刀刃上任一點相對于網(wǎng)眼板的速度，將可以分解為垂直于刃的法向速度分量和平行于刃的切向速度 分量。[參見圖5-7] 即： 其值為： 圖5－7 刀刃上任一點的速度示意圖 又因為： 所以： 整理得 （） 式中：－刀刃上任一點位置的法向速度分度m／s； －刀刃上任一點位置的切向速度分量m／s； －刀刃上任一點至刀片旋轉(zhuǎn)中心距離mm； －刀刃的初始刃傾角； －與刀刃相切的圓計算半徑mm； R－刀刃的終點半徑mm； r－刀刃的起點半徑mm； 5.1.6刀片的結構 根據(jù)以上對滾刀各個幾何參數(shù)的分析，得出滾刀的結構圖（圖5-8），此滾刀的特點： 1、 后角取4，刀片的壽命較長； 2、 前角取30，以減小攪碎所需的力及功率； 3、 增加刃傾角，以提高刀刃的鋒利度； 4、 采用全圓弧形的前刀面結構，以改善刀刃的強度； 5、 采用可換式刀片結構，以節(jié)約刀體材料并可選用不同幾何參數(shù)刀片。 圖5－8 2刃、4刃、8刃滾刀 第6章 生產(chǎn)能力分析 6.1滾刀的切割能力 切刀的切割能力，可用下式計算： 式中：F－滾刀切割能力（）； n－滾刀轉(zhuǎn)速（r/min）;326r/min D－擠草樣板外徑（mm）；168mm －孔眼總面積與樣板面積之比，一般取0.3－0.4；取0.4 Z－滾刀刃數(shù)；取 6.2 環(huán)保型剪草機設計說明書的生產(chǎn)能力G 生產(chǎn)能力G（kg/h）： 式中：－被切割1kg物料的面積，其值與孔眼直徑有關（）； A－滾刀切割能力利用系數(shù)，一般為0.7－0.75； 6.3功率消耗N 功率消耗N可用下式計算： (kw) 式中：W－切割1kg物料耗用能量，其值與孔眼有關（kwh/kg）； －傳動效率； 由生產(chǎn)能力計算可知，在N、D一定的條件下，滾刀的刃數(shù)越多，生產(chǎn)能力越大。但是不同刃數(shù)的滾刀應與不同孔徑的擠草樣板相匹配，才能得到較為合理的生產(chǎn)量和功率消耗。在使用能過程中，可根據(jù)附表中推薦的值來選用。 樣板孔徑mm 3 8、10 16 滾刀刃數(shù) 8 4 2 生產(chǎn)能力kg/h 800 1000 1400  第7章 環(huán)保剪草機的三維建模 總結 漫長而又倍感充實的畢業(yè)設計階段即將結束，通過這幾十天的學習，我覺得自己的專業(yè)知識和獨立思考問題的能力有了很大的提高，對我走向社會從事專業(yè)工作有著深遠的影響?，F(xiàn)在談談對本次畢業(yè)設計的認識和體會。 首先，我感觸最深的就是：實踐的重要性。這次設計中我做了許多重復性的工作，耽誤了很多的時間，但是這些重復性的工作卻增強了我的實踐能力和動手能力，積累了設計經(jīng)驗。同時也得到一條經(jīng)驗，搞設計不能只在腦子里想它的結構，必須動手，即使你想的很完美，但是到實際的設計過程時，會遇到許多意不到的問題。 其次，我學會了查閱資料和獨立思考。當開始拿到畢業(yè)設計題目時，心里真的是一點頭緒也沒有，根本不知道從那里下手。在xxx老師的指導下，我開始查閱相關書籍，借鑒他人的經(jīng)驗，結合自己的構想，再利用自己所學過的專業(yè)知識技能，，深入了解了機械傳動原理及機械系統(tǒng)的設計方案。把設計意圖從構想階段變?yōu)榭勺x者付諸生產(chǎn)的實現(xiàn)階段。我發(fā)現(xiàn)每一個設計都是一個創(chuàng)新、修改、完善的過程，在設計的過程中，運用自己所掌握的知識，發(fā)揮自己的想象力來搞好自己的設計，這個過程也是一個學習的過程。這是一個艱辛的過程，很幸運能在劉杰華老師的指導下，邊學邊用，才能按時按量完成規(guī)定的任務。 設計的完成，給了我很大的信心：我完全有能力利用自己所學過的知識和技能完成我并不熟悉的任務。在設計過程我更深切的體會到：獨立自主是關鍵，互協(xié)作更重要。 參考文獻 【1】 吳宗澤主編．機械設計實用手冊．第一版．北京：化學工業(yè)出版社．1999 【2】 濮良貴、紀名剛主編．機械設計．第七版．北京：高等教育出版社．2001 【3】 張裕中主編．食品加工技術裝備．第一版．北京：中國輕工業(yè)出版社．2000 【4】 無錫輕工業(yè)學院、天津輕工業(yè)學院編．食品工廠機械與設備．第二版．北京：輕工業(yè)出版社．1985 【5】 胡繼強主編．食品機械與設備．第一版．北京：中國輕工業(yè)出版社．1999 【6】 李興國主編．食品機械學（下冊）．第一版．四川：四川教育出版社．1992 【7】 中國農(nóng)業(yè)機械化科學研究院編．實用機械設計手冊（下）．北京：中國農(nóng)業(yè)機械出版社．1985 【8】 成大先主編．機械設計手冊（第4卷）．第四版．北京：化學工業(yè)出版社．2002 【9】 [蘇]卡查科夫、馬爾切諾夫著．食品機械制造工藝學．北京：機械工業(yè)出版社．1984 【10】 張萬昌主編．熱加工工業(yè)基礎．第一版．北京:高等教育出版社．1997 【11】 馬曉湘、鐘均祥主編．畫法幾何及機械制圖．第二版．華南理工大學出版社1992 【12】 毛謙德、李振清主編．袖珍機械設計師手冊．第二版．北京：機械工業(yè)出版社．2002 33 Ming Cong and Bo Fang School of Mechanical Engineering, Dalian University of Technology Dalian, 116024, China * This work is supported by national natural science fund #50675027to Ming Cong Abstract - This paper presents a multisensor system for combining measurements from ultrasonic sensors and navigation for robot mowers. The proposed sensing system enables robot mowers to mapping unknown environments. It is important for an autonomous robot mower to explore its surroundings in performing the task of localization and navigation for mowing. Because of the complexity of the environment, one simple kind of sensors is not sufficient for robot mower to accomplish these tasks. We develop a robot mower equipped with DSP TMS320F2812 as its CPU. The sensing system integrates with ultrasonic sensors, infrared sensors, collision sensors, encoders, a temperature sensor and an electronic compass. A method of high accuracy ultrasonic ranging technology based on wavelet transform is reported to improve the measurement precision of ultrasonic sensors. Simulation studies show that the proposed multisensor fusion method is very effective for the navigation of robot mowers. Experimental results indicate that this sensing system based on generalized auto-correlation method for obstacle detection and localization shows great potential for providing a high performance-to-price ratio and robust solution for robot mowers in dynamic working condition. Index Terms - multisensor fusion, ultrasonic sensors, robot mower, mapping, navigation I. INTRODUCTION Lawn mowing is considered by many to be one of the most boring and tiring routine tasks. The environmental robots are needed urgently to perform the task. Some predictions indicate that the robot mowers will be one of the most promising personal robot applications and have substantial market in the world. Therefore, the concept of Intelligent Robot Mower (IRM) had been proposed for the first time in 1997 s annual conference of the OPEI (Outdoor Power Equipment Institute) 1. The robots mainly face to the general families to help the busy people and the hypodynamic old folks save the payments for hiring labours, also remove people from noise, pollen and danger of mowing blade. The robot mowers serve for home care as the outdoor mobile robots, actually kind of intelligent mechatronics devices for environment clean-up 23. The important thing is that the robot mowers are representative of some area-covering environmental robots used not only for indoor floor cleaning as in 4 but also in hazardous environments such as removing landmines, cleaning up radiant points and prospecting for resources etc. The robot mowers get great challenges differing from indoor mobile robots. The robot mowers use sensors to understand environments as well as their real-time states for obstacle avoidance, map building, location and navigation in the whole work area. Because of the complexity of the environment, one simple kind of sensors is not sufficient for robot mower to accomplish these tasks. It is necessary to combine the observed sensor data coming from different sensors to reduce the uncertainties of the robot in any working environment. To merge the information from the various sensors, robust and real-time sensor fusion is required 5. In cases of sensor error or failure, multisensor fusion can also reduce uncertainty in the information and increase its reliability. A sensing system of low cost, low power consumption, high performance is described. The detecting range of ultrasonic sensors is 0.3m5m, they provide good range information. However, uncertainties in ultrasonic sensors caused by the specular reflection from environments make them less attractive. The detecting range of infrared sensors is 0.02m1m, they can detect the obstacles within the ultrasonic sensor s blind zone. In order to satisfy the needs of robot mowers for the low cost and high accuracy ranging technology, the research on the high accuracy ultrasonic ranging technology based on wavelet transform (WT) is reported to improve the measurement precision of ultrasonic sensors. Measurement data gathered from the sensing system are integrated to avoid the robot mower from unknown obstacles and plan an optimum, reliable and realizable plan completely coverage of entire working area. Finally, simulation studies and experimental results show the effectiveness of the sensing system for the navigation, obstacle detection and localization of robot mowers. II. SYSTEM HARDWARE OF IRM The IRM uses DSP TMS320F2812 as its CPU, including four units: vehicle system, cutting system, sensing system and control system. The sensing system is used to collect the external dynamic information of the working environment for obstacle avoidance, map building, navigation and localization. It is also used to detect vehicle system s movement parameters and cutting mechanism s working status. The controller compares the acquired information with the database, and then sends out revisory and accurate command to the robot to perform its tasks. The hardware of the IRM is shown in Fig. 1. Multisensor Fusion and Navigation for Robot Mower* 978-1-4244-1758-2/08/$25.00 2008 IEEE.417Proceedings of the 2007 IEEEInternational Conference on Robotics and BiomimeticsDecember 15 -18, 2007, Sanya, China Fig. 1 Hardware overview of IMR The robot must be physically strong, computationally fast, behaviourally accurate and safety. It should have the ability to perform on its own, and required no human intervention during the whole or most part of the mowing period. The IRM is modularized designed and each unit of the IRM is relatively independent. Modularized design makes the maintenance much easier. Any broken unit of the IRM can be replaced directly without influencing the functions of other units. III. SENSING SYSTEM A. Ultrasonic Sensor Unit Because ultrasonic sensors can provide good range information based on the time of the flight (TOF) principle, mainly due to their simplicity and relatively low cost, they have been widely used in mobile robots for obstacle avoidance, map building and so on. This type of external sensor is very good in obstacles distance measurement. The main lobe of the sensitivity function is contained within an angle of 20 degrees, as shown in Fig. 2 6. A number of tests showed that the range accuracy of the sensors is in the order of 2cm. Fig. 2 Typical intensity distribution of an ultrasonic sensor On IRM, we set up a sensor array which consists of 12 ultrasonic sensors spaced 30 degrees apart. The ultrasonic signals can cover all the space around and satisfy the space requirement about which robot can detect the environmental signals. Classical techniques used in ultrasonic transducers are based on TOF measurement, which calculates the distance of the nearest reflector using the speed of sound in air and the emitted pulse and echo arrival times. The distance d to a reflected object is calculated by () 2dct= (1) where c is the speed of sound, and t is the time-of-flight. The TOF method produces a range value when the echo amplitude first exceeds the threshold level after transmitting, ignoring a second echo from a further reflector. The ultrasonic sensor unit includes a trigger pulse generation unit, a multi-channel selection unit and an echo receiving unit. A sensor interface circuitry designed to send and receive ultrasonic sound pulses catches always the first returning echo. The range data related to an object is considered to be on the conic axes even if it is located off the axes. The ultrasonic wave typically has a frequency between 40 and 180 kHz, and the frequency of the ultrasonic sensors used in the system is 40 kHz. The beam angle is 20 degrees. The 40 kHz PWM pulse is generated by the general-purpose timer unit of DSP. To drive the transmitter effectively and not to bring much vibration, an 8 cycle burst of ultrasound at 40 kHz is sent out once a time. When the ultrasonic pulse is emitted, the sensor will experience “ringing” . Ringing caused by the transmitted pulse can cause the receiver to detect a false echo. This problem is solved by not enabling the capture interrupt of DSP until a delay interval has passed. This means that the ranger can not detect an object whose distance from the sensor is less than half the distance that sound travels during the delay interval. This is the blind zone of the ultrasonic sensor, as shown in Fig. 3. Trigger pulseEmitted signalReceived signalTOFBlind zoneEcho Fig. 3 The sketch map of ultrasonic transmission and reception B. Infrared Sensor Unit and Other Sensors To overcome the ultrasonic sensor s blind zone, infrared sensors are added. The infrared sensors can detect obstacles within 20cm, which patch up the problem caused by the blind zone problem of ultrasonic sensors. This unit has 16 infrared sensors. Each infrared range finder has a conic view of 6 degrees which is the main lobe of the sensitivity function. This sensor has a useful measuring range of a target up to about one meter with high accuracy. A number of tests showed that the range accuracy of the sensors is in the order of lcm. In order to save the DSP s resource, 16 infrared sensors are connected with DSP TMS320F2812 s data interface 418instead of the IO interface. This kind of architecture can also read the sensors status at the same time, ensuring the real-time capability of the system. A sensor interface circuitry designed to send and receive infrared pulses catches always the first retuning echo to process its amplitude. Robot mower works in an outdoor environment, where the temperature changes rapidly. The changing of temperature will affect the speed of sound. Therefore, a temperature sensor is used to guarantee the precision of the ultrasonic sensor. Collision sensor is a group of sensitive swatches, which used to prevent the damage caused by unexpected collision. Because moist environment do harm to the circuit of the IRM, humidity sensors are introduced to detect the humidity of the environment. Although these sensors are not absolutely necessary for an autonomous robot mower, they can provide helpful functions to make the work availability and safety. IV. SENSOR-BASED NAVIGATION A. Mapping As seen in Fig. 4, a reference direction x is defined and the robot coordinates are shown asRx,Ry. By the help of an electronic compass built in on the robot 7, the anglei, which is the ith sensor s angle from the 1st sensor, can be easily measured. Actually if only the angle S (heading angle of the robot) is measured, other sensor angles can be found as iSi=+ (2) where iis the angle to the our world coordinate center. The number of maximum sensor group on the ultrasonic ring is n, and the radius is r (in our system n=12 and r=0.25m). The distance between the origin and the center of the ring is R, and reference angle to the center is. The reference position of the robots center is (Rx,Ry). The distance from the origin to object which is detected by the ith sensor data on the two dimensional plane is callediR. Now letidmdenote measured value which is combined data from the ultrasonic and infrared sensors, for the exact distanceiR. There will be an error i between these values as iiidmd=+. (3) In this work we naturally assume that i is a uniform random variable in the range of (-W, W). Here W denotes the maximum distance measurement error. Here the problem is, givenRx,Ry, r, 12,n ?, and 12,ndm dmdm?, to estimate the coordinates of the occupied cells ixand iy(or equivalently iR) in most efficient way. The equations involving the detected object can be written as 222()cos()()sin()iRiiRiiRxrdyrd=+ (4) 222()2()( cos()sin()iiiiiRRrdrdxy=+ 222()2()cos()iiiRiRRrdrd=+ (5) yxxy RR ?ddO Fig. 4 The robot position on x-y section The equations involving the robot due to the object can be written as 222()cos()()sin()iiiiiiRxrdyrd=+ (6) 2222()2()(cos()sin()iiiiiiiiRxyrdrdxy=+If we define the positions as: 11,TTiniiPp ppx y=?, then we have 222()2() cos(),sin()iiiiiiiRRrdrdyP=+ (7) After the inserting the 2iRin 2R, ()cos()cos(),sin()iiiiiirdRyP+= (8) Here again we have n such equations. And we write them in matrix form imA P= (9) And if we introduce new matrix as ()cos(),sin()iiiiLP= and 0,0=, then (10), can be written as 11112cos()()()cos()()RnRnnnrdmRLpLrdmRLp+ ?=?+ ?Here if we perform the least squares estimate foriP, we obtain 1()()TTlsqiPA AA m= (11) Thus we find the best squares estimate of the positions. B. Simulation Studies Sensor-based navigation has been tested with simulation to shown the usefulness of this sensor fusion method in the two environments respectively as shown in Fig. 5 and Fig. 6. The mower has been primarily tested in a structured laboratory as shown in Fig. 5. Start at (0.3m, 0.5m, 0degree), a virtual 419robot was driven around a virtual square corridor one time. The walls in the artificial environment are denoted by the real map. The entire vehicle is self-contained. It has a maximum travel speed on 0.4 m/s. The laboratory area was surveyed out to a 10cm grid with accuracy better than about 1cm. To extract the mapping, a start and goal points were presented. The robot position and orientation were established by the electronic compass 8. Fig. 5 Data collection and navigation result in structured environment The result in Fig. 5 demonstrates the mapping quality and the usefulness of this sensor fusion method. In the tests, we find that the average error () in estimating the position of the obstacles in the environment was in the range of -0.2, 0.2m. In the simulations we see that ()lsq iPin (11), obtained does not satisfy ()ilsq iRP=which actually should. In the case a better estimate for the positions can be given as ()()()ieilsqilsqiRPPP= (12) In this case, estimate for the angle i does not change but the estimate for distanceiR is scaled to it best estimate. Therefore for the position, the distance estimate iR remains the same as before, while the least squares estimate works only for the anglei . Simulations show that this way produces more accurate results. Fig. 6 The simulation result of wall-following behavior Wall following was selected for the initial problem domain because it is a fairly simple problem to set up and evaluate 9. It also lays the groundwork for more complex problem domains, such as maze traversal, mapping and complete coverage path planning which is used on lawn mowing and vacuuming. The simulation result of wall-following behavior shown in Fig. 6, and the experimental result in Fig. 6 demonstrate that the IRM have the capability to perform its mowing task in unstructured environment. The program of sensor-based navigation simulation in Fig. 5 is given below. Sub Main Dim PI,Fcr,Fct,X_target,Y_target,X,Y As Single Dim X_grid, Y_grid, i, j, C As Integer Dim Frx,Fry,d, dist_targ, rot, Fx, Fy As Single Dim Fcx,Fcy, Rx,Ry As Single PI=3.1415927 Fcr=1 Fct=1 X_target=GetMarkX(0) Y_target=GetMarkY(0) SetCellSize(0,0.1) Set cell size 10 cm x 10 cm SetTimeStep(0.1) Set simulation time step of 0.1 seconds Do Start main loop X=GetMobotX(0) Present mobot coordinates (in meters) Y=GetMobotY(0) X_grid=CoordToGrid(0,X) indexes of cells where the Y_grid=CoordToGrid(0,Y) mobot center is MeasureRange(0,-1,3) Perform a range scan and update the Certainty Grid (max. cell value=3) Frx=0 Fry=0 Each ocuppied cell inside the windows of 33 x 33 cells applies a repulsive force to the mobot. For i=X_grid-16 To X_grid+16 For j=Y_grid-16 To Y_grid+16 C=GetCell(0,i,j) If C0 Then d=Sqr(X_grid-i)2+(Y_grid-j)2) If d0 Then Frx=Frx+Fcr*C/d2*(X_grid-i)/d Fry=Fry+Fcr*C/d2*(Y_grid-j)/d End If End If Next Next dist_targ=Sqr(X-X_target)2+(Y-Y_target)2) Fcx=Fct*(X_target-X)/dist_targ Fcy=Fct*(Y_target-Y)/dist_targ Rx=Frx+Fcx Ry=Fry+Fcy rot=RotationalDiff(0,X+Rx,Y+Ry) shortest rotational difference between current direction of travel and direction of vector R SetSteering(0,0.5,3*rot)mobot turns into the direction of R at constant speed and steering rate proportional to the rotational difference StepForward Loop Until dist_targ0.1 Loop until mobot reaches the target End Sub 420V. ULTRASONIC RANGING TECHNOLOGY BASED ON WT Unfortunately, the practical received multi-echoes has time-varying property and is a typical non-stationary signal because the influence of the environmental complexity and the noise. Furthermore, the noise mixed in the ultrasonic pulse-echo is Non-Gaussian white noise but colored noise, and correlated with the target echo. The TOF method can not be used directly in such conditions. Referencing the generalized correlation method for estimation of time delay 10, we put forward the generalized auto-correlation method for estimation of time-of-flight based on wavelet transform 11 and present in Fig. 7. Fig. 7 Delay estimation of generalized auto-correlation based on WT Where( ) tis the mother wavelet and( )atis the daughter wavelet. The coefficient is the scale (or scaling factor) andis the time displacement. The wavelet transform of the signal( )x tis( )y t. Actually this is a filtering process of the ultrasonic echo using a multitude of bandpass filters of equalQ, which is equivalent to the whitening filter of the generalized correlation method for estimation of time delay, in order to eliminate the input noise which can influence the following processing.( )yyRcan be found as ( ) ( ) ()( ) ( )()yyxxaaRE y t y tRttt= As there has the relationship of Fourier transform between auto-correlation function( )yyR and his power spectrume:2( )( )( )()()( )()yyyyxxxxGF RGaaGa= We obtain the generalized auto-correlation function as Last, the peak values of( )yyRare detected to accomplish the estimation of TOF and calculate the real ultrasonic velocity. Fig. 8 Noisy ultrasonic echo Fig. 9 Denoised echo using WT Fig. 10 Auto-correlation function( )yyR Fig. 11 Peak detection The noisy ultrasonic echo is shown in Fig. 8, and the denoised ultrasonic echo by wavelet transform is shown in Fig. 9. It is obvious that the noise mixed in the ultrasonic echo is effectively eliminated after WT operation. The auto-correlation operation ( )yyRof the denoised ultrasonic echo is shown in Fig. 10. Fig. 11 shows the envelope of( )yyRthrough Hilbert transform. As we can see, if the abscissa of every peak point is determined, the estimation of TOF?ND can be calculated. Considered the attenuation of the ultrasonic echo and the demand of the high precision in practice, only the former four echoes are used to estimate the TOF. The values of the TOF estimation are ?3 , 2 ,2 ,3DDD DDD, which are symmetrical to the x-axis. Using this method, the estimation of the ultrasonic velocity can be calculated. So far, an obstacle detection and localization system has been implemented successfully. By means of above method, an obstacle detection and localization system has been implemented successfully. The generalized auto-correlation method based on wavelet transform is put forward to realize the real-time ultrasonic velocity measurement, and this method can ()11( )( )( )( )22gjjyyyygyyRGedGed=?421eliminate the influence of temperature, humidity and wind on ultrasonic velocity measurements when the robots are working in dynamic condition. And this sensing system based on generalized auto-correlation method shows great potential for providing a robust solution for robot mowers in dynamic working condition. VI. EXPERIMENTAL RESULTS We measure the distance between the robot and plane objects using the ultrasonic sensors. The measured results and the actual distances are shown in TABLE I. TABLE I THE EXPERIMENTAL DATA OF THE ULTRASONIC SENSORS (unit: cm) Actual distance Measured value1 Measured value2 Average error 30 30.62 30.61 2.50% 40 40.70 41.69 1.73% 50 50.64 50.67 1.31% 60 60.73 60.73 1.22% 70 70.81 70.84 1.19% 80 81.09 81.04 1.33% 90 91.10 91.13 1.24% 100 98.82 99.15 1.02% 150 148.24 148.37 1.13% 200 201.85 201.85 0.93% 250 252.71 252.74 1.09% 300 302.52 302.58 0.85% 350 347.