调度绞车的说明书.doc

JD-1型调度绞车设计【8张CAD图纸和说明书】

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目    录


1 概述……………………………………………………………………………………………1

  1.1调度绞车的简介…………………………………………………………………………1

  1.2用途及适用范围…………………………………………………………………………1

  1.3 本文所做的基本工作……………………………………………………………………2

2 调度绞车的总体设计…………………………………………………………………………2

  2.1设计参数…………………………………………………………………………………2

  2.2结构特征与工作原理……………………………………………………………………2

  2.3 选择电动机………………………………………………………………………………3

  2.3.1电动机输出功率的计算………………………………………………………………3

  2.3.2确定电动机的型号……………………………………………………………………4

3 滚筒及其部件的设计…………………………………………………………………………4

  3.1 钢丝绳直径的确定及滚筒直径的确定…………………………………………………4

  3.1.1钢丝绳的选择…………………………………………………………………………4

  3.1.2滚筒参数的确定………………………………………………………………………5

  3.1.3卷筒钢丝绳运动参数的计算…………………………………………………………6

4 行星齿轮传动概论……………………………………………………………………………6

  4.1行星齿轮传动的定义……………………………………………………………………6

  4.2行星齿轮传动符号………………………………………………………………………7

  4.3行星齿轮传动的特点……………………………………………………………………7

5 减速器设计……………………………………………………………………………………9

  5.1总传动比及传动比分配…………………………………………………………………9

  5.1.1总传动比………………………………………………………………………………9

  5.1.2传动比分配……………………………………………………………………………9

  5.2高速级计算………………………………………………………………………………9

  5.2.1配齿计算………………………………………………………………………………9

  5.2.2 按接触强度初算a-g传动的中心距和模数…………………………………………9

  5.2.3几何尺寸计算…………………………………………………………………………10

  5.2.4 验算a-g传动的接触强度和弯曲强度………………………………………………11

  5.2.5根据接触强度计算来确定内齿轮材料………………………………………………16

  5.2.6 g-b传动的弯曲强度验算……………………………………………………………17

  5.3低速级计算………………………………………………………………………………19

  5.3.1配齿计算………………………………………………………………………………19

  5.3.2按接触强度初算b-g传动的中心距和模数…………………………………………19

  5.3.3几何尺寸计算…………………………………………………………………………20

  5.3.4验算b-g传动的接触强度和弯曲强度………………………………………………21

  5.3.5根据接触强度计算来确定内齿轮材料………………………………………………26

  5.3.6 g-b传动的弯曲强度验算……………………………………………………………27

  5.4传动装置运动参数计算…………………………………………………………………29

6传动轴的设计计算……………………………………………………………………………30

  6.1计算作用在齿轮上的力…………………………………………………………………30

  6.2初步估算轴的直径………………………………………………………………………30

  6.3轴的结构设计……………………………………………………………………………30

  6.3.1确定轴的结构方案……………………………………………………………………31

  6.3.2确定各轴段直径和长度………………………………………………………………31

  6.3.3确定轴承及齿轮作用力位置…………………………………………………………31

  6.4绘制轴的弯矩图和扭矩图………………………………………………………………31

  6.5轴的计算简图……………………………………………………………………………33

  6.6按弯矩合成强度校核轴的强度…………………………………………………………34

7滚动轴承的选择与寿命计算…………………………………………………………………34

  7.1基本概念及术语…………………………………………………………………………34

  7.2轴承类型选择……………………………………………………………………………35

  7.3按额定动载荷选择轴承…………………………………………………………………35

8键的选择与强度验算…………………………………………………………………………36

  8.1电机轴与中心轮联接键的选择与验算…………………………………………………37

  8.1.1键的选择………………………………………………………………………………37

  8.1.2键的验算………………………………………………………………………………37

  8.2 主轴(滚筒轴)与行星架联接键的选择与验算………………………………………38

  8.2.1键的选择………………………………………………………………………………38

  8.2.2 键的验算……………………………………………………………………………38

  8.3 行星架与滚筒联接键的选择与验算…………………………………………………38

  8.3.1 键的选择……………………………………………………………………………38

  8.3.2 键的验算……………………………………………………………………………38

9 制动器的设计计算…………………………………………………………………………39

  9.1制动器的作用与要求……………………………………………………………………39

  9.1.1 制动器的作用:………………………………………………………………………39

  9.1.2 制动器的要求:………………………………………………………………………39

  9.2 制动器的类型比较与选择……………………………………………………………39

  9.2.1制动器的类型有:……………………………………………………………………39

  9.2.2 制动器的选择………………………………………………………………………39

9.3 外抱带式制动器结构…………………………………………………………………40

  9.4 外抱带式制动器的几何参数计算……………………………………………………40

10 结构设计……………………………………………………………………………………49

  10.1 行星齿轮传动的均载机构……………………………………………………………49

  10.1.1 均载机构的类型和特点……………………………………………………………49

  10.1.2 行星轮间载荷分布不均匀性分析…………………………………………………49

  10.1.3 行星轮间载荷分布均匀的措施……………………………………………………51

  10.2 行星轮的结构及支承结构……………………………………………………………52

10.2.1 行星轮的结构………………………………………………………………………52

  10.2.2 行星轮的支承结构…………………………………………………………………54

11 主要零件的技术要求………………………………………………………………………55

  11.1 对齿轮的要求…………………………………………………………………………55

  11.1.1 齿轮精度……………………………………………………………………………55

  11.1.2 对行星轮制造方面的几点要求……………………………………………………56

  11.1.3 齿轮材料和热处理要求……………………………………………………………56

12 绞车的安装及安装调试……………………………………………………………………56

  12.1 绞车的安装……………………………………………………………………………56

  12.2 绞车安装调试…………………………………………………………………………56

13 使用与操作…………………………………………………………………………………57

  13.1 一般要求………………………………………………………………………………57

  13.2 操作前注意事项………………………………………………………………………57

  13.3 操作要求和操作方法…………………………………………………………………57

14 安全保护……………………………………………………………………………………58

15 维护与保养…………………………………………………………………………………58

16 可能发生的故障及消除方法………………………………………………………………59

17 绞车的润滑…………………………………………………………………………………59

小结……………………………………………………………………………………………61

参考文献………………………………………………………………………………………62

附录……………………………………………………………………………………………63

翻译部分

英文原文……………………………………………………………………………………64

中文译文……………………………………………………………………………………70

致谢……………………………………………………………………………………………74

1 概 述

1.1调度绞车的简介

调度绞车是通过两级行星轮系及所采用的浮动机构完成绞车的减速和传动。通过控制电机的正反转及操纵两个刹车闸的不同刹紧状态实现绞车卷筒的正转、反转和停转,从而实现对重物的牵引、下放和停止三种工作状态。深度指示器通过指示器的齿轮与卷筒上内齿轮的啮合带动与指示器相联的丝杠的旋转,达到显示深度的目的。绞车内部各转动部分均采用滚动轴承,运转灵活。绞车是用卷筒缠绕钢丝绳或链条以提升或牵引重物的轻小型起重设备(见起重机械),又称卷扬机。绞车可以单独使用,也可作为起重、筑路和矿井提升等机械中的组成部件,因操作简单、绕绳量大、移置方便而广泛应用。

调度绞车是矿山生产系统中最常用的机电设备。绞车在工作过程中普遍存在的一个问题就是钢丝绳在绞车滚筒上缠绕不均,出现咬绳、压绳等现象。尤其是使用了一段时间后的旧钢丝绳,严重时钢丝绳只集中缠绕在滚筒的一侧进而跳出滚筒导致重大事故,对于牵引距离较长的绞车这个问题尤其突出。调度绞车的工作往往是间歇性的,当完成一次牵引任务绳段载荷去掉后,绳头呈自由状态,钢丝绳会因自身弹力作用使缠绕在滚筒上的钢丝绳松圈而出现乱绳现象,同样会影响绞车的正常工作。针对小绞车提升运输中出现的上述问题,研制开发适用于平巷以及巷道起伏。

调度绞车护绳装置,属于矿山用调度绞车装置技术领域。以往绞车仅在滚筒后部设置护绳板,操作人员违章处理容易发生钢丝绳缠伤操作人员事故。该实用新型的技术方案为:支架上设置有轴套、上滑套管和下滑套管;上护绳架的垂直架在上滑套管内,其水平架上套有上滑转轮;下护绳架的垂直架在下滑套管内,其水平架上套有下滑转轮;弹簧一端固定在下护绳架上,其另一端固定在支架上;支架下端固定在铁板固定座上;上护罩两端分别连接轴套和护绳板。它的优点是:该装置有效的解决了绞车滚筒的部分封闭和缠绳质量差引起的安全问题,在一定程度上减少了绞车钢丝绳跑偏、乱绳等故障的发生。

绞车有手动和电动两类。手动绞车的手柄回转的传动机构上装有停止器(棘轮和棘爪),可使重物保持在需要的位置。装配或提升重物用的手动绞车还应设置安全手柄和制动器。手动绞车一般用在起重量小、设施条件较差或无电源的地方。

电动绞车广泛用于工作繁重和所需牵引力较大的场所。单卷筒电动绞车的电动机经减速器带动卷筒,电动机与减速器输入轴之间装有制动器。为适应提升、牵引和回转等作业的需要,还有双卷筒和多卷筒装置的绞车。

例如,安装在直升机上的救援设备,主要功用是将人或物吊起、放下,自有动力,可控制,直升机在保持高度悬停时,通过绞车手的控制可收放钢索将人或物吊起放下。绞车的电器设备具有防爆性能,可用于煤尘及瓦斯的矿井中。

绞车的运输方式可选用火车或汽车托运。可采用包装箱或敞车托运。若敞车托运应有防雨和固定设施,以防受潮湿和碰撞磕伤绞车。

????绞车贮存应存放在干燥的无腐蚀性气体的库房内,露天存放应有防潮、防雨、防锈设施。以防绞车部件及面漆受损。

1.2用途及适用范围

矿用调度绞车性能特点:具有隔爆性能、设计合理、操作方便用途和特点。

JD系列调度绞车,主要用于煤矿井下和其他矿山在倾角度小于30度的巷道中拖运矿车及其它辅助搬运工作,也可用于回采工作面和掘进工作面装载站上调度编组矿车。本绞车严禁用于提升和载人。

JD型绞车均用行星齿轮传动,绞车具有结构紧凑、刚性好、效率高、安装移动方便、起动平稳、操作灵活、制动可靠、噪音低等特点。绞车的电气设备具有防爆性能,可用于有煤尘及瓦斯的矿井。

?JD型调度绞车的电气设备有两种,一种为防爆,另一种为非防爆的,前一种可用于有煤尘及瓦斯的矿井中。

绞车的电机具有防爆性能,其他配套电器设备由用户自备,但必须选用

上个月在有效期内的《矿用产品安全标志证书》的产品,以适用在有瓦斯(甲烷)及煤尘爆炸危险的矿井中使用。

使用环境和工作条件

1)环境温度为;环境相对湿度不超过;海拔高度以下。

2)周围空气中的甲烷、煤尘、硫化氢和二氧化碳等不得超过《煤矿安全规程》中所规定的安全含量。

1.3本文所做的基本工作

1)设计完成总体装配图设计;

2)设计完成主减速器装配图设计;

3)完成主要传动组件、零件的工作图设计;

4)编写主要零件的加工工艺;

5)编写完成整体设计计算说明书。



2 调度绞车的总体设计

2.1设计参数

最大牵引力:;容绳量:

平均速度:

2.2结构特征与工作原理

绞车由下列主要部分组成。电动机、卷筒、行星齿轮传动装置、刹车装置和机座。

绞车在结构上采用两级行星齿轮传动,分别布置在主轴的两端,主轴贯穿滚筒,左端支承在左支架上,右端支承在右支架上,电动机采用法兰盘固定在左支架上。


内容简介:
International Journal of Plant Engineering and Management V0112 No4 December 2007A Method for Incipient Fault Diagnosis of Roller BearingsFilter and Hilbert TransformZENG Qinghu,qw Ji,lg,LIU Guan-junCollege of Mechatronic Engineering and Automation,National University ofDefense Technology,Changsha 410073,PRChinaAbstract:Noise is the biggest obstacle that makes the incipient丘ult diagnosis results of roller bearingsincipient如ult of roller bearings based on the Wavelet Trans-扣m Correlation Filter and Hilbert Transform WritSare picked印加m the roller bearingsFirst,the weak扣ult information features如ult vibration signals妙琊e of a denoising characteristic of them Correlation Filter as the preprocessing of the Hilbert Envelope AnalysisThen,讯order to get知uh features frequency,de-noised wavelet of high scales which represent highfrequency signal were analyzed by Hilbert Envelope Spectrum AnalysisThe simulation signals and diagnosing examples analysis results reveal that the proposed method is more effective than the method ofdirect wavelet coefficientsHilbert Transform in denoising and clarifying roller bearing incipient知uhKey words:wavelet correlation Filter,Hilbea transform,envelope spectrum,fault diagnosis,rollerbearings1 IntroductionRoller bearings are frequently applied components in the vast majority of rotating machinesTheirrunning quality influences the working performance of equipmentAt present,the generally usedmethods for diagnosing roller bearing fault include FFvr spectrum analysis and high frequency demodulation analysis,but the two methods are deficientThe reasons are:(1)beating fault vibration sig-nals usually have unstable characteristics;(2)the feature information of roller bearing incipientfault is weak and the working condition is full of noise;feature information is inundated with noiseand difficulty identifiedSo how to pick up fault feature information and how to increase signal-tonoise ratio are the key technologies for diagnosing roller bearing incipient faultWavelet analysis came forth in the 1980sSince then,people began to use wavelet analysis to dealwith vibration signals and achieved some favorable effects卜31Almost all methods use WaveletTransform(WT)or Wavelet Pocket Translation(WPT)to pick up fault characteristics directly,which were not ideal when the working condition is full of strong noiseThe reason is that fault sig-nals are inundated with noise in each frequency channelThe Wavelet Transform Correlation Filter(WTCF)is based on the fact that sharp edges have large signals over many wavelet scales and noiseReceived 1 August 2007万方数据A Method for Incipient Fault Diagnosis of Roller Bearings Based on the WaveletTmnsform Correlation Filter and Hilbert Tmnsform 193will die out swiftly with scale;the direct spatial correlation of wavelet coefficients at several adjacentscales sharpens and enhances edges and significant features while suppressing noise and small sharpfeatures;edges and significant features can be obtained from the noise,and noise is removed basedon threshold inspection;signal-to-noise ratio of wavelet coefficients of WTCF is much higher thanthat of wavelet coefficients of WTIn this papera new method of diagnosing incipient fault of rollerbearings based on WTCF and Hilbert Transform is proposedFirst,the weak fault information features are picked up from the roller beating fault vibration signals by use of a de-noising characteristicof the WTCF as the preprocessing of the Hilbert Envelope AnalysisThen,in order to get fault fea-turo frequency,denoised wavelet coefficients of high scales which represent a high frequency signalis analyzed by the Hilbert Envelope SpectrumThe simulation signals and diagnosing examples anal-ysis results reveal that the proposed method is more effective than the method of direct wavelet coef6cients-Hilbert Transform in denoising and clarifying roller bearing incipient fault2 Wavelet transfotin correlation filterThe de-noising idea of the Wavelet Transform Correlation Filter(WTCF)41 is based on the fact thatsharp edges have large signals over many wavelet scales and noise will die out swiftly with scale;thedirect spatial correlation of wavelet coefficients at several adjacent scales sharpens and enhances edges and significant features while suppressing noise and small sharp features;edges and significantfeatures can be obtained from the noise and noise is removed based on threshold inspectionSignal-tonoise ratio of wavelet coefficients of WTCF is much higher than that of wavelet coefficients of WTThe WTCF have easily implemented and robust characteristics,and it can be as a signal processingtool applied to pick up incipient fault features of mechanical equipmentWe are using the directspatial correlation Corrl(m,玮)of wavelet transform contents at several adjacent scales to accuratelydetect the locations of edges or other significant features1一lCorrl(m,n)=I-Y(m+f,n), 厅=1,2,N (I)#0Where N is the point number of a discrete signal,n is the translation index,m is the scale index,Ydenotes tlle wavelet transform data o“,l is the number of scales involved in the direct multiplicationmMl+1,and M is the total number at scalesUsually。we select l=2The presence of edgesor other significant features in a localized region of the signal allows the noisy background to be removedThe direct spatial correlation of edge-detection data over several scales sharpens and enhances major edges while suppressing noise and small sharp featuresIn this paper,the proposed a1gorithm makes use of the correlation characteristics to pick up significant features from the noiseThe algorithm is described briefly as follows:the filtered data is referred to as Yf,the initializationsof all elements are zero(I)Compute the correlation Corr2(m,n)for every wavelet scale m to obtain enhanced significantfeatures and suppressed noise(2)Rescale the power ofCorr2(m,n)to that of】,(m,n)and getNew Corr2(m,New Corr2(m,n)=Corr2(m,n)n)(2)万方数据194 International Journal of Plant Engineering and Management V0112 No4 December 2007Where PY(m、=PCorr2(m)=Y(m,17,)2 (3)Corr2(rn,昂)2 (4)PY(m)is the mth scale wavelet coefficients and PCorr2(m)is the mth power of Corr2(m,n)(3)If INew Corr2(m,n)IIY(m,n)I,we accept the point as an edgePass Y(m,It)to rf,and reset y(m,乃)and Corr2(m,n)to 0Otherwise,we assume y(m,n)is produced by noiseand then retain y(m,n)and Corr2(m,n)(4)Return to(1),repeat(2)and(3)until the power ofy(m,n)is nearly equal to the thresholdratio th(m)which is correlated with some reference noise power at the mth wavelet scaleThis procedure of power normalization,data value comparison,and edgebe iterated many times until the power of un-extracted data points in y(some reference noise power at the mth wavelet scale561On the start of the process,it isnoise will be extracted鹪edgesinformation extraction canm,n)is nearly equal tonecessary to estimate the reference noiseIn fact,we find that too muchthrough experiment analysis,to avoid this,we multiply i l,(m,n)I bya weight A(m)31 and impose that only when 1New Cbrr2(m,n)IA(m)Iy(m,It)I cail we extractr(m,n)鸥edgesThe detailed content of reference noise estimation refers to literature63 The method of diagnosing incipient fault of roller bearings based on the wave-let transform correlation filter and Hilbert transformHigh frequency scales wavelet coefficients acquired by WTCF denoising can not only divide mutatedvibration signals of roller bearing fault,but more important,it keeps the time information,which re-Sects the repetitive frequency and their changing rules and includes roller bearing fault information。“In order to get fault information effectively,it needs to do a Hilbert Transform on high fre-quency scales wavelet coefficients,and then to do Envelope Spectrum AnalysisIfd()is the wavelet coe蚯cient of one scale,and the hilbert Transform ofd(t)isci(t):Hi d(t)-上r业dt1T J*t-r(5)And the envelope signal of wavelet coefficient d(t)isb(t)=d2(t)+ci2(t) (6)All fault characteristic frequencies of roller bearings are low compared with the sample frequency;low frequency spectrum analysis on Hilbert Envelope Signals of denoised wavelet coefficients is nec-essary to improve the envelope spectrum differentiate rateWhen directly do low frequency spectrumanalysis on discrete vibration signals笫(n),菇(n)is necessarily re-sampledFor example,in orderto process 8 times spectrum analysis,firstly,a new data sequence名(m)is reformed by the datapoint which is sampled from茗(n)every other 8 points,and then frequency analysis of彳(m)isdoneThe relation between石(m)and并(n)is:(m)=戈(8m) m=I,2,膨 (7)When we do a low frequency spectrum analysis on the Hilbert Envelope Signal of wavelet coefficientd(t),it is necessary to resample wavelet coefficient d(t),but the resample rule is different from。万方数据A Method for Incipient Fault Diagnosis of Roller Bearings Based on the WaveletTransform Correlation Filter and Hilbert Transfornl 195the aforementioned rule of discrete vibration signal resampleBecause every time a decomposed resuh of wavelet transform is obtained by resampling one point from two points,the sample frequencydecreases by one halfFurthermore,resample frequency will decrease by the rate of 2一along withthe augment of scale J,so when we do a spectrum analysis on the Hilbert Envelope Signal of everyscale wavelet coefficient,the resample interval needs to decrease by the rate of 2一。along with theaugment of scale JFor example,when we do 8 times spectrum analysis on the Hilbert Envelope Sig-nal of wavelet coefficient dl(I),the resample interval is 4 points in the dl layerIn this paper,theHilhert Envelope Signal of high frequency scales wavelet coefficient dt(t),which is denoised byWTCF,is re-sampled based on the aforementioned resample rule,and then we do a power spectrumanalysisThe process for diagnosing incipient fault of rollerbearings based on WTCF and Hilbert Transformis divided into two phases(shown in Figure 1):(1)Based on the denoising idea of WaveletTransform Correlation Filter(WTCF),the directspatial correlation of wavelet coefficients at sever-al adjacent scales sharpens and enhances edgesand significant features while suppressing noiseand small sharp featuresEdges and significantfeatures can be obtained from the noise and noiseis removed based on threshold inspection,SignaltoNoise of wavelet coefficients of W-ICF is muchHigII signal-tonoise wavelet coefficients which arede-noised by WTCFlHigh frequency scales wavelet coefficient吐(,)isprocessed by Hilbert transformlLow frequency spectrum analysis on Hilbert envelopesignal ofwavelet coefficienthigher than that of the wavelet coefficients Figure l The flow chart of fault diagnosis method basedof WT on WrcF and Hilbert transform(2)High frequency scales wavelet coefficient dl(t),which is de-noised by WTCF,is processed byHilbert Transform Envelope Spectrum Analysis,and then we can get the feature frequency of thefault4 Simulation analysisThe analyzed data are obtained as follows:(1)The impulse train of 120 Hz imitates passing vibration,which has a single fault point;(2)A single harmonic of 3000 Hz with an exponential decay imitatesthe natural frequency excited is added;(3)Two low component frequencies of 20 Hz and 130 Hz imitate factors such as unbalance,misalignment,mechanical looseness etc,are added;(4)Strong whiteGaussian noise is added to imitate environmental disturbancesSample frequency is 16384 HzFigure 2(a)presents the original vibration signal and the fault frequency is 1 20 HzThe fault 8ig-nal is inundated with noiseFigure 2(b)presents the envelope spectrum analysis of a direct waveletcoefficient-Hilbert Transform,there is no means to judge whether the fault existsFigure 2(c)shows the envelope spectrum analysis of the WTCFHilbea Transform;the fault frequency 1 20 Hzand its higher harmonics are clearly observed万方数据196 International Journal of Plant Engineering and Management V0112 No4 December 20075 Analysis of diagnosis example fIn order to validate the validity and practica-吾bility of the proposed method based on WTCF星and Hilbert Transform in diagnosing the incip-墨ient fault of a roller bearing,several mainfaults of roller bearings testbed are analyzedTester and test data come from USA Case e吕Western Reserve University electric engineer-吾ing lab91In the tester。threephase indue善嚣tion motors whose power is 15 kW is joined稍tll a power meter and a torque sensor by oneself-calibration coupling,to drive fansDatais gathered by the vibration acceleration sell-o80r which is a vertically fixed shell of the sup-童porting beating of the induction motors export-童shaftSimulating three running states of roller罾beatings:(1)outer race slight fault;(2)in、ner race slight fault;(3)ball slight fault,andthe defect size is 018 mmIn the three running states,the work frequency of bearingf is30 Hz,outer race fault feature frequency工u1ris 916 Hz,inner race fault feature frequencyf。,is 1484 Hz,and ball fault feature frequency五棚is 1 196 HzSampling point is 4096,samplingfrequency is 12 kHzTime field wave shape of three incipient weakfaults are shown in Figure 3;we know from Figure 3 that the incipient fault signal is very weakand basically inundated with noise;it is difficultto distinguish the existence of fault and fault feature frequency,especially as the ball fault iscompletely inundated with noiseFigure 4 shows the envelope spectrum analysis ofthe WTCFHilbert Transform5O0 500 1000 1500 2000 2500 3000 3500 4000Sample point(a)Original vibration signalFrequency(Hz)(b)The envelope spectrum analysis ofdirectwavelet coefncientHilbert TransformFrequency(Hz)(c)The envelope spectrum analysis ofWTCFHilbert TransforrnFigure 2 Simulation vibration signal analysis30一)曼25詈0拿一25O5005(a)Outer race fault(b)Inner lace fault2048Data pointN(c)BalI faultFigure 3 Time field wave shape of originalvibration signalWhen there is outer race fault,Figure 4(a)presents the envelope spectrum analysis of the WTCFHilbert Transform,there are distinct spectrum lines in the outer race fault feature frequency fom,(916Hz)and its hi。gh frequenciesWhen there is inner race fault,Figure 4(b)illustrates the envelope spectrum analysis of the WTCF万方数据A Method for Incipient Fault Diagnosis of Roller Bearings Ba8ed on the WaveJetTmnafo珊Conel8tion Filter and Hilbert Tmndorm 197一Hilbert Tran8fo肌;there are distinct spectmm lines in the inner race fault feature fi。(1484 nz)叭dwork frequency f(30 Hz)of the bearingsWhen there is ball fauIt,Figure 4(c)shows the envelope spectrum analysis of the WTCF-HilbenTransfo珊:there are distinct spectrum lines in the ball fault feature fb。lI(1 1 96 nz)FigIlle 5 shows the envelope spectrum analysis of direct wavelet coefficient-HilbertTransformfromFigure 5(a)删d(b),we know that when there are outer racefaults and inner race faults,the meh。od c眦diagnolse the existence of fault,but the amplitude of fault frequency is not distinctand the di-agnosis e讹ct is not good,when there is ball fault;the envelope spectrum analY81sof dlrect w8VeletcoefficientHilbert Tran8f0眦can not diagnose the existence of fault as shown in Figure 5(c)p 10。暑05O0,6吖吕q已 O3=L宣0016O08Frequency(az)(a)Outer race faultP邑名量Eg1O050 0OFrequency(Hz)(b)Inner race faultFrequency(Hz)(C)Ball faultFigure 4 The envelope spectrum analysis ofWTCFHiIberr TransformO603OFrequency(Hz)(a)Outer race fault0016O080Frequency(Hz)(b)Inner race faultFrequency(Hz)(C)Ball faultOFigure 5 The envelope spectrum analysis of directwavelet coemeientHilbert Transform6 ConclusiOIISWhen there are ineipient faults of roller bearings,very weak fault feature signals are often inundatedwith vib眦ion signals and noise,the de-noising of the vibration signal is a main approach ot diagnosing ineipient fauh of roiler bearingsIn this paper,an approach of diagnosing incipient fault of roller bearin98 i8 Proposed ba8ed 0n the Wavelet Transform Correlation Filter and Hilbert TransformFirstthe weak fault infomation features are picked up from the roller bearings fault vibration signal8r0J二I一i一疋k卫一等皇11Qg_sIIl一。口君II岛暑一IIIo口暑11dlIl一乙叠一u口暑II口暑万方数据198 International Journal of Plant Engineering and Management V0112 No4 December 2007by use of a de-noising characteristic of the Wavelet Correlation Filter as the preprocessing of the Hil-bert Envelope Analysis;Then,in order to get fault features frequency,de-noised wavelet coefficients of high scales which represent a high frequency signal is analyzed by the Hilbert EnvelopeSpectrumThe simulation signals and diagnosing examples analysis results reveal that the proposedmethod iS more effective than the method of direct wavelet eoefficients。Hilbert Transform in de-noising and clarifying incipient faultReferences1XXHe,et a1,An application of continuous wavelet transform to扣ult diagnosis of roller bear-ingsMechanical Science and Technology,V0120,No7,PP571574,2001(In Chinese)2QYFu,et a1,Extraction offailure character signal of roller bearings by waveletChineseJournal of Mechanical Engineering,V0137,No2,PP3033,2001(In Chinese)3LLWang,Ea咖知ult diagnosis of the roller beadngs using wavelet transformationChineseJournal of Applied Mechanics,V0116,No2,PP95一100,1999(In Chinese)4LZCheng,The theory and application of waveletBeijing:Science Press,2004(In Chinese)5YXXu,BWJohn and MH Denis,et a1,Wavelet transform domain filters:a spatiallyIEEE Transon Image Processing,V013,No6,PP747758,19946 QPan,LZhang,GZDai,et a1,Two de-noising methods by wavelet transformIEEETrans on Signal Processing,V0147,No2,PP34013406,19997ZMZhang,et a1s如in roller bearings,Application of the envelope spectrum of wavelet coefficients to向ult diagno-Journal of Vibration Engineering,V011 1,No。1,PP6569,1998(In Chinese)8NGNikolaou,Rolling element bearing fault diagnosis using wavelet pa
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