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  • 共振频率与固有频率

    2011-11-22 21:31:51
    关于共振频率与固有频率的讨论,可为大家做参考啊
  • 本征频率有时也称为特征频率,固有频率,本振频率等,是一个或一组能够以纯正弦或余弦三角函数的角度参数表示的频率参数,是表表示所研究对象内在属性的一种参数。...
    本征频率有时也称为特征频率,固有频率,本振频率等
    ,是一个或一组能够以纯正弦或余弦三角函数的角度参数表示的频率参数,是表表示所研究对象内在属性的一种参数。
    展开全文
  • 研究结果表明:调整环的质量对定子纵向振动扭转振动的固有频率的影响程度相同,但调整环在定子上的位置对纵向振动的固有频率的影响程度有较大差异。当改变调整环在定子上的位置,纵向振动一阶固有频率的变化很小,...
  • 当正弦激励电压频率等于LC串联电路固有频率的1/N( N=2,3,4…)时,RLC串联回路中也会产生电磁固有振荡。通过改变电路参数,观察对非共振固有振荡波形产生的影响情况。分析研究了非共振固有振荡不是谐波共振,它谐波...
  • 采煤机工作是由于受到外界荷载影响发生受迫振动,当驱动频率与固有频率接近时会发生共振,影响采煤机的使用寿命。利用计算机技术建立采煤机三维结构模型图,将模型导入有限元分析软件进行仿真计算,得到采煤机前几阶振动...
  • 首先分析油浸式电力变压器振动产生机理以及油箱...并对所有测点固有频率特性进行分析,并变压器空载运行时油箱表面测得的振动信号进行比较,由比较可知当使用振动测量法诊断变压器故障时需考虑油箱壁共振现象的影响。
  • 分析讨论了动力学法测杨氏模量基频固有频率的最小二乘法拟合,指出在笔者采用数据的试验条件下,拟合多项式的幂次以3~4次为宜。
  • 由于LC元件的储能作用,当简谐激励频率fsLC串联电路的固有频率fo成整数倍: fo=nfs(n=2,3,4,……)时,LC回路中也会产生电磁振荡.讨论了这种非共振固有振荡不同于谐波共振的原理;运用等效负阻的方法,导出了...
  • 2.固有频率介绍

    千次阅读 2020-05-11 17:14:17
    固有频率与外界激励没有关系,是结构的一种固有属性。不管外界有没有对结构进行激励,结构的固有频率都是存在的,只是当外界有激励时,结构是按固有频率产生振动响应的。 2.固有频率的影响因素 从上面的公式我们...

    1.固有频率的定义

            结构系统在受到外界激励产生运动时,将按特定频率发生自然振动,这个特定的频率被称为结构的固有频率,通常一个结构有很多个固有频率。固有频率与外界激励没有关系,是结构的一种固有属性。不管外界有没有对结构进行激励,结构的固有频率都是存在的,只是当外界有激励时,结构是按固有频率产生振动响应的。

    2.固有频率的影响因素

           从上面的公式我们可以看出,结构的固有频率只受刚度分布和质量分布的影响,而阻尼对固有频率的影响非常有限。而在百度百科中说固有频率受形状、材质的影响,我个人觉得是不准确的。材质不同,其材料属性(密度、杨氏模量和泊松比等)不同,影响的最终参数还是质量和刚度;而形状的不同,影响的也是这两个参数。

           因此,影响固有频率的只有质量和刚度,而其他任何因素,最终影响的也是这两个因数。如结构的边界条件不同,固有频率必然不同,这是因为边界条件会影响到结构的刚度分布。

           质量增大,结构的固有频率必然降低;刚度增大,结构的固有频率必然增大。但是刚度继续增大,固有频率不会无限增大,只会增大一定距离。刚度增加越快,频率移动越慢。

    3.为什么存在多阶固有频率?

    我们在对结构系统进行固有频率测试时,通常能得到多阶固有频率。

    因为1个自由度对应1阶固有频率(或者是1阶模态)。自由度是指用于确定结构在空间上运动所需要的最少独立的坐标个数。质点有三个平动自由度;刚体有六个自由度,分别为三个平动和三个转动自由度。

    一个连续体或弹性体实际上有无穷多个自由度,此时,任意连续结构都可以看成是无限多个微刚体组成的,每个微刚体有6个自由度,因而,我们可以认为任意连续结构具有无限多个自由度,但是,所有这些结构又可以近似地看作是由有限个微刚体组成的(比方有限元分析时只能划分有限数量的单元),因此又可以认为连续结构具有有限个自由度。该自由度数决定了解析质量矩阵、刚度矩阵和阻尼矩阵的维数,也决定理论上存在的固有频率阶数和模态振型阶数。

    虽然连续体在理论上是有无限多阶固有频率,但很多情况下我们只关心低阶的固有频率或者特定阶的固有频率。这是因为固有频率越低,越容易被外界所激励起来。另外,结构也可能受到特定的激励,如在某恒定转速下运行,因此,也可能关心特定阶的固有频率。

    4.基频和主频

    基频是指结构的第一阶固有频率。结构发生振动时,通常不会是以某一个频率振动,而是有多个振动频率,通常在这些振动频率中,能量最大的振动频率称为主频。因此,这个主频可能是结构的固有频率,也可能是强迫响应频率。

    基频一定是固有频率,主频可能不一定是结构的固有频率,主频主要看的是能量的大小。因为我们知道,当结构产生强迫振动时,振动的频率是与外界激励频率相等的,但此时,这个激励频率很大程度上不是结构的固有频率,而它的能量又是最大的,此时,主频就不是固有频率。

    5.与共振频率的关系

    共振是指系统受到外界激励时产生的响应表现为大幅度的振动,此时外界激励频率与系统的固有振动频率相同或者非常接近。共振是一种现象,共振发生时的频率称为共振频率。不管共振发生与否,结构的固有频率是不变的,而只有当外界的激励频率接近或等于系统的固有频率时,系统才发生共振现象。

    当结构的阻尼非常小时,共振频率近似等于结构的固有频率,也是材料自身分子的自由振动频率。因而,单个共振是外界的激励频率等于或非常接近结构或材料的固有频率时,结构或材料发生大幅度的振动。共振时,结构的振动非常剧烈,这将导致不可预料的行为。因此,通常都要避免共振,但也有利用共振原理的,如振动筛。

    当激励频率与固有频率相等或接近时,才发生共振。因而,共振频率不一定完全与固有频率相等,共振频率是按外界的激励频率来讲的,而固有频率是从结构来讲的。虽然很多情况下,都认为共振频率就是固有频率。 在频响函数曲线中,共振峰所对应的频率为结构的固有频率,如下图所示。但很多情况,共振不是发生在单一频率(固有频率)处,而是具有一定宽度的共振带。也就是存在一个频率区间,在这个区间内很容易发生共振。

    展开全文
  • 主要对卷筒的振动特性进行研究,在NX8.5软件中建立其三维模型,并利用Hyper Works分析其约束状态下前4阶...结果表明,该方法使卷筒固有频率得到较好地提高,避免了共振现象的产生,同时为进一步合理地设计卷筒提供了参考。
  • 7 8 2007 1 36 1MA T LA B文 涛, 胡青春( , 510 640): 多自由度振动系统固有频率及主振型计算分析是研究其振动特性的 础, 矩阵迭代法是计算固有频率及主振型的 本方法之一根据矩阵迭代的方法, 利用MA T LA B 编程并...

    7 8 2007 1 36 1

    MA T LA B

    文 涛, 胡青春

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    算固有频率及主振型的 本方法之一根据矩阵迭代的方法, 利用MA T LA B 编程并验证程序的

    正确性通过程序的运行, 能快速获得多自由度振动系统的固有频率以及主振型, 为设计人员提

    供了防止系统共振的理论依据, 也为初步分析各构件的振动情况以及解耦分析系统响应奠定了

    : M AT L AB; 多自由度; 振动系统; 固有频率; 主振型

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    展开全文
  • 如果把迭代看作振动,那输出就应该振动频率直接相关,每个系统都有固有共振频率,这也就解释了为什么乙烯,乙炔,甲醛,亚硝酸的网络模型会收敛出不同的值。 如果把神经网络的学习过程理解成是一个寻找...

    在《用神经网络做分子模型:乙烯和乙炔的实验数据》文中将乙烯模型运行了60次,得到C=C的位置的输出是0.5051,本文中将乙烯模型运行了300次,测试这个值是否可以重现。


    得到数据


      

    平均值C=CC=CC-HC-HC-HC-H迭代次数平均值
    0-500.5041811730.50419480.50037270.50043090.499807050.500144511792146
    50-1000.5043046950.50414150.49971190.50007270.499768260.50008729643485.4
    100-1500.5052200030.50520330.50042120.50024080.500454990.500661615839743
    150-2000.5044268250.50433380.50009720.49972520.499541990.499597113957599
    200-2500.5040997820.50416650.49974990.49966520.500602970.50039755671932.5
    250-3000.5047446190.50485620.50061530.50076540.500336890.500471111469966
    平均值0.5044961830.50448270.50016140.500150.500085360.500226511395812

      可以得到C=C双键位置的网络输出值是0.5044,非常稳定,由此数据画图




    只要运行次数足够多就可以得到H=I=S=R=0.5044,这是一个不用训练就可以使用的神经网络,乙烯的网络模型特征的收敛于0.5044, 比如可以通过多次迭代判断是否可以得到0.5044来判断这个结构是不是乙烯的结构。当然不排除CH2与其他结构结合产生的键值也接近0.5044,但如果结构足够复杂得到的键值区分度足够高,应该可以用来区分不同的结构,而且这个网络不用训练就可以使用。如果把分子看作神经网络,大自然的策略是先有的特征输出比如化学键的键值,再由特征输出去构建网络结构,而神经网络的策略是先有的结构再这个结构去得到不同的输出。


    如果把迭代看作振动,那输出就应该与振动频率直接相关,每个系统都有固有的共振频率,这也就解释了为什么乙烯,乙炔,甲醛,亚硝酸的网络模型会收敛出不同的值。


    如果把神经网络的学习过程理解成是一个寻找系统共振频率的过程,就自然的让人想到了傅里叶变换,数学上只有傅里叶级数和泰勒级数等少数几种方法可以将函数展开,如果神经网络可以拟合任意函数,那在数学上只能是在逼近一个级数。否则如何用同一种结构表达所有函数?

    第一组数据


    C=CC=CC-HC-HC-HC-H迭代次数
    0.50023490.50044090.498753760.501974480.495555170.494811324009931
    0.50431630.50496070.50110620.504051750.502320970.5037603710492342
    0.50580790.50535860.499936390.509956460.499924850.5001571711947483
    0.50068510.5009140.499938050.499998120.500425310.50022886291737864
    0.50612070.50495630.498880750.49686490.504259730.502840126939695
    0.50191940.50168650.499953580.500346470.498329210.5005720246621516
    0.50175230.50137760.499969190.499923040.499977750.4997299349070087
    0.50684340.50677250.499792810.500232840.499764960.499782324457368
    0.51450210.51124440.499410150.502733740.497467820.499573231694789
    0.49953060.49876430.498103910.500520510.493712560.4888725753675410
    0.5036950.50370080.496168220.498288310.499924810.49965855130995011
    0.50467280.50399310.499857470.49966430.496588290.4994875580245312
    0.51213440.51007760.50203550.49941670.497696130.4992753218889613
    0.50084350.50115680.500569490.500656770.500638520.498397962457737914
    0.50042120.50027510.499999390.499998310.499998810.4999982214881182615
    0.50849760.50856110.502598610.504319350.499755820.5031736646092816
    0.50146260.50149290.499989420.499990760.499956070.5007047905368017
    0.50063680.50064510.499995810.499998010.499966020.499978037008687718
    0.50392920.50605760.499089750.499950570.502924780.50288365144719819
    0.50349290.50318790.499782270.496490330.497568870.499908293415220
    0.50400260.50569050.499683310.500803450.504963510.5042763357262721
    0.50306490.50415830.499959710.50119780.499951910.50253512177691922
    0.50227460.50147370.499399730.500998940.499906110.49783968493158723
    0.50461310.50622630.501640630.496385080.503370880.5013811286867024
    0.50438840.50527170.499851050.499854630.496762780.499823553222225
    0.50409390.50492190.502391010.499787580.499931980.49923119134956026
    0.50879030.50899490.50252220.499670420.499611050.5045296534663127
    0.50181430.50164880.499958170.499974590.500909080.49998313517014928
    0.50281870.50383990.501042230.498539580.501827470.50200801267939129
    0.50193750.50196790.499861310.497390250.49675750.49575852231478430
    0.508210.51024170.503407280.504576140.504668710.5044873951054131
    0.50899580.50972730.504262110.49939150.503646380.5017427534739632
    0.50556560.50469010.50341470.499862640.497083720.4963125375533233
    0.5109190.5076110.500606080.504950160.504096380.4998833380481934
    0.5075690.50757490.501609460.501630020.499715750.5047266243572635
    0.50471930.50458860.502347450.499928460.496247170.49984416109882536
    0.50143880.50143840.499995490.500993310.500943190.499936992381230137
    0.50674890.50637420.499839370.4997570.496622890.5016170255373938
    0.50740570.50573960.499834990.499691110.49668710.4986947549676339
    0.50089690.50082610.499996820.499997070.49999490.499843463326563940
    0.50285820.50319340.50131120.499877110.498362590.49995063288862941
    0.50190090.50201840.501661870.499979860.499987320.50200096960659742
    0.50491980.50623770.496148510.502359470.502213060.4997976758502543
    0.50170530.501690.499545650.499943610.499327080.49889768409091944
    0.50135050.50171480.49998350.499806120.499946670.49989862515830845
    0.50092130.50074130.499477860.499974070.500214750.500454483705343646
    0.5005450.50083690.499990840.499942490.499992490.499994872879674147
    0.50058530.50046050.499211340.499995340.499996860.499997375957939548
    0.50070480.50062950.499996310.49939230.500524720.499983735815287549
    0.51248590.51319410.503460160.499495290.499150640.4983000616457650
           
    0.50419490.50418690.500366820.500430420.499803420.500150511792146.36平均值




    第二组数据


    C=CC=CC-HC-HC-HC-H迭代次数
    0.5003990.5002570.4996940.4999990.4999960.4999981.32E+081
    0.5068470.5077740.4997160.5047750.4997310.4989194659722
    0.4990780.4991670.4860720.5013760.499040.4987022483273
    0.5055770.507260.5022550.5049280.5026890.4998756716614
    0.5082870.5085980.5036440.4994870.5024060.5043913859125
    0.5006720.5009740.4999870.4983860.5003280.499995250782506
    0.5006110.5006540.5003670.4999990.5003090.499998939371437
    0.5032190.5040920.4963530.4995980.5004190.49982510929148
    0.5044720.5039730.4999270.4990850.4998770.4998839442989
    0.5023720.5036750.4999540.499770.4999240.499947174988810
    0.5011560.5007950.4992040.4997950.5006350.5005571632217111
    0.5098550.5089180.4993340.4981190.499290.49920126393012
    0.5002540.5009590.4979330.4980450.4999470.498876199383313
    0.502160.5025130.4996480.50.4979320.499367267184214
    0.5010020.502120.5011410.501950.4999930.5002621681085915
    0.5051710.5070970.4970570.4998070.5048170.50494451214116
    0.508780.5061530.5049430.5021870.5016630.49979452066017
    0.5014310.5015830.4999890.5009850.4999760.499986728590618
    0.5033770.5026770.4999270.5025640.4963470.500433184884119
    0.5100740.5062920.4983390.499690.5023010.50457133026220
    0.5086960.5102650.4996270.4995670.4972280.50407232271521
    0.5010930.5009730.4999930.4999910.4999930.4999941765412622
    0.5090330.5065640.4997590.5044080.4995540.49975241457923
    0.5078660.5062220.4988830.4972450.5050050.49967532083024
    0.5056360.5056740.5018240.4998170.4972680.49963464583425
    0.499110.4994680.4916110.496690.4992490.499769190192826
    0.5114320.5086890.4996270.497780.4981690.49941620408227
    0.503430.5044850.5018080.4998950.501160.500473138625528
    0.50720.5067720.4995660.4997480.4993720.4974229379629
    0.5045840.50420.4990350.4999070.4999270.499899110035830
    0.5096390.5091690.5042420.5013760.4989770.49935731357131
    0.5047340.5040350.4998520.5003080.4966640.49884383887032
    0.5050380.5052960.4975940.4968670.4993360.4998461598233
    0.5007830.5008420.4999940.4999950.4999860.4953811834635134
    0.5010950.5008750.4999930.4999960.4999960.4999482433000935
    0.5036620.5032350.4995770.4963120.499910.49958998961736
    0.5018470.5019930.5013850.5006860.499950.499985619250437
    0.500970.5015190.5004860.499860.4999870.499805992075738
    0.5019670.502670.499980.4999620.4999780.501062488479139
    0.5033740.50310.4998390.4997970.4964750.49847884028140
    0.5006090.5003750.4999340.4999720.499990.5003437456940141
    0.5047740.5043780.4998510.4998520.4960610.4998771719842
    0.5037930.5036360.5004420.5004980.4999430.500547205320643
    0.5064350.5076380.5042480.5048940.5020690.50302997062444
    0.507560.50790.5001870.4997170.4997770.50464443502645
    0.513210.5118830.4991910.4985680.5007430.49832212459346
    0.5047440.5044360.4998980.5025370.4961510.49987100106347
    0.5013950.4997880.4979680.4960470.4965730.49936951492148
    0.5023680.5012390.4999750.4980.5020610.499939450354649
    0.5040630.5038370.5039120.5029250.4986080.496313106925950
    ********
    0.5042990.5041340.4997150.5000750.4997560.5000839643485平均值


    第三组数据

    C=CC=CC-HC-HC-HC-H迭代次数 
    0.5032870.5030960.4991250.4999290.4999120.49993814866121
    0.5073560.5063410.4993690.499610.4997580.4996743735112
    0.5074590.5089660.5013440.5038640.5050390.5030846998733
    0.51110.5094950.4993220.5050690.4971690.4995512319314
    0.5079380.5080010.5037220.5023610.4967670.4997263422285
    0.5008740.5012010.499980.499190.5011210.500795186755136
    0.5039580.5040850.499160.4966960.502210.4979227853057
    0.5066890.5069630.5027520.5030760.5003440.4997494675858
    0.5074510.5073740.5032720.5077240.5004770.50155213356699
    0.5026090.5032680.4996530.4999220.5013950.500077139503810
    0.5003050.5003180.4999990.50.4999920.4999942.22E+0811
    0.500410.5004560.4999480.4999990.4992130.4998536005512812
    0.5058460.5075210.4998190.4998210.5009470.50497451651713
    0.509790.5098040.499480.4992960.4994140.49953325371814
    0.5012340.5010170.5000870.5005940.5015510.4999932638675715
    0.5060970.5057980.5031670.5047180.4999230.503774126491716
    0.5081350.5060080.4991220.4996160.5050510.49933827561817
    0.507080.5093520.4996960.4996660.5008380.50391635761218
    0.5017430.5022440.4999870.4999730.4996880.500992613930719
    0.5004380.5005720.4999490.5004690.4999970.4999974602371220
    0.5006180.5012960.499140.4989510.4956090.49555933805421
    0.5062550.5041980.5027410.5042510.4969340.49925657559822
    0.5043150.5039440.4993220.4964590.4999180.499923120076623
    0.5003240.5002740.4999980.4999990.5001650.50031.98E+0824
    0.5089570.5077690.503720.4995860.5024460.50381534810625
    0.500970.5012380.5007110.4992380.4999670.5003121722126026
    0.516420.5142830.4986880.498880.498690.4980568671327
    0.5042060.5048090.5019920.4969440.499860.499444124282028
    0.505880.507420.4962720.504260.5018090.49996274517929
    0.5137940.5134590.4995140.4979280.5027440.50018318490830
    0.502160.5021850.499990.4999850.5014570.49997785673731
    0.5060990.5097950.5049040.5010940.5009780.50249455180132
    0.5098440.5132610.4994550.4995040.499340.50246816995933
    0.5008590.50070.5004720.4999230.4999930.4999952837029834
    0.5046050.5042330.4984460.4958940.4979950.49974188724135
    0.5055180.5062630.5035630.5039610.505050.502928100494136
    0.5028630.5033360.4991060.499850.4976870.499055130569837
    0.5061720.5056680.496670.4966210.4980310.49979261864038
    0.5016660.5019240.496590.4958640.4998740.499906309626439
    0.5081260.5068170.5036710.501370.4965810.50302259691240
    0.5065980.5065820.501910.5009290.4998280.49981675061441
    0.5083520.5044920.4985950.4969220.5047780.50279251031442
    0.5108460.5055070.5042230.5042490.4999030.50295656963143
    0.5038090.5041940.5007710.4990720.499940.500294159672744
    0.5056840.5062850.5074390.4998110.5047270.50208858608745
    0.5009030.5007580.499680.500320.5003510.4987413409980046
    0.507920.510160.4983440.4997720.5042460.50480436913847
    0.5031110.5031110.4999220.4999580.4999510.499824189599048
    0.5004730.5004070.4999990.4999970.5003670.4999539465037349
    0.5032680.5033960.4961290.4992410.5030130.501958138140650
            
    ********
    0.5052080.5051930.5004190.5002490.5004610.50067715839743平均值




    第四组数据


    C=CC=CC-HC-HC-HC-H迭代次数 
    0.5007990.5005540.4999980.500390.4999950.499989477506031
    0.5003460.5002290.50.50.4999990.4999351.8E+082
    0.5059630.5080440.5037230.5044630.5035780.5031789464843
    0.4998070.4999640.4999420.4999640.4937670.4965367563354
    0.5033580.5028640.497220.4967160.4996980.4998649169745
    0.5069760.5075890.4997130.4991270.5048830.5049965607886
    0.5013890.500860.50.5024350.5005290.499996480994797
    0.5096520.5091040.504670.5029540.4997390.4993633562638
    0.5032840.5017810.4989180.4991630.5012140.50075427597289
    0.5033570.5026310.4999520.4986730.4999440.499933173278010
    0.5077540.5073220.5018570.4973520.4999650.49966245954111
    0.5045850.5040890.4993990.4961660.5001050.50337132492712
    0.49920.4991530.4997480.4986390.4846380.48533398541413
    0.503340.5051440.4989140.4968590.4998480.49695648060414
    0.5096980.5091920.5049320.5013350.4998630.50363861495715
    0.5008130.5014250.5001140.500520.4999760.4988541306462916
    0.4999140.4994930.4993670.4997430.4931180.49358333159317
    0.5056480.5063410.5020760.4997120.4967580.50288159343518
    0.5081890.5063210.5048970.5028290.50050.49984581921119
    0.5058020.5077420.5031040.4998720.5016350.49698264403320
    0.5003980.5005620.50.4999920.5002820.5002971.42E+0821
    0.5102530.5090410.4997980.4973280.5042160.50413338576922
    0.5132410.5116750.5023840.4987160.5017690.49887111798323
    0.5021080.5018220.4999670.4999560.5004120.495975242339724
    0.5087250.5086590.4997370.4998050.4997560.4995738089225
    0.5005290.5007470.4999980.4999940.5004380.5002796737266326
    0.501130.5010190.4999850.4999770.4999890.4999911480618327
    0.5068140.5071640.4995240.4997420.4995650.49980345807428
    0.5034320.5043560.4965730.4994790.4984470.502722107505229
    0.5074910.5051110.5037060.4968850.4998320.49983258744330
    0.5065120.5044240.4970890.499850.5030550.49983855106731
    0.5029630.5027910.4998790.4979310.4999780.499256148438232
    0.5080290.5078580.4979850.499590.4987510.49895631735633
    0.5076790.5084990.4996270.5012870.5010260.5046941822134
    0.503570.5032220.4999260.5009060.5023810.499942166860935
    0.5001120.4997130.4963740.4999050.4973390.495404142045136
    0.507210.5048180.4968360.5038330.4997460.4998170193237
    0.5008420.5009830.5005150.5005230.4998460.4993991599670438
    0.5005250.5009730.4999820.4999980.4999810.4999963258150939
    0.5021510.5023610.4962950.4960160.4967330.499947239393640
    0.5082280.5097970.4995430.4997280.4996470.49991938785341
    0.5108320.5117960.4992840.5036410.5023060.49818718856042
    0.5004140.5004950.4999930.4998530.4999980.4999987471147843
    0.5022940.5022090.4999770.501510.4999860.499937676486644
    0.5029040.5029050.4998380.4998830.4958620.496439149162945
    0.5017390.5024910.4994430.4959840.5009140.4999319714046
    0.5065480.5064570.5023970.4997580.4969110.50027249402047
    0.5013490.5014830.4999830.5003310.4999860.498266739843548
    0.5124350.5107980.4998220.4975140.4981730.50256922726549
    0.5011420.5021690.4999380.5001620.4999830.4999756418692 
            
    ********
    0.5044290.5043250.5000990.499740.4995410.49959613957599平均值

    第五组数据



    C=CC=CC-HC-HC-HC-H迭代次数 
    0.5032210.5051420.5033890.5017360.4965990.50184113282141
    0.504890.5061790.499850.5005470.5034690.4968694956712
    0.5041410.5036170.4971140.4996560.4998990.49651311960843
    0.5006040.5005280.4951270.4963430.5015170.504322972374
    0.5076820.5088860.4992930.4974070.500730.4992362801795
    0.5077960.5102580.5010140.5045080.5045480.5049626024216
    0.5048310.5045940.4965920.49990.5013560.5033919502577
    0.5046160.5036910.499310.4999230.5013660.50332912736708
    0.5082280.5070830.5028170.4997520.499760.4975793515849
    0.5013830.5007360.4992990.5005580.4999920.4999881563411810
    0.5004760.50050.4999860.5003950.5002570.500317106042911
    0.5016110.5021210.4988080.4999820.4998970.499901472159912
    0.5069990.5064270.4968170.4997750.4997640.50264458244113
    0.5033720.5041590.4998950.496580.4997910.49811387171014
    0.5007070.5004270.499990.4999940.50060.4999954097221015
    0.5036330.5036050.4998790.4992380.4964530.499913100956216
    0.5024820.5030750.4999650.5008870.4999720.499953284722417
    0.5021660.5015010.4986140.4995810.5001280.500648475546818
    0.5057470.5055470.5048790.4997450.4997460.49683457049619
    0.4979610.4988370.4939360.4909460.5007610.49759625659220
    0.5042910.503730.4982720.4993510.4991920.499719142594721
    0.505790.5043660.4998770.4987550.5017530.49987669689822
    0.5017470.502090.4998880.5004950.4999750.499978545884823
    0.5026790.502090.4979830.4999490.4996490.497692186997424
    0.5024770.501980.5008490.4982620.4999820.499978564428525
    0.5053370.5067030.5034430.4998140.5046470.50468561437126
    0.5053660.5071680.497210.5029730.4997140.49901742409427
    0.506740.5067420.5048570.5013190.4997630.50185769584128
    0.5049260.5046370.4994670.4998620.4967580.49948368140529
    0.5025690.5017440.5017230.499010.4998510.499961331122630
    0.5041390.5055460.499850.4997160.4989470.49987680693631
    0.5020420.502070.5014550.5006940.5011120.501261082843332
    0.5010290.5010210.5001030.4999910.4997550.4999871126191433
    0.5003680.5005930.496490.4999960.5001050.5003835533294334
    0.5034120.5017190.5010990.5015010.5005490.501126865046535
    0.5069690.507190.4998230.4997980.5035430.49970246408736
    0.5057120.5062810.4998150.5013550.5023890.50493763276137
    0.5026960.502080.5014390.4999830.5008830.501333565346338
    0.5032260.5021820.5017630.501020.5001080.49991366687939
    0.4996320.5014290.4904660.4911210.4994070.50396929893840
    0.5016970.5026360.4995850.4999260.4999370.495961229578941
    0.5017770.5022260.4999670.499930.4999320.495737317988442
    0.5072040.5059280.4973940.4996110.5025240.50152442837643
    0.5083540.5076270.5037490.4997030.4996620.49938932423344
    0.5080140.5071570.5023740.4998930.5040740.50504983057945
    0.5074830.5071250.4967540.499830.5010980.50000573247846
    0.5089410.5108480.5024020.4991270.4987150.49911913470047
    0.5072070.5082190.4995190.5036890.5043860.50427849000148
    0.5092770.5072830.5038990.4984040.5050140.50018756116149
    0.5017590.501710.4994690.5005980.5005280.499975614254950
            
    ********
    0.5041080.5041810.4997510.4996630.5006110.5003985671932平均值


    第六组数据


    C=CC=CC-HC-HC-HC-H迭代次数
    0.506530.5060320.5033010670.49991350.4994940.4967074450091
    0.5006290.5007820.4999952220.49998490.4999960.499748234504222
    0.5085150.507970.49722720.50410590.4997820.5007694886323
    0.5003390.5006720.4999986970.5002090.4999960.500341707980394
    0.5008230.5004650.5001407820.50036030.4999940.499998572413575
    0.5028240.503480.4984246540.5014340.5012960.4998129185996
    0.5013180.5013960.4999735550.49999040.4999470.499978140864237
    0.5076180.5059450.4997911880.50469540.4993840.500765482148
    0.50640.5076340.4972957010.50069650.4978760.4996833998419
    0.5036020.5028750.5014069880.49994890.4988450.499959250691110
    0.5017580.5021130.4999294060.49996450.4999420.499967317000011
    0.5105680.5079550.5030831670.50379380.4997970.50284946244112
    0.5026160.5047770.4983909550.49991060.4998390.49657371770013
    0.5051950.5081760.504932510.49978170.5038160.50187973150414
    0.5029910.5030030.4999130970.50006880.496010.499908134216215
    0.5019530.5015160.5008618340.49943510.5008680.499971510095516
    0.5048340.5072230.4997852920.50310440.5009160.503575102921217
    0.508660.5098440.4996344980.50493650.5031270.49892847610218
    0.508370.5069510.5016156620.50430240.4997680.49702744172019
    0.5035870.5031580.5002394680.49995340.4998520.498891161182120
    0.5090910.5081510.5024313720.50416380.5034570.5050588539021
    0.5061020.5053420.4965661160.4998480.5031990.49984272761922
    0.5065450.506640.4997923240.50477930.4997220.49962642017923
    0.5079160.5060720.5038147440.50342340.4997680.5026244969824
    0.5025420.5027320.4993434910.49989860.4958860.49951178737425
    0.5057830.5047880.5030163260.49910790.4986550.49976490509526
    0.5078650.5079090.5011046490.50060550.4995910.49987336575427
    0.5030260.5032610.5011066280.49866810.4999280.496613113384728
    0.5078850.5055260.503989110.50262590.5046290.50244649038029
    0.5033210.5052640.5022957580.49990690.4964070.50286880754230
    0.5003610.5005810.5003000550.5000410.4999990.4999552.18E+0831
    0.5011520.5017060.4999932290.49999320.4999880.5007091157873832
    0.5021540.5027270.4999316090.49997870.4999750.499981540483233
    0.5034670.5047840.4998409080.4999240.4999220.496057113662234
    0.5085990.5093760.5046398630.5000290.5043930.50337951718135
    0.5087770.5085040.4998713550.50490160.4996330.5045360215836
    0.5070440.5079540.5043274380.50374720.5049680.50351563516437
    0.5057030.50360.4995024720.496420.5028770.50128668569338
    0.508030.5070880.4997433710.49928220.5032620.49937330644139
    0.5068380.5075010.5006588090.49966970.499870.49679859494140
    0.505830.5055930.4999137870.50267070.4958540.499919109922641
    0.5056420.5074950.4998769520.50037890.505050.50354889492742
    0.5028180.5023750.4999379720.49603910.5009390.499957353754943
    0.5037460.5040580.5034005420.49992370.4997190.499835109262144
    0.5047720.5084920.4987615980.49964940.4995150.50495539971345
    0.5023850.5014560.4999839250.49950670.4999690.499965569817446
    0.5005860.500590.5003932730.49999010.4995160.4999985056582647
    0.5004460.5003730.4999878120.49987350.4999980.4999957328645948
    0.5037320.5050830.5005693080.4960390.4999190.499921118269949
    0.5056990.5052570.4992922060.49988990.499840.5045862859450
    ********
    0.504740.5048450.5006065590.50075130.500340.50047611469966平均值



    展开全文
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  • 可以发现筛体的前阶模态基本都为局部振动,容易发生弯曲破坏,所以在实际生产中要注意提高部件的抗弯强度,并确定了在正对称的第10阶中结构出现了共振现象,为确保在实际结构设计中要避免出现共振的危险段频率提供了...
  • 然后基于振动理论,分析了传输功率的频率分裂现象,阐述并推导了系统的几个关键参数:系统固有频率、电路固有频率共振频率。接着深入分析了系统固有频率和电路固有频率之间的关系,进一步揭示了频率分裂及系统共振的...
  • 指出设备工作中奇数倍频现象产生的原因,确定了工况下的固有频率,说明设备工作频率在共振频率附近.结果表明,动力学分析实际测试的结果基本一致,该分析方法可以正确应用到共振筛的动力学分析及优化设计上.
  • 可参考文涛,基于Matlab语言的多自由度振动系统的固有频率及主振型计算分析,2007 对于无阻尼系统 [VEC,VAL]=eig(inv(A)*K) 对于有阻尼系统,参考振动论坛计算程序 输入M,D,K function [v,w,zeta]=vbr_sf...
  • 文献中是不是求得第一阶的,后文写着从传递函数得到第一阶共振频率
  • 介绍了测试梁固有频率及...利用QLVC-ZSA1型振动信号分析仪、电磁激振器、加速度传感器等,通过共振相位判别法及锤击法测得了简支梁的1阶、2阶固有频率,并通过共振法绘制了相应的主振型曲线,实验结果理论解答非常接近。
  • 机械共振的资料集

    2011-10-02 07:29:39
    电子自旋共振仪扫场信号的改进设计.pdf ...用共振法测定弹性梁固有频率及振型.pdf 利用欠阻尼二阶线性随机共振抑噪的模型设计及实现.pdf 齿轮传动中几种典型故障的振动图谱分析.pdf 还有更多。。。。。。
  •  基于喇叭的共振原理,提高扬声器的发声强度并尽可能的降低因振动而消耗的能量,从而提高喇叭的效率。...试验结果表明当输入谐振频率与喇叭的固有频率相同时,喇叭出现共振,此时检测喇叭的声能是相对较弱的。
  • 阻尼弹簧质量系统在固有频率下的响应并无阻尼弹簧质量系统进行比较.. 对于无阻尼弹簧质量函数下载先前上传的 ..spring_mass(F,m,k,w,t,y) 函数文件。
  • 结果发现:弹簧摆动弹簧振子的固有频率之比f为1/2且初始摆角极小时,弹簧摆有内共振现象且作准周期运动;在初始摆角不变时,通过改变参数f,弹簧摆的运动特点不同;在参数f不变时,通过改变初始摆角,弹簧摆呈现出复杂的...
  • 提出了一种利用光纤的共振来测微振动的新方法,从理论上阐述了其原理并取得了实验数据。最后展望了其应用前景。
  • 波长与频率的关系

    万次阅读 2019-04-12 09:40:51
    波长与频率的关系

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