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通讯作者:

宋智广,E-mail:z.g.song@hrbeu.edu.cn

中图分类号:V214.3+2

文献标识码:A

文章编号:1672-6553-2023-21(1)-051-009

DOI:10.6052/1672-6553-2021-065

参考文献 1
郑栋梁,李中付,华宏星.结构早期损伤识别技术的现状和发展趋势 [J].振动与冲击,2002,21(2):1-6.ZHENG D L,LI Z F,HUA H X.A summary review of structural initial damage identification methods [J].Journal of Vibration and Shock,2002,21(2):1-6.(in Chinese)
参考文献 2
李慧民,董美美,熊雄,等.基于振动的结构损伤识别研究综述 [J].建筑结构,2021,51(4):45-50.LI H M,DONG M M,XIONG X,et al.State-of-the-art review of vibration-based damage identification framework for structures [J].Building Structure,2021,51(4):45-50.(in Chinese)
参考文献 3
饶文碧,吴代华.RBF神经网络及其在结构损伤识别中的应用研究 [J].固体力学学报,2002,23(4):477-482.RAO W B,WU D H.RBFN and its application for structural damage recognition [J].Chinese Journal of Solid Mechanics,2002,23(4):477-482.(in Chinese)
参考文献 4
KUMAR M,SHENOI R A,COX S J.Experimental validation of modal strain energies based damage identification method for a composite sandwich beam [J].Composites Science and Technology,2009,69:1635-1643.
参考文献 5
李兆霞,王滢,吴佰建,等.桥梁结构劣化与损伤过程的多尺度分析方法及其应用 [J].固体力学学报,2010,31(6):731-756.LI Z X,WANG Y,WU B J,et al.Multi-scale modeling and analyses on structural deterioration and damage in long-span bridges and its application [J].Chinese Journal of Solid Mechanics,2010,31(6):731-756.(in Chinese)
参考文献 6
Li Y Y.Hypersensitivity of strain-based indicators for structural damage identification:a review [J].Mechanical Systems and Signal Processing,2010,24:653-664.
参考文献 7
聂振华,马宏伟.基于重构相空间的结构损伤识别方法 [J].固体力学学报,2013,34(1):83-92.NIE Z H,MA H W.Structural damage detection based on reconstructed phase space [J].Chinese Journal of Solid Mechanics,2013,34(1):83-92.(in Chinese)
参考文献 8
徐伟华,吕中荣,刘济科.基于振动响应的杆结构损伤检测 [J].固体力学学报,2010,31(1):48-52.XU W H,LV Z R,LIU J K.Damage detection for rods from vibration responses [J].Chinese Journal of Solid Mechanics,2010,31(1):48-52.(in Chinese)
参考文献 9
郭惠勇,李正良.基于应变能等效指标的结构损伤识别技术研究 [J].固体力学学报,2013,34(3):286-291.GUO H Y,LI Z L.Structural damage identification method based on strain energy equivalence parameter [J].Chinese Journal of Solid Mechanics,2013,34(3):286-291.(in Chinese)
参考文献 10
FAN W,QIAO P Z.Vibration-based damage identification methods:a review and comparative study [J].Structural Health Monitoring,2011,10:83-110.
参考文献 11
ZHANG Y,BERNAL D.Damage localization from projections of free vibration signals [J].Journal of Sound and Vibration,2017,394:146-154.
参考文献 12
SAHIN M,SHENOI R A.Quantification and localisation of damage in beam-like structures by using artificial neural networks with experimental validation [J].Engineering Structures,2003,25:1785-1802.
参考文献 13
赵才友,王平,全顺喜,等.基于应变模态变化率的钢轨损伤检测 [J].振动、测试与诊断,2012,32(5):723-729.ZHAO C Y,WANG P,QUAN S X,et al.Detection method for broken rail based on rate of change of strain mode [J].Journal of Vibration,Measurement & Diagnosis,2012,32(5):723-729.(in Chinese)
参考文献 14
梁岗,史单艳,沈奎双.多裂纹梁不确定性损伤识别和实验研究 [J].机械科学与技术,2020,39(9):1335-1345.LIANG G,SHI D Y,SHEN K S.Uncertain damage detection and experimental study of multiple cracks in beams [J].Mechanical Science and Technology for Aerospace Engineering,2020,39(9):1335-1345.(in Chinese)
参考文献 15
徐强,刘博,陈健云,等.基于加权最小二乘的结构模态参数与损伤识别 [J].水利学报,2020,51(1):23-32.XU Q,LIU B,CHEN J Y.Structural modal parameters and damage region identification based on least squares method with frequency band weighting approach [J].Journal of Hydraulic Engineering,2020,51(1):23-32.(in Chinese)
参考文献 16
PENG Z K,CHU F L.Application of the wavelet transform in machine condition monitoring and fault diagnostics:a review with bibliography [J].Mechanical Systems and Signal Processing,2004,18:199-221.
参考文献 17
ZHONG S C,OYADIJI S O.Detection of cracks in simply-supported beams by continuous wavelet transform of reconstructed modal data [J].Computers and Structures,2011,89:127-148.
参考文献 18
缪炳荣,杨树旺,王名月,等.利用振动响应的多种结构损伤识别方法比较 [J].振动工程学报,2020,33(4):724-733.MIAO B R,YANG S W,WANG M Y.Comparison of various structural damage identification methods using vibration response [J].Journal of Vibration Engineering,2020,33(4):724-733.(in Chinese)
参考文献 19
宋子收,周奎,李胡生,等.基于曲率模态和小波系数差的损伤识别 [J].公路交通科技,2010,27(11):61-66.SONG Z S,ZHOU K,LI H S,et al.Damage identification based on curvature mode and difference of wavelet coefficients [J].Journal of Highway and Transportation Research and Development,2010,27(11):61-66.(in Chinese)
参考文献 20
唐冶,王涛,丁千.主动控制压电旋转悬臂梁的参数振动稳定性分析 [J].力学学报,2019,51(6):1872-1881.TANG Y,WANG T,DING Q.Stability analysis on parametric vibration of piezoelectric rotating cantilever beam with active control [J].Chinese Journal of Theoretical and Applied Mechanics,2019,51(6):1872-1881.(in Chinese)
参考文献 21
ARVIN H,HOSSEINI H M S,KIANI Y.Free vibration analysis of pre/post buckled rotating functionally graded beams subjected to uniform temperature rise [J].Thin-Walled Structures,2021,158:107187.
参考文献 22
ARVIN H,KIANI Y.Vibration analysis of rotating composite beams reinforced with carbon nanotubes in thermal environment [J].International Journal of Mechanical Sciences,2019,164:105187.
参考文献 23
LEI Y G,LIN J,HE Z J,et al.A review on empirical mode decomposition in fault diagnosis of rotating machinery [J].Mechanical Systems and Signal Processing,2013,35(1-2):108-126.
参考文献 24
CHEN J L,LI Z P,PAN J,et al.Wavelet transform based on inner product in fault diagnosis of rotating machinery:a review [J].Mechanical Systems and Signal Processing,2016,70:1-35.
参考文献 25
宋振华,王志华,马宏伟.基于小波分析的超声导波管道裂纹检测方法研究 [J].固体力学学报,2009,30(4):368-375.SONG Z H,WANG Z H,MA H W.Study on wavelet-based crack detection in pipes using ultrasonic longitudinal guided-wave [J].Chinese Journal of Solid Mechanics,2009,30(4):368-375.(in Chinese)
目录contents

    摘要

    本文采用旋转悬臂梁模型模拟旋翼直升机桨叶结构,并对其开展损伤识别问题研究.首先,基于有限元方法,采用Hamilton变分原理,建立旋转结构的动力学模型,通过对比理论和实验的结果验证模型的正确性.其次,利用不同模态参数(位移模态、应变模态)对旋转悬臂梁结构进行损伤识别研究.最后,针对位移模态,基于小波变换的奇异性分析特性,研究通过小波系数辅助损伤识别的方法.计算结果表明,对于旋转结构,应变模态的损伤识别效果较好,而位移模态若结合小波变换的奇异性分析,同样可以实现较为准确的损伤识别效果.

    Abstract

    In this paper, a rotating cantilever beam is used to simulate the rotor helicopter blade structure, and the damage identification problem is studied. Firstly, based on finite element method and Hamilton variational principle, a dynamic model of rotating structure is established. The model is verified by comparing theoretical and experimental results. Secondly, the damage identification of the rotating cantilever beam is studied by choosing different mode parameters (displacement mode and strain mode). Thirdly, for the displacement mode, based on singularity analysis characteristics of wavelet transform, the method of damage identification assisted by wavelet coefficients is studied. The results show that the damage identification effect of strain mode is better for rotating structure, and the displacement mode can achieve a more accurate damage identification if it can be combined with the singularity analysis of wavelet transform.

  • 引言

  • 近年来,随着直升机的飞行工况要求越来越高,直升机桨叶开始大量采用复合材料进行设计,并向轻量化方向开始发展.而在制造和飞行工况中,直升机桨叶长期处于腐蚀环境、强冲击、重载或高温等恶劣复杂条件下,不可避免地会产生各种各样的损伤,桨叶一旦出现故障,可能会导致灾难性事故和巨大的经济损失.因此,研究桨叶的损伤识别具有重要的理论意义和实际应用价值.

  • 从20世纪90年代开始,国内外科学家们[1-9]对于新型结构损伤识别的方法做了大量研究.近10年来,科学家们发现模态参数可以有效识别工程结构的损伤状态.一般来说,结构损伤会引起模态参数的变化,测量这些参数可以帮助识别损伤的状态:存在、位置、严重程度,甚至是损伤趋势.因此利用不同模态参数进行工程结构损伤识别的技术已经逐渐发展成为损伤识别领域研究的热点问题.Fan和Qiao[10]对基于模态参数的梁或板结构损伤识别方法进行了综述,文中将模态参数损伤识别法具体分类,并详细讨论了每种类型的优缺点.Zhang和Bernal[11]提出了一种在损伤工况下利用振动模态信号进行损伤定位的方法并设计实验验证了该方法的有效性.Sahin和Shenoi[12]设计出了一种将结构固有频率和曲率模态作为分析数据的损伤识别方法.国内学者们也对模态参数损伤识别法做大量研究.为了准确检测钢轨结构损伤,赵才友等[13]提出了基于模态参数变化率的损伤检测方法.梁岗等[14]通过构建结构模态参数与损伤参数的映射关系来进行多损伤工况梁的损伤识别.徐强等[15]通过加权最小二乘法来提高模态参数损伤识别的精确度.

  • 近年来,小波分析在损伤检测中的应用已经成为结构和机器健康监测中的一个重要研究领域.使用小波分析技术的主要优点是能够对信号进行局部分析并且对于信号微小突变极其敏感.这一特性对于损伤识别应用尤为重要.Peng和Chu[16]进行了小波变换在机械状态监测和故障诊断中的应用的文献综述.Zhong和Oyadiji[17]提出了一种在无基线模态参数的情况下梁结构小损伤检测的小波变换新方法.缪炳荣等[18]利用小波变换结合不同模态参数开展了梁结构小尺度损伤识别方法的研究.为了解决两跨连续梁的损伤识别问题,宋子收等[19]提出了基于曲率模态和小波系数差的损伤识别方法.

  • 通过以上文献综述可以发现,国内外学者已经对不同结构的损伤识别问题开展了大量的研究,但对于旋转结构的损伤识别研究还相对较少.本文以直升机桨叶为主要研究对象,采用旋转悬臂梁模型对其进行模拟,通过Hamilton原理,基于有限元法,建立含有损伤的结构动力学分析模型.分别采用应变模态、位移模态、以及小波变换的奇异性分析,研究旋转结构的损伤识别方法.本文的研究将为旋翼直升机桨叶的健康监测提供理论依据.

  • 1 理论公式

  • 1.1 旋转悬臂梁动力学建模

  • 如图1所示,本文采用旋转的Euler-Bernoulli梁模型模拟直升机桨叶.结构位移场、几何方程和本构方程为:

  • u(x,t)=-zwxw(x,t)=w0(x,t),εx=-z2wx2,σx=Eεx
    (1)
  • 其中,u是沿x方向的纵向位移,w是沿z方向的横向位移,σx是结构任意一点应力,εx是结构任意一点应变,E是材料弹性模量.

  • 当悬臂梁绕定轴转动时,旋转所产生的离心轴力Ftx)可以表示为[20]:

  • Ft(x)=xL mωR2ζdζ=12mL2-x2ωR2=F-(x)ωR2
    (2)
  • 其中,m为单位长度梁的质量,L为梁沿x方向的长度,ωR为旋转角速度.

  • 根据哈密顿原理建立旋转结构的动力学模型

  • t1t2 δ(T-U)dt=0
    (3)
  • 其中TU分别为旋转梁结构的动能和势能,具体表达式如下[20-23]:

  • T=12ρV u˙2+w˙2+ωR2(x+u)2dVU=12V σxεxdV+120L Ft(x)wx2dx
    (4)
  • 其中,ρ为梁结构材料密度,V为梁结构体积.

  • 本文采用有限元方法对连续梁结构进行离散化,为此将结构位移表示成如下形式:

  • we=i=14 Ni(ξ)qi=NeTqe
    (5)
  • 其中,Neqe为有限元中的插值函数和单元节点位移向量.插值函数具体表达形式由下式给出:

  • N1(ξ)=1-3ξ2+2ξ3,N2(ξ)=leξ-2ξ2+ξ3N3(ξ)=3ξ2-2ξ3,N4(ξ)=le-ξ2+ξ3
    (6)
  • 其中,le为单元的长度,ξ=x-xl/le是归一化的局部坐标,xl是单元左侧节点的坐标.

  • 图1 旋转悬臂梁及损伤示意图

  • Fig.1 Rotating cantilever beam and damage diagram

  • 通过变分运算,可得旋转结构单元的运动方程:

  • Meq¨e+Kes+Keg-Kerqe=0
    (7)
  • 其中,Me为结构单元质量阵,Ke为结构单元刚度阵,角标“s”,“g”和“r”分别表示结构自身刚度,由应力刚化效应产生的刚度和由旋转软化效应产生的刚度,具体形式如下:

  • Me=ρhxlxr NeNeTdx+ρh312xlxr NexNeTxdxKes=Eh312xlxr 2Nex22NeTx2dxKeg=12mωR2xlxr L2-x2NexNeTxdxKer=ρh3ωR212xlxr NexNeTxdx
    (8)
  • 其中,xr = xl + le为单元右侧节点坐标,h为梁沿z方向的厚度.将单元动力学方程式(7)进行组装,将得到整体结构的动力学方程:

  • Mq¨+Ks+Kg-Krq=0
    (9)
  • 由上面结构动力学模型可知,旋转会使结构产生应力刚化和旋转软化效应,应力刚化将引起结构刚度的增大,而旋转软化与其相反,会减小结构的刚度,两种效应的耦合会影响结构固有频率,通常应力刚化的作用偏大,所以旋转状态下结构固有频率比静止状态下的固有频率更高.

  • 1.2 模态参数损伤识别的原理

  • 为了求解模态参数,设广义坐标的解为q = q 0ejωt,将其代入动力学方程,可得如下频率方程:

  • Ks+Kg-Kr-ω2Mq0=0
    (10)
  • 其中ωq0为结构固有频率和位移模态.为了获得结构的应变模态,将位移模态代入式(1)中所示的几何方程,然后通过采用如下中心差分方法,进而获得应变模态:

  • ε=-zw,xx-zwi+1-2wi+wi-1/le
    (11)
  • 其中,wi表示任意一节点的某阶位移模态,ε表示该阶位移模态对应的应变模态.

  • 1.3 小波变换原理

  • 小波变换是通过对一个原始小波(称为母小波或基本小波)的缩放和转换从而产生后续小波(称为子小波)的过程.小波函数ψx)可以通过平移和缩放来创建小波基函数ψuax [2425]

  • ψu,a(x)=1aψx-ua
    (12)
  • 其中uaRa ≠ 0,u为平移因子,反映信号频率和时间等信息,a为缩放因子.通过小波变换进行信号函数奇异性检测时,连续小波变换函数可以写成信号函数与小波复共轭函数的内积[24]

  • Wf(a,u)=1a- f(x)ψ*x-uadx
    (13)
  • 其中,fx)为信号函数,ψ*表示小波函数的复共轭,称为小波系数,其二进制小波变换可以表示为:

  • Wf2j,u=12j- f(x)ψ*x-u2jdx
    (14)
  • u = k2j时,式(14)即为离散小波变换.

  • 由于多尺度、空间属性和冗余系数的特点,小波分析能够检测信号中的细微变化或奇异性,如损伤或不连续性,因此可以采用小波分析辅助模态参数进行损伤识别.

  • 2 数值算例与实验验证

  • 2.1 模型验证

  • 在数值计算中梁的几何尺寸和材料参数为:长L=0.5m、宽b=0.025m、厚h=0.005m、密度ρ=2700kg/m3、弹性模量E=70GPa.为了验证有限元计算程序的正确性,首先采用了有限元法、COMSOL仿真软件及实验分别获得了不同情况下悬臂梁结构的前三阶固有频率,如表1和表2所示.计算中,损伤通过改变某单元的截面尺寸来模拟.实验中,在距固定端0.235m处人工制造一矩形切口用来模拟损伤,损伤宽为0.002m,深为0.0015m.损伤程度S由裂纹深度he与梁厚度h之比定义,即S = he/h.为保证有限元模型精确性,将梁结构均匀划分为500个单元进行计算.

  • 表1 不同方法计算的无旋转结构固有频率(Hz)对比

  • Table1 Comparison of natural frequencies of structures without rotation

  • 表2 不同方法计算的旋转结构固有频率(Hz)对比

  • Table2 Comparison of natural frequencies of structures with rotation

  • 由表1和表2可知,通过不同方法得到的结构固有频率十分接近,从而证明了本文建立的结构动力学模型是正确的.

  • 2.2 模态参数损伤识别

  • 下面进行损伤识别研究.首先,当ωR=0rad/s时,即不考虑结构旋转时,分别通过理论方法(有限元法)和实验方法获得了结构的位移和应变模态,如图2和图3所示.实验中,梁的几何尺寸和材料参数与2.1节中相同.同样在距固定端0.235m处人工制造矩形切口来模拟损伤,其宽度和深度分别为0.002m和0.0015m.实验中采用LMS SCADAS Mobile进行数据采集,该设备既可以采集加速度信号也可以采集应变信号.实验装置如图4所示.有限元法计算中,将梁结构均匀划分为500个单元进行计算.

  • 对于位移模态,采用加速度传感器测量梁上各点的振动信号.实验中,共设置17个振动测点,分别为距固定端0.05m、0.075m、0.1m、0.125m、0.15m、0.175m、0.2m、0.235m、0.25m、0.275m、0.3m、0.325m、0.35m、0.375m、0.4m、0.425m、0.45m处.采用敲击法对结构进行模态识别.通过对振动信号分析计算可以得到结构的位移模态.而对于应变模态,采用电阻应变片进行测量,共设置10个应变测点,分别为位于距固定端0.05m、0.1m、0.15m、0.2m、0.235m、0.25m、0.3m、0.35m、0.4m、0.45m处.应变片采用1/4桥进行接线.测量方法同样选择非常成熟的敲击模态识别法.

  • 图2 由理论方法和实验方法获得的结构位移模态

  • Fig.2 Displacement modes obtained by the theoretical and experimental methods

  • 图3 不同方法获得的结构应变模态(E1-实验无损,E2-实验有损(S=30%),T1-理论有损(S=30%))

  • Fig.3 Strain modes obtained by the different methods (E1-experimental mode of undamaged structure; E2-experimental mode of damaged structure (S=30%) ; T1-theoretical mode of damaged structure (S=30%) )

  • 图4 不考虑旋转悬臂梁结构损伤识别的实验装置

  • Fig.4 Experimental devices for damage identification of cantilever beam structures without rotation

  • 从图2可以看出,无论是有损还是无损结构,理论和实验的结果吻合都较好,因此再一次证明本文所建立的理论分析模型是正确的.同时由位移模态分析结果可知,损伤前后的差别并不明显,因此,必须附加其他信号处理方法,才能进行准确的损伤识别.若采用应变模态对损伤进行识别,由图3可见,在损伤附近(距固定端0.235m处),结构应变模态发生明显突变,由此便可判断损伤的位置.

  • 图5 实验中有损结构(S=30%)位移模态经过连续小波变换的灰度图

  • Fig.5 Gray images of wavelet transform for the displacement modes obtained by the experiment (S=30%)

  • 由以上分析可知,通过位移模态较难直接判断损伤位置,下面对实验得到的结构位移模态进行连续小波变换(采用双正交样条小波进行尺度因子为10的连续小波变换)和小波分解(采用“bior6.8”小波基函数进行三层离散小波分解),将得到的损伤前后小波系数作差,从而得到如下小波系数灰度图(图5)与小波系数差折线图(图6).由图5中的灰度分布可以发现,在距左端0.23m附近,存在一处亮度突变,由小波分析原理,该处即为损伤位置.但由于实验误差和边界效应影响,图中其他位置也出现了亮度突变,因此无法进行准确的损伤位置识别.需要同时借助图6中的小波系数差图进行判断.由图6可以发现,在损伤处(x=0.235m),位移模态小波系数差出现了明显的突变,这与采用应变模态进行损伤识别的实验结果是一致的,因此证实了采用小波分析技术与结构位移模态相结合来进行损伤识别是可行的.

  • 以上对不考虑旋转时悬臂梁结构的损伤识别研究证明,本文采用的损伤识别方法是正确的.在此基础上,将该方法应用于旋转结构的损伤识别中.在旋转悬臂梁损伤识别的算例中,梁的几何尺寸和材料参数为:L=0.8m、b=0.05m、h=0.007m、ρ=7860kg/m3E=210GPa、ωR=20rad/s.将梁结构沿轴线方向划分80个单元,单元长度为le=0.01m.将损伤位置设置在第40个单元处,并考虑四种损伤程度:S=0%(无损)、5%、20%和30%.

  • 图6 实验中有损结构(S=30%)位移模态的小波系数差

  • Fig.6 Differences of wavelet coefficient for the displacement modes obtained by the experiment (S=30%) )

  • 图7 不同损伤程度下旋转结构的位移模态

  • Fig.7 The displacement modes under different degrees of damage with rotation

  • 图8 不同损伤程度下旋转结构的应变模态

  • Fig.8 The strain modes under different degrees of damage with rotation

  • 图9 旋转结构位移模态的小波系数差

  • Fig.9 Differences of wavelet coefficient for the displacement modes with rotation

  • 图10 旋转结构位移模态经过连续小波变换的灰度图

  • Fig.10 Gray images of wavelet transform for the displacement modes with rotation

  • 针对四种不同的损伤程度,采用有限元法分别计算出结构前三阶位移模态和应变模态,如图7和图8所示.从图7可以看出,四种损伤程度下,结构的位移模态差别非常小且难以分辨,因此证明在旋转结构中仅使用位移模态很难进行损伤识别.而由图8所示的应变模态可以看出,对于旋转结构,应变模态对损伤仍然十分敏感,它通常在损伤处会发生突变,因此应变模态十分适合进行损伤识别.但第三阶应变模态在损伤处并未产生可识别的突变,这是因为损伤恰巧位于第三阶应变模态的节点附近.因此,在采用应变模态进行损伤识别时,应同时选择多阶应变模态进行对比识别.

  • 由于位移模态较难直接识别损伤,现采用小波分解技术结合位移模态参数进行损伤识别,首先提取S=0%和S=5%下的前三阶位移模态,采用“bior6.8”小波基函数对位移模态进行三层离散小波分解,并将损伤前后高频小波系数作差后便可以得到小波系数差,如图9所示.由图可知,在损伤处小波系数差出现突变,由此可以判断损伤位置,且其与采用应变模态进行识别的结果相同.

  • 最后,采用连续小波变换结合位移模态对旋转结构进行损伤识别,同样,采用S=0%和S=5%下的三阶位移模态,对位移模态进行采用双正交样条小波进行尺度因子为10的连续小波变换并将得到的损伤前后小波系数差的绝对值绘制出小波变换灰度图,采用信号延伸的处理方式减小了边界效应的影响,结果如图10所示.由图可知,处理后边界效应对这三阶小波变换灰度图的影响极小,利用灰度图的亮度突变可以准确判断损伤位置.因此,综上可知采用位移模态结合小波分析技术进行旋转结构损伤识别的方法是可行的.

  • 3 结论

  • 本文进行了基于模态参数(位移模态和应变模态)的旋转结构损伤识别的研究.具体以有限元法构建旋转悬臂梁动力学模型,通过改变结构某单元厚度来模拟结构损伤,并提取不同阶次模态参数分析比较以确定损伤位置,主要结论如下:

  • (1)通过对结构损伤前后的模态参数进行对比,发现损伤前后位移模态的差别并不明显,而应变模态的损伤识别效果很好,可以根据损伤前后应变模态的突变位置来进行损伤识别.

  • (2)采用应变模态进行损伤识别时,为避免损伤位于某阶次模态节点而影响识别效果的情况,有必要提取多阶应变模态进行比较识别.

  • (3)对位移模态进行小波分析技术处理后,可以较准确地进行结构损伤识别.

  • (4)在进行小波分析技术结合位移模态损伤识别时,应对模态数据进行处理,减少小波边界效应的影响,以提高损伤识别的精确度.

  • (5)算例证明基于模态参数的损伤识别方法对于旋转结构同样有效.

  • 参考文献

    • [1] 郑栋梁,李中付,华宏星.结构早期损伤识别技术的现状和发展趋势 [J].振动与冲击,2002,21(2):1-6.ZHENG D L,LI Z F,HUA H X.A summary review of structural initial damage identification methods [J].Journal of Vibration and Shock,2002,21(2):1-6.(in Chinese)

    • [2] 李慧民,董美美,熊雄,等.基于振动的结构损伤识别研究综述 [J].建筑结构,2021,51(4):45-50.LI H M,DONG M M,XIONG X,et al.State-of-the-art review of vibration-based damage identification framework for structures [J].Building Structure,2021,51(4):45-50.(in Chinese)

    • [3] 饶文碧,吴代华.RBF神经网络及其在结构损伤识别中的应用研究 [J].固体力学学报,2002,23(4):477-482.RAO W B,WU D H.RBFN and its application for structural damage recognition [J].Chinese Journal of Solid Mechanics,2002,23(4):477-482.(in Chinese)

    • [4] KUMAR M,SHENOI R A,COX S J.Experimental validation of modal strain energies based damage identification method for a composite sandwich beam [J].Composites Science and Technology,2009,69:1635-1643.

    • [5] 李兆霞,王滢,吴佰建,等.桥梁结构劣化与损伤过程的多尺度分析方法及其应用 [J].固体力学学报,2010,31(6):731-756.LI Z X,WANG Y,WU B J,et al.Multi-scale modeling and analyses on structural deterioration and damage in long-span bridges and its application [J].Chinese Journal of Solid Mechanics,2010,31(6):731-756.(in Chinese)

    • [6] Li Y Y.Hypersensitivity of strain-based indicators for structural damage identification:a review [J].Mechanical Systems and Signal Processing,2010,24:653-664.

    • [7] 聂振华,马宏伟.基于重构相空间的结构损伤识别方法 [J].固体力学学报,2013,34(1):83-92.NIE Z H,MA H W.Structural damage detection based on reconstructed phase space [J].Chinese Journal of Solid Mechanics,2013,34(1):83-92.(in Chinese)

    • [8] 徐伟华,吕中荣,刘济科.基于振动响应的杆结构损伤检测 [J].固体力学学报,2010,31(1):48-52.XU W H,LV Z R,LIU J K.Damage detection for rods from vibration responses [J].Chinese Journal of Solid Mechanics,2010,31(1):48-52.(in Chinese)

    • [9] 郭惠勇,李正良.基于应变能等效指标的结构损伤识别技术研究 [J].固体力学学报,2013,34(3):286-291.GUO H Y,LI Z L.Structural damage identification method based on strain energy equivalence parameter [J].Chinese Journal of Solid Mechanics,2013,34(3):286-291.(in Chinese)

    • [10] FAN W,QIAO P Z.Vibration-based damage identification methods:a review and comparative study [J].Structural Health Monitoring,2011,10:83-110.

    • [11] ZHANG Y,BERNAL D.Damage localization from projections of free vibration signals [J].Journal of Sound and Vibration,2017,394:146-154.

    • [12] SAHIN M,SHENOI R A.Quantification and localisation of damage in beam-like structures by using artificial neural networks with experimental validation [J].Engineering Structures,2003,25:1785-1802.

    • [13] 赵才友,王平,全顺喜,等.基于应变模态变化率的钢轨损伤检测 [J].振动、测试与诊断,2012,32(5):723-729.ZHAO C Y,WANG P,QUAN S X,et al.Detection method for broken rail based on rate of change of strain mode [J].Journal of Vibration,Measurement & Diagnosis,2012,32(5):723-729.(in Chinese)

    • [14] 梁岗,史单艳,沈奎双.多裂纹梁不确定性损伤识别和实验研究 [J].机械科学与技术,2020,39(9):1335-1345.LIANG G,SHI D Y,SHEN K S.Uncertain damage detection and experimental study of multiple cracks in beams [J].Mechanical Science and Technology for Aerospace Engineering,2020,39(9):1335-1345.(in Chinese)

    • [15] 徐强,刘博,陈健云,等.基于加权最小二乘的结构模态参数与损伤识别 [J].水利学报,2020,51(1):23-32.XU Q,LIU B,CHEN J Y.Structural modal parameters and damage region identification based on least squares method with frequency band weighting approach [J].Journal of Hydraulic Engineering,2020,51(1):23-32.(in Chinese)

    • [16] PENG Z K,CHU F L.Application of the wavelet transform in machine condition monitoring and fault diagnostics:a review with bibliography [J].Mechanical Systems and Signal Processing,2004,18:199-221.

    • [17] ZHONG S C,OYADIJI S O.Detection of cracks in simply-supported beams by continuous wavelet transform of reconstructed modal data [J].Computers and Structures,2011,89:127-148.

    • [18] 缪炳荣,杨树旺,王名月,等.利用振动响应的多种结构损伤识别方法比较 [J].振动工程学报,2020,33(4):724-733.MIAO B R,YANG S W,WANG M Y.Comparison of various structural damage identification methods using vibration response [J].Journal of Vibration Engineering,2020,33(4):724-733.(in Chinese)

    • [19] 宋子收,周奎,李胡生,等.基于曲率模态和小波系数差的损伤识别 [J].公路交通科技,2010,27(11):61-66.SONG Z S,ZHOU K,LI H S,et al.Damage identification based on curvature mode and difference of wavelet coefficients [J].Journal of Highway and Transportation Research and Development,2010,27(11):61-66.(in Chinese)

    • [20] 唐冶,王涛,丁千.主动控制压电旋转悬臂梁的参数振动稳定性分析 [J].力学学报,2019,51(6):1872-1881.TANG Y,WANG T,DING Q.Stability analysis on parametric vibration of piezoelectric rotating cantilever beam with active control [J].Chinese Journal of Theoretical and Applied Mechanics,2019,51(6):1872-1881.(in Chinese)

    • [21] ARVIN H,HOSSEINI H M S,KIANI Y.Free vibration analysis of pre/post buckled rotating functionally graded beams subjected to uniform temperature rise [J].Thin-Walled Structures,2021,158:107187.

    • [22] ARVIN H,KIANI Y.Vibration analysis of rotating composite beams reinforced with carbon nanotubes in thermal environment [J].International Journal of Mechanical Sciences,2019,164:105187.

    • [23] LEI Y G,LIN J,HE Z J,et al.A review on empirical mode decomposition in fault diagnosis of rotating machinery [J].Mechanical Systems and Signal Processing,2013,35(1-2):108-126.

    • [24] CHEN J L,LI Z P,PAN J,et al.Wavelet transform based on inner product in fault diagnosis of rotating machinery:a review [J].Mechanical Systems and Signal Processing,2016,70:1-35.

    • [25] 宋振华,王志华,马宏伟.基于小波分析的超声导波管道裂纹检测方法研究 [J].固体力学学报,2009,30(4):368-375.SONG Z H,WANG Z H,MA H W.Study on wavelet-based crack detection in pipes using ultrasonic longitudinal guided-wave [J].Chinese Journal of Solid Mechanics,2009,30(4):368-375.(in Chinese)

  • 参考文献

    • [1] 郑栋梁,李中付,华宏星.结构早期损伤识别技术的现状和发展趋势 [J].振动与冲击,2002,21(2):1-6.ZHENG D L,LI Z F,HUA H X.A summary review of structural initial damage identification methods [J].Journal of Vibration and Shock,2002,21(2):1-6.(in Chinese)

    • [2] 李慧民,董美美,熊雄,等.基于振动的结构损伤识别研究综述 [J].建筑结构,2021,51(4):45-50.LI H M,DONG M M,XIONG X,et al.State-of-the-art review of vibration-based damage identification framework for structures [J].Building Structure,2021,51(4):45-50.(in Chinese)

    • [3] 饶文碧,吴代华.RBF神经网络及其在结构损伤识别中的应用研究 [J].固体力学学报,2002,23(4):477-482.RAO W B,WU D H.RBFN and its application for structural damage recognition [J].Chinese Journal of Solid Mechanics,2002,23(4):477-482.(in Chinese)

    • [4] KUMAR M,SHENOI R A,COX S J.Experimental validation of modal strain energies based damage identification method for a composite sandwich beam [J].Composites Science and Technology,2009,69:1635-1643.

    • [5] 李兆霞,王滢,吴佰建,等.桥梁结构劣化与损伤过程的多尺度分析方法及其应用 [J].固体力学学报,2010,31(6):731-756.LI Z X,WANG Y,WU B J,et al.Multi-scale modeling and analyses on structural deterioration and damage in long-span bridges and its application [J].Chinese Journal of Solid Mechanics,2010,31(6):731-756.(in Chinese)

    • [6] Li Y Y.Hypersensitivity of strain-based indicators for structural damage identification:a review [J].Mechanical Systems and Signal Processing,2010,24:653-664.

    • [7] 聂振华,马宏伟.基于重构相空间的结构损伤识别方法 [J].固体力学学报,2013,34(1):83-92.NIE Z H,MA H W.Structural damage detection based on reconstructed phase space [J].Chinese Journal of Solid Mechanics,2013,34(1):83-92.(in Chinese)

    • [8] 徐伟华,吕中荣,刘济科.基于振动响应的杆结构损伤检测 [J].固体力学学报,2010,31(1):48-52.XU W H,LV Z R,LIU J K.Damage detection for rods from vibration responses [J].Chinese Journal of Solid Mechanics,2010,31(1):48-52.(in Chinese)

    • [9] 郭惠勇,李正良.基于应变能等效指标的结构损伤识别技术研究 [J].固体力学学报,2013,34(3):286-291.GUO H Y,LI Z L.Structural damage identification method based on strain energy equivalence parameter [J].Chinese Journal of Solid Mechanics,2013,34(3):286-291.(in Chinese)

    • [10] FAN W,QIAO P Z.Vibration-based damage identification methods:a review and comparative study [J].Structural Health Monitoring,2011,10:83-110.

    • [11] ZHANG Y,BERNAL D.Damage localization from projections of free vibration signals [J].Journal of Sound and Vibration,2017,394:146-154.

    • [12] SAHIN M,SHENOI R A.Quantification and localisation of damage in beam-like structures by using artificial neural networks with experimental validation [J].Engineering Structures,2003,25:1785-1802.

    • [13] 赵才友,王平,全顺喜,等.基于应变模态变化率的钢轨损伤检测 [J].振动、测试与诊断,2012,32(5):723-729.ZHAO C Y,WANG P,QUAN S X,et al.Detection method for broken rail based on rate of change of strain mode [J].Journal of Vibration,Measurement & Diagnosis,2012,32(5):723-729.(in Chinese)

    • [14] 梁岗,史单艳,沈奎双.多裂纹梁不确定性损伤识别和实验研究 [J].机械科学与技术,2020,39(9):1335-1345.LIANG G,SHI D Y,SHEN K S.Uncertain damage detection and experimental study of multiple cracks in beams [J].Mechanical Science and Technology for Aerospace Engineering,2020,39(9):1335-1345.(in Chinese)

    • [15] 徐强,刘博,陈健云,等.基于加权最小二乘的结构模态参数与损伤识别 [J].水利学报,2020,51(1):23-32.XU Q,LIU B,CHEN J Y.Structural modal parameters and damage region identification based on least squares method with frequency band weighting approach [J].Journal of Hydraulic Engineering,2020,51(1):23-32.(in Chinese)

    • [16] PENG Z K,CHU F L.Application of the wavelet transform in machine condition monitoring and fault diagnostics:a review with bibliography [J].Mechanical Systems and Signal Processing,2004,18:199-221.

    • [17] ZHONG S C,OYADIJI S O.Detection of cracks in simply-supported beams by continuous wavelet transform of reconstructed modal data [J].Computers and Structures,2011,89:127-148.

    • [18] 缪炳荣,杨树旺,王名月,等.利用振动响应的多种结构损伤识别方法比较 [J].振动工程学报,2020,33(4):724-733.MIAO B R,YANG S W,WANG M Y.Comparison of various structural damage identification methods using vibration response [J].Journal of Vibration Engineering,2020,33(4):724-733.(in Chinese)

    • [19] 宋子收,周奎,李胡生,等.基于曲率模态和小波系数差的损伤识别 [J].公路交通科技,2010,27(11):61-66.SONG Z S,ZHOU K,LI H S,et al.Damage identification based on curvature mode and difference of wavelet coefficients [J].Journal of Highway and Transportation Research and Development,2010,27(11):61-66.(in Chinese)

    • [20] 唐冶,王涛,丁千.主动控制压电旋转悬臂梁的参数振动稳定性分析 [J].力学学报,2019,51(6):1872-1881.TANG Y,WANG T,DING Q.Stability analysis on parametric vibration of piezoelectric rotating cantilever beam with active control [J].Chinese Journal of Theoretical and Applied Mechanics,2019,51(6):1872-1881.(in Chinese)

    • [21] ARVIN H,HOSSEINI H M S,KIANI Y.Free vibration analysis of pre/post buckled rotating functionally graded beams subjected to uniform temperature rise [J].Thin-Walled Structures,2021,158:107187.

    • [22] ARVIN H,KIANI Y.Vibration analysis of rotating composite beams reinforced with carbon nanotubes in thermal environment [J].International Journal of Mechanical Sciences,2019,164:105187.

    • [23] LEI Y G,LIN J,HE Z J,et al.A review on empirical mode decomposition in fault diagnosis of rotating machinery [J].Mechanical Systems and Signal Processing,2013,35(1-2):108-126.

    • [24] CHEN J L,LI Z P,PAN J,et al.Wavelet transform based on inner product in fault diagnosis of rotating machinery:a review [J].Mechanical Systems and Signal Processing,2016,70:1-35.

    • [25] 宋振华,王志华,马宏伟.基于小波分析的超声导波管道裂纹检测方法研究 [J].固体力学学报,2009,30(4):368-375.SONG Z H,WANG Z H,MA H W.Study on wavelet-based crack detection in pipes using ultrasonic longitudinal guided-wave [J].Chinese Journal of Solid Mechanics,2009,30(4):368-375.(in Chinese)

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