随机减量时域模态识别技术——译文集

随机减量时域法是国外七十年代发展起来的模态识别技术。它由随机减量法和依氏时域法组成。其主要原理是在输入未知的情况下,根据实测的随机振动响应得到结构的随机减量特征,然后从随机减量特征识别结构的模态参数:自然频率、阻尼系数和振型。随机减量技术最初是由Cole按单模态发展的,后来Ibrahim将它加以改进,保持了多站信号的相位关系,得到了多站随机减量特征。Ibrahim的时域模态识别法则利用时域的自由衰减响应来识别     

基于速度响应信号的模态参数识别ITD算法研究

以环境随机激励作用下的大型塔架结构为研究背景,提出了一种基于速度响应信号的ITD方法。首先应用随机减量技术从速度随机响应信号中提取速度自由响应信号,然后推导出基于速度信号的ITD法并应用于识别系统的模态参数。该方法不用将速度信号积分成位移信号,而是直接对速度信号进行模态参数识别,避免了积分过程中引入误差。将试验结果与传统的基于位移响应的ITD法和峰值谱法进行对比,证明该方法具有较高的计算精度。     

基于随机减量技术的模态参数识别方法探讨

大型基础工程结构的特征参数识别通常是通过对环境载荷激励的结构响应进行分析来实现,随机减量(Random Decrement,RD)技术是环境激励下的模态参数识别方法中应用较广的方法。在实际应用中受环境、测量等条件的限制,信号常为含有某些优势频率的非平稳信号,常常导致随机减量技术在识别结构参数尤其是系统阻尼时带来较大误差。为提高随机减量技术在环境激励作用下识别结构参数的准确性,文中从分析随机减量信号频谱中的频率分布特性入手,结合随机减量函数产生的触发条件,给出了一种利用信号频谱的统计特征进行模态参数识别的方法。数值仿真结果表明该函数能准确识别在含有优势频率环境载荷作用下的结构参数。     

基于环境激励的塔器模态参数识别研究

塔器的模态参数是影响设备动力学特性的重要指标,如何准确方便地获取塔器的模态参数是亟待解决的问题。首次将环境激励法用于塔器的参数识别,通过结合随机减量技术,从塔器的加速度响应信号中提取了模态参数。模拟计算与现场测试结果表明本文的方法易实施、精度高,具有工程应用价值。此方法可为今后塔器模态参数的测量和识别提供参考。     

模态辨识中随机减量技术的实用改进

针对模态辨识实践中的随机减量加速度特征信号奇异值问题和结构实模态提取问题,提出相应的特征信号截断方法和最小距离法,改善结构模态辨识效果。首先,分析随机减量加速度特征信号的奇异值产生原因,提出特征信号截断方法,用于后续Ibrahim时域处理;其次,通过优化模型建立最小距离法的计算公式,便于从辨识所得复模态中提取结构实模态;最后,通过数值算例和结构模型实验,验证所提方法的可行性。结果表明:随机减量加速度特征信号的有效截断比例可取为1/200～1/50;最小距离法适用于各种类型响应下的结构实模态提取,抗噪能力强。     

短时脉冲激励下隧道振动响应与模态参数识别

为了研究短时脉冲激振力下隧道结构振动响应及有效地提取隧道结构的模态特征。首先分析了锤击作用下的不同短时脉冲激振力精度及其频域特性,其次将短时脉冲激振力应用于上海地铁12号某盾构隧道进行了现场动力测试,最后分析了脉冲激振与隧道结构响应之间的传递函数,并结合随机减量、正交多项式法及自回归滑动平均模型法有效地提取隧道结构的模态参数。结果表明:短时脉冲激振力的中低频振动信号在隧道结构中传递特性较好,传递距离较远。隧道结构的模态频率呈现明显低频特征,前10阶模态频率在100 Hz以下。因此,短时脉冲激振力能够很好地应用于隧道动力测试及模态识别,可为基于模态特征的隧道结构损伤识别及健康监测多个研究领域提供有效的支撑和参考依据。     

随机减量法在斜拉桥拉索模态参数识别中的应用

斜拉桥拉索模态参数(固有频率、阻尼比)在索力测试、拉索减振、实时控制等方面起着重要作用。文中利用随机减量技术从岳阳洞庭桥环境激励下拾取的拉索的加速度响应中分离出自由衰减振动加速度响应信号，将获取的加速度响应信号表达为一理论形式，综合运用参数识别、最优估计理论，识别出拉索的模态参数，与理论值吻合良好。本文方法简单，试验容易实施，具有工程实用价值。数字仿真与工程测试结果表明了方法的有效性和可行性。     

短样本条件下提高HHT识别模态参数精度的方法

由于在短样本条件下Hilbert-Huang变换(Hilbert-Huang transform,简称HHT)识别模态参数的精度主要受经验模态分解(empirical modal decomlposition,简称EMD)模式混合和随机减量法(random decrement teelarlology,简称RDT)提取自由衰减响应时平均次数不足的影响,针对这两个影响因素,引入带宽限制信号抑制EMD的模式混合,提高EMD的精度;并引入分层抽样技术,提出基于拟合偏差和样本量的层权确定方法来进行多次识别,然后加权平均,提高RDT的总平均次数.仿真试验和应用实例表明,结合分层抽样的限制带宽EMD识别模态参数的方法能提高短样本条件下HHT识别模态参数的精度.     

循环对称结构随机子空间法模态分析及验证

为探究仅基于响应测量的随机子空间法能否准确识别循环对称结构的重根模态,以制动盘为例,分别对其进行基于随机子空间法的模态分析及传统的试验模态分析,并提取了相应的模态参数,结果显示二者前9阶固有频率最大误差仅为0.66%,且振型吻合。表明仅基于响应测量的随机子空间法同样适用于循环对称类结构的模态分析。     

基于Hilbert-Huang变换与理想带通滤波器的系统识别

针对经验模态分解存在模态混叠现象,提出基于Hilbert-Huang变换与理想带通滤波器的系统识别方法。该方法利用傅里叶变换得到结构加速度响应频响函数,粗略估计固有频率范围,通过半功率带宽法设计理想带通滤波器,定量化确定通带带宽,使信号在经过滤波器后频域内零相移,同时不改变其幅值谱。结构响应通过指定频带的理想带通滤波器产生若干窄带信号,利用经验模态分解获取结构模态响应,经Hilbert变换构造模态响应解析信号,并通过线性最小二乘拟合提取结构模态参数与物理参数。结果表明:半功率带宽法可实现带通滤波器频带的定量化设计,理想带通滤波器的零相移特点较好契合Hilbert-Huang变换用于系统识别的要求,两者结合可有效地解决模态混叠现象,减少虚假模态,大大提高结构系统识别精度。     

Output-only modal analysis of wind turbine tower based on vibration response under emergency stop

The identification technique of output-only modal parameters is proposed for the large wind turbine tower under emergency stop. Compared with the response of regular operating conditions, the immediate tower structural response under emergency stop much more resembles a state of free vibration, which is more appropriate for the modal identification of the wind turbine tower. The vibration response is measured in the nacelle, which is easy to perform in the field modal test. The variational mode decomposition (VMD) is applied to decompose the vibration response into several band-limited intrinsic mode functions. The free responses of decomposed functions are extracted by applying the random decrement technique (RDT). Finally, the modal damping ratio and natural frequency are identified from each free modal response by using the Hilbert transform method. Simulations and a 1.5 MW wind turbine field modal test results verify the effectiveness of the proposed identification method. The main modal parameters of wind turbine, including weak modes, are effectively extracted by using output-only vibration responses under emergency stop. The modal parameter identification method is provided for the large wind turbine structure under the engineering condition.     

A modified random decrement technique for modal identification from nonstationary ambient response data only

Modal identification is considered from response data of structural system under nonstationary ambient vibration. In a previous paper, we showed that by assuming the ambient excitation to be nonstationary white noise in the form of a product model, the nonstationary response signals can be converted into free-vibration data via the correlation technique. In the present paper, if the ambient excitation can be modeled as a nonstationary white noise in the form of a product model, then the nonstationary cross random decrement signatures of structural response evaluated at any fixed time instant are shown theoretically to be proportional to the nonstationary cross-correlation functions. The practical problem of insufficient data samples available for evaluating nonstationary random decrement signatures can be approximately resolved by first extracting the amplitude-modulating function from the response and then transforming the nonstationary responses into stationary ones. Modal-parameter identification can then be performed using the Ibrahim time-domain technique, which is effective at identifying closely spaced modes. The theory proposed can be further extended by using the filtering concept to cover the case of nonstationary color excitations. Numerical simulations confirm the validity of the proposed method for identification of modal parameters from nonstationary ambient response data.     

Measurements of dynamic properties of a medium span suspension bridge by using the wavelet transforms

The aim of this paper is to show the capabilities of the real-time kinematic (RTK) global positioning network system (GPS) to measure the low-frequency vibration of a medium span suspension bridge. In particular, this paper presents the results of studies conducted on the identification of modal parameters including natural frequencies, damping coefficients and mode shapes of a suspension bridge using ambient excitation loads. A real-time kinematic (RTK) global positioning system (GPS) was designed and installed on the Nottingham Wilford Bridge to provide long-term and real-time measurement of bridge deck movement. An approach to estimate modal parameters, from only output data in the time domain using the wavelet transform, is presented. Displacements responses of the bridge are used in the wavelet transform to identify its dynamic characteristics. The modal properties were extracted using a two-step methodology. In the first step, the random decrement method was used to transform random signals in free vibration responses. Secondly, a wavelets-based technique was used to extract natural frequencies and to determine the mode shapes of the structure. This method was compared with the well-established techniques eigensystem realisation algorithm showing a difference of 1% in the estimated first natural frequency.The efficiency of RTK–GPS was demonstrated in the full-scale measurement. In particular, the results showed that the RTK–GPS data can be used for extracting modal properties from in-service-loads induced low-frequency vibration (<5 Hz) by processing the signal with the wavelets transform.     

Harmonics elimination algorithm for operational modal analysis using random decrement technique

Operational modal analysis (OMA) extracts modal parameters of a structure using their output response, during operation in general. OMA, when applied to mechanical engineering structures is often faced with the problem of harmonics present in the output response, and can cause erroneous modal extraction. This paper demonstrates for the first time that the random decrement (RD) method can be efficiently employed to eliminate the harmonics from the randomdec signatures. Further, the research work shows effective elimination of large amplitude harmonics also by proposing inclusion of additional random excitation. This obviously need not be recorded for analysis, as is the case with any other OMA method. The free decays obtained from RD have been used for system modal identification using eigen-system realization algorithm (ERA). The proposed harmonic elimination method has an advantage over previous methods in that it does not require the harmonic frequencies to be known and can be used for multiple harmonics, including periodic signals. The theory behind harmonic elimination is first developed and validated. The effectiveness of the method is demonstrated through a simulated study and then by experimental studies on a beam and a more complex F-shape structure, which resembles in shape to the skeleton of a drilling or milling machine tool. Cases with presence of single and multiple harmonics in the response are considered.     

基于递归理论的泵站压力管道运行状态监测

针对不利因素导致的管道运行异常问题，提出一种基于递归理论的泵站管道运行状态监测方法。首先，通过振动传感器提取压力管道关键部位的实测信息，并将同一位置不同方向的数据信息进行融合，得到一组反映结构整体动力特性的综合数据；其次，利用伪近临法与互信息法分别选取相空间重构参数m和τ；最后，绘制并计算代表管道动力特性的递归图及递归量化指标。将该方法应用于景泰川工程二期七泵站管道运行监测，通过设置不同的运行工况进行验证，结果表明：机组开关瞬间与稳定运行工况下，管道结构振动信号的递归图呈现不同模式，递归量化指标-确定性、对角线平均长度L、递归率及递归熵也呈现明显差异，能有效区分管道振动状态。该方法为压力管道的无损动态监测提供了新思路。     

基于递归理论的泵站压力管道运行状态监测

为了准确地识别建筑结构的模态参数，提出了一种基于多重信号分类算法（multiple signal classification,简称MUSIC）、经验小波变换（empirical wavelet transform,简称EWT）和同步提取小波变换（synchroextracting transform ，简称SET）的结构模态参数识别方法。首先，通过MUSIC-EWT对实测振动信号进行分解；其次，使用SET对单模态信号进行去噪处理；然后，采用自然环境激励技术（natural excitation technique,简称NExT）得到单模态信号的自由衰减响应；最后，利用Hilbert变换（hilbert transform,简称HT）和曲线拟合获得结构的自振频率和阻尼比。通过三层框架结构的数值模拟验证了该方法的准确性和鲁棒性。利用该方法对台风“达维”作用下广州中信广场的实测加速度数据进行分析，并将估计的结构模态参数和其他识别方法的分析结果进行对比，进一步证明了该方法的准确性和鲁棒性。     

Response-only modal identification using random decrement algorithm with time-varying threshold level

Modal Identification from response data only is studied for structural systems under nonstationary ambient vibration. The topic of this paper is the estimation of modal parameters from nonstationary ambient vibration data by applying the random decrement algorithm with time-varying threshold level. In the conventional random decrement algorithm, the threshold level for evaluating randomdec signatures is defined as the standard deviation value of response data of the reference channel. The distortion of randomdec signatures may be, however, induced by the error involved in noise from the original response data in practice. To improve the accuracy of identification, a modification of the sampling procedure in random decrement algorithm is proposed for modal-parameter identification from the nonstationary ambient response data. The time-varying threshold level is presented for the acquisition of available sample time history to perform averaging analysis, and defined as the temporal root-mean-square function of structural response, which can appropriately describe a wide variety of nonstationary behaviors in reality, such as the time-varying amplitude (variance) of a nonstationary process in a seismic record. Numerical simulations confirm the validity and robustness of the proposed modal-identification method from nonstationary ambient response data under noisy conditions.     

Influence of a harmonic in the response on randomdec signature

Operational Modal Analysis (OMA) extracts modal parameters of a structure using their output response, during operation in general. OMA, when applied to mechanical engineering structures is often faced with the problem of harmonics present in the output response, and can cause erroneous modal extraction. The random decrement (RD) method of OMA helps extract randomdec signature data that can be further processed to obtain modal parameters of a structure. This paper for the first time analyses influence of a harmonic in the response on randomdec signature. Fundamental equations based on probability are derived for analyzing the influence of a harmonic on randomdec signature. These probabilistic equations are then used to predict the amplitude of the harmonic in randomdec signature. Randomdec signature of a pure harmonic signal is also derived and it is shown that it is of the same frequency as that of the harmonic signal, but has an amplitude equal to the trigger level used to find the randomdec.Based on the developed theory, new insights into the influence of harmonic on randomdec are presented based on an example. It is shown that the influence of the harmonic on randomdec is characterized by the conditional probability density function of the harmonic. It is found that more unsymmetrical is this PDF, more is the amplitude of the harmonic that is present in the randomdec signature. The amplitude of the harmonic in the randomdec is shown to be the conditional expected value of the harmonic. It is also shown that as the random component of the response increases then the amplitude of the harmonic in the randomdec decreases and in the limit can be completely eliminated.