共查询到17条相似文献，搜索用时 187 毫秒
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详细推导了多自由度结构多测点加速度响应的互功率谱模态矩阵展开式。进而给出了未知激励条件下基于各测点加速度响应互功率谱的频域多参考点模态识别法,同文献相比,该法适用于更广范围的激励条件。在频域平均法的辅助下,对ASCE SHM Benchmark问题的解析模型仿真加速度响应数据进行识别,结果表明该法有较好的识别精度,是一个有望应用于在线监测环境下的模态识别算法。 相似文献
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为开展MEMS型加速度传感器在超高层建筑振动监测应用中的性能对比测试,选取4种不同类型MEMS型加速度传感器与G1B型力平衡式加速度传感器,将其安装在地王大厦相同测点,对MEMS型、G1B型加速度传感器记录的结构环境振动数据进行时程、频谱和模态频率对比分析,并对其记录的结构地震响应进行时域及频域对比。研究结果表明,不同类型MEMS型加速度传感器仪器噪声均大于G1B型加速度传感器,其中MEMS-I型加速度传感器噪声水平相对较小,与G1B型加速度传感器模态频率识别结果及地震响应监测数据吻合较好,验证了MEMS-I型加速度传感器可较准确地记录到结构强振动响应,适用于超高层建筑日常结构振动监测。 相似文献
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基于Hilbert-Huang变换和随机子空间识别技术提出了两种土木工程结构的模态参数识别方法。方法一是基于Hilbert-Huang变换和自然激励技术,通过经验模态分解和Hilbert变换提取信号的瞬时特性,进而利用自然激励技术和模态分析的基本理论识别结构的模态参数;方法二是基于经验模态分解和随机子空间识别技术,通过经验模态分解对信号进行预处理,进而运用随机子空间识别方法处理得到的结构单阶模态响应以识别结构的模态参数。利用这两种方法,通过对一12层钢筋混凝土框架模型振动台试验测点加速度记录的处理,识别了该模型结构的模态参数。识别结果与传统的基于傅里叶变换的识别结果及有限元分析结果的对比验证了这两种方法的可行性和实用性。 相似文献
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Morlet 小波用于环境激励下的模态参数识别研究 总被引：2，自引：0，他引：2
本文分别从卷积和Parseval定理的角度推导了非正交小波变换系数的实用计算方法。在环境激励下以互相关函数代替系统的自由响应数据,给出了基于Morlet小波变换的频率、阻尼比的参数识别方法,重点介绍了基于最小二乘法的振型识别技术。采用2层楼仿真算例和潮白河桥应用实例验证本算法,识别结果表明基于Morlet小波变换的模态参数识别技术能够有效地识别出环境激励下系统的模态参数。 相似文献
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基于Hilbert-Huang变换和随机减量技术的模态参数识别 总被引：2，自引：0，他引：2
傅里叶分析的信号处理方法对非线性、非平稳信号的处理能力差,传统的模态参数识别方法也存在阻尼比识别精度不高的问题。基于Hilbert-Huang变换和随机减量技术提出了一种新的、实用的模态参数识别方法,首先对结构振动信号进行滤波处理和经验模态分解,得到若干阶本征模态响应,然后利用随机减量技术提取自由衰减响应,进而由Hilbert-Huang变换得到信号的瞬时特性,最后结合模态识别的基本理论识别结构的模态频率和模态阻尼比。为了验证这一方法的有效性,对12层钢筋混凝土框架模型振动台试验一测点的加速度记录进行了处理,识别了模态参数,识别结果与其它识别方法及有限元分析结果的对比表明该方法识别模态频率是可靠的,而模态阻尼比识别的精准性仍然难以确认。 相似文献
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模态参数是有效评估结构安全状况的关键参数,在结构抗震加固和健康诊断领域得到广泛应用。与频域法相比较,时域法直接利用实测的振动信号识别模态参数,不需要进行频域变换,减少数据处理带来的误差,并且可以实现大型结构的在线识别,真实地反应结构的现状。以同济大学12层钢筋混凝土标准框架振动台模型试验完整数据为对象,在详细介绍ITD法和复指数法2种时域法理论的基础上,通过编程选取结构不同测点的振动加速度时程数据,识别了小震和强震工况下12层钢筋混凝土框架模型振动台试验模型的模态频率和阻尼比,并结合移动谱识别结构模态参数的时变特性。结果表明:ITD法和复指数法可有效地识别结构的模态参数,自振频率的识别精度较高,而阻尼比的离散度较大;小震工况频率变化值不大,而强震工况频率值较初始时刻有明显的下降,这与试验现象是吻合的,进一步说明移动谱与这2种时域法相结合可以反应结构在塑性阶段的参数时变特性。 相似文献
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珠江黄埔大桥模态频率连续监测中的温度影响Ⅰ:频率识别 总被引：2，自引：2，他引：0
为研究环境温度对珠江黄埔大桥频率监测的影响,首先要对大桥模态频率进行连续识别。珠江黄埔大桥上架设的监测系统为强震动台阵,相较于其他健康监测系统测点较少,因此,应基于强震动台阵系统的特点,选取合适的方法对大桥频率进行识别。本文通过对比分析平均正则化功率谱法(ANPSD)、频域分解法(FDD)和协方差驱动的随机子空间法(Cov-SSI)的识别结果,择优应用于珠江黄埔大桥的频率自动识别中。采用珠江黄埔大桥强震动台阵记录的2013年4月至11月加速度响应数据进行频率识别,识别结果可用于观测和研究大桥频率在环境影响下的波动情况。 相似文献
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有限观测信息下的参数识别是结构健康监测领域内的一个热点问题,传统的卡尔曼滤波(Kalman Filter,KF)不能识别结构参数,递推最小二乘法(Recursive Least Square Estimation,RLSE)可用于参数识别,但需已知结构全部响应,为此提出一种基于KF和RLSE的参数联合识别法,该方法首先利用部分自由度上的加速度响应观测值,通过KF估计下一步的系统响应信息,包括速度和位移响应;然后,基于该响应估计信息和当前步的结构参数估计值,根据运动平衡方程,获得下一步的加速度响应估计值;最后,利用已观测的有限加速度响应,获得改进的加速度响应向量,进而基于RLSE获得下一步的结构参数识别值。简支梁数值算例结果表明,该方法能准确识别结构参数,同时能实现系统响应的有效估计。 相似文献
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对一基础隔震钢筋混凝土框架结构在无填充墙情况下进行了环境激励下的动力测试,重点利用Hilbert-Huang变换与随机减量技术相结合的方法识别了其模态参数,并与随机子空间识别法、有理分式多项式法识别的结果进行了对比。识别结果表明在环境激励下,基础隔震结构的基本周期远小于多遇和罕遇地震工况下设计计算的基本周期;等效黏滞阻尼比很小,近乎于基础固定模型。对隔震层阻尼特性的分析表明,环境激励下可以将基础隔震结构视为经典的比例阻尼系统。进一步以识别的模态参数为基准,采用优化的方法数值反演了环境激励下该结构隔震层的实际水平等效刚度,结果表明其值为多遇地震下计算刚度取值的10.75倍。 相似文献
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A frequency and spatial domain decomposition method （FSDD） for operational modal analysis （OMA） is presented in this paper, which is an extension of the complex mode indicator function （CMIF） method for experimental modal analysis （EMA）. The theoretical background of the FSDD method is clarified, Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density （PSD） is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method. 相似文献
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工作状态下桥梁结构的模态参数识别是桥梁损伤识别的重要环节,考虑桥梁检测的实用性,桥梁检测一般应建立在环境激励的基础上,已有的环境激励下模态参数识别的方法对模态频率的识别的精度较高,而对位移模态的识别则误差较大。提出了一种利用移动质量块在不同位置时对桥梁的模态频率进行多次测量,用各次测得的频率值确定位移模态的新方法,使得位移模态识别的精度接近频率识别的精度,建立了该方法的初步模型,推导了频率与位移模态关系的理论公式,并通过数值模拟对该方法的有效性进行了说明。 相似文献
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In this paper an efficient methodology applying modal analysis is developed to assess systematically the combined soil–structure interaction and torsional coupling effects on asymmetric buildings. This method is implemented in the frequency domain to accurately incorporate the frequency‐dependent foundation impedance functions. For extensively extracting the soil–structure interaction effects, a diagonal transfer matrix in the modal space is derived. A comprehensive investigation of asymmetric building–soil interaction can then be conveniently conducted by examining various types of response quantities. Results of parametric study show that the increasing height‐to‐base ratio of a structure generally amplifies its translational and torsional responses. Moreover, both the translational and torsional responses are reduced for the case where the two resonant frequencies are well separated and this reduction is enhanced with the decreasing values of the relative soil stiffness and the height‐to‐base ratio. The most noteworthy phenomenon may be the fact that the SSI effects can enlarge the translational response if the structure is slender and the two resonant frequencies are very close. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
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Output‐only modal identification is needed when only structural responses are available. As a powerful unsupervised learning algorithm, blind source separation (BSS) technique is able to recover the hidden sources and the unknown mixing process using only the observed mixtures. This paper proposes a new time‐domain output‐only modal identification method based on a novel BSS learning algorithm, complexity pursuit (CP). The proposed concept—independent ‘physical systems’ living on the modal coordinates—connects the targeted constituent sources (and their mixing process) targeted by the CP learning rule and the modal responses (and the mode matrix), which can then be directly extracted by the CP algorithm from the measured free or ambient system responses. Numerical simulation results show that the CP method realizes accurate and robust modal identification even in the closely spaced mode and the highly damped mode cases subject to non‐stationary ambient excitation and provides excellent approximation to the non‐diagonalizable highly damped (complex) modes. Experimental and real‐world seismic‐excited structure examples are also presented to demonstrate its capability of blindly extracting modal information from system responses. The proposed CP is shown to yield clear physical interpretation in modal identification; it is computational efficient, user‐friendly, and automatic, requiring little expertise interactions for implementations. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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基于环境振动的斜拉桥拉索基频识别 总被引：16，自引：1，他引：16
斜拉索是现代斜拉桥最重要的结构构件，索力在斜拉桥的施工控制和长期监测中起着重要作用。振动测试法是斜拉桥索力测定、监测和状态评估中应用最广泛的一种方法。振动法测索力的关键在于准确地识别出索的基频。本文使用自功率谱和倒频谱方法，基于MATLAB平台，开发出了斜拉桥拉索环境振动模态分析图形用户交互(GUI)工具箱，实现了斜拉索基频的快速自动识别。应用本文的方法，对福州青洲闽江主跨605m斜拉桥拉索的环境振动实测加速度数据进行了分析处理，斜拉索基频识别方便直观，结果可靠。 相似文献
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Techniques developed for structural identification of a structural model are typically based on information regarding the response and the forcing actions. However, in some situations it can be necessary, or simply useful, to refer only to the measured responses. In this paper we describe a technique suitable for identifying the modal model of a spatial frame in the frequency domain when the seismic input is unknown both in time contents and direction. In some previous theoretical works we established that this identification problem has a unique solution when at least three time‐history responses are known. Here numerical techniques are developed which allow the evaluation of the modal quantities in practice. Numerical applications are carried out on plane and spatial framed structures by using a modal model which may be complete, including all the structure's modes, or incomplete, including only the lowest modes. In most cases the obtained results are satisfactory. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
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Dynamic characteristics of structures — viz. natural frequencies, damping ratios, and mode shapes — are central to earthquake‐resistant design. These values identified from field measurements are useful for model validation and health‐monitoring. Most system identification methods require input excitations motions to be measured and the structural response; however, the true input motions are seldom recordable. For example, when soil–structure interaction effects are non‐negligible, neither the free‐field motions nor the recorded responses of the foundations may be assumed as ‘input’. Even in the absence of soil–structure interaction, in many instances, the foundation responses are not recorded (or are recorded with a low signal‐to‐noise ratio). Unfortunately, existing output‐only methods are limited to free vibration data, or weak stationary ambient excitations. However, it is well‐known that the dynamic characteristics of most civil structures are amplitude‐dependent; thus, parameters identified from low‐amplitude responses do not match well with those from strong excitations, which arguably are more pertinent to seismic design. In this study, we present a new identification method through which a structure's dynamic characteristics can be extracted using only seismic response (output) signals. In this method, first, the response signals’ spatial time‐frequency distributions are used for blindly identifying the classical mode shapes and the modal coordinate signals. Second, cross‐relations among the modal coordinates are employed to determine the system's natural frequencies and damping ratios on the premise of linear behavior for the system. We use simulated (but realistic) data to verify the method, and also apply it to a real‐life data set to demonstrate its utility. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献