复指数方法降噪技术及其试验研究

实测信号中的噪声,以及模型阶次的不确定性给模态参数的准确识别带来困难.以提高模态参数识别精度为目标,提出基于模30-定阶和信噪分离的复指数模态参数识别方法.该方法借助奇异值分解技术确定模型阶次,采用结构低秩逼近方法进行信噪分离.在此基础上.利用复指数法进行模态参数识别.分别选取一维的悬臂梁模型和二维的悬挂板模型进行物理模型实验,结果表明:该方法提高模态参数的识别梢度,尤其是阻尼比的识别精度,具有较好的工程应用前景.     

一种模态参数识别的虚假模态剔除技术

针对背景噪声下结构的模态参数识别结果存在虚假模态的情况,分析虚假模态产生的原因,通过理论推导提出辨别虚假模态的判断条件,根据判断条件剔除识别模态参数中包含的虚假模态。以比例阻尼海洋平台结构数值模型为例,在模拟噪声水平5%的工况下,获得结构脉冲响应信号,对基于奇异值分解定阶消噪后的信号用复指数法进行模态参数识别,对识别的模态频率和阻尼比进行虚假模态剔除。结果表明:根据判断条件可有效剔除所识别参数中的虚假模态。     

波浪作用下海洋石油井架模态参数识别与承载力评价

提出基于试验模态参数识别和优化算法修改动力有限元模型的海洋石油井架安全承载能力评价方法.推导基于波浪脉动的试验模态参数识别公式,介绍有限元模型动力修正的一阶优化方法.以海洋随机波浪脉动作为激励,对勘探三号海洋石油井架进行了现场模态试验,识别出前二阶固有频率.以此作为有限元模型修正的基础,应用一阶搜索优化算法,对动力有限元模型进行了修正,结果表明:该修正模型比较准确反映了井架目前的结构状态,能够用于进一步的静、动力分析和安全承载能力评价.     

浅海导管架平台结构损伤诊断试验研究

基于模型试验研究了浅海导管架平台的结构损伤诊断,采用标量型ARMA模型识别出结构的三阶模态参数,分别采用遗传算法和模态应变能法对试验模型不同模拟损伤工况进行了损伤诊断。基于遗传算法,提出了采用不同自由度一阶模态参数的损伤诊断方法。研究表明,由于海洋平台的前三阶模态分别为不同自由度的一阶模态,采用两阶或三阶模态识别损伤时,损伤杆件影响较小的自由度方向的模态参数对结构的损伤诊断将产生不利的影响,成为识别噪声。因此,可分别采用不同自由度的一阶模态进行结构损伤诊断。     

环境激励下海上风电结构模态参数识别

针对海上风电结构,研究了环境激励下海上风电结构的模态参数识别问题。采用了一种时域联合算法:自然激励法(Natural Excitation Technique,简称NExT)和多参考点复指数法(Polyreference Complex Exponential,简称PRCE)的结合(简称NExT/PRCE方法)对海上风电结构的模态参数进行识别。对某三脚架式海上风电结构进行数值模拟,考虑了风电结构的实际操作工况,对结构施加了随机波浪荷载和风机载荷。利用动力响应数据进行了环境激励下风电整体结构模态参数识别,采用了稳定图与模态置信准则进行了虚假模态的剔除,并分析了NExT中参考通道选取对于模态参数识别效果的影响。通过与有限元模型模态参数比较,验证了NExT/PRCE方法对于风电结构参数识别的有效性。     

振动模态分析法在单立柱海洋平台上应用

提出联合经验模态分解和二次时频分布的参数识别方法.将结构的响应信号用经验模态分解的方法分解为单频率响应的振动信号,进而计算模态频率和模态阻尼,用Choi-Williams分布计算模态振型.对单立柱海洋平台的计算表明,该方法能比较理想地识别出结构的模态参数,且具有较强的抗噪能力.     

特征系统实现算法中的噪声问题研究

研究特征系统实现算法在模态识别过程中的噪声处理问题。特征系统实现算法为目前土木工程领域应用较为广泛的一种模态识别法。在处理实测数据时,特征系统实现算法将实测数据分解为结构真实信号和噪声信号,从而将噪声消除。分块Hankel矩阵的维数对信噪分离过程影响很大。提出当分块Hankel矩阵的分块行与分块列数接近时,真实和噪声信号可以最好的分离。通过在实测信号里添加噪声(产生噪声-噪声信号),将实测信号和噪声-噪声信号识别的结果进行比较,提出了1种验证识别模态参数是否为结构真实模态的检验方法。本文应用导管架平台实例来验证提出方法的适用性。结果表明,当分块Hankel矩阵的分块行与分块列数接近时,真实和噪声信号能够有效地分离,此时添加的噪声主要影响噪声信号部分。由实测信号和噪声-噪声信号识别的模态参数非常吻合。     

采用两步式模型修正过程识别海上风电支撑结构的损伤

针对海上风电支撑结构损伤识别的难点,将一种新的模型修正方法应用到了三脚架式海上风电支撑结构的损伤识别中。采用数学上常用的正则化方法,解决了实测模态含噪声条件下损伤识别"病态"方程组的求解问题;结合Guyan扩阶技术,实现了基于低阶不完备模态的损伤识别。另外,为提高损伤识别精度,结合算例提出一种两步式模型修正过程:第一步,初步定位损伤位置;第二步,精确识别损伤位置和损伤程度。数值研究结果表明,采用两步式模型修正过程的方法对于海上风电支撑结构的损伤识别是有效的。     

特征系统实现算法中的噪声问题研究

研究特征系统实现算法在模态识别过程中的噪声处理问题.特征系统实现算法为目前土木工程领域应用较为广泛的一种模态识别法.在处理实测数据时,特征系统实现算法将实测数据分解为结构真实信号和噪声信号,从而将噪声消除.分块Hankel矩阵的维数对信噪分离过程影响很大.提出当分块Hankel矩阵的分块行与分块列数接近时,真实和噪声信号可以最好的分离.通过在实测信号里添加噪声(产生噪声-噪声信号),将实测信号和噪声—噪声信号识别的结果进行比较,提出了1种验证识别模态参数是否为结构真实模态的检验方法.本文应用导管架平台实例来验证提出方法的适用性.结果表明,当分块Hankel矩阵的分块行与分块列数接近时,真实和噪声信号能够有效地分离,此时添加的噪声主要影响噪声信号部分.由实测信号和噪声噪声信号识别的模态参数非常吻合.     

基于模型修正的海洋平台结构损伤识别试验研究

损伤识别是海洋平台结构健康监测的核心问题,对于保障结构的安全服役具有重要的意义。文中将交叉模型交叉模态(CMCM)有限元模型修正方法应用到了导管架式海洋平台结构的损伤识别中。针对实测模态含噪声条件下该方法遇到的"病态"求解难题,引入了截断奇异值分解正则化方法,提出了基于正则化模型修正的损伤识别过程。为验证该过程的有效性,制做了某导管架平台的钢质缩尺简化模型,并在两个典型构件处设置了损伤;利用冲击激励对结构进行了振动测试;根据模态识别结果,采用正则化模型修正过程对各损伤工况进行了损伤识别。结果表明,利用有限的低阶含噪声模态,借助正则化求解技术,该模型修正方法可有效地识别导管架平台结构的损伤。     

Identification of modal parameters of a floating system from impulse motion

The modal parameters of a scale-modeled discus-shaped data buoy in heave and pitch are estimated from the experimentally measured impulse response time histories. The use of phase-time, time–frequency domains for derivation of natural frequencies and damping are demonstrated in this paper. The phase-time method is based on the Hilbert transformation, whereas, the time–frequency method is based on the continuous wavelet transformation (CWT) of the measured time histories. In addition, the conventional time and frequency domain method of modal parameter estimation is also adopted for the comparison of results. The details of the model, test procedure, analysis and results are presented in this paper. The modal parameters obtained through CWT are found to be accurate compared to that obtained from the time and frequency domain analysis.     

Damage Localization of Offshore Platforms Under Ambient Excitation

In this paper Nondestructive Damage Detection (NDD) for offshore platforms is investigated under operational conditions. As is known, there is no easy way to measure ambient excitation, so damage detection methods based on ambient excitation have become very vital for the Structural Health Monitoring (SHM) of offshore platforms. The modal parameters (natural frequencies, damping ratios and mode shapes) are identified from structural response data with the Natural Excitation Technique (NExT) in conjunction with the Eigensystem Realization Algorithm (ERA) . A new method of damage detection is presented, which utilizes the invariance property of element modal strain energy. This method is to assign element modal strain energy to two parts, and defines two damage detection indicators. One is compression modal strain energy change ratio (CMSECR); the other is flexural modal strain energy change ratio (FMSECR). The present modal strain energy is obtained by incomplete modal shape and structural stiffness matr     

A Study on Crack Detection with Modal Parameters of A Jacket Platform

Crack detection procedures by different modal parameters are analyzed for identitying a crack and its location and magnitude in a jacket plafform. The first ten natural frequencies and modal shapes of the jacket models are obtained by numerical experiments based on NASTRAN Code. A crack at different locations and of different magnitudes is imposed in the model at the underwater beams. Then, the modal evaluation parameters are calculated numerically, to illustrate the evaluation of modal parameter criteria used in jacket crack detection. The sensitivities of different modal parameters to different cracks are analyzed. A new technique is presented for predicting the approximate location of a breakage in the absence of the data of an intact model. This method can be used to detect a crack in underwater menbers by use of incomplete mode shapes of the top members of the jacket.     

基于VMD对SAR海洋内波参数的自动反演

经验模态分解(empirical mode decomposition,简称EMD)是反演海洋内波参数的有效方法之一,但由于EMD存在模态混叠等问题,对海洋内波进行参数反演时会产生一定误差。相比较于EMD,变分模态分解(variational mode decomposition,简称VMD)能够有效地抑制模态混叠现象。为了更好地对海洋内波进行参数反演,提出了一种基于VMD对合成孔径雷达(synthetic aperture radar,简称SAR)遥感图像中的内波参数进行自动反演的方法。该方法先对SAR图像进行Canny处理,获取图像中的内波条纹信息,再根据内波传播方向自动选取灰度剖面;然后利用集合经验模态分解(ensemble empirical mode decomposition,简称EEMD)信号特征自适应分解模态函数的特点,再将分解得到的有效模态数作为VMD中参数K的参考值;最后利用VMD分解后的数据进行内波参数反演。试验结果表明:通过对Canny预处理后的条纹信息进行灰度剖面自动选取,解决了人为选取剖面所可能导致的误差;通过对剖面信号进行VMD处理不仅解决了EMD模态混叠的问题,成功地反演出内波的前导波振幅,而且所反演的结果与EEMD反演参数以及实测资料数据吻合得很好。     

纵横加筋圆锥壳振动特性多变量分析

为了全面掌握纵横加筋圆锥壳结构参数与其振动特性之间的关系,采用有限元软件ANSYS对纵横加筋圆锥壳进行参数化建模,并基于设计变量全组合数据,采用相关性分析、主效应分析和主成分分析方法,对纵横加筋圆锥壳结构参数与结构第一阶总体弯曲模态频率、激励力处的加速度响应总级以及结构质量之间的关系进行研究,得到了各结构参数与目标量之间关系的定量描述。为正确理解纵横加筋圆锥壳结构参数与振动特征量之间的关系提供了数据支撑,同时为此类结构的工程设计提供了参考依据。     

Single point mooring system modal parameter identification based on empirical mode decomposition and time-varying autoregressive model

A method based on empirical mode decomposition (EMD) and time-varying autoregressive (TVAR) model is proposed here to identify the modal parameters of time-varying systems, such as the Floating Production Storage and Offloading (FPSO) single point mooring system. For the EMD–TVAR method, the original signal is decomposed into a finite number of ‘intrinsic mode functions’ (IMFs) by the EMD. Each IMF can be represented as a TVAR model. Then, the time-varying modal parameters i.e., instantaneous frequency (IF) and modal dumping, can be obtained by the basis functions expansion method. The proposed EMD–TVAR method has good results in two experiments compared with the Huang–Hilbert transformation and Short Time Fourier Transform method, and it has been used to analysis the modal parameters of FPSO single point mooring system successfully. The system's time-varying characteristic and its frequency distribution can be known from the modal analysis results.     

On natural frequencies and modal shapes in two-dimensional asymmetric and symmetric moonpools in finite water depth

In this paper theoretical models are proposed for computing the natural frequencies and modal shapes of two-dimensional asymmetric and symmetric moonpools in the finite water depth. The boundary value problem is solved by using a domain decomposition approach. On the outer vertical boundary bounded by the beam of the two bodies, linearized velocity potential is assumed to be nil. Eigenvalue problem is formulated by matching the velocity potential and fluid flux on the common boundaries to obtain the natural frequencies and modal shapes of the free surface elevation. In the symmetric moonpool cases, so-called single mode approximations (SMA) have been derived and can be adopted for rapid estimation of the natural frequencies for both piston and sloshing modes. The present results have been extensively compared with the solutions using the two-dimensional infinite water depth model developed by Molin [1], the numerical solutions and experimental data by Faltinsen et al. [2]. It is found that the solutions have been improved from the infinite water depth model. It is demonstrated that the proposed models can well predict the resonance frequencies and modal shapes for the two-dimensional asymmetric and symmetric moonpools.     

Inversion Method for Sound Velocity Profile of Eddy in Deep Ocean

The modal wave number tomography approach is used to obtain sound speed profile of water column in deep ocean. The approach consists of estimation of the local modal eigenvalues from complex pressure field and use of these data as input to modal perturbative inversion method for obtaining the local sound speed profile. The empirical orthonormal function (EOF) is applied to reduce the parameter search space. The ocean environment used for numerical simulations includes the Munk profile as the unperturbed background speed profile and a weak Gaussian eddy as the sound speed profile perturbation. The results of numerical simulations show the method is capable of monitoring the oceanic interior structure.     

Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: Application to skipjack tuna

A Spatial Ecosystem and Population Dynamic Model (SEAPODYM) is used in a data assimilation study aiming to estimate model parameters that describe dynamics of Pacific skipjack tuna population on ocean-based scale. The model based on advection–diffusion–reaction equations explicitly predicts spatial dynamics of large pelagic predators, while taking into account data on several mid-trophic level components, oceanic primary productivity and physical environment. In order to improve its quantitative ability, the model was parameterized through assimilation with commercial fisheries data, and optimization was carried out using maximum likelihood estimation approach. To address the optimization task we implemented an adjoint technique to obtain an exact, analytical evaluation of the likelihood gradient. We conducted a series of computer experiments in order to (i) determine model sensitivity with respect to variable parameters and, hence, investigate their observability; (ii) estimate observable parameters and their errors; and (iii) justify the reliability of the computed solution. Parameters describing recruitment, movement, habitat preferences, natural and fishing mortality of skipjack population were analysed and estimated. Results of the study suggest that SEAPODYM with achieved parameterization scheme can help to investigate the impact of fishing under various management scenarios, and also conduct forecasts of a given species stock and spatial dynamics in a context of environmental and climate changes.