基于灵敏度分析的机械系统损伤识别方法

提出了一种基于振动灵敏度分析的机械系统损伤识别方法。该方法同时考虑了固有频率灵敏度和固有模态灵敏度 ,既可用于损伤定位 ,也能用于确定损伤大小 ,且对单个损伤和多个损伤情况都适用。为了提高识别的精度 ,考虑了二阶灵敏度。针对工程实际的需要 ,分析了不完备模态和模态测量误差对该方法识别精度的影响。算例表明 :本方法合理可靠 ,具有足够的精度。     

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。     

Frequency response function interpolation for damage detection under changing environment

Damage detection can be carried out based on measured dynamic characteristics of the monitored structure. Several experimental investigations have shown that structural parameters are affected by environmental conditions. This circumstance can lead to erroneous conclusions if damage detection methods based on variations of global structural parameters are applied without properly taking into account this influence. In this paper the sensitivity to changing temperature of a new damage detection method, denoted as interpolation damage detection method (IDDM), is investigated with reference to an experimental example, widely studied by several researchers to check damage detection algorithms: the I40 bridge. Results show that, despite the changes of temperature, the IDDM provides a correct identification of damage location even for cases where the evolution of modal frequencies belies the actual damaged state of the structure. The sensitivity of the IDDM to the joint effect of gradient of temperature and noise in the recorded data is also investigated with reference to a numerical example.     

Damage identification by multi-model updating in the modal and in the time domain

Computational model updating techniques are used to adjust selected parameters of finite element models in order to make the models compatible with experimental data. This is done by minimizing the differences (residuals) of analytical and experimental data, for example, natural frequencies and mode shapes by numerical optimization procedures. For a long-time updating techniques have also been investigated with regard to their ability to localize and quantify structural damage. The success of such an approach is mainly governed by the quality of the damage model and its ability to describe the structural property changes due to damage in a physical meaningful way. Our experience has shown that due to unavoidable modelling simplifications and measurement errors the changes of the corresponding damage parameters do not always indicate structural modifications introduced by damage alone but indicate also the existence of other modelling uncertainties which may be distributed all over the structure. This means that there are two types of parameters which have to be distinguished: the damage parameters and the other parameters accounting for general modelling and test data uncertainties. Although these general parameters may be physically meaningless they are necessary to achieve a good fit of the test data and it might happen that they cannot be distinguished from the damage parameters. For complex industrial structures it is seldom possible to generate unique structural models covering all possible damage scenarios so that one has to expect, that the parameters introduced for describing the damage will not be fully consistent with the physical reality. Even then the change of such parameters identified from test data taken continuously or temporarily over the time may serve as a feature for structural health monitoring. It is well known that low-frequency modal test data or static response data are not very well suited for detecting and quantifying localized small size damage. Time domain response data from impact tests carry high-frequency information which usually is lost when experimental modal data are utilized for damage identification. Even so only little literature was found addressing the utilization of experimental time histories for model updating in conjunction with damage identification.In the present paper we summarize the methodology of computational model updating and report about our experience with damage identification using two different model updating techniques. The first is based on classical modal residuals (natural frequencies and mode shapes) which is extended to allow for simultaneous updating of two models, one for the initial undamaged structure and the second for the damaged structure using the test data of both states (multi-model updating). The second technique uses residuals composed of measured and analytical time histories. Time histories have the advantage of carrying high-frequency information which is beneficial for the detection of local damage and which usually is lost when modal residuals are used. Both techniques have been applied to the same beam structure consisting of two thin face sheets which were bonded together by an adhesive layer. It was the aim of this application to study the performance of the two techniques to localize and quantify the damage which was introduced locally in the adhesive layer.     

Monitoring historical masonry structures with operational modal analysis: Two case studies

The paper addresses two complex case studies of modal and structural identification of monuments in Portugal: the Clock Tower of Mogadouro and the Church of Jerónimos Monastery, in Lisbon. These are being monitored by University of Minho with vibration, temperature and relative air humidity sensors. Operational modal analysis is being used to estimate the modal parameters, followed by statistical analysis to evaluate the environmental effects on the dynamic response. The aim is to explore damage assessment in masonry structures at an early stage by vibration signatures, as a part of a health monitoring process that helps in the preservation of historical constructions. The paper presents the necessary preliminary dynamic analysis steps before the monitoring task, which includes installation of the monitoring system, system identification and subsequent FE model updating analysis, automatic modal identification and investigation of the influence of the environment on the identified modal parameters.     

An experimental study on damage detection of structures using a timber beam

Using vibration methods for the damage detection and structural health monitoring in bridge structures is rapidly developing. However, very little work has so far been reported on timber bridges. This paper intends to address such shortcomings by experimental investigation on a timber beam using a vibration based method to detect damage. A promising damage detection algorithm based on modal strain energy was adopted and modified to locate/evaluate damage. A laboratory investigation was conducted on a timber beam inflicted with various damage scenarios using modal tests. The modal parameters obtained from the undamaged and damaged state of the test beam were used in the computation of damage index, were then applied using a damage detection algorithm utilising modal strain energy and a statistical approach to detect location of damage. A mode shape reconstruction technique was used to enhance the capability of the damage detection algorithm with limited number of sensors. The test results and analysis show that location of damage can be accurately identified with limited sensors. The modified method is less dependent on the number of modes selected and can detect damage with a higher degree of confidence.     

Improvement of damage detection methods based on experimental modal parameters

The objective of this paper is to introduce a new method for structural damage detection based on experimentally obtained modal parameters. The new method is suitable for detection of fatigue damage occurring in an aluminium cantilever beam. The damage has been practically realised as saw cuts of different sizes and at different locations. The first step of analysis included an attempt of damage identification with the most often used damage indicators based on measured modal parameters. For that purpose special signal processing technique has been proposed improving the effectiveness of indicators tested. However the results obtained have not been satisfactory. That was the motivation for defining new damage indicators (frequency change based damage indicator, Hybrid Damage Detection method), utilising the change of natural frequencies and any mode shape (measured or modelled) as the measurement of frequencies is much less time consuming in comparison to total mode shape measurement. It has been shown that the proposed technique is suitable for damage localisation in beam-like structures.     

EXTRACTION OF RITZ VECTORS FROM VIBRATION TEST DATA

Modal parameters obtained from modal testing (such as modal vectors, natural frequencies, and damping ratios) have been used extensively in system identification, finite element model updating, and structural health monitoring. As an alternative to modal vectors, load-dependent Ritz vectors have been shown useful in various areas of structural dynamics such as model reduction and damage detection. The applications of Ritz vectors, however, have been mainly limited in analytical and numerical analyses because of the difficulty to identify them from vibration tests. This paper presents a procedure to extract load-dependent Ritz vectors using a complete flexibility matrix constructed from measured vibration test data. The proposed method cannot only construct the Ritz vectors corresponding to the actual load pattern employed in vibration tests, but also generate Ritz vectors from arbitrary load patterns. Experimental data obtained from the vibration test of a grid-type bridge structure are employed to validate and illustrate the proposed extraction procedure.     

Identification of modal parameters of unmeasured modes using multiple FRF modal analysis method

Current modal analysis methods seek to identify the modal parameters of some or all of the modes in the measured frequency range of interest. In many applications however, it will be very useful if modal parameters of some of the out-of-range modes can be identified during modal analysis. Such a goal is obviously theoretically possible since the raw measured frequency response functions (FRFs), upon which modal analysis is performed, do contain adequate information about the out-of-range modes in the form of residue contributions. In this paper, a new method for the estimation of modal parameters using multiple FRFs analysis is presented. In the process of modal identification, the proposed method not only presents accurate modal parameters of the modes which are present in the measurement frequency range, but also quite accurately identifies some of the modes which are not measured. The method calculates the required modal parameters by solving eigenvalue problem of an equivalent eigensystem derived from those measured FRF data. All measured FRFs are used simultaneously to construct the equivalent eigensystem matrices from which natural frequencies, damping loss factors and modeshape vectors of interest are solved. Since the identification problem is reduced to an eigenvalue problem of an equivalent system, natural frequencies and damping loss factors identified are consistent. Applications of the method to both numerically simulated and practically measured FRF data are given to demonstrate the practicality of the proposed method and the results have shown the method is capable of accurately identifying modal parameters of out-of-range modes.     

Dynamic characteristics and model updating of damaged slab from ambient vibration measurements

This paper reports a field investigation using ambient vibration testing on a damaged floor slab of a reinforced concrete frame building. Due to unexpected heavy rainfall, the hill slope at the rear of building failed triggering a major landslide and causing major damage to the perimeter beams and parts of the slab on the first floor. The modal parameters namely natural frequencies and mode shapes were acquired using output only identification technique and the results obtained from the undamaged and damaged floor slabs were compared. It was observed that there was a 25–53% drop in natural frequencies of the damaged slab compared to the undamaged slab, with a much bigger drop for the lower modes. The irregularities in mode shapes identified correlates with the location of the cracks as revealed from visual examination on the damaged slab. Two finite element models of the slab were created using a finite element software package. The damaged slab was updated manually so as to match the modal parameters obtained experimentally. The results from this study further highlight the possibility and feasibility of using non-destructive vibration testing for condition monitoring of structures over more conventional testing techniques.     

DAMAGE DETECTION OF THE Z24 BRIDGE USING CONTROL CHARTS

Structural health monitoring of the Z24 Bridge in Switzerland was studied using the measurement data from three damage configurations. Changes in the modal parameters were used to detect possible damage to the structure. The identification of the modal parameters from the response data was automated using the stochastic subspace identification technique and the stabilisation diagram. Damage detection was performed using control charts, one of the primary techniques of statistical process control. An advantage of control charts is that they can be automated for on-line structural health monitoring. Univariate and multivariate Shewhart, x, CUSUM, and EWMA control charts were studied with different features including natural frequencies, mode shapes, and damping ratios. The sensitivity of the control chart to damage was substantially increased by further dimensionality reduction applying the principal component analysis.     

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。     

一种基于模型修改的结构多点损伤识别方法

可用于结构损伤识别的方法很多。一般来讲正向方法直接利用结构模态参数的变化，逆向方法则利用模态参数变化反演结构物理参数变化，还有些方法利用了神经网络和模式识别技术。文中利用模型修改的思想，通过逆向方法计算结构单元刚度变化系数来对结构的多点损伤进行识别。以一个七自由度弹簧阻尼质量系统作为研究对象，用数值模拟方法及特征系统实现算法计算系统的模态参数，并用这些模态参数验证所提出方法的可行性，结果表明该方法对多点损伤的识别是简单而可行的。     

固支梁振型与损伤关系的试验模态分析

结构的动力特性和结构参数直接相关,结构的损伤将引起相应动力特性的改变。因此,如果能建立结构动力特性变化与结构损伤之间的映射关系,则可以利用结构振动测试信息实现结构损伤识别。按照采用数据和识别原理的不同,大致可以分为基于频率的方法、基于振型的方法、基于模态柔度的方法以及基于神经网络的方法等,但是在大型土木工程结构的测试中,一般只能获得低阶模态及不完备的自由度测试信息。     

基于支持向量机和模态频率的结构损伤诊断

支持向量机（support vector machine,SVM）是一种基于统计学习理论的机器学习算法,能够较好地解决小样本的学习问题。文中介绍支持向量机回归算法,并应用于结构损伤诊断领域;构造基于模态频率的损伤标识量,作为特征参数训练支持向量机实现对结构损伤的定位和程度标识;最后以梁的损伤识别为例进行验证。结果表明,支持向量机在结构损伤诊断领域中具有很好的应用前景。     

基于遗传算法的梁结构边界条件识别

利用波动理论建立梁结构振动的行波模型,并基于遗传算法提出了一种识别梁结构边界条件的新方法。该方法直接利用结构振动的频响函数,将边界条件的识别问题转化为优化问题,然后利用遗传算法的全局优化特性得到全局最优解。实验结果表明,本文提出的方法能够很好的识别结构的边界条件。     

EFFECTS OF TESTING,ANALYSIS, DAMAGE,AND ENVIRONMENT ON MODAL PARAMETERS

Experimental and analytical modal analysis techniques have been widely used in civil engineering for a number of years, mostly in seismic applications. Since the beginning of this decade, these techniques have received considerable attention in non-seismic applications such as structural damage detection, analytical model calibration and remote-monitoring systems. In these applications, most studies have concentrated on correlating modal parameters to changes in structural condition. However, for reliable performance of modal techniques in field situations, it is essential to understand and establish the variability of modal parameters due to test procedures and in-service environments of structures. New York has been researching this subject extensively for the past few years, and has tested several structures including (1) a 1/6-scale model highway bridge, (2) an abandoned fracture-critical highway bridge and (3) an in-service highway bridge. Both the abandoned highway bridge and model bridge were tested under intact and simulated-damage conditions. This paper briefly describes these studies. Results indicate that modal frequencies in conjunction with mode shapes may be used to identify the existence of bridge damage or deterioration of interest, but it is difficult to isolate damage locations using these modal parameters. Operating conditions affect the modal properties and are critical in establishing a baseline for structural monitoring.     

LOCALISATION OF DAMAGE IN SMART STRUCTURES THROUGH SENSITIVITY ENHANCING FEEDBACK CONTROL

The concept of sensitivity enhancing control (SEC) introduced previously by the authors exploits the relationship between feedback control gains and classic measures of root and system sensitivity in order to increase the magnitude of variation in modal characteristics when damage occurs. This paper further develops the SEC concept, focusing on the ability tolocate damage in smart structures. Two distinct methods are considered for locating damage. Forward methods rely on a priori knowledge of how certain damage scenarios affect modal properties. Using this information, the correlation between measured modal frequency shifts and predicted modal frequency shifts for a given set of damage scenarios is used to identify damage location. Inverse, or model updating methods attempt to update mass and/or stiffness matrices of structural models based on measured modal frequencies and mode shapes. The resulting perturbation matrices indicate damage location. Here, both methods are evaluated through finite-element simulation of controlled structures with local stiffness damage, with the goal of determining whether inclusion of modal data from feedback controlled structures enhances the localisation process. Results show that application of both forward and inverse methods to measured closed-loop modal characteristics increases both the accuracy with which stiffness damage can be located and the ability to tolerate noise in measurement of modal properties used to locate damage.     

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.