The Interpolation Evolution Method for damage localization in structures under seismic excitation

In the aftermath of an earthquake, data acquired by a monitoring system can be used to identify possible damage that occurred in the structure by using algorithms to estimate proper damage features. In this paper, a new method is proposed for damage localization in beam‐like structures under seismic excitation. The proposed algorithm, named the Interpolation Evolution Method (IEM), is based on the combination of two existing methods: the Interpolation Method and the Curvature Evolution Method. Only responses recorded in story accelerations are required to estimate the damage feature with the combined IEM approach. This method does not require a priori knowledge of a “signature” of the structure because it exploits responses recorded during a single strong motion event. Herein, the IEM is applied to case studies of 2 reinforced concrete frames excited by several different ground motions, simulated using nonlinear finite element models and recorded during experimental tests carried out on a shaking table at the University of California, San Diego (USA) and at the University of Basilicata (Italy).     

Simulation of structural response under high‐frequency ground excitation

The structural response to high‐frequency ground motions is complicated due to the involvement of local‐mode vibration. At present such a characteristic is not well recognized and this can cause confusion over the analytical and experimental modelling of the corresponding response and damage. The fact that most existing regulatory guides for limits on allowable construction vibrations are necessarily simplified for administrative reasons calls upon the derivation of more sophisticated approaches for special cases. This requires accumulation of pertinent experimental evidence. This paper attempts to provide some insights into the local‐mode dynamic response characteristics, with emphasis on appropriate modelling techniques and experimental measurements. A preliminary testing program is reported, in which efforts were made to reproduce high‐frequency response with a reduced scale reinforced concrete model with shaking table facilities. The results demonstrate the dependence of the response amplitudes with the excitation frequency. On a ppv‐basis, the current test results indicate that a substantial increase of the allowable ppv value from those specified by various standards may be considered for structural damage to reinforced concrete building structures. More analytical and experimental data are needed for further evaluation of the local‐mode effects and to quantify their impact on the structural damage process. Copyright © 2001 John Wiley & Sons, Ltd.     

Effects of excitation frequency on detection accuracy of orthogonal wavelet decomposition for structural health monitoring

Accurate estimation of stiffness loss is a challenging problem in structural health monitoring. In this study orthogonal wavelet decomposition is used for identifying the stiffness loss in a single degree of freedom spring-mass-damper system. The effects of excitation frequency on accuracy of damage detection is investigated. Results show that pseudo-alias effects caused by the orthogonal wavelet decomposition (OWD), affect damage detectability. It is demonstrated that theproposed approach is sunable for damage detection when the excitation frequency is relatively low. This study shows how a priori knowledge about the signal and ability to control the sampling frequency can enhance damage detectability.     

Uncertainty analysis of strain modal parameters by Bayesian method using frequency response function

Structural strain modes are able to detect changes in local structural performance, but errors are inevitably intermixed in the measured data. In this paper, strain modal parameters are considered as random variables, and their uncertainty is analyzed by a Bayesian method based on the structural frequency response function (FRF). The estimates of strain modal parameters with maximal posterior probability are determined. Several independent measurements of the FRF of a four-story reinforced concrete frame structural model were performed in the laboratory. The ability to identify the stiffness change in a concrete column using the strain mode was verified. It is shown that the uncertainty of the natural frequency is very small. Compared with the displacement mode shape, the variations of strain mode shapes at each point are quite different. The damping ratios are more affected by the types of test systems. Except for the case where a high order strain mode does not identify local damage, the first order strain mode can provide an exact indication of the damage location.     

环境激励下基于波动能量法的结构损伤识别

目前作为结构健康监测系统核心的损伤识别大多是基于模态参数变化而进行的,但模态参数对局部损坏不敏感,导致损伤识别精度不够。波在结构中的传播状态可以更好地反映局部损伤状况,波动能量可以作为损伤识别的有效指标。为了提高环境激励下结构损伤识别的精度,采用S变换分析了结构输出信号,建立波动能量指标,从而使波动能量指标的使用领域扩展到非平稳信号范围。最后通过三层钢框架试验及弹性分层剪切梁的数值模型对该方法进行了验证,结果表明:该方法不仅能够有效识别结构损伤位置,而且能够识别出损伤程度。     

Earthquake-induced damage detection and localization in masonry structures using smart bricks and Kriging strain reconstruction: A numerical study

The intrinsic vulnerability of masonry structures to seismic events makes structural health monitoring of the utmost importance for the conservation of the built heritage. The development of piezoresistive bricks, also termed smart bricks, is an innovative technology recently proposed by the authors for the monitoring of such structures. Smart bricks exhibit measurable variations in their electrical properties when subjected to external loads or, alternatively, strain self-sensing capabilities. Therefore, the deployment of a network of smart bricks into a masonry structure confers self-diagnostic properties to the host structure. In this light, this paper presents a theoretical investigation on the application of smart bricks to full-scale masonry structures for seismic assessment. This includes the study of the convenience of providing electrical isolation conditions to the sensors, as well as the effectiveness of smart bricks when installed into either new constructions or in pre-existing structures. Secondly, numerical results are presented on the seismic analysis of a three-dimensional masonry building equipped with a network of smart bricks. Finally, in order to map the strain field throughout the structure exploiting the outputs of a limited number of sensors, an interpolation-based strain reconstruction approach is proposed.     

Shaking table tests on a masonry building monitored using smart bricks: Damage detection and localization

The seismic behavior of unreinforced masonry buildings is typically characterized by premature brittle collapse mechanisms that can cause serious consequences for the protection of human lives and for the preservation of historical and cultural heritage. Structural health monitoring can be a powerful tool enabling a quick post-earthquake assessment of the structure's performance, but its applications are still scarce as a consequence of the severe limitations affecting off-the-shelf sensing technologies, in terms of local nature of the measurements, costs, as well as long-term behavior, installation, and maintenance. To overcome some of these limitations, the authors have recently proposed a new sensing technology, called “smart brick,” that is a durable clay brick doped with stainless steel microfibers, working as a smart strain sensor for masonry buildings. This paper presents the first full-scale application of smart bricks, used for detecting and localizing progressive earthquake-induced damage in an unreinforced masonry building subjected to shaking table tests. Smart bricks are employed to detect changes in load paths on masonry walls, comparing strain measurements acquired after each step of the seismic sequence with those referring to the undamaged structure. Experimental results are interpreted using a 3D finite element model built to reproduce the shaking table tests. Overall, the results demonstrate that the smart bricks can effectively reveal local permanent changes in structural conditions following a progressive damage, therefore being apt for earthquake-induced damage detection and localization.     

多点输入下大跨结构地震反应的频域精细传递矩阵法

地震输入问题一直是工程结构抗震研究所关注的焦点.在对大跨度结构进行抗震设计时,需要考虑多点地震输入的影响已成为国内外学术界和工程界的共识.本文根据傅氏变换,运用精细传递矩阵法推导出了大跨结构在多点地震输入下的频域精细传递矩阵,并在频域内对大跨度结构进行了动力分析.这种方法公式简单,能够快速、高精度地进行结构的地震反应分析.算例显示了本文方法的有效性.     

Development of fragility functions as a damage classification/prediction method for steel moment‐resisting frames using a wavelet‐based damage sensitive feature

Fragility functions are commonly used in performance‐based earthquake engineering for predicting the damage state of a structure subjected to an earthquake. This process often involves estimating the structural damage as a function of structural response, such as the story drift ratio and the peak floor absolute acceleration. In this paper, a new framework is proposed to develop fragility functions to be used as a damage classification/prediction method for steel structures based on a wavelet‐based damage sensitive feature (DSF). DSFs are often used in structural health monitoring as an indicator of the damage state of the structure, and they are easily estimated from recorded structural responses. The proposed framework for damage classification of steel structures subjected to earthquakes is demonstrated and validated with a set of numerically simulated data for a four‐story steel moment‐resisting frame designed based on current seismic provisions. It is shown that the damage state of the frame is predicted with less variance using the fragility functions derived from the wavelet‐based DSF than it is with fragility functions derived from an alternate acceleration‐based measure, the spectral acceleration at the first mode period of the structure. Therefore, the fragility functions derived from the wavelet‐based DSF can be used as a probabilistic damage classification model in the field of structural health monitoring and an alternative damage prediction model in the field of performance‐based earthquake engineering. Copyright © 2011 John Wiley & Sons, Ltd.     

桥梁健康监测及诊断研究综述

本文分析了桥梁结构健康监测和诊断的必要性和紧迫性，对桥梁结构损伤探测的方法进行了详细的分类及论述。提出了桥梁健康监测和诊断的研究新领域——无线监测系统。最后指出了桥梁健康监测和诊断中存在的问题及发展趋势。     

Damage identification method using harmonic excitation force considering both modelling and measurement errors

A method of structural damage identification using harmonic excitation force is presented. It considers the effects of both measurement and modelling errors in the baseline finite element model. Damage that accompanies changes in structural parameters can be estimated for a damaged structure from the change between measured vibration responses and ones calculated from the analytical model of the intact structure. In practice, modelling errors exist in the analytical model due to material and geometric uncertainties and a reduction in the degrees of freedom as well as measurement errors, making identification difficult. To surmount these problems, bootstrap hypothesis testing, which enables statistical judgment without information about these errors, was introduced. The method was validated by numerical simulation using a three‐dimensional frame structure and real vibration data for a three‐storey steel frame structure. Copyright © 2005 John Wiley & Sons, Ltd.     

Application of clan member signal method in structural damage detection

It is well known that in most cases, a reference is necessary for structural health diagnosis, and it is very difficult to obtain such a reference for a given structure. In this paper, a clan member signal method (CMSM) is proposed for use in structures consisting of groups (or clans) that have the same geometry, i.e., the same cross section and length, and identical boundary conditions. It is expected that signals measured on any undamaged member in a clan after an event could be used as a reference for any other members in the clan. To verify the applicability of the proposed method, a steel truss model is tested and the results show that the CMSM is very effective in detecting local damage in structures composed of identical slender members.     

Theoretical models and recorded response in the estimation of cumulative seismic damage on non‐linear structures

A damage‐function model is proposed for the inelastic response of structures in terms of initial damage and of displacement amplitudes and secant stiffnesses of response cycles. The model is used to obtain an analytical closed‐form solution for the probability distribution of cumulative damage after an earthquake ground motion given the distribution prior to such excitation and information on the inelastic structural response. The formulation is applied to a reinforced concrete frame and the results show the capabilities of the method to yield updated distributions of damage. Copyright © 2000 John Wiley & Sons, Ltd.     

A method for non-parametric damage detection through the use of neural networks

A neural network-based approach is presented for the detection of changes in the characteristics of structure-unknown systems. The approach relies on the use of vibration measurements from a ‘healthy’ system to train a neural network for identification purposes. Subsequently, the trained network is fed comparable vibration measurements from the same structure under different episodes of response in order to monitor the health of the structure. The methodology is applied to actual data obtained from ambient vibration measurements on a steel building structure that was damaged under strong seismic motion during the Hyogo-Ken Nanbu Earthquake of 17 January 1995. The measurements were done before and after repairs to the damaged frame were made. A neural network is trained with data after the repairs, which represents ‘healthy’ condition of the building. The trained network, which is subsequently fed data before the repairs, successfully identified the difference between the damaged storey and the undamaged storey. Through this study, it is shown that the proposed approach has the potential of being a practical tool for a damage detection methodology applied to smart civil structures. © 1998 John Wiley & Sons, Ltd.     

Earthquake damage detection in the Imperial County Services Building I: The data and time–frequency analysis

The former Imperial County Services Building was a six-story reinforced concrete structure in the El Centro, California, severely damaged by the 1979 Imperial Valley earthquake. It represents a rare case of an instrumented building that has been damaged, and thus can serve as a full-scale benchmark to evaluate and further develop structural health monitoring methods. This paper presents an analysis of inter-story drifts, and of changes in the first NS and EW system frequencies (estimated from the ridge of the Gabor transform of the relative roof displacement response) as indicators of the occurrence of damage. The detected initial decreases of system frequency, of about 28% for NS and 24% for EW motions, are not believed to be due to severe damage. The subsequent decreases, of about 44% for NS and 21% for EW motions, are attributed to damage. Near the end of shaking, increases of about 35% for the NS and 36% for EW motions were detected. (These percentage changes were computed with respect to the previous value for particular interval, rather than a fixed reference). During the most severe shaking, the inter-story drifts exceeded 0.5% for NS and 1.5% for EW motions.     

Output only modal identification and structural damage detection using time frequency ＆ wavelet techniques

The primary objective of this paper is to develop output only modal identifi cation and structural damage detection.Identif ication of multi-degree of freedom(MDOF) linear time invariant(LTI) and linear time variant(LTV—due to damage) systems based on Time-frequency(TF) techniques—such as short-time Fourier transform(STFT),empirical mode decomposition(EMD),and wavelets—is proposed.STFT,EMD,and wavelet methods developed to date are reviewed in detail.In addition a Hilbert transform(HT) approach to determine ...     

土木工程结构安全性评估、健康监测及诊断述评

阐述了土木工程结构的安全性评估、健康监测及损伤诊断的必要性和迫切性，系统论述了结构健康监测和诊断的概念、理论和方法，重点讨论了传感器的优化布置、损伤识别等健康监测中的关键问题，介绍了光纤等新型传感器的应用情况，最后指出了值得进一步研究的问题。     

Wavelet transformation of mode shape difference function for structural damage location identification

In this paper, a new approach to structural damage detection is presented using mode shape difference between the reference and damage states. In order to capture and display the signal of damage, wavelet transformation is performed upon the mode shape difference function. Results show that this presentation of signal is effective for damage detection. Furthermore, practical aspects of damage identification are investigated, including understanding and using the frequency contents of the mode shape difference function, the mother wavelet function and the resulting wavelet coefficients due to the band‐limited filtering of wavelet transformation. This proposition is experimented. Results are assertive of the proposed concept. Copyright © 2007 John Wiley & Sons, Ltd.     

A procedure on ground motion selection and scaling for nonlinear response of simple structural systems

This study presents a ground-motion selection and scaling methodology that preserves the basic seismological features of the scaled records with reduced scatter in the nonlinear structural response. The methodology modifies each strong-motion recording with known fundamental seismological parameters using the estimations of ground-motion prediction equations for a given target hazard level. It provides robust estimations on target building response through scaled ground motions and calculates the dispersion about this target. This alternative procedure is not only useful for record scaling and selection but, upon its further refinement, can also be advantageous for the probabilistic methods that assess the engineering demand parameters for a given target hazard level. Case studies that compare the performance of the proposed procedure with some other record selection and scaling methods suggest its usefulness for building performance assessment and loss models. Copyright © 2012 John Wiley & Sons, Ltd.     

基于EMD方法与RBF神经网络的结构损伤检测

针对结构损伤检测中损伤的识别、定位以及程度的标定这三个独立并按一定先后顺序进行的检测过程,提出了一种能将以上三者同时进行的联合检测方法。该方法首先利用经验模态分解(EMD)方法将三层钢筋混凝土剪切型结构在各种损伤工况下的顶层地震作用加速度响应分解为若干固有模态函数(IMF)分量,然后以此IMF分量和未经EMD分解的原始加速度响应数据来构造损伤标识量,作为特征参数依次输入到径向基函数神经网络(RBFNN)中进行损伤检测。给出了应用此方法的具体步骤,通过仿真实验证明了利用该方法进行结构损伤一次检测的可行性和有效性,结果表明,由加速度响应经EMD分解而得到的IMF分量输入到RBFNN中能够更为精确地一次检测出结构所有损伤信息,并且RBFNN在结构损伤损度大时具有更好的检测效果。