Structural impedance based damage diagnosis by piezo‐transducers

Although structural mechanical impedance is a direct representation of the structural parameters, its measurement is difficult at high frequencies owing to practical considerations. This paper presents a new method of damage diagnosis by means of changes in the structural mechanical impedance at high frequencies. The mechanical impedance is extracted from the electro‐mechanical admittance signatures of piezoelectric‐ceramic (PZT) patches surface bonded to the structure using the electro‐mechanical impedance (EMI) technique. The main feature of the newly developed approach is that both the real as well as the imaginary component of the admittance signature is used in damage quantification. A complex damage metric is proposed to quantify damage parametrically based on the extracted structural parameters, i.e. the equivalent single degree of freedom (SDOF) stiffness, the mass, and the damping associated with the drive point of the PZT patch. The proposed scheme eliminates the need for any a priori information about the phenomenological nature of the structure or any ‘model’ of the structural system. As proof of concept, the paper reports a damage diagnosis study conducted on a model reinforced concrete (RC) frame subjected to base vibrations on a shaking table. The proposed methodology was found to perform better than the existing damage quantification approaches, i.e. the low‐frequency vibration methods as well as the traditional raw‐signature based damage quantification in the EMI technique. Copyright © 2003 John Wiley & Sons, Ltd.     

基于小波分析的结构损伤检测研究进展

近10几年来,在土木和机械领域结构损伤识别方法已引起不同领域的相关学者的极大研究兴趣。小波分析是一种新的数学分析和信号处理工具,可以对非稳态信号进行详细的时频分析,是传统傅里叶分析所不能及的,已广泛应用于土木、机械和航空工程领域中,特别是在结构损伤识别和健康监测中的应用尤为突出。本文回顾和总结了小波分析理论及其在结构损伤识别、损伤定位和损伤程度确定中的应用,对今后的研究进行了讨论和展望。     

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.     

Active sensing using impedance‐based ARX models and extreme value statistics for damage detection

In this paper, the applicability of an auto‐regressive model with exogenous inputs (ARX) in the frequency domain to structural health monitoring (SHM) is established. Damage sensitive features that explicitly consider non‐linear system input/output relationships are extracted from the ARX model. Furthermore, because of the non‐Gaussian nature of the extracted features, Extreme Value Statistics (EVS) is employed to develop a robust damage classifier. EVS provides superior performance to standard statistical methods because the data of interest are in the tails (extremes) of the damage sensitive feature distribution. The suitability of the ARX model, combined with EVS, to non‐linear damage detection is demonstrated using vibration data obtained from a laboratory experiment of a three‐story building model. It is found that the vibration‐based method, while able to discern when damage is present in the structure, is unable to localize the damage to a particular joint. An impedance‐based active sensing method using piezoelectric (PZT) material as both an actuator and a sensor is then investigated as an alternative solution to the problem of damage localization. Copyright © 2005 John Wiley & Sons, Ltd.     

基于结构振动信息的损伤识别研究综述

随着传感技术、信号采集与处理和系统建模等技术的发展,基于结构振动信息的损伤识别已经成为土木工程结构健康监测与损伤检测领域的研究热点。本文系统地综述了近20年来国内外基于振动信息的结构损伤识别的研究和应用现状,评述了各类方法的优缺点,并针对土木工程结构损伤识别的特点,对有待于进一步研究的问题进行了展望。     

A simple LMS‐based approach to the structural health monitoring benchmark problem

A structure's health or level of damage can be monitored by identifying changes in structural or modal parameters. However, the fundamental modal frequencies can sometimes be less sensitive to (localized) damage in large civil structures, although there are developing algorithms that seek to reduce this difficulty. This research directly identifies changes in structural stiffness due to modeling error or damage using a structural health monitoring method based on adaptive least mean square (LMS) filtering theory. The focus is on computational simplicity to enable real‐time implementation. Several adaptive LMS filtering based approaches are used to analyze the data from the IASC–ASCE Structural Health Monitoring Task Group Benchmark problem. Results are compared with those from the task group and other published results. The proposed methods are shown to be very effective, accurately identifying damage to within 1%, with convergence times of 0.4–13.0 s for the twelve different 4 and 12 degree of freedom benchmark problems. The resulting modal parameters match to within 1% those from the benchmark problem definition. Finally, the methods developed require 1.4–14.0 Mcycles of computation and therefore could easily be implemented in real time. Copyright © 2004 John Wiley & Sons, Ltd.     

Structural health monitoring of long-span suspension bridges using wavelet packet analysis

During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vibration-based health monitoring methods is to seek some damage indices that are sensitive to structural damage. This paper proposes an online structural health monitoring method for long-span suspension bridges using wavelet packet transform (WPT). The WPT- based method is based on the energy variations of structural ambient vibration responses decomposed using wavelet packet analysis. The main feature of this method is that the proposed wavelet packet energy spectrum (WPES) has the ability to detect structural damage from ambient vibration tests of a long-span suspension bridge. As an example application, the WPES-based health monitoring system is used on the Runyang Suspension Bridge under daily environmental conditions. The analysis reveals that changes in environmental temperature have a long-term influence on the WPES, while the effect of traffic loadings on the measured WPES of the bridge presents instantaneous changes because of the nonstationary properties of the loadings. The condition indication indices VD reflect the influences of environmental temperature on the dynamic properties of the Runyang Suspension Bridge. The field tests demonstrate that the proposed WPES-based condition indication index VD is a good candidate index for health monitoring of long-span suspension bridges under ambient excitations.     

Damage localization under ambient vibration using changes in flexibility

In recent years, Structural Health Monitoring (SHM) has emerged as a new research area in civil engineering. Most existing health monitoring methodologies require direct measurement of input excitation for implementation. However, in many cases, there is no easy way to measure these inputs - or alternatively to externally excite the structure. Therefore, SHM methods based on ambient vibration have become important in civil engineering. In this paper, an approach is proposed based on the Damage Location Vector (DLV) method to handle the ambient vibration case. Here, this flexibility-matrix-based damage localization method is combined with a modal expansion technique to eliminate the need to measure the input excitation. As a by-product of this approach, in addition to determining the location of the damage, an estimate of the damage extent also can be determined. Finally, a numerical example analyzing a truss structure with limited sensors and noisy measurement is provided to verify the efficacy of the proposed approach. Sponsored by: Notional Science Foundation Grant CMS 99-00234     

Two‐stage damage detection algorithms of structure using modal parameters identified from recursive subspace identification

Structural damage assessment under external loading, such as earthquake excitation, is an important issue in structural safety evaluation. In this regard, appropriate data analysis and feature extraction techniques are required to interpret the measured data and to identify the state of the structure and, if possible, to detect the damage. In this study, the recursive subspace identification with Bona‐fide LQ renewing algorithm (RSI‐BonaFide‐Oblique) incorporated with moving window technique is utilized to identify modal parameters such as natural frequencies, damping ratios, and mode shapes at each instant of time during the strong earthquake excitation. From which the least square stiffness method (LSSM) combined with the model updating technique, called efficient model correction method (EMCM), is used to estimate the first‐stage system stiffness matrix using the simplified model from the previously identified modal parameters (nominal model). In the second stage, 2 different damage assessment algorithms related to the nominal system stiffness matrix were derived. First, the model updating technique, called EMCM, is applied to correct the nominal model by the newly identified modal parameters during the strong motion. Second, the element damage index can be calculated using element damage index method (EDIM) to quantify the damage extent in each element. Verification of the proposed methods through the shaking table test data of 2 different types of structures and a building earthquake response data is demonstrated to specify its corresponding damage location, the time of occurrence during the excitation, and the percentage of stiffness reduction.     

Semi‐explicit rate‐dependent modeling of damage‐avoidance steel connections using HF2V damping devices

A rate‐dependent modeling technique is developed for moment resisting steel connections that utilize non‐linear viscous dampers. First, a model of the Maxwell‐type is developed that considers the non‐linear viscous damper and connection flexibility for translational motion. This model is compared with experimental results at several input motion frequencies to validate the results. The model is then extended to represent an exterior steel beam‐to‐column connection using damage‐avoidance design and non‐linear viscous dampers. By including terms to represent structural member and connection flexibility, using appropriate geometric transformations the model can be formulated to give the overall lateral load‐drift structural performance. Validation analysis shows good agreement between experimental observations and the model predictions. Copyright © 2010 John Wiley & Sons, Ltd.     

Quadratic jerk regulation and the seismic control of civil structures

Regulation of the total structural jerk is a means of managing the structural energy and enhancing the performance of civil structures undergoing large seismic events. A quadratic regulator is derived for the total structural jerk that produces a single algebraic Riccati equation to define the control gains. The resulting control method is tested using a realistic non‐linear structural control case study where the structural response is statistically quantified for large suites of scaled earthquakes. The control method developed is shown to be more effective than typical displacement‐focused active and semi‐active civil structural control methods. In particular, quadratic jerk regulation provides better performance than typical structural control methods for near‐field seismic events where the response is dominated by a large impulse, and relatively poorer results for far‐field seismic inputs where the response is vibratory. Hence, this type of control approach has strong potential for mitigating the damage for large impulse, near‐field events, where jerk regulation provides much more efficient response and damage management. Copyright © 2003 John Wiley & Sons, Ltd.     

Disbond detection with piezoelectric wafer active sensors in RC structures strengthened with FRP composite overlays

The capability of embedded piezoelectric wafer active sensors (PWAS) to perform in-situ nondestructive evaluation (NDE) for structural health monitoring (SHM) of reinforced concrete (RC) structures strengthened with fiber reinforced polymer (FRP) composite overlays is explored. First, the disbond detection method were developed on coupon specimens consisting of concrete blocks covered with an FRP composite layer. It was found that the prescnce of a disbond crack drastically changes the electromecbanical (E/M) impedance spectrum measured at the PWAS terminals. The spectral changes depend on the distance between the PWAS and the crack tip. Second, large scale experiments were conducted on a RC beam strengthened with carbon fiber reinforced polymer (CFRP) composite overlay. The beam was subject to an acccleratcd fatigue load regime in a three-point bending configuration up to a total of807,415 cycles. During these fatigue tests, the CFRP overlay experienced disbonding beginning at about 500,000 cycles. The PWAS were able to detect the disbonding before it could be reliably seen by visual inspection. Good correlation between the PWAS readings and the position and extent of disbond damage was observed. These preliminary results demonstrate the potential of PWAS technology for SHM of RC structures strengthened with FRP composite ovcrlays.     

Post‐earthquake damage assessment using residual displacements

This paper presents a new, improved, post‐earthquake damage assessment method that takes into account residual deformations attained by the damaged structure during the earthquake. Local and global residual deformations and visual damage indicators are considered to estimate the maximum deformations experienced by the structure. As a particular development, the method allows measured displacements and rotations to be considered jointly. Uncertainties associated with both the excitation and the damaged structure are explicitly accounted for. The resulting maximum displacement estimates allow a more accurate evaluation of the extent of structural damage when judging the usability/reparability of the investigated structure. A trial application of the method to a real structure tested on a shaking table is presented. The results confirm the capability of the method to estimate the maximum displacement and the residual stiffness of the damaged structure. Copyright © 2011 John Wiley & Sons, Ltd.     

基于结构动态响应统计特征的损伤指标研究

为了提高土木工程结构损伤识别的可靠性和有效性,本文提出一种基于结构动态响应统计特征的损伤指标,并对其可行性进行研究。文中首先在结构随机振动理论基础上推导出结构动态响应（包括位移、速度和加速度）的统计特征（包括均值和方差）与结构损伤位置和损伤程度之间的关系;然后通过敏感性分析确定以结构位移的方差作为结构损伤识别的损伤指标;最后,数值模拟-六层钢筋混凝土框架结构在白噪声激励下的动态响应,观察在不同损伤位置和损伤程度下结构动态位移方差的变化,从而对选择结构位移的方差作为损伤指标的可行性进行评估。研究得出结论,使用结构动态响应的统计特征作为土木工程结构损伤识别的损伤指标是可行的。     

结构损伤识别方法研究综述

对工程结构进行损伤识别与检测,可以发现结构损伤位置,评估损伤程度,为结构加固与修复提供依据,从而保证工程结构正常运行,进而保护人们生命财产安全,因此结构损伤识别方法研究一直是土木工程领域重要研究课题。结构损伤识别方法总体上分为确定性方法和不确定性方法,相比于确定性方法,不确定性方法考虑了识别过程中不确定因素的影响,成为目前损伤识别领域的研究热点。本文回顾了确定性方法和不确定性方法发展历程,阐述了几种常见的损伤识别方法及其优缺点,并根据国内外研究现状对结构损伤识别方法发展进行了展望,可供损伤识别方法研究与应用参考。     

Structural damage detection using the optimal weights of the approximating artificial neural networks

This work presents a novel neural network‐based approach to detect structural damage. The proposed approach comprises two steps. The first step, system identification, involves using neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The partial derivatives of the outputs with respect to the inputs of the NSIN, which identifies the system in a certain undamaged or damaged state, have a negligible variation with different system errors. This loosely defined unique property enables these partial derivatives to quantitatively indicate system damage from the model parameters. The second step, structural damage detection, involves using the neural damage detection network (NDDN) to detect the location and extent of the structural damage. The input to the NDDN is taken as the aforementioned partial derivatives of NSIN, and the output of the NDDN identifies the damage level for each member in the structure. Moreover, SDOF and MDOF examples are presented to demonstrate the feasibility of using the proposed method for damage detection of linear structures. Copyright © 2001 John Wiley & Sons, Ltd.     

一种基于时间序列与核岭回归的结构损伤定位方法

结构健康监测的一个重要目的是实现结构损伤识别与定位,文章将结构监测数据的时间序列模型与机器学习中的核岭回归相结合,提出了一种新的结构损伤定位方法.先定义结构损伤识别矩阵,推导出结构损伤系数向量与损伤结构和未损伤结构的自回归系数向量差值的关联关系,结构的损伤识别矩阵可以通过机器学习中的核岭回归算法获得.对比其他回归算法,核岭回归的正则化、核函数特性可以大幅提高模型的拟合性能与泛化性能,更好地应用于结构损伤识别.然后通过一混凝土框架数值模型对该方法进行验证.结果表明该方法对结构的单损伤、多损伤均可进行有效识别,准确率较高.     

Damage identification of a 3D full scale steel–concrete composite structure with partial‐strength joints at different pseudo‐dynamic load levels

Partial‐strength composite steel–concrete moment‐resisting (MR) frame structures represent an open research field in seismic design from both a theoretical and an experimental standpoint. Among experimental techniques, vibration testing is a well‐known and powerful technique for damage detection, localization and quantification, where actual modal parameters of a structure at different states can be determined from test data by using system identification methods. However, the identification of semi‐rigid connections in framed structures is limited, and hence this paper focuses on a series of vibration experiments that were carried out on a realistic MR frame structure, following the application of pseudo‐dynamic and quasi‐static cyclic loadings at the European laboratory for structural assessment of the Joint Research Centre at Ispra, Italy, with the scope of understanding the structural behaviour and identifying changes in the dynamic response. From the forced vibration response, natural frequencies, damping ratios, modal displacements and rotations were extracted using the circle fitting technique. These modal parameters were used for local and global damage identification by updating a 3D finite element model of the intact structure. The identified results were then correlated with observations performed on the structure to understand further the underlying damage mechanisms. Finally, the latin hypercube sampling technique, a variant of the Monte Carlo method, was employed in order to study the sensitivity of the updated parameters of the 3D model to noise on the modal inputs. Copyright © 2009 John Wiley & Sons, Ltd.     

Comparison of adaptive structural damage identification techniques in nonlinear hysteretic vibration isolation systems

Early structural damage identification to obtain an accurate condition assessment can assist in the reprioritization of structural retrofitting schedules in order to guarantee structural safety. Nowadays, seismic isolation technology has been applied in a wide variety of infrastructure, such as buildings, bridges, etc., and the health conditions of these nonlinear hysteretic vibration isolation systems have received considerable attention. To effectively detect structural damage in vibration isolation systems based on vibration data, three time-domain analysis techniques, referred to as the adaptive extended Kalman filter （AEKF）, adaptive sequential nonlinear least-square estimation （ASNLSE） and adaptive quadratic sum-sqnares error （AQSSE）, have been investigated. In this research, these analysis techniques are compared in terms of accuracy, convergence and efficiency, for structural damage detection using experimental data obtained through a series of laboratory tests based on a base-isolated structural model subjected to E1 Centro and Kobe earthquake excitations. The capability of the AEKF, ASNLSE and AQSSE approaches in tracking structural damage is demonstrated and compared.     

A frequency response function change method for damage localization and quantification in a shear building under ground excitation

A frequency response function change (FRFC) method to detect damage location and extent based on the change in the frequency response functions of a shear building under the effects of ground excitation was proposed in this paper. The damage identification equation was derived from the motion equations of the system before and after the occurrence of the damage. Efforts to make the FRFC method less model‐dependent were made. Intact system matrices, which could be estimated using the measured data without the need for an analytical model, and the frequency response functions were required for the FRFC method. The effects of measurement noise and model parameter error in the FRFC method were studied numerically. The proposed FRFC method was validated by experimental studies of a six‐story steel building structure with single and multiple damage cases. Copyright © 2012 John Wiley & Sons, Ltd.