• Journal of Mechanical Science and Technology
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• v.19 no.10
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• pp.1891-1901
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• 2005

Recently the authors tried to find damage position only using measured frequency response functions. According to their work, it seems that the algorithm is very practical since it needs only measured frequency responses while other methods require exact analytic model. But when applying the method to a real structure, it requires lots of experiment. The authors, in this time, propose a method to reduce its experimental load by detecting damage within a substructure. This method searches damages not within an entire structure but within substructures. In addition, damage severity was treated in this paper since it is worthy to know damage severity. Optimization technique is used to estimate damage level using measured responses and damage model. Two test examples, a plate and a jointed structure, are chosen to verify the suggesting method.

• Computers and Concrete
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• v.1 no.2
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• pp.131-150
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• 2004

We present in this work a coupled phenomenological chemo-mechanical model that represents the degradation of concrete-like materials. The chemical behaviour is described by the nowadays well known simplified calcium leaching approach. And the mechanical damage behaviour is described by a continuum damage model which involves the gradient of the damage quantity. The coupled nonlinear problem at hand is addressed within the context of the finite element method. For the equation governing the calcium dissolution-diffusion part of the problem, special care is taken to treat the highly nonlinear calcium conductivity and solid calcium functions. The algorithmic design is based on a Newton-type iterative scheme where use is made of a recently proposed relaxed linearization procedure. And for the equation governing the damage part of the problem, an augmented Lagrangian formulation is used to take into account the damage irreversibility constraint. Finally, numerical simulations are compared with experimental results on cement paste.

• Structural Engineering and Mechanics
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• v.8 no.3
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• pp.285-297
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• 1999

A method is presented to find the location and magnitude of damage in a structure using data from dynamic tests. The test data include a combination of natural frequency measurements, taken before and after the occurrence of damage, and response measurements taken after damage. An algorithm is developed to identify localized increases in the flexibility of the structural members. Increases in flexibility are attributed to damage. The algorithm uses the sensitivity of the flexibility matrix to changes in the natural frequencies of the structure to identify the damage. A set of under determined equations is solved using an objective function which is derived from measurements of the system moments. Damage ranging from 10 to 60% increase in the flexibility of a member was successfully identified in a 50 d.o.f. structure, using a small number of natural frequency and velocity measurements.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.789-797
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• 2017

Recently, some integrated structural identification/damage detection and reliability evaluation of structures with uncertainties have been proposed. However, these techniques are applicable for off-line synthesis of structural identification and reliability evaluation. In this paper, based on the recursive formulation of the extended Kalman filter, an on-line integration of structural identification/damage detection and reliability evaluation of stochastic building structures is investigated. Structural limit state is expanded by the Taylor series in terms of uncertain variables to obtain the probability density function (PDF). Both structural component reliability with only one limit state function and system reliability with multi-limit state functions are studied. Then, it is extended to adopt the recent extended Kalman filter with unknown input (EKF-UI) proposed by the authors for on-line integration of structural identification/damage detection and structural reliability evaluation of stochastic building structures subject to unknown excitations. Numerical examples are used to demonstrate the proposed method. The evaluated results of structural component reliability and structural system reliability are compared with those by the Monte Carlo simulation to validate the performances of the proposed method.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.119-126
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• 2005

Load bearing structural members in a wide variety of applications accumulate damage over their service life. From a standpoint of both safety and performance, it is desirable to monitor the occurrence, location, and extent of such damage. Structures require complicated element models with a number of degrees of freedom in structural analysis. During experiment much effort and cost is needed for measuring structural parameters. The sparseness and errors of measured data have to be considered during the parameter estimation Of Structures. In this paper we introduces damage identification algorithm by a system identification(S.I) using static and dynamic response. To study the behaviour of the estimators in noisy environment Using Monte Carlo simulation and a data measured perturbation scheme is adopted to investigate the influence of measurement errors on identification results. The assessment result by static and dynamic response were compared, and the efficiency and applicabilities of the proposed algorithm are demonstrated through simulated static and dynamic responses of a truss bridge. The assessment results by each method were compared and we could observe that the 5.1 method is superior to the other conventional methods.

• Smart Structures and Systems
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• v.2 no.2
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• pp.141-154
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• 2006

Recently, the Hilbert-Huang transform (HHT) has gained considerable attention as a novel technique of signal processing, which shows promise for the system identification and damage detection of structures. This study investigates the effectiveness and accuracy of the HHT method for the system identification and damage detection of structures through a series of experiments. A multi-degree-of-freedom (MDOF) structural model has been constructed with modular members, and the columns of the model can be replaced or removed to simulate damages at different locations with different severities. The measured response data of the structure due to an impulse loading is first decomposed into modal responses using the empirical mode decomposition (EMD) approach with a band-pass filter technique. Then, the Hilbert transform is subsequently applied to each modal response to obtain the instantaneous amplitude and phase angle time histories. A linear least-square fit procedure is used to identify the natural frequencies and damping ratios from the instantaneous amplitude and phase angle for each modal response. When the responses at all degrees of freedom are measured, the mode shape and the physical mass, damping and stiffness matrices of the structure can be determined. Based on a comparison of the stiffness of each story unit prior to and after the damage, the damage locations and severities can be identified. Experimental results demonstrate that the HHT method yields quite accurate results for engineering applications, providing a promising tool for structural health monitoring.

• Smart Structures and Systems
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• v.11 no.6
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• pp.589-604
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• 2013

Identification of damage has become an evolving area of research over the last few decades with increasing the need of online health monitoring of the large structures. The visual damage detection can be impractical, expensive and ineffective in case of large structures, e.g., offshore platforms, offshore pipelines, multi-storied buildings and bridges. Damage in a system causes a change in the dynamic properties of the system. The structural damage is typically a local phenomenon, which tends to be captured by higher frequency signals. Most of vibration-based damage detection methods require modal properties that are obtained from measured signals through the system identification techniques. However, the modal properties such as natural frequencies and mode shapes are not such good sensitive indication of structural damage. Identification of damaged jacket type offshore platform members, based on wavelet packet transform is presented in this paper. The jacket platform is excited by simple wave load. Response of actual jacket needs to be measured. Dynamic signals are measured by finite element analysis result. It is assumed that this is actual response of the platform measured in the field. The dynamic signals first decomposed into wavelet packet components. Then eliminating some of the component signals (eliminate approximation component of wavelet packet decomposition), component energies of remained signal (detail components) are calculated and used for damage assessment. This method is called Detail Signal Energy Rate Index (DSERI). The results show that reduced wavelet packet component energies are good candidate indices which are sensitive to structural damage. These component energies can be used for damage assessment including identifying damage occurrence and are applicable for finding damages' location.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.24-31
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• 2000

An integrated damage identification system (IDIS) using modal information to detect damage in structures is presented. The objective of this study is to develop a system of softwares that facilitates detecting damage locations and estimating damage severities in bridges. Firstly, the theoretical background for IDIS is outlined. Secondly, a GUI-based IDIS software is programmed. Finally, the feasibility and applicability of the IDIS software are experimentally demonstrated using small-scaled plate-girder models.

• Steel and Composite Structures
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• v.14 no.4
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• pp.367-377
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• 2013

Damage in structures often leads to failure. Thus it is very important to monitor structures for the occurrence of damage. When damage happens in a structure the consequence is a change in its modal parameters such as natural frequencies and mode shapes. Artificial Neural Networks (ANNs) are inspired by human biological neurons and have been applied for damage identification with varied success. Natural frequencies of a structure have a strong effect on damage and are applied as effective input parameters used to train the ANN in this study. The applicability of ANNs as a powerful tool for predicting the severity of damage in a model steel girder bridge is examined in this study. The data required for the ANNs which are in the form of natural frequencies were obtained from numerical modal analysis. By incorporating the training data, ANNs are capable of producing outputs in terms of damage severity using the first five natural frequencies. It has been demonstrated that an ANN trained only with natural frequency data can determine the severity of damage with a 6.8% error. The results shows that ANNs trained with numerically obtained samples have a strong potential for structural damage identification.

• Earthquakes and Structures
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• v.9 no.6
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• pp.1221-1232
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• 2015

In recent decades, wavelet transforms as a strong signal processing tool have attracted attention of researchers for damage identification. Apart from the wide application of wavelet transforms for damage identification, influence of higher order modes on the quality of damage detection has been a challenging matter for researchers. In this study, influence of higher order modes and different mass configurations on the quality of damage detection through Discrete Wavelet Transform (DWT) was studied. Nine different damage scenarios were imposed to four cantilever structures having different mass configurations. The first four mode shapes of the cantilever structures were measured experimentally and analyzed by DWT. A damage index was defined in order to study the influence of higher order modes. Results of this study showed that change in the mass configuration had a great impact on the quality of damage detection even when the changes altered natural frequencies slightly. It was observed that for successful damage detection all available mode shapes should be taken into account and measured mode shapes had no significant priority for damage detection over each other.