• Smart Structures and Systems
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• 제12권3_4호
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• pp.399-414
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• 2013

The smart sensor technology has opened new horizons for assessing and monitoring structural health of civil infrastructure. Smart sensor's unique features such as onboard computation, wireless communication, and cost effectiveness can enable a dense network of sensors that is essential for accurate assessment of structural health in large-scale civil structures. While most research efforts to date have been focused on realizing wireless smart sensor networks (WSSN) on bridge structures, relatively less attention is paid to applying this technology to buildings. This paper presents a decentralized damage detection using the WSSN for building structures. An existing flexibility-based damage detection method is extended to be used in the decentralized computing environment offered by the WSSN and implemented on MEMSIC's Imote2 smart sensor platform. Numerical simulation and laboratory experiment are conducted to validate the WSSN for decentralized damage detection of building structures.

• Structural Engineering and Mechanics
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• 제53권2호
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• pp.249-260
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• 2015

Damage detection based on a reference set of measured data usually has the problem of different environmental temperature in the two sets of measurements, and the effect of temperature difference is usually ignored in the subsequent model updating. This paper attempts to identify the structural damage including the temperature difference with artificial measurement noise. Both local damages and the temperature difference are identified in a gradient-based model updating method based on dynamic response sensitivity. The sensitivities of dynamic response with respect to the system parameters and temperature difference are calculated by direct integration method. The measured dynamic responses of the structure from two different states are used directly to identify the structural local damages and the temperature difference. A single degree-of-freedom mass-spring system and a planar truss structure are studied to illustrate the effectiveness of the proposed method.

• Structural Monitoring and Maintenance
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• 제7권3호
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• pp.261-281
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• 2020

Civil structures may experience progressive deterioration and damage under environmental and operational conditions over their service life. Finite element (FE) model updating method is one of the most important approaches for damage identification in structures due to its capabilities in structural health monitoring. Although various damage detection approaches have been investigated on structures, there are limited studies on large-sized space structures. Thus, this paper aims to investigate the applicability and efficiency of sensitivity-based FE model updating framework for damage identification in large space structures from a distinct point of view. This framework facilitates modeling and model updating in large and geometric complicated space structures. Considering sensitivity-based FE model updating and vibration measurements, the discrepancy between acceleration response data in real damaged structure and hypothetical damaged structure have been minimized through adjusting the updating parameters. The feasibility and efficiency of the above-mentioned approach for damage identification has finally been demonstrated with two numerical examples: a flat double layer grid and a double layer diamatic dome. According to the results, this method can detect, localize, and quantify damages in large-scaled space structures very accurately which is robust to noisy data. Also, requiring a remarkably small number of iterations to converge, typically less than four, demonstrates the computational efficiency of this method.

• Steel and Composite Structures
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• 제25권4호
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• pp.485-496
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• 2017

In this paper, damage detection has been introduced as an optimization problem and a two-step method has been proposed that can detect the location and severity of damage in truss structures precisely and reduce the volume of computations considerably. In the first step, using the residual force vector concept, the suspected damaged members are detected which will result in a reduction in the number of variables and hence a decrease in the search space dimensions. In the second step, the precise location and severity of damage in the members are identified using the genetic algorithm and the results of the first step. Considering the reduced search space, the algorithm can find the optimal points (i.e. the solution for the damage detection problem) with less computation cost. In this step, the Efficient Correlation Based Index (ECBI), that considers the structure's first few frequencies in both damaged and healthy states, is used as the objective function and some examples have been provided to check the efficiency of the proposed method; results have shown that the method is innovatively capable of detecting damage in truss structures.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.608-613
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• 2003

In this paper, the variability of modal properties caused by temperature effects is assessed to adjust modal data used for frequency-based damage detection in plate-girder bridges. First, experiments on model plate-girder bridges are described. Next, the relationship between temperature and natural frequencies is assessed and a set of empirical frequency-correction formula are analyzed for the test structure. Finally, a frequency-eased method is used to locate and estimate severity of damage in the test structure using experimental modal data which are adjusted by the frequency-correction formula. Here, local damage in beam-type structures is detected by using measured frequencies and analytical mode shapes.

• 한국해양공학회지
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• 제30권4호
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• pp.287-293
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• 2016

This paper presents an effective damage detection method for offshore jackets using natural frequency change ratios. Two parameters, cosine similarity and magnitude index, are considered to estimate the location and severity of the damage in the structure. A numerical jacket structure model is considered to verify the performance of the proposed method. As observed through analysis, the damages in the structure are detected accurately.

• Structural Engineering and Mechanics
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• 제63권6호
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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.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2011년도 정기 학술대회
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• pp.680-683
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• 2011

This study deals with damage detection in beam structure by using modal strain energy-based technique with three different sensor types: accelerometer, lead zirconate titanate (PZT) piezoelectric sensor and electrical strain gage. First, the use of direct piezoelectric effect of PZT sensor for dynamic strain response are presented. Next, a modal strain energy-based damage detection method is outlined. For validation, forced vibration tests are carried out on lab-scale aluminum cantilever beam. The dynamic responses are measured for several damage scenarios. Based on damage localization results, the performance of three different sensor types is evaluated.

• 한국공간구조학회논문집
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• 제19권1호
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• pp.93-100
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• 2019

There has been considerable recent interest in deep learning techniques for structural analysis and design. However, despite newer algorithms and more precise methods have been developed in the field of computer science, the recent effective deep learning techniques have not been applied to the damage detection topics. In this study, we have explored the structural damage detection method of truss structures using the state-of-the-art deep learning techniques. The deep neural networks are used to train knowledge of the patterns in the response of the undamaged and the damaged structures. A 31-bar planar truss are considered to show the capabilities of the deep learning techniques for identifying the single or multiple-structural damage. The frequency responses and the elasticity moduli of individual elements are used as input and output datasets, respectively. In all considered cases, the neural network can assess damage conditions with very good accuracy.

• 한국소음진동공학회논문집
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• 제20권3호
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• pp.272-278
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• 2010

A method for damage detection in a plate structure is presented based on strain waves that are generated by impact or damage in the structure. Strain responses from continuous sensors, which are long ribbon-like sensors made from piezoceramic fibers or other materials, were used with a neural network technique to estimate the damage location. The continuous sensor uses only a small number of channels of data acquisition and can cover large areas of the structure. A grid type structural neural system composed of the continuous sensors was developed for effective damage localization in a plate structure. The ratios of maximum strains and arrival times of the maximum strains obtained from the continuous sensors were used as input data to a neural network. Simulated damage localizations on a plate were carried out and the identified damage locations agreed reasonably well with the exact damage locations.