• Title/Summary/Keyword: damage/damage identification

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Using frequency response function and wave propagation for locating damage in plates

  • Quek, Ser-Tong;Tua, Puat-Siong
    • Smart Structures and Systems
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    • v.4 no.3
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    • pp.343-365
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    • 2008
  • In this study, the frequency domain method which utilizes the evaluation of changes in the structural mode shape is adopted to identify regions which contain localized damages. Frequency response function (FRF) values corresponding to the modal frequency, analogous to the mode shape coefficients, are used since change in natural frequency of the system is usually insignificant for localized damage. This method requires only few sensors to obtain the dynamic response of the structure at specific locations to determine the FRF via fast-Fourier transform (FFT). Numerical examples of an aluminum plate, which includes damages of varying severity, locations and combinations of multiple locations, are presented to demonstrate the feasibility of the method. An experimental verification of the method is also done using an aluminum plate with two different degrees of damage, namely a half-through notch and a through notch. The inconsistency in attaining the FRF values for practical applications due to varying impact load may be overcome via statistical averaging, although large variations in the loading in terms of the contact duration should still be avoided. Nonetheless, this method needs special attention when the damages induce notable changes in the modal frequency, such as when the damages are of high severity or cover more extensive area or near the boundary where the support condition is modified. This is largely due to the significant decrease in the frequency term compared to the increase in the vibration amplitude. For practical reasons such as the use of limited number of sensors and to facilitate automation, extending the resolution of this method of identification may not be efficient. Hence, methods based on wave propagation can be employed as a complement on the isolated region to provide an accurate localization as well as to trace the geometry of the damage.

Structural damage detection through longitudinal wave propagation using spectral finite element method

  • Kumar, K. Varun;Saravanan, T. Jothi;Sreekala, R.;Gopalakrishnan, N.;Mini, K.M.
    • Geomechanics and Engineering
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    • v.12 no.1
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    • pp.161-183
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    • 2017
  • This paper investigates the damage identification of the concrete pile element through axial wave propagation technique using computational and experimental studies. Now-a-days, concrete pile foundations are often common in all engineering structures and their safety is significant for preventing the failure. Damage detection and estimation in a sub-structure is challenging as the visual picture of the sub-structure and its condition is not well known and the state of the structure or foundation can be inferred only through its static and dynamic response. The concept of wave propagation involves dynamic impedance and whenever a wave encounters a changing impedance (due to loss of stiffness), a reflecting wave is generated with the total strain energy forked as reflected as well as refracted portions. Among many frequency domain methods, the Spectral Finite Element method (SFEM) has been found suitable for analysis of wave propagation in real engineering structures as the formulation is based on dynamic equilibrium under harmonic steady state excitation. The feasibility of the axial wave propagation technique is studied through numerical simulations using Elementary rod theory and higher order Love rod theory under SFEM and ABAQUS dynamic explicit analysis with experimental validation exercise. Towards simulating the damage scenario in a pile element, dis-continuity (impedance mismatch) is induced by varying its cross-sectional area along its length. Both experimental and computational investigations are performed under pulse-echo and pitch-catch configuration methods. Analytical and experimental results are in good agreement.

Damage Detection of Bridge Structures Considering Uncertainty in Analysis Model (해석모델의 불확실성을 고려한 교량의 손상추정기법)

  • Lee Jong-Jae;Yun Chung-Bang
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.19 no.2 s.72
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    • pp.125-138
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    • 2006
  • The use of system identification approaches for damage detection has been expanded in recent years owing to the advancements in data acquisition system andinformation processing techniques. Soft computing techniques such as neural networks and genetic algorithm have been utilized increasingly for this end due to their excellent pattern recognition capability. In this study, damage detection of bridge structures using neural networks technique based on the modal properties is presented, which can effectively consider the modeling uncertainty in the analysis model from which the training patterns are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness and applicability of the proposed method.

Damage assessment of shear connectors with vibration measurements and power spectral density transmissibility

  • Li, Jun;Hao, Hong;Xia, Yong;Zhu, Hong-Ping
    • Structural Engineering and Mechanics
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    • v.54 no.2
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    • pp.257-289
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    • 2015
  • Shear connectors are generally used to link the slab and girders together in slab-on-girder bridge structures. Damage of shear connectors in such structures will result in shear slippage between the slab and girders, which significantly reduces the load-carrying capacity of the bridge. Because shear connectors are buried inside the structure, routine visual inspection is not able to detect conditions of shear connectors. A few methods have been proposed in the literature to detect the condition of shear connectors based on vibration measurements. This paper proposes a different dynamic condition assessment approach to identify the damage of shear connectors in slab-on-girder bridge structures based on power spectral density transmissibility (PSDT). PSDT formulates the relationship between the auto-spectral densities of two responses in the frequency domain. It can be used to identify shear connector conditions with or without reference data of the undamaged structure (or the baseline). Measured impact force and acceleration responses from hammer tests are analyzed to obtain the frequency response functions at sensor locations by experimental modal analysis. PSDT from the slab response to the girder response is derived with the obtained frequency response functions. PSDT vectors in the undamaged and damaged states can be compared to identify the damage of shear connectors. When the baseline is not available, as in most practical cases, PSDT vectors from the measured response at a reference sensor to those of the slab and girder in the damaged state can be used to detect the damage of shear connectors. Numerical and experimental studies on a concrete slab supported by two steel girders are conducted to investigate the accuracy and efficiency of the proposed approach. Identification results demonstrate that damages of shear connectors are identified accurately and efficiently with and without the baseline. The proposed method is also used to evaluate the conditions of shear connectors in a real composite bridge with in-field testing data.

Power spectral density method performance in detecting damages by chloride attack on coastal RC bridge

  • Mehrdad, Hadizadeh-Bazaz;Ignacio J., Navarro;Victor, Yepes
    • Structural Engineering and Mechanics
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    • v.85 no.2
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    • pp.197-206
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    • 2023
  • The deterioration caused by chloride penetration and carbonation plays a significant role in a concrete structure in a marine environment. The chloride corrosion in some marine concrete structures is invisible but can be dangerous in a sudden collapse. Therefore, as a novelty, this research investigates the ability of a non-destructive damage detection method named the Power Spectral Density (PSD) to diagnose damages caused only by chloride ions in concrete structures. Furthermore, the accuracy of this method in estimating the amount of annual damage caused by chloride in various parts and positions exposed to seawater was investigated. For this purpose, the RC Arosa bridge in Spain, which connects the island to the mainland via seawater, was numerically modeled and analyzed. As the first step, each element's bridge position was calculated, along with the chloride corrosion percentage in the reinforcements. The next step predicted the existence, location, and timing of damage to the entire concrete part of the bridge based on the amount of rebar corrosion each year. The PSD method was used to monitor the annual loss of reinforcement cross-section area, changes in dynamic characteristics such as stiffness and mass, and each year of the bridge structure's life using sensitivity equations and the linear least squares algorithm. This study showed that using different approaches to the PSD method based on rebar chloride corrosion and assuming 10% errors in software analysis can help predict the location and almost exact amount of damage zones over time.

Pipeline Structural Damage Detection Using Self-Sensing Technology and PNN-Based Pattern Recognition (자율 감지 및 확률론적 신경망 기반 패턴 인식을 이용한 배관 구조물 손상 진단 기법)

  • Lee, Chang-Gil;Park, Woong-Ki;Park, Seung-Hee
    • Journal of the Korean Society for Nondestructive Testing
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    • v.31 no.4
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    • pp.351-359
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    • 2011
  • In a structure, damage can occur at several scales from micro-cracking to corrosion or loose bolts. This makes the identification of damage difficult with one mode of sensing. Hence, a multi-mode actuated sensing system is proposed based on a self-sensing circuit using a piezoelectric sensor. In the self sensing-based multi-mode actuated sensing, one mode provides a wide frequency-band structural response from the self-sensed impedance measurement and the other mode provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. In this study, an experimental study on the pipeline system is carried out to verify the effectiveness and the robustness of the proposed structural health monitoring approach. Different types of structural damage are artificially inflicted on the pipeline system. To classify the multiple types of structural damage, a supervised learning-based statistical pattern recognition is implemented by composing a two-dimensional space using the damage indices extracted from the impedance and guided wave features. For more systematic damage classification, several control parameters to determine an optimal decision boundary for the supervised learning-based pattern recognition are optimized. Finally, further research issues will be discussed for real-world implementation of the proposed approach.

A Study on Reforming the National Personal Identification Number System : The Unconnected Random Personal Identification Number System (국가 개인식별번호체계 개선에 관한 연구 : 독립적 난수기반 개인식별번호체계로 전환)

  • Han, Mun-Jung;Jang, GyeHyun;Hong, Seokhie;Lim, Jong-In
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.24 no.4
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    • pp.721-737
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    • 2014
  • The Resident Registration Number(RRN) system has been effectively acted as a national identification system since it was enforced. On the other hand, there are some problems such as leakages of personal informations including RRNs on a large scale and each RRN makes a pair with each person in all areas of the society. Nevertheless leakages of them might cause a big damage, there is no radical countermeasure for they are never changed in actual fact. In Republic of Korea, a RRN acts as a primary key of a database, so it has to be protected by severing the connectivity between leaked RRNs and the other personal data. In this paper, the Unconnected Random Personal Identification Number system is proposed for preventing damage of data spills by removing a dependency which the RRN has. Furthermore, this paper suggests the solutions against some potential issues in the system.

Overall damage identification of flag-shaped hysteresis systems under seismic excitation

  • Zhou, Cong;Chase, J. Geoffrey;Rodgers, Geoffrey W.;Xu, Chao;Tomlinson, Hamish
    • Smart Structures and Systems
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    • v.16 no.1
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    • pp.163-181
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    • 2015
  • This research investigates the structural health monitoring of nonlinear structures after a major seismic event. It considers the identification of flag-shaped or pinched hysteresis behavior in response to structures as a more general case of a normal hysteresis curve without pinching. The method is based on the overall least squares methods and the log likelihood ratio test. In particular, the structural response is divided into different loading and unloading sub-half cycles. The overall least squares analysis is first implemented to obtain the minimum residual mean square estimates of structural parameters for each sub-half cycle with the number of segments assumed. The log likelihood ratio test is used to assess the likelihood of these nonlinear segments being true representations in the presence of noise and model error. The resulting regression coefficients for identified segmented regression models are finally used to obtain stiffness, yielding deformation and energy dissipation parameters. The performance of the method is illustrated using a single degree of freedom system and a suite of 20 earthquake records. RMS noise of 5%, 10%, 15% and 20% is added to the response data to assess the robustness of the identification routine. The proposed method is computationally efficient and accurate in identifying the damage parameters within 10% average of the known values even with 20% added noise. The method requires no user input and could thus be automated and performed in real-time for each sub-half cycle, with results available effectively immediately after an event as well as during an event, if required.

A novel adaptive unscented Kalman Filter with forgetting factor for the identification of the time-variant structural parameters

  • Yanzhe Zhang ;Yong Ding ;Jianqing Bu;Lina Guo
    • Smart Structures and Systems
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    • v.32 no.1
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    • pp.9-21
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    • 2023
  • The parameters of civil engineering structures have time-variant characteristics during their service. When extremely large external excitations, such as earthquake excitation to buildings or overweight vehicles to bridges, apply to structures, sudden or gradual damage may be caused. It is crucially necessary to detect the occurrence time and severity of the damage. The unscented Kalman filter (UKF), as one efficient estimator, is usually used to conduct the recursive identification of parameters. However, the conventional UKF algorithm has a weak tracking ability for time-variant structural parameters. To improve the identification ability of time-variant parameters, an adaptive UKF with forgetting factor (AUKF-FF) algorithm, in which the state covariance, innovation covariance and cross covariance are updated simultaneously with the help of the forgetting factor, is proposed. To verify the effectiveness of the method, this paper conducted two case studies as follows: the identification of time-variant parameters of a simply supported bridge when the vehicle passing, and the model updating of a six-story concrete frame structure with field test during the Yangbi earthquake excitation in Yunnan Province, China. The comparison results of the numerical studies show that the proposed method is superior to the conventional UKF algorithm for the time-variant parameter identification in convergence speed, accuracy and adaptability to the sampling frequency. The field test studies demonstrate that the proposed method can provide suggestions for solving practical problems.