• Journal of Ocean Engineering and Technology
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• v.29 no.5
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• pp.351-358
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• 2015

This paper presents an effective damage detection method using a meta model. A meta model is an approximation model that uses the relations between the design and response variables. It eliminates the need for repetitive analyses of computationally expensive models during the optimization process. In this study, a response surface model was employed as the meta model. The surface model was estimated using the correlation of the stiffness and natural frequencies of the structures. The locations and values of the damages were identified using a meta model-based damage detection method. Two numerical examples (a cantilever beam and jacket structure) were considered to verify the performance of the proposed method. As a result, the damages to the structures were accurately detected.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.549-555
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• 2003

The objective of かis study is to investigate the feasibility of piezoelectric transducers as a damage detection system for civil infrastructures. There have been considerable amount of efforts by the modal analysis community to localize damage and evaluate its severity without looking at a reliable way to excite the structure. The detection of damages by modal analysis and similar vibration techniques depends upon the knowledge and estimation of various modal parameters. In addition to the associated difficulties, such low-frequency dynamic response based techniques fail to detect incipient damages. Smart piezoelectric ceramic (PZT) transducers which act as both actuators and sensors in a self-analyzing manner are emerging to be effective in non-parametric health monitoring of structural systems. In this paper, we present the results of an experimental study for the detection of damages using smart PZT transducers on the steel plate. The method of extracting the impedance characteristics of the PZT transducer, which is electro-mechanically coupled to the host structure, is adopted for damage detection. Two damages are simulated and assessed by the bonded PZT transducers for characterization. The experimental results verified the efficacy of the proposed approach and provided a demonstration of good robustness at the realistic steel structures, emphasizing the great potential for developing an automated in situ structural health monitoring system for application to large civil infrastructures without the need to blow the modal parameters.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.258-264
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• 2015

The first 77 GHz transceiver that applies a heterodyne structure-based linear frequency modulation-frequency shift keying (LFM-FSK) front-end module (FEM) is presented. An LFM-FSK waveform generator is proposed for the transceiver design to avoid ghost target detection in a multi-target environment. This FEM consists of three parts: a frequency synthesizer, a 77 GHz up/down converter, and a baseband block. The purpose of the FEM is to make an appropriate beat frequency, which will be the key to solving problems in the digital signal processor (DSP). This paper mainly focuses on the most challenging tasks, including generating and conveying the correct transmission waveform in the 77 GHz frequency band to the DSP. A synthesizer test confirmed that the developed module for the signal generator of the LFM-FSK can produce an adequate transmission signal. Additionally, a loop back test confirmed that the output frequency of this module works well. This development will contribute to future progress in integrating a radar module for multi-target detection. By using the LFM-FSK waveform method, this radar transceiver is expected to provide multi-target detection, in contrast to the existing method.

• 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.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.373-380
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• 2004

This paper presents the feasibility of an impedance-based damage detection technique using piezoelectric (PZT) transducers for civil infrastructures such as steel bridges. The impedance-based damage detection method is based on monitoring the changes in the electrical impedance. Those changes in the electrical impedance are due to the electro-mechanical coupling property of the piezoelectric material and structure. An effective integrated structural health monitoring system must include a statistical process of damage detection that is automated and real time assessment of damage in the structure. Once measured, damage sensitive features from this impedance change can be statistically quantified for various damage cases. The results of the experimental study on three kinds of structural members show that cracks or loosened bolts/nuts near the PZT sensors may be effectively detected by monitoring the shifts of the resonant frequencies. The root mean square (RMS) deviations of impedance functions between before and after damages were also considered as a damage indicator. The subsequent statistical methods using the impedance signature of the PZT sensors were investigated.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.747-754
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• 2003

An enhancement of the probabilistic data association filter is presented for tracking a single maneuvering target in clutter environment. The use of the variable dimensional structure leads the probabilistic data association filter to adjust to real motion of a target. The detection of the maneuver for the model switching is performed by the acceleration estimates taken from a bias estimator of the two stage Kalman filter. The proposed algorithm needs low computational power since it is implemented with a single filtering procedure. A simple Monte Carlo simulation was performed to compare the performance of the proposed algorithm and the IMMPDA filter.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.92-97
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• 2014

A novel method for extracting frequency slippage signal from radar full pulse sequence is presented. For the radar full pulse sequence received by radar interception receiver, radio frequency (RF) and time of arrival (TOA) of all pulses constitute a two-dimensional information sequence. In a complex and intensive electromagnetic environment, the TOA of pulses is distributed unevenly, randomly, and in a nonstationary manner, preventing existing methods from directly analyzing such time series and effectively extracting certain signal features. This work applies Gaussian noise insertion and structure function to the TOA-RF information sequence respectively such that the equalization of time intervals and correlation processing are accomplished. The components with different frequencies in structure function series are separated using empirical mode decomposition. Additionally, a chaos detection model based on the Duffing equation is introduced to determine the useful component and extract the changing features of RF. Experimental results indicate that the proposed methodology can successfully extract the slippage signal effectively in the case that multiple radar pulse sequences overlap.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.55-67
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• 2015

An important problem in cluster analysis is the selection of variables that define cluster structure that also eliminate noisy variables that mask cluster structure; in addition, outlier detection is a fundamental task for cluster analysis. Here we provide an automated K-means clustering process combined with variable selection and outlier identification. The Automated K-means clustering procedure consists of three processes: (i) automatically calculating the cluster number and initial cluster center whenever a new variable is added, (ii) identifying outliers for each cluster depending on used variables, (iii) selecting variables defining cluster structure in a forward manner. To select variables, we applied VS-KM (variable-selection heuristic for K-means clustering) procedure (Brusco and Cradit, 2001). To identify outliers, we used a hybrid approach combining a clustering based approach and distance based approach. Simulation results indicate that the proposed automated K-means clustering procedure is effective to select variables and identify outliers. The implemented R program can be obtained at http://www.knou.ac.kr/~sskim/SVOKmeans.r.

• Structural Engineering and Mechanics
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• v.46 no.2
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• pp.231-244
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• 2013

An efficient method is proposed here to identify multiple damage cases in structural systems using the concepts of flexibility matrix and strain energy of a structure. The flexibility matrix of the structure is accurately estimated from the first few mode shapes and natural frequencies. Then, the change of strain energy of a structural element, due to damage, evaluated by the columnar coefficients of the flexibility matrix is used to construct a damage indicator. This new indicator is named here as flexibility strain energy based index (FSEBI). In order to assess the performance of the proposed method for structural damage detection, two benchmark structures having a number of damage scenarios are considered. Numerical results demonstrate that the method can accurately locate the structural damage induced. It is also revealed that the magnitudes of the FSEBI depend on the damage severity.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.97.2-97
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• 2002

A method for the non-destructive detection of damage using parameterized partial differential equations and Galerkin approximation techniques is presented. This method provides the theoretical and experimental verification of a nondestructive time domain approach to examine structural damage in smart structure. The time histories of the vibration response of structure were used to identify the presence of damage. Damage in a structure causes changes in the physical coefficients of mass density, elastic modulus and damping coefficient. This paper examines the beam-like structures with PVDF sensor and PZT actuator to perform identification of those physical parameters and to detect the...