Browsing by Author "Hung, S. L."

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DETECTION OF DAMAGE LOCATION USING A NOVEL SUBSTRUCTURE-BASED FREQUENCY RESPONSE FUNCTION APPROACH WITH A WIRELESS SENSING SYSTEM
(2012-07-01)
Lin, T. K.
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Hung, S. L.
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Huang, C. S.
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土木工程學系
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Department of Civil Engineering
"This paper intends to detect the damage locations for building structures under an earthquake excitation using a novel substructure-based FRF approach with a damage location index (SubFRFDI). An Imote2.NET-based wireless structural health monitoring system was developed and employed in the experimental studies for the sake of deployment flexibility, low maintenance cost, low power consumption, self-organization capability, and wireless communication capability. The feasibility of the proposed approach for damage detection was examined using the numerical response of a six-storey shear plane frame structure subjected to a base excitation. The results demonstrate that the SubFRFDI can be successfully used to identify the damage of different levels at a single site or multiple sites. The SubFRFDI is independent of the responses to various input earthquake excitations. Even with the addition of noises, the SubFRFDI still functions well. The feasibility and robustness of the proposed Imote2.NET-based wireless structural health monitoring system were assessed using a 1/8-scale three-storey steel-frame model. Following this, the proposed SubFRFDI was further applied to identifying the damage locations in a 1/4-scale six-storey steel structure with the proposed Imote2.NET-based wireless monitoring system. It was confirmed experimentally that good data transportation quality can be achieved via reliable data transmission and sensing protocol in identifying the structural dynamic properties, and the proposed SubFRFDI can be used to identify the damage locations effectively."
Enhancing particle swarm optimization algorithm using two new strategies for optimizing design of truss structures
(2013-10-01)
Lu, Y. C.
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Jan, J. C.
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Hung, S. L.
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Hung, G. H.
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土木工程學系
This work develops an augmented particle swarm optimization (AugPSO) algorithm using two new strategies,: boundary-shifting and particle-position-resetting. The purpose of the algorithm is to optimize the design of truss structures. Inspired by a heuristic, the boundary-shifting approach forces particles to move to the boundary between feasible and infeasible regions in order to increase the convergence rate in searching. The purpose of the particle-position-resetting approach, motivated by mutation scheme in genetic algorithms (GAs), is to increase the diversity of particles and to prevent the solution of particles from falling into local minima. The performance of the AugPSO algorithm was tested on four benchmark truss design problems involving 10, 25, 72 and 120 bars. The convergence rates and final solutions achieved were compared among the simple PSO, the PSO with passive congregation (PSOPC) and the AugPSO algorithms. The numerical results indicate that the new AugPSO algorithm outperforms the simple PSO and PSOPC algorithms. The AugPSO achieved a new and superior optimal solution to the 120-bar truss design problem. Numerical analyses showed that the AugPSO algorithm is more robust than the PSO and PSOPC algorithms.
Identification of Time-Variant Modal Parameters Using Time-Varying Autoregressive with Exogenous Input and Low-Order Polynomial Function
(2009)
Huang, C. S.
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Hung, S. L.
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Su, W. C.
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Wu, C. L.
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土木工程學系
This work presents an approach that accurately identifies instantaneous modal parameters of a structure using time-varying autoregressive with exogenous input (TVARX) model. By developing the equivalent relations between the equation of motion of a time-varying structural system and the TVARX model, this work proves that instantaneous modal parameters of a time-varying system can be directly estimated from the TVARX model coefficients established from displacement responses. A moving least-squares technique incorporating polynomial basis functions is adopted to approximate the coefficient functions of the TVARX model. The coefficient functions of the TVARX model are represented by polynomials having time-dependent coefficients, instead of constant coefficients as in traditional basis function expansion approaches, so that only low orders of polynomial basis functions are needed. Numerical studies are carried out to investigate the effects of parameters in the proposed approach on accurately determining instantaneous modal parameters. Numerical analyses also demonstrate that the proposed approach is superior to some published techniques (i.e., recursive technique with a forgetting factor, traditional basis function expansion approach, and weighted basis function expansion approach) in accurately estimating instantaneous modal parameters of a structure. Finally, the proposed approach is applied to process measured data for a frame specimen subjected to a series of base excitations in shaking table tests. The specimen was damaged during testing. The identified instantaneous modal parameters are consistent with observed physical phenomena.
Locating damaged storeys in a shear building based on its sub-structural natural frequencies
(2012-06-01)
Su, W. C.
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Huang, C. S.
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Hung, S. L.
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Chen, U.
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Lin, W. J.
Vibration-based damage detection methods are simple and conventionally adopted to monitor the structural health of buildings. This work proposes a simple and efficient approach to locating the storeys whose properties (stiffness and mass) change in the life cycle of a shear building. The storeys that may be damaged are determined by comparing the natural frequencies of sub-structures in different stages in the life cycle of a building. An appropriate ARX (autoregressive with exogenous input) model of a sub-structure of a shear building is established from the sub-structural dynamic responses in terms of acceleration or velocity. The parameters in an ARX model of a sub-structure are identified through the continuous wavelet transform, and the natural frequency and damping ratio of the sub-structure are estimated directly through these identified parameters. The effectiveness of the proposed procedure is verified using the numerically simulated earthquake acceleration responses and ambient vibration responses of a six-storey shear building that is damaged at one or two storeys with different damage levels. The effect of noise on the accuracy of the proposed approach is also examined. The proposed scheme is demonstrated to be superior to COMAC (Coordinate Modal Assurance Criterion) and the frequency response function curvature method in identifying damaged storeys. The proposed method is also applied to process the dynamic responses of three five-storey steel frames, which are not shear buildings, in shaking table tests. The differences in the floor mass or storey stiffness among these frames are accurately reflected in the sub-structural natural frequencies that are obtained by the proposed approach. (C) 2012 Elsevier Ltd. All rights reserved.
Unsupervised fuzzy neural networks for damage detection of structures
(2007-02-01)
Wen, C. M.
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Hung, S. L.
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Huang, C. S.
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Jan, J. C.
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土木工程學系
This work presents an artificial neural network (ANN) approach for detecting structural damage. In place of the commonly used supervised neural network, this work adopts an unsupervised neural network which incorporates the fuzzy concept (named the unsupervised fuzzy neural network, UFN) to detect localized damage. The structural damage is assumed to take the form of reduced elemental stiffness. The damage site is demonstrated to correlate with the changes in the modal parameters of the structure. Therefore, a feature representing the damage location, termed the damage localization feature (DLF) is presented. When the structure experiences damage or change in the structural member, the measured DLF is obtained by analyzing the recorded dynamic responses of the structure. The location of the structural damage then can be identified using the UFN according to the measured DLF information. This study verifies the proposed model using an example involving a five-storey frame building. Both single- and multiple-dam aged sites are considered. The effects of measured noise and the use of incomplete modal data are introduced to inspect the capability of the proposed detection approach. Additionally, the simulation results of well-known back-propagation network (BPN) and UFN are compared. The analysis results indicated that the use of fuzzy relationship in UFN made the detection of structural damage more robust and flexible than the BPN. Copyright (c) 2005 John Wiley & Sons, Ltd.