• Advances in nano research
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• v.12 no.1
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• pp.65-72
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• 2022

The dynamic properties (frequencies, mode shapes, damping ratios) of the scaled WPC warehouse are compared using the operational modal analysis approach to the dynamic parameters (frequencies, mode shapes, damping ratios) of the full outer surface of titanium dioxide, 70 micron in thickness. Micro tremor ambient vibration data on ground level was used to provide ambient excitation. For the output-only modal identification, Enhanced Frequency Domain Decomposition (EFDD) was used. This study discovered a strong correlation between mode shapes. Titanium dioxide applied to the entire outer surface of the scaled WPC warehouse results in an average 14.05 percent difference in frequency values and 7.61 percent difference in damping ratios, demonstrating that nanomaterials can be used to increase rigidity in structures, or for reinforcement. Another significant finding in the study was the highest level of adherence of titanium dioxide and similar nanomaterials mentioned in the introduction to WPC structure surfaces.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.149-160
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• 2008

In this study, the research was carried out on how to identify the modal parameter by acquiring the output response of the structure only through the smart sensor system. The objective of this research is to verify the performance and the on-site adaptability of the smart sensor system that have been actively researched as the advanced measuring system so far. Smart Sensor System was developed so that the real-time dynamic measurement can be performed by means of MEMS-type accelerated sensor, 8 bit CPU, wireless MODEM. In the modal parameter identification test, random excitation was added to the cantilever beam, and then the response of the structure was obtained using the smart sensor system and the wire measurement system respectively. In analyzing the data, modal parameter was identified using NExT & ERA algorithm. Furthermore, the optimal measurement location was selected through EOT algorithm in order to obtain the qualified output response. Result of the test, it was possible to verify the on-site applicability of the smart sensor.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.337-362
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• 2015

This paper presents a feasibility study on structural damage alarming and localization of long-span cable-supported bridges using multi-novelty indices formulated by monitoring-derived modal parameters. The proposed method which requires neither structural model nor damage model is applicable to structures of arbitrary complexity. With the intention to enhance the tolerance to measurement noise/uncertainty and the sensitivity to structural damage, an improved novelty index is formulated in terms of auto-associative neural networks (ANNs) where the output vector is designated to differ from the input vector while the training of the ANNs needs only the measured modal properties of the intact structure under in-service conditions. After validating the enhanced capability of the improved novelty index for structural damage alarming over the commonly configured novelty index, the performance of the improved novelty index for damage occurrence detection of large-scale bridges is examined through numerical simulation studies of the suspension Tsing Ma Bridge (TMB) and the cable-stayed Ting Kau Bridge (TKB) incurred with different types of structural damage. Then the improved novelty index is extended to formulate multi-novelty indices in terms of the measured modal frequencies and incomplete modeshape components for damage region identification. The capability of the formulated multi-novelty indices for damage region identification is also examined through numerical simulations of the TMB and TKB.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.52.6-52
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• 2002

The method of identifying the plant models in this paper is the Observer Kalman filter identification (OKID) method. This method of system identification has several pertinent advantages. First, it assumes that the system in question is a discrete linear time-invariant (LTI) state-space system. Second, it requires only input and output data to formulate the model, no a priori knowledge of the system is needed. Third, the OKID method produces a psudo-Kalman state estimator, which is very useful for control applications. Last, the modal balanced realization of the system model means that tuncation errors will be small. Thus, even in the case of model order error the results of that error will...

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.840-840
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• 2003

Operational Modal Analysis (OMA) is a technique for identification of modal parameters by measurement of only the system's response. On many lightweight structures, such as load-speaker cones and disk drive read/write heads, is impossible or impractical to measure the input forces. Another characteristic of lightweight structure is their sensitivity to mass loading from sensors. The Scanning Laser Doppler Vibrometry(SLDV) allows response measurements to be taken without mass loading. One disadvantage of OMA testing compared to tradition input output modal testing is the OMA mode shapes are un-scaled. This means that the mode shape obtained from an OMA test can not used for analytical structural modification studies. However, the un-scaled mode shapes from an OMA test can be used to update a Finite Element Model (FEM). The updated FEM can then be used to analytically predict the effect of structural modifications. This paper will present the results of an OMA test performed on a simple plate and motor in operating conditions. The un-scaled mode shapes from this test will be used to update a FEM model of the system. The updated FEM model will be then be used to predict the effect of attaching a mass to the plate. The shapes predicted by the FEM for the modified system will be compared to a second OMA test on the modified system

• Structural Engineering and Mechanics
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• v.34 no.5
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• pp.625-634
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• 2010

The objective of this paper is to apply a new proposed accuracy indicator to quantify the true and false modes for Eigensystem Realization Algorithm using output-based responses. First, a discrete mass-spring system and a simply supported continuous beam were modelled using finite element method. Then responses are simulated under random excitation. Natural Excitation Technique using only response measurements is applied to compute the impulse responses. Eigensystem Realization Algorithm is employed to identify the modal parameters on the simulated responses. A new accuracy indicator, Normalized Occurrence Number-NON, is developed to quantitatively partition the realized modes into true and false modes so that the false portions can be disregarded. Numerical simulation demonstrates that the new accuracy indicator can determine the true system modes accurately.

• Structural Engineering and Mechanics
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• v.15 no.3
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• pp.299-314
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• 2003

This investigation presents an efficient method for identifying modal characteristics from the measured displacement, velocity and acceleration signals of multiple channels on structural systems. A Vector Backward Auto-Regressive model (VBAR) that describes the relationship between the output information in different time steps is used to establish a backward state equation. Generally, the accuracy of the identified dynamic characteristics can be improved by increasing the order of the Auto-Regressive model (AR) in cases of measurement of data under noisy circumstances. However, a higher-order AR model also induces more numerical modes, only some of which are the system modes. The proposed VBAR model provides a clear characteristic boundary to separate the system modes from the spurious modes. A numerical example of a lumped-mass model with three DOFs was established to verify the applicability and effectiveness of the proposed method. Finally, an offshore platform model was experimentally employed as an application case to confirm the proposed VBAR method can be applied to real-world structures.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.4
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• pp.19-33
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• 2008

Dynamic response measurements from natural excitation were carried out for 25- and 42-story buildings to evaluate their inherent properties, such as natural frequencies, mode shapes and damping ratios. Both are reinforced concrete buildings adopting a core wall, or with shear walls as the major lateral force resisting system, but frames are added in the plan or elevation. In particular, shear walls in a 25-story building are converted to frames from the 4th floor level downwards while maintaining a core wall throughout, resulting in a fairly complex structure. Due to this, along with similar stiffness characteristics in the principal directions, significantly coupled and closely spaced modes of motion are expected in this building, making identification rather difficult. By using various state-of-the-art system identification methods, the modal parameters are extracted, and the results are then compared. Three frequency-domain and four time-domain based operational modal identification methods are considered. Overall, all natural frequencies and damping ratios estimated from the different identification methods showed a greater consistency for both buildings, while mode shapes exhibited some degree of discrepancy, varying from method to method. On the other hand, in comparison with analysis results obtained using the initial finite element(FE) models, test results exhibited a significant difference of about doubled frequencies, at least for the three lower modes in both buildings. To improve the correlation between test and analysis, a few manual schemes of FE model updating based on plausible reasons have been applied, and acceptable results are obtained. The advantages and disadvantages of each identification method used are addressed, and some difficulties that might arise from the updating of FE models, including automatic procedures, for such large structures are carefully discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.605-609
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• 2006

In this study, two kinds of smart accelerometers are investigated for the application of smart sensors to the structural health monitoring of infrastructures. Smart optical Fiber Bragg Grating (FBG) type and Micro-Electo-Mechanical System (MEMS) type accelerometers are selected for this study and the high sensitive ICP type accelerometer is used for the reference sensor. Small size shaking table tests were performed with 3-story shear building model using random input ground motions. The output only modal identification was carried out using stochastic subspace identification and the performances of sensors are compared in modal domain indirectly. The modal sensitivity method was applied to update the story stiffness of numerical model and the updated results were verified using the additional experiments for the same structure with additional mass.

• Journal of Korean Society of Steel Construction
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• v.24 no.1
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• pp.119-128
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• 2012

In this study, experimental vibration tests are performed on a real full-scale railway steel plate girder bridge, which resides in open-space environments. Using experimental modal analysis techniques, the modal parameters of the railway steel plate girder bridge yielded by the modal testing of the impact hammer are compared and investigated with the natural frequencies and mode shapes obtained by finite element analysis. This work focuses on the application of model updating techniques to measured experimental data and output-only data from an analytical vibration study that takes into account various geometric and material properties of the bridge members. A finite element model of the railway bridge structure is used to verify the modal experimental results. It is subsequently updated using the corresponding modal identification technique. The basic database is provided to evaluate damage, which can be determined based on the changes in the element properties, resulting from the process of updating the finite element model benchmark and experimental data.