• 오토저널
• /
• 제14권1호
• /
• pp.25-37
• /
• 1992

Interior noise in a car is known to have an important influence on product acceptability. This noise is closely correlated with structural-acoustic vibration. When considering noise problem, the structural-acoustic relation of a vehicle cabin model needs to be identified. However, it is very difficult to get the modal parameters of this kind of cabin structure composed of thin plates: because it not only can be excited by the acoustic vibration of cavity, but also tends to have decoupling effects of one plate from another. In order to obtain modal parameters more precisely, various excitation techniques, i.e. impact, pure random, burst random, and swept sine testing are applied for the first step. In the case of the cabin model, impact and swept sine testing show good results. Next, the determination of the excitation point by trial- and-error and the accurate measurements of FRF's are performed with these methods. The modal parameter extraction is carried out for the final step. This paper proposes a new approach to find the modal parameters more reliably in the case of high decoupling effects. That is, the convergence of MIF and MCF in each panel, which provide some criteria for the validity of the obtained modal parameters, is observed. And from those results, the pretty accurate modal parameters can be determined. A comparative assessment between the modal testing and the FEM is also performed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권1호
• /
• pp.51-73
• /
• 2023

Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.

• 소음진동
• /
• 제9권1호
• /
• pp.163-173
• /
• 1999

Precise and reasonable modelling is necessary and indispensable to the analysis of dynamic characteristics of mechanical structures. Also. the effective prediction of the change of modal properties due to the variation of design parameters is required especially for the application of finite element method to the structural dynamics problems. To meet those necessity and requirement, three model updating algorithms are proposed for finite element methods. Those algorithms are based on sensitivity analysis of the modal data obtained from experimental modal analysis(EMA) and analytical modal analysis(AMA). The adapted sensitivity analysis methods of the algorithms are 1)eigensensitivity(EGNS) method. 2)frequency response function sensitivity(FRFS) method. 3)sensitivity based element-by-element method (SBEEM), Singular value decomposition(SVD) is used for performing eigenanalysis and parameter estimation in the updating process. Those algorithms are applied to finite element of a plate and the updating capability of each algorithm is compared in terms of accuracy. reliability and stability of the updating process. It is shown that the model updating method using frequency response function is superior to the other methods in view of various updating capabilities.

• Architectural research
• /
• 제10권2호
• /
• pp.21-26
• /
• 2008

The number of measured degrees of freedom for detecting the damage of any structures is usually less than the number of model degrees of freedom. It is necessary to expand the measured data to full set of model degrees of freedom for updating modal data. This study presents the expansion methods to estimate all static displacements and dynamic modal data of finite element model from the measured data. The static and dynamic methods are derived by minimizing the variation of the potential energy and the Gauss's function, respectively. The applications illustrate the validity of the proposed methods. It is observed that the numerical results obtained by the static approach correspond with the Guyan condensation method and the derived static and dynamic approaches provide the fundamental idea for damage detection.

• Earthquakes and Structures
• /
• 제18권1호
• /
• pp.27-44
• /
• 2020

This work presents a comparison of three performance-based seismic design methods (PBSD) as applied to plane steel frames having eccentric braces (EBFs) and buckling restrained braces (BRBFs). The first method uses equivalent modal damping ratios (ξ_k), referring to an equivalent multi-degree-of-freedom (MDOF) linear system, which retains the mass, the elastic stiffness and responds in the same way as the original non-linear MDOF system. The second method employs modal strength reduction factors (${\bar{q}}_k$) resulting from the corresponding modal damping ratios. Contrary to the behavior factors of code based design methods, both ξ_k and ${\bar{q}}_k$ account for the first few modes of significance and incorporate target deformation metrics like inter-storey drift ratio (IDR) and local ductility as well as structural characteristics like structural natural period, and soil types. Explicit empirical expressions of ξ_k and ${\bar{q}}_k$, recently presented by the present authors elsewhere, are also provided here for reasons of completeness and easy reference. The third method, developed here by the authors, is based on a hybrid force/displacement (HFD) seismic design scheme, since it combines the force-base design (FBD) method with the displacement-based design (DBD) method. According to this method, seismic design is accomplished by using a behavior factor (q_h), empirically expressed in terms of the global ductility of the frame, which takes into account both non-structural and structural deformation metrics. These expressions for q_h are obtained through extensive parametric studies involving non-linear dynamic analysis (NLDA) of 98 frames, subjected to 100 far-fault ground motions that correspond to four soil types of Eurocode 8. Furthermore, these factors can be used in conjunction with an elastic acceleration design spectrum for seismic design purposes. Finally, a comparison among the above three seismic design methods and the Eurocode 8 method is conducted with the aid of non-linear dynamic analyses via representative numerical examples, involving plane steel EBFs and BRBFs.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2005년도 춘계학술대회논문집
• /
• pp.124-127
• /
• 2005

As computer capability and test skill become more and more advanced, finite element method and modal test are being widely applied in engineering design. In order to correlate and reconcile the inevitable discrepancies between the analytical and experimental models, many techniques have been developed. Among these methods, multiple-system methods are known as the effective tools in that they can supply the rich modal data available which are experimentally obtained. These abundant modal data can help structural system parameters estimated well. Multiple-system methods can be classified into the structural modification methods and feedback controller methods. The structural modification methods need the physical attachment of structures and their concept may limit the application of them. To overcome this drawback, the feedback controller methods are addressed which enable us to get more modal data without the structural change. Mode decoupling controller(MDC), one of them, is to use acceleration out)ut feedback to perturb an open-loop system. The output feedback controller generally cannot guarantee the stability of a closed-loop system. However, MDC can solve this problem under the certain constraints. So far, MDC utilizes accelerations as the sensor signals. In this research, strain sensors are going to be picked up to apply to the MDC. Strain output is recently used for structural system identification due to the drastically improved and miniaturized strain sensor. In this paper, we show that the MDC using strain output has differences compared with acceleration output in estimating the structural system parameters. The associated simulation is performed to demonstrate the above mentioned characteristics.

• Smart Structures and Systems
• /
• 제24권2호
• /
• pp.243-256
• /
• 2019

Determination of the most meaningful structural modes and gaining insight into how these modes evolve are important issues for long-term structural health monitoring of the long-span bridges. To address this issue, modal parameters identified throughout the life of the bridge need to be compared and linked with each other, which is the process of mode tracking. The modal frequencies for a long-span bridge are typically closely-spaced, sensitive to the environment (e.g., temperature, wind, traffic, etc.), which makes the automated tracking of modal parameters a difficult process, often requiring human intervention. Machine learning methods are well-suited for uncovering complex underlying relationships between processes and thus have the potential to realize accurate and automated modal tracking. In this study, Gaussian mixture model (GMM), a popular unsupervised machine learning method, is employed to automatically determine and update baseline modal properties from the identified unlabeled modal parameters. On this foundation, a new mode tracking method is proposed for automated mode tracking for long-span bridges. Firstly, a numerical example for a three-degree-of-freedom system is employed to validate the feasibility of using GMM to automatically determine the baseline modal properties. Subsequently, the field monitoring data of a long-span bridge are utilized to illustrate the practical usage of GMM for automated determination of the baseline list. Finally, the continuously monitoring bridge acceleration data during strong typhoon events are employed to validate the reliability of proposed method in tracking the changing modal parameters. Results show that the proposed method can automatically track the modal parameters in disastrous scenarios and provide valuable references for condition assessment of the bridge structure.

• Smart Structures and Systems
• /
• 제10권4_5호
• /
• pp.393-410
• /
• 2012

The 610 m high Canton Tower (formerly named Guangzhou New Television Tower) is currently considered as a benchmark problem for structural health monitoring (SHM) of high-rise slender structures. In the benchmark study task I, a set of 24-hour ambient vibration measurement data has been available for the output-only system identification study. In this paper, the vector autoregressive models (ARV) method is adopted in the operational modal analysis (OMA) for this TV tower. The identified natural frequencies, damping ratios and mode shapes are presented and compared with the available results from some other research groups which used different methods, e.g., the data-driven stochastic subspace identification (SSI-DATA) method, the enhanced frequency domain decomposition (EFDD) algorithm, and an improved modal identification method based on NExT-ERA technique. Furthermore, the environmental effects on the estimated modal parameters are also discussed.

• Structural Engineering and Mechanics
• /
• 제61권2호
• /
• pp.267-274
• /
• 2017

In this study was investigated of possibility using the recorded micro tremor data on ground level as ambient vibration input excitation data for investigation and application Operational Modal Analysis (OMA) on the bench-scale earthquake simulator (The Quanser Shake Table) for model steel structures. As known OMA methods (such as EFDD, SSI and so on) are supposed to deal with the ambient responses. For this purpose, analytical and experimental modal analysis of a model steel structure for dynamic characteristics was evaluated. 3D Finite element model of the building was evaluated for the model steel structure based on the design drawing. Ambient excitation was provided by shake table from the recorded micro tremor ambient vibration data on ground level. Enhanced Frequency Domain Decomposition is used for the output only modal identification. From this study, best correlation is found between mode shapes. Natural frequencies and analytical frequencies in average (only) 2.8% are differences.

• 소음진동
• /
• 제6권1호
• /
• pp.97-106
• /
• 1996

This paper presents systematic study of the experimental application of a free-interfaced component mode synthesis method. In the free-interfaced component mode synthesis method, an error the to truncated higher modes and neglected ineria loadings on a component from the connected component is inherent. Also, it is difficult to directly use experimental modal data in a modal synthesis method which links experimental model to finite-element model because of many inconsistencies between experimentally obtained and analytically obtained modal vectors and missing degrees-of-freedom (DOFs) such as rotational DOFs. In order to solve these problems, three methods, the first one based on attaching auxiliary weights to the connection points, the second one utillizing the normalization of experimental modal vector, and the third one generating smoothed and expanded experimental mode shapes, are studied in this paper. Finally, the study is illustrated for a flat-plate structure by using simulated and measured experimental data.