• Smart Structures and Systems
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• v.11 no.1
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• pp.19-34
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• 2013

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.

• Food Science and Biotechnology
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• v.17 no.5
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• pp.1038-1046
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• 2008

This study was carried out to develop a small-sized biosensor based on surface plasmon resonance (SPR) for the rapid identification of insecticide residues for food safety. The SPR biosensor module consists of a single 770 nm-light emitting diodes (LED) light source, several optical lenses for transferring light, a hemisphere sensor chip, photo detector, A/D converter, power source, and software for signal processing using a computer. Except for the computer, the size and weight of the sensor module are 150 (L)$\times$70 (W)$\times$120 (H) mm and 828 g, respectively. Validation and application procedures were designed to assess refractive index analysis, affinity properties, sensitivity, linearity, limits of detection, and robustness which includes an analysis of baseline stability and reproducibility of ligand immobilization using carbamate (carbofuran and carbaryl) and organophosphate (cadusafos, ethoprofos, and chlorpyrifos) insecticide residues. With direct binding analysis, insecticide residues were detected at less than the minimum 0.01 ppm and analyzed in less than 100 sec with a good linear relationship. Based on these results, we find that the binding interaction with active target groups in enzymes using the miniaturized SPR biosensor could detect low concentrations which satisfy the maximum residue limits for pesticide tolerance in Korea, Japan, and the USA.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1123-1123
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• 2001

In recent years, a miniature spectrometer has been extensively developed due to the marriage of fiber optics and semiconductor detector array. This type of miniature spectrometer has advantages of low price and robustness due to the capability of mass production and no moving parts are required such as lenses, mirrors and scanning monochromator. These systems are ideal for use in teaching labs, process monitoring and field analyses. A portable near infrared (NIR) system has been developed for qualitative and quantitative analysis. This system includes a tungsten halogen lamp for light source, a fiber optics connected a light source, and a sample module to the microspectrometer, The size of spectrometer can be as small as 2.5 cm x 1.5 cm x 0.1 cm. Wavelength ranges can be chosen as 360-800 nm, 800-1100 nm and 1100-1900 nm depending on the type of detector. The software consists of various tools for multivariate analysis and pattern recognition techniques. To evaluate the system, long and short-term stability, wavelength accuracy, and stray light have been investigated and compared with conventional scanning type NIR spectrometer. This developed system can be sufficiently used for quantitative and qualitative analysis for various samples such as agricultural product, herbal medicine, food, petroleum, and pharmaceuticals, etc.

• Journal of Auto-vehicle Safety Association
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• v.13 no.3
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• pp.32-40
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• 2021

Composite material is very attractive because it has excellent mechanical property and is possible to lightweight due to the low density. However, composite material is less used compared to other systems in the chassis system because it is very hard to solve NVH problem when composite material is applied to vehicle. Especially, reducing squeal noise of composite brake system is essential to apply it to vehicle successfully. In this paper, we present a new solution to reduce squeal noise of composite brake system. To achieve this goal, we analyze main causes of noise using RCA (Root Cause Analysis), CA (Contradiction Analysis) and sequentially get IFR (Ideal Final Result) to solve the problem. Next, we define the function of composite brake system and derive control factors and noise factors. A variety of tests for factors like chamfer, slot, damping shim, underlayer of brake pad are done. In addition, we analyze level of contribution for control factors theoretically. Finally, we get the effective solution for reducing squeal noise.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1187-1200
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• 2002

This paper is concerned with the design or an LMI (Linear Matrix Inequality) -based H$\infty$ controller for a line of sight (LOS) stabilization system and with its robustness performance. The linearization of the system is necessary to analyze various nonlinear characteristics, but the linearization entails modeling uncertainties which reduce its performance. In addition, the stability of the LOS can be adversely affected by angular velocity disturbances while the vehicle is moving. As the vehicle accelerates, all the factors that are Ignored and simplified for the linearization tend to Inhibit the performance of the system. The robustness in the face of these uncertainties needs to be assured. This paper employs H$\infty$ control theory to address these problems and the LMI method to provide a suitable controller with minimal constraints for the system. Even though the system matrix does not have a full rank, the proposed method makes it possible to design a H$\infty$ controller and to deal with R and S matrices for reducing the system order. It can be also shown that the proposed robust controller has a better disturbance attenuation and tracking performance. The LMI method is also used to enhance the applicability of the proposed reduced-order H$\infty$ controller for the system given. The LMI-based H$\infty$ controller has superior disturbance attenuation and reference input tracking performance, compared with that of the conventional controller under real disturbances.

• Journal of Radiation Protection and Research
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• v.41 no.2
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• pp.149-154
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• 2016

Background: Any real application of Bayesian inference must acknowledge that both prior distribution and likelihood function have only been specified as more or less convenient approximations to whatever the analyzer's true belief might be. If the inferences from the Bayesian analysis are to be trusted, it is important to determine that they are robust to such variations of prior and likelihood as might also be consistent with the analyzer's stated beliefs. Materials and Methods: The robust Bayesian inference was applied to atmospheric dispersion assessment using Gaussian plume model. The scopes of contaminations were specified as the uncertainties of distribution type and parametric variability. The probabilistic distribution of model parameters was assumed to be contaminated as the symmetric unimodal and unimodal distributions. The distribution of the sector-averaged relative concentrations was then calculated by applying the contaminated priors to the model parameters. Results and Discussion: The sector-averaged concentrations for stability class were compared by applying the symmetric unimodal and unimodal priors, respectively, as the contaminated one based on the class of ${\varepsilon}$-contamination. Though ${\varepsilon}$ was assumed as 10%, the medians reflecting the symmetric unimodal priors were nearly approximated within 10% compared with ones reflecting the plausible ones. However, the medians reflecting the unimodal priors were approximated within 20% for a few downwind distances compared with ones reflecting the plausible ones. Conclusion: The robustness has been answered by estimating how the results of the Bayesian inferences are robust to reasonable variations of the plausible priors. From these robust inferences, it is reasonable to apply the symmetric unimodal priors for analyzing the robustness of the Bayesian inferences.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.185-193
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• 2022

This paper proposes an adaptive sliding mode control with radial basis function neural network(RBFNN) scheme to enhance the performance of position and attitude tracking control of quadrotor UAV. The RBFNN is utilized on the approximation of nonlinear function in the UAV dynmic model and the weights of the RBFNN are adjusted online according to adaptive law from the Lyapunov stability analysis to ensure the state hitting the sliding surface and sliding along it. In order to compensate the network approximation error and eliminate the existing chattering problems, the sliding mode control term is adjusted by adaptive laws, which can enhance the robust performance of the system. The simulation results of the proposed control method confirm the effectiveness of the proposed controller which applied for a nonlinear quadrotor UAV is presented. Form the results, it's shown that the developed control system is achieved satisfactory control performance and robustness.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.1
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• pp.235-242
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• 2011

The control performance in active structural control system can be drastically deteriorated when the modeling errors and the uncertainties existing in the disturbances are disregarded in the designing stage. It can even throw the control system into an unstable phase, resulting in out of control against the seismic excitations. The purpose of the study is to investigate the control effectiveness of a non-linear control system called sliding mode controller(SMC) in cooperation with a Tuned Mass Damper subjected to the three seismic excitations selected from the FFT analysis. Even though the transient performance such as settling time and overshoot were deteriorated, the robustness against the system stability was appeared from SMC when the structural masses and stiffness perturbed within the range of ${\pm}30%$. SMC is a feasible technique for active structural control in cooperation with TMD against seismic disturbances, exhibiting robustness in perturbation of system stiffness and mass as well as uncertainties of the disturbances.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3258-3273
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• 2021

Malware is a severe threat to the computing system and there's a long history of the battle between malware detection and anti-detection. Most traditional detection methods are based on static analysis with signature matching and dynamic analysis methods that are focused on sensitive behaviors. However, the usual detections have only limited effect when meeting the development of malware, so that the manual update for feature sets is essential. Besides, most of these methods match target samples with the usual feature database, which ignored the characteristics of the sample itself. In this paper, we propose a new malware detection method that could combine the features of a single sample and the general features of malware. Firstly, a structure of Directed Cyclic Graph (DCG) is adopted to extract features from samples. Then the sensitivity of each API call is computed with Markov Chain. Afterward, the graph is merged with the chain to get the final features. Finally, the detectors based on machine learning or deep learning are devised for identification. To evaluate the effect and robustness of our approach, several experiments were adopted. The results showed that the proposed method had a good performance in most tests, and the approach also had stability with the development and growth of malware.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.9
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• pp.2242-2251
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• 1993

The mesh-based frictional contact model has been developed which does not rely on the spatial derivatives of the tool surface. Only points on the surface are evaluated from the description. which can then be simplified because of the relaxed demands placed on it. The surface tangents, normals, and corresponding derivatives at each finite-element node are evaluated directly from the finite-element mesh, in terms of the connecting nodal positions. The advantages accrue because there is no longer a need for a smooth tool surface to assure reasonable normals and derivatives. Furthermore, it can be shown that the equilibrium equations can only be properly written with a special normal derived from the mesh itself. The validity, accuracy, computation time, and stability of mesh-based contact model were discussed with the numerical examples of rounded flat-top and rough, flat-top rounded punch forming operations. Also, the forming process of a automobile inner panel section was simulated for testing the robustness of new contact model. In the discussion, the superiority of new model was examined, comparing with tool-based contact one.