• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.121-130
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• 2012

This paper proposes an intuitive real-time robot control system using human body movement. Recently, it has been developed that motion generation for humanoid robots with reflecting human body movement, which is measured by a motion capture. However, in the existing studies about robot control system by human body movement, the detailed structure information of a robot, for example, degrees of freedom, the range of motion and forms, must be examined in order to calculate inverse kinematics. In this study, we have proposed Associative Motion Generation as humanoid robot motion generation method which does not need the detailed structure information. The associative motion generation system is composed of two neural networks: nonlinear principal component analysis and Jordan recurrent neural network, and the associative motion is generated with the following three steps. First, the system learns the correspondence relationship between an indication and a motion using training data. Second, associative values are extracted for associating a new motion from an unfamiliar indication using nonlinear principal component analysis. Last, the robot generates a new motion through calculation by Jordan recurrent neural network using the associative values. In this paper, we propose a real-time humanoid robot control system based on Associative Motion Generation, that enables user to control motion intuitively by human body movement. Through the task processing and subjective evaluation experiments, we confirmed the effective usability and affective evaluations of the proposed system.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.243-248
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• 2003

An incremental kernel principal component analysis (IKPCA) is proposed for the nonlinear feature extraction from the data. The problem of batch kernel principal component analysis (KPCA) is that the computation becomes prohibitive when the data set is large. Another problem is that, in order to update the eigenvectors with another data, the whole eigenspace should be recomputed. IKPCA overcomes these problems by incrementally computing eigenspace model and empirical kernel map The IKPCA is more efficient in memory requirement than a batch KPCA and can be easily improved by re-learning the data. In our experiments we show that IKPCA is comparable in performance to a batch KPCA for the feature extraction and classification problem on nonlinear data set.

• Smart Structures and Systems
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• v.31 no.2
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• pp.113-130
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• 2023

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

• Smart Structures and Systems
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• v.31 no.1
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• pp.13-27
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• 2023

Fatigue crack is a fatal problem for steel structures. Early detection and maintenance can help extend the service life and prevent hazards. This paper presents the ultrasonic guided waves-based (UGWs-based) fatigue crack detection of a steel I-beam. The semi-analytical finite element model has been built to obtain the wave propagation characteristics. Damage indices in both time and frequency domains were analyzed by considering the characteristic variations of UGWs including the amplitude, phase angle, and wave packet energy. The pulse-echo and pitch-catch methods were combined in the detection scheme. Lab-scale experiments were conducted on welded steel I-beams to verify the proposed method. Results show that the damage indices based on the characteristic variations in the time domain can identify and localize the fatigue crack before it enters the rapid growth stage. The damage severity can be reasonably evaluated by analyzing the time-domain damage indices. Two nonlinear damage indices in the frequency domain give earlier warnings of the fatigue crack than the time-domain damage indices do. The identification results based on the above two nonlinear indices are found to be less consistent under various excitation frequencies. More robust nonlinear techniques needed to be searched and tested for early crack detection in steel I-beams in further study.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.2
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• pp.77-83
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• 2006

Ultrasonic nonlinearity has been considered as a solution for the detection of microcracks or interfacial delamination in a layered structure. The distinguished phenomenon in nonlinear ultrasonics is the generation of higher-order harmonic waves during the propagation. Therefore, in order to quantify the nonlinearity, the conventional method measures a parameter defined as the amplitude ratio of a second-order harmonic component and a fundamental frequency component included in the propagated ultrasonic wave signal. However, its application In field inspection is not easy at the present stage because no standard methodology has yet been made to accurately estimate this parameter. Thus, the aim of this paper is to propose an advanced signal processing technique for the precise estimation of a nonlinear ultrasonic parameter, which is based on power spectral and bispectral analysis. The method of estimating power spectrum and bispectrum of the pulse-like ultrasonic wave signal used in the commercial SAM (scanning acoustic microscopy) equipment is especially considered in this study The usefulness of the proposed method Is confirmed by experiments for a Newton ring with a continuous air gap between two glasses and a real semiconductor sample with local delaminations. The results show that the nonlinear parameter obtained tv the proposed method had a good correlation with the delamination.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.140-145
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• 2010

In this work, to theoretically analyze the nonlinear charging characteristic, a Radial Basis Function Neural Network (RBFNN) is adopted. Based on the RBFNN, an charging characteristic tendency of a Linear Type Magnetic Flux Pump (LTMFP) is analyzed. In the paper, we developed the LTMFP that generates stable and controllable charging current and also experimentally investigated its charging characteristic in the cryogenic system. From these experimental results, the charging current of the LTMFP was also found to be frequency dependent with nonlinear quality due to the nonlinear magnetic behaviour of superconducting Nb foil. On the whole, in the case of essentially cryogenic experiment, since cooling costs loomed large in the cryogenic environment, it is difficult to carry out various experiments. Consequentially, in this paper, we estimated the nonlinear characteristic of charging current as well as realized the intelligent model via the design of RBFNN based on the experimental data. In this paper, we view RBF neural networks as predominantly data driven constructs whose processing is based upon an effective usage of experimental data through a prudent process of Fuzzy C-Means clustering method. Also, the receptive fields of the proposed RBF neural network are formed by the FCM clustering.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4B
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• pp.243-251
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• 2012

To investigate the characteristics of rip current occurring at Haeundae beach, observations obtained from a buoy and a CCTV were analyzed and numerical experiments were conducted. During observed rip-current events, the CCTV images showed that a couple of wave-trains, which are close to regular waves with slightly different directions, propagated to the beach, and wavelet analyses of data from the buoy showed very narrow-banded spectra with a peak frequency. From the evidences, it was inferred that a known mechanism of generating rip current due to the nodal line area of honeycomb-patterned wave crest was one of the significant factors of rip current occurrences of Haeundae beach. The mechanism has been explained by the following: When two wave-trains with slightly different directions propagate to a beach, wave crests of the incident wave-trains form honeycomb pattern due to nonlinear interaction. The nodal lines of honeycomb pattern are developed in the cross-shore direction. And longshore currents flow toward the nodal line area which has very low wave energy. Consequently their mass flux is expelled through the area toward the sea direction. To confirm the generation, numerical experiments were performed using a nonlinear Boussinesq equation model. In the cases with two incident wave-trains with slightly different directions and with a monochromatic wave propagating over a submerged shoal, it was seen that the honeycomb pattern of wave crests was well developed, and thus rip currents were evolved along the nodal lines.

• Journal of the Korea Concrete Institute
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• v.24 no.5
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• pp.567-575
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• 2012

A research was conducted to develop a 2-D nonlinear Galerkin finite element analysis of reinforced concrete structures subjected to high temperature with experiments. Algorithms for calculating the closed-form element stiffness for a triangular element with a fully populated material conductance are developed. The validity of the numerical model used in the program is established by comparing the prediction from the computer program with results from full-scale fire resistance tests. Details of fire resistance experiments carried out on reinforced concrete slabs, together with results, are presented. The results obtained from experimental test indicated in that the proposed numerical model and the implemented codes are accurate and reliable. The changes in thermal parameters are discussed from the point of view of changes of structure and chemical composition due to the high temperature exposure. The proposed numerical model takes into account time-varying thermal loads, convection and radiation affected heat fluctuation, and temperature-dependent material properties. Although, this study considered standard fire scenario for reinforced concrete slabs, other time versus temperature relationship can be easily incorporated.

• Proceedings of the Materials Research Society of Korea Conference
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• 1994.11a
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• pp.125-126
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• 1994

The chemorheological changes and kinetics during curing reaction of an silica filled epoxy system (DGEBA with curing agent Polyxoypropylenediamine) were investigated. This study concentrates on the influence of silica on the reaction kinetics and rheological behavior of the eopxy system. The concentration of the filler was varied 0~200phr. Curing behavior of the silica filled epoxy system was measured at various heating rates with DSC. Conversion was also measured by integrating the obtained DSC curve and Kinetic parameters measured by using the nonlinear regression method. DSC experiments showed that the presence of silica was found to accelerate the progress of the curing reaction and of reduce the heat of reaction compared with that of unfilled epoxy systems . Rheological experiments were conducted on a Physica by using a disposable parallel plate fixture. Material properites were measured such as the elastic modulus(G′), the loss modulus(G"), the loss tangent(tan $\delta$), and the viscosity was at the initial stahe, and the more the silica filler was added, and the lower the gel temperature was in the epoxy system. In this study it is concluded that the curing of the silica filled epoxy system was found to be accelerated, as silica was added to the epoxy compound.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2064-2071
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• 2011

We are developing an innovative super-speed land transportation system running in a partial vacuum in tunnels with small inside diameter to reduce the aerodynamic drag forces. This paper presents the experimental results obtained on a small scale model when a super-speed train model passing through a tunnel with small inside diameter and a partial vacuum to reduce the aerodynamic drag forces. The experiments were performed on a 1/52-scale moving model rig in which a train model with a diameter of 58 mm and a length of 603 mm was accelerated in a launching tube with 12.27 m length by means of the compressed air launcher and then passed through a tunnel model with 17.149 m length. The partial vacuum was maintained in the tunnel in order to reduce the energy consumption of the propulsion system of the super-speed tube train at super-speed of 700 km/h. In this study, the blockage ratio of train to tunnel model is 0.336. Experimental results show the nonlinear effects of the vacuum on the speed-up of the train model in the tunnel model under the partial vacuum up to 0.21 atm and at the velocity up to 684 km/h. This paper is first study for experiments on the speed-up of a super-speed train model in the partial vacuum tunnels.