• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.221-224
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• 2005

The authors have recently developed a method for identification of Volterra kernels of nonlinear systems by using M-sequence and correlation technique. In this paper, we apply the proposed method to identification of a robot manipulator which has two degrees of freedom. From the results of the experiment, the nonlinear characteristics of the robot manipulator can be identified by the proposed method.

• Korean Journal of Optics and Photonics
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• v.14 no.4
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• pp.383-391
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• 2003

A new optical security system for the protection of personal identification information is proposed. Personal identification information consisting of a pure face image and an identification number is used for verification and authentication. Image encryption is performed by a fully phase image encryption technique with two random phase masks located in the input and the Fourier plane of 4-f correlator. The personal information, however, can be leaked out in the decryption process. To cope with this possibility, the encrypted image itself is used in the identification process. An encrypted personal identification number is discriminated and recognized by using the proposed MMACE_p (multiplexed MACE_p) filter, and then authenticity of the personal information is verified by correlation of the face image using the optical wavelet matched filter (OWMF). MMACE_p filter is a synthetic filter with four MACE_p (minimum average correlation energy_phase encrypted) filters multiplexed in one filter plane to recognize 10 different encrypted-numbers at a time. OWMF can improve discrimination capability and SNR (signal to noise ratio). Computer simulations confirmed that the proposed security technique can be applied to the protection of personal identification information.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.7
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• pp.620-628
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• 2010

Using the responses of deck plate, a new bridge weigh-in-motion system has been introduced. The approach includes not only a systematic algorithm for the extraction of moment influence sequence but also a sensitivity-based system identification technique. The algorithm indentifies the influence sequence, the axle loads, and axle location of moving vehicles on a bridge, simultaneously. The accuracy and practicability of the algorithm have been examined experimentally for a folded deck plate on Yongjong Grand suspension bridge. It turns out that the two-dimensional effects of the behavior of deck plate should be considered for further accuracy improvement.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.2062-2069
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.182-188
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.133-140
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• 2018

In electronic warfare(EW), low probability of intercept(LPI) radar signal is a survival technique. Accordingly, identification techniques of the LPI radar waveform have became significant recently. In this paper, classification and extracting parameters techniques for 7 intrapulse modulated radar signals are introduced. We propose a technique of classifying intrapulse modulated radar signals using Convolutional Neural Network(CNN). The time-frequency image(TFI) obtained from Choi-William Distribution(CWD) is used as the input of CNN without extracting the extra feature of each intrapulse modulated radar signals. In addition a method to extract the intrapulse radar modulation parameters using binary image processing is introduced. We demonstrate the performance of the proposed intrapulse radar waveform identification system. Simulation results show that the classification system achieves a overall correct classification success rate of 90 % or better at SNR = -6 dB and the parameter extraction system has an overall error of less than 10 % at SNR of less than -4 dB.

• Smart Structures and Systems
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• v.7 no.2
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• pp.133-152
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• 2011

System identification is a fundamental step towards the application of structural health monitoring and damage detection techniques. On this respect, the development of evolved identification strategies is a priority for obtaining reliable and repeatable baseline modal parameters of an undamaged structure to be adopted as references for future structural health assessments. The paper presents the identification of the modal parameters of the Guangzhou New Television Tower, China, using a data-driven stochastic subspace identification (SSI-data) approach complemented with an appropriate automatic mode selection strategy which proved to be successful in previous literature studies. This well-known approach is based on a clustering technique which is adopted to discriminate structural modes from spurious noise ones. The method is applied to the acceleration measurements made available within the task I of the ANCRiSST benchmark problem, which cover 24 hours of continuous monitoring of the structural response under ambient excitation. These records are then subdivided into a convenient number of data sets and the variability of modal parameter estimates with ambient temperature and mean wind velocity are pointed out. Both 10 minutes and 1 hour long records are considered for this purpose. A comparison with finite element model predictions is finally carried out, using the structural matrices provided within the benchmark, in order to check that all the structural modes contained in the considered frequency interval are effectively identified via SSI-data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1636-1647
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• 1997

As most of today's automatic transmissions in passenger car adopt a electro-hydraulic control system, the role of electronically controlled solenoid valves occupies an important position and it is essential to predict solenoid transient characteristics in order to design and evaluate the performance of the hydraulic control system. However, in general, both the magnetic and electrical parameters f the solenoid system are hardly known and it is not easy to model this section with moderate complexity although mechanical system could be developed using the classical second order system. This paper presents a dynamic modelling technique of a solenoid valve, that is controlled by pulse width modulation for an automatic transmission, in terms of system identification theory. In nonlinear computer simulation, it is shown that the identified systems which produce magnetic force to input duty cycle for various excitation signals predict the static and dynamic performance very well near the operating point and in experiment conducted to confirm the validity of identification theory for PWM solenoid valve, we find that there is a good agreement between the experimental data and simulation result. Hence, this model can be utilized in the development of pressure control system with PWM solenoid valve.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.331-338
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• 2004

In this paper, stiffness and damping matrices are experimentally constructed using structural modal information on frequencies, damping ratios and modal vectors, which are obtained by shaking table tests. The acceleration of the shaking table is used as the input signal, and the resulting acceleration of each floor is measured as output signal. The characteristic and limitation of modal information from shaking table test are obtained by Common Based-normalized System Identification(CBSI) technique which is based on time domain information.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.93.1-93
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• 2001

An evolutionary approach for the design of Fuzzy Logic Systems(FLSs) is proposed. Membership functions(MFs) in Takagi-Sugeno type fuzzy logic system is optimized through evolutionary process. Output singleton values are obtained through pseudo-inverse method. The proposed technique is unique for that, to prevent overfilling phenomenon, limited-level RBF membership functions are used and the new fitness function is invented. To show the effectiveness of the proposed method, some simulations results on model identification are given.