• Journal of KSNVE
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• v.7 no.4
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• pp.701-708
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• 1997

Up to now, numerical methods such as Finite Element Method(FEM) or Boundary Element Method(BEM) have been widely used to find the optimized resonator's position during designing a car intake system. However, these methods are not useful at the first stage of car design since it is not easy to change a numerical model consist of a large mesh size. A software has been developed to cover the defects using 4-pole parameter method. The software is running at Windows 95 environment for a user's convenience. To show its usefulness, it is applied to a real automobile intake system.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.8
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• pp.157-163
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• 2001

This paper presents the new linear notion device so called \"inch-werm\" which gets large displacement by incrementally summing small displacements of PZT actuators. Dynamic stiffness of inch-worm is generally low compared to its driving condition due to the requirement of inch-worm like small size and light weight. This low stiffness may degenerate the positional precision of inch-worm. An inch-worm is realized using three PZT actuators, a monolithic moving device and a guide way frame. Finite element method and experimental approach are used to analyse the static and dynamic motion of the designed inch-worm. Command reference input is shaped to reduce the residual vibration of inch-worm. The practical feasibility of inch-worm is also examined by running tests.ing tests.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1233-1240
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• 2004

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the nitration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• Wind and Structures
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• v.15 no.3
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• pp.263-283
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• 2012

This paper presents a framework of nonlinear dynamic analysis of a low-speed moving maglev (magnetically levitated) vehicle subjected to cross winds and controlled using a clipped-LQR actuator with time delay compensation. A four degrees-of-freedom (4-DOFs) maglev-vehicle equipped with an onboard PID (Proportional-Integral-Derivative) controller traveling over guideway girders was developed to regulate the electric current and control voltage. With this maglev-vehicle/guideway model, dynamic interaction analysis of a low-speed maglev vehicle with guideway girders was conducted using an iterative approach. Considering the time-delay issue of unsynchronized tuning forces in control process, a clipped-LQR actuator with time-delay compensation is developed to improve control effectiveness of lateral vibration of the running maglev vehicle in cross winds. Numerical simulations demonstrate that although the lateral response of the maglev vehicle moving in cross winds would be amplified significantly, the present clipped-LQR controller exhibits its control performance in suppressing the lateral vibration of the vehicle.

• Structural Engineering and Mechanics
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• v.30 no.1
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• pp.99-117
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• 2008

This paper presents a comprehensive approach to the evaluation of macroscopic material parameters for natural stone and quarry masonry. To that end, a reliable non-linear material model on a meso-scale is developed to cover the random arrangement of stone blocks and quasi-brittle behaviour of both basic components, as well as the impaired cohesion and tensile strength on the interface between the blocks and mortar joints. The paper thus interrelates the following three problems: (i) definition of a suitable periodic unit cell (PUC) representing a particular masonry structure; (ii) derivation of material parameters of individual constituents either experimentally or running a mixed numerical-experimental problem; (iii) assessment of the macroscopic material parameters including the tensile and compressive strengths and fracture energy.

• Structural Engineering and Mechanics
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• v.26 no.4
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• pp.377-392
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• 2007

A discrete sliding mode control (SMC) method based on hybrid model of neural network and nominal model is proposed to reduce the vibration of flexible structures, which is a robust active controller developed by using a sliding manifold approach. Since the thick boundary layer will reduce the virtue of SMC, the multilayer feed-forward neural network is adopted to model the uncertainty part. The neural network is trained by Levenberg-Marquardt backpropagation. The design objective of the sliding mode surface is based on the quadratic optimal cost function. In course of running, the input signal of SMC come from the hybrid model of the nominal model and the neural network. The simulation shows that the proposed control scheme is very effective for large uncertainty systems.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.9 no.3
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• pp.364-375
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• 1997

The fundamental theory and technical approach to aid design and development of an automotive air-conditioning system are presented. The evaluation methods for transient cooling load transferred to a passenger compartment and simulation of automotive air-conditioning components are outlined. The structure of the computer program, the experiemntal correlations, and the simulation results are also included. The total cooling load of the white-colored car is reduced upto 5% for that of the black-colored car when the car is running. Using the infrared reflectance glass, we can also obtain 5% reduction of the total cooling load for the common glass.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1960-1963
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• 2003

For applications such as video surveillance and human computer interface, we propose an efficiently integrated method to detect and track faces. Various visual cues are combined to the algorithm: motion, skin color, global appearance and facial pattern detection. The ICA (Independent Component Analysis)-SVM (Support Vector Machine based pattern detection is performed on the candidate region extracted by motion, color and global appearance information. Simultaneous execution of detection and short-term tracking also increases the rate and accuracy of detection. Experimental results show that our detection rate is 91％ with very few false alarms running at about 4 frames per second for 640 by 480 pixel images on a Pentium IV 1㎓.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.870-875
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• 2008

The main objective of this paper is to control a trajectory tracking of the fish-mimetic robot by CPG (Central Pattern Generator), which is biological approach. CPG is biological neural networks that generate rhythmic movements for locomotion of animals, such as walking, running, swimming and flying. Animals show marvelous ability of autonomous dynamic adaptation for an unsteady fluid dynamic environment or various environments. So, we propose the 3-DOF CPG controller to track the trajectory of the fish robot in plane motion. The conformity of the proposed control algorithm is validated by simulation for a fish robot model, which is made by a commercial dynamic package.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.537-543
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• 2003

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the vibration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.