In general, it is noted that the time domain technique becomes difficult to predict with the use of the accurate fatigue life, due to the lack of dynamic information of the structure. When the multi-axial stress is generated by the random vibration excitation in the mechanical structure, the fatigue analysis should have performed in the frequency domain as based on the multi-axial PSDs due to the problems presented above. Notably, Premont proposed a method to calculate the equivalent stress using PSDs in the frequency domain. In calculating the equivalent stress PSD, the phase difference between the multi-axial stress components was not considered at that time. This study propose a frequency domain fatigue analysis technique which can calculate the equivalent stress from the multi-axial PSD, as it works considering the phase difference that can appear in the real vibration excited structure. To verify this method, the conventional time-domain method as similar to a multi-axial rainflow method, is compared with the proposed frequency domain method in a simple simulation model. The multi-axial PSD and finally the von Mises stress model is reviewed, according to whether the phase difference between the multi-axial stress components is considered or not is analyzed.

This paper contributes to development of a new method for detecting rear-side vehicles and estimating the positions for blind spot region or providing the lane change information by using vision systems. Because the real image acquired during car driving has a lot of information including the target vehicle and background image as well as the noises such as lighting and shading, it is hard to extract only the target vehicle against the background image with satisfied robustness. In this paper, the target vehicle has been detected by repetitive image processing such as sobel and morphological operations and a Kalman filter has been also designed to cancel the background image and prevent the misreading of the target image. The proposed method can get faster image processing and more robustness rather than the previous researches. Various experiments were performed on the highway driving situations to evaluate the performance of the proposed algorithm.

This study proposes a map-based control method to improve a vehicle’s lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. The performances of modelreferenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with low friction coefficient. The simulation results show that map-based control provides better stability than model-referenced control.

The machine vision has been applied to a number of industrial applications for quality control and automations to improve the manufacturing processes. In this paper, the automation system using the machine vision is developed, which is applicable to the marking process in a steel production process line. The working environment is very harsh to workers so that the automatic system in the steel industry is required increasingly. The developed automatic marking system consists of several mechanical and electrical elements such as the laser position detecting sensor system for a structured laser beam which is projected to the billet in order to detect the geometry of the billet. An image processing algorithm has been developed to percept the two center positions of a camera and a billet, respectively, and to align two centers. A series of experiments has been conducted to investigate the performance of the proposed algorithm. The results show that two centers of the camera and the billet could be detected very well and differences between two center positions could be also decreased via the proposed location error decreasing algorithm.

Permanent magnetic gears are magneto-mechanical devices that are widely used to replace the ordinary mechanical gear and to transmit torque without the mechanical contact. This study investigates the characteristics of touch free permanent magnetic gear according to the employing systems. The effect of the magnetic torque is analyzed by using 3 dimensional Finite Element Method (FEM). To estimate the transmission torque of FEM model, the numerical results are compared with the experimental results. The influences of geometry size, magnet number on transmission torque are obtained. As results of this paper, it is confirmed that the transmission torque behavior is associated with the configuration of the magnet numbers and the air gap between the two permanent magnetic gears.