This paper proposes a self-calibration method of robots those are use in industrial vehicle assembly lines. The proposed method is a position compensation using laser sensor and vision cameras. Because the laser sensor is cross type sensor which can scan a horizontal and vertical line, it is efficient way to detect a feature of vehicle and winding shape of vehicle's body. For position compensation of 3-Dimensional axis, we applied block interpolation method. For selecting feature point, pattern matching method is used and 3-D position is selected by Euclidean distance mapping between 462 feature values and evaluated feature point. In order to evaluate the proposed algorithm, experiments are performed in real industrial vehicle assembly line. As the result of the field test, it shows that robot's working point can be displayed 3-D points. These points are used to diagnosis error of position and reselecting working point.
In this paper, we proposed a new algorithm that can be detected impact position on LPMS using the characteristic of RMS(Root Mean Square) values and analysis of frequency. The proposed estimation algorithm of impact position uses the arriving difference time method using the analysis of frequency and the RMS value. The LPMS(Loose Parts Monitoring System) are used for detecting and evaluating metallic loose parts in reactor systems. On experiment, we use the modeling steel drum instead of real reactor and 4 accelerometer sensors for acquiring the impact signal. And the Computer is connected the accelerometer sensor input and used for monitoring and analyzing of impact signal with Lab-view and Matlab programs. It is efficiently used for reducing processing time and estimated impact position.
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