• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.612-616
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• 2007

This paper describes a procedure to improve road noise using DPDS estimation. We can estimate a body local stiffness at chassis mounting point where the path of road input vibration by DPDS with experiment and FE simulation. DPDS result from FE model has a good correlation with experiment data. FE model DPDS shows weak points among chassis mounting points. Body panel thickness and shape were changed to meet DPDS target. Improved DPDS of critical points makes a road noise level lower.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.5
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• pp.327-333
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• 2003

Several tests are performed to evaluate road booming noise. Baseline test delivers the information of road noise characteristics. Coupling effect between structure and acoustics is obtained from the mode shapes and the natural frequencies by the modal test. Equivalent stiffness at joint areas between chassis and car-body system can be determined by the input point inertance test. Noise sensitivity of body mounting point of a chassis part can be obtained from the noise transfer function test with input point inertance test. Operational deflection shape makes us analyze the actual vibration modes of the chassis system under actual leading and find noise sources very easily. Finally, the transfer path analysis is used to Identify noise Paths through the chassis system. The objectives and the procedures of the tests are described in this Paper Also, the guideline for efficient road noise evaluation test can be found.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.980-985
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• 2002

Several tests are performed to evaluate road booming noise. Baseline test delivers the information of road noise characteristics. Coupling effect between structure and acoustics is obtained from the mode shapes and the natural frequencies by the modal test. Equivalent stiffness at joint areas between chassis and car-body system can be determined by the input point inertance test. Noise sensitivity of body mounting point of a chassis part can be obtained from the noise transfer function test with input point inertance test. Operational deflection shape makes us analyze the actual vibration modes of the chassis system under actual loading and find noise sources very easily. finally, the transfer function analysis is used to identify noise paths through the chassis system. However, all of the tests above mentioned must be performed to evaluate road booming noise. The objectives and the procedures of the tests are described in this paper. Also, the guideline for efficient road noise evaluation test can be found.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.42-48
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• 1996

In this paper, a position correction system of industrial robot for door-chassis assembly tast is developed in connection with the position correction algorithm shown in Part I. Tow notches and a hole of auto chassis are selected as the reference measure points and a vision based error detection algorithm is devised to measure in accuracy of less than 0.07mm. And also, the transformation between base and tool coordinates of the robot is shown to send the suitable correction quantities caaording to robot's option. The obtained algorithms were satisfactorily implemented for a real door-chassis model such that the system could accomplish visually acceptable door-chassis assembly task.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.34-41
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• 1996

This work deals with finding a suitable position correction algorithm of industrial robot based on measuring particular points, which calculates two dimensional correction quantities and the must allow visually acceptable door-chassis assembly task. Three optimizing algorithms corresponding to three differ- ent error based performance indices are compared and selected to the best one, in terms of the predefined total uniformity, line uniformity and computational time. The selected algorithm(Total Error Minimization) is implemented for a simple door-chassis model to show its effectiveness.