• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.950-955
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• 2005

This paper describes an intelligent filler wire feeding device which can control 3- dimensional seam tracking and the filler wire speed by measuring the gap position and the joint gap width in laser welding. By means of visual sensor controlled filling the missing material into the joint gap and 3 dimensional seam tracking, lineup errors from manufacturing tolerances and the repeatability of lineup jigs and weld robot can be balanced and at an even seam quality which avoids weld defects. In this paper, we assessed weld quality in 2mm sheets of A16061 which had various gap width by using the intelligent filler wire feeding device.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.327-330
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• 2021

In this paper, a new noise filling method is proposed for improving the performance of the 3D audio codec. In the new method, the core band is limited up to MAX_SFB, not up to the IGF start frequency. And the noise filling is applied to all frequency range of the IGF source patches. We conduct the MUSHRA test and find that the proposed noise filling method demonstrates better performance than the conventional method.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.59-66
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• 2006

In laser welding, automatic seam tracking is important to adjust the laser head position in real time as it moves along the seam. Also if the joint gap is occurred, filling the missing material into the joint gap is necessary to prevent welding defects and bad welding quality. In general, the joint gap width is not constant along the seam due to a variety of reason. So it is essential to control the filler wire speed into the joint gap to acquire good welding quality. This paper describes an intelligent filler wire feeding device which can control 3-dimensional seam tracking and the filler wire speed by measuring the gap position and the joint gap width in laser welding. We call this device as Smart Micro Control system(SMC). To achieve this objective, we assessed weld quality in 2mm sheets of A16061 which had various gap width by using the developed device. From the experimental results, It was found the possibility that the developed device could be used in welding various 3-dimensional structures.

• Journal of IKEEE
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• v.24 no.4
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• pp.1122-1128
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• 2020

Bandwidth Extension refers to restoring and expanding a narrow band signal(NB) that is damaged or damaged in the encoding and decoding process due to the lack of channel capacity or the characteristics of the codec installed in the mobile communication device. It means converting to a wideband signal(WB). Bandwidth extension research mainly focuses on voice signals and converts high bands into frequency domains, such as SBR (Spectral Band Replication) and IGF (Intelligent Gap Filling), and restores disappeared or damaged high bands based on complex feature extraction processes. In this paper, we propose a model that outputs an bandwidth extended signal based on an autoencoder among deep learning models, using the residual connection of one-dimensional convolutional neural networks (CNN), the bandwidth is extended by inputting a time domain signal of a certain length without complicated pre-processing. In addition, it was confirmed that the damaged high band can be restored even by training on a dataset containing various types of sound sources including music that is not limited to the speech.