• 대한임베디드공학회논문지
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• 제19권2호
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• pp.83-90
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• 2024

CNC tools contribute to the production of high-precision and consistent results. However, employing damaged CNC tools or utilizing compromised numerical control can lead to significant issues, including equipment damage, overheating, and system-wide errors. Typically, the assessment of external damage to CNC tools involves capturing a single viewpoint through a camera to evaluate tool wear. This study aims to enhance existing methods by using only a single manually focused Microscope camera to enable comprehensive external analysis from multiple perspectives. Applying the NeRF (Neural Radiance Fields) algorithm to images captured with a single manual focus microscope camera, we construct a 3D rendering system. Through this system, it is possible to generate scenes of areas that cannot be captured even with a fixed camera setup, thereby assisting in the analysis of exterior features. However, the NeRF model requires considerable training time, ranging from several hours to over two days. To overcome these limitations of NeRF, various subsequent models have been developed. Therefore, this study aims to compare and apply the performance of Instant NGP, Mip-NeRF, and DS-NeRF, which have garnered attention following NeRF.