2023 年 143 巻 3 号 p. 216-221
In painting processes, to prevent the occurrence of painting defects, the rotational speed of the bell cup should be adjusted online based on the painting quality. However, there is a considerable time-delay between the painting process and the evaluation of painting quality. This paper proposes a database-driven painting quality predictor, which has a mechanism to adaptively change the threshold to classify through learning to reduce the delay. A numerical simulation is performed to verify the effectiveness of the proposed method. As a result, the accuracy of the proposed method is superior to that of the conventional method.
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