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Drill breakage detection and prediction using self-organized neural networks

This paper is concerned with drill breakage prediction using self-organized neural networks. In this research, self-organized neural networks are used to classify the sample data and extract standard patterns of all kinds of cutting process states. From standard patterns, the drill breakage can be detected and predicted. Application to drill machine tools verifies the effectiveness of proposed methods.