Abstract
In the paper chatter detection in band sawing is considered as a signal processing and classification problem. A multi-sensory experimental setup was established on an industrial band saw including sound, acceleration and cutting force, and measurements. Based on an experimental analysis sound signal is shown to be the most appropriate for chatter detection, therefore a sound-based online chatter detection method is proposed. The method consists of a sound signal pre-processing with Short-Time Fourier Transform, extraction of features in frequency space with optimal threshold and application of Quadratic Discriminant Analysis for chatter detection. The proposed method tested with twofold cross validation yields over 96% success of chatter detection.
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