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.
The paper presents recurrence plot based stability analysis of the horizontal band sawing process of structural steel profiles. The analysis is performed in the parameter space defined by the cutting ...speed, the distance between the blade supports, and the feed rate. The corresponding stability diagrams have been constructed using the recurrence plot characteristic, the determinism of the sound pressure emitted by the process, which quantifies the process predictability. The topology of the experimentally obtained stability diagrams revealed non-linear non-monotonic dynamic behaviour, which made two different chatter avoidance strategies possible by cutting speed variation.
With the development and application of expensive, difficult to cut metals and metal alloys, the minimization of waste material for final operations has, together with the quality of the band sawing ...process, become more and more important. As the onset of chatter can have a very detrimental effect on the quality of the cut, on the quality of the resulting surface, and on process performance in general, the prompt detection of chatter is of high importance. In the paper a multisensory approach is investigated for chatter detection in the band sawing process. In the experiments steel workpieces of geometrically different profiles were used. Based on an analysis of the acquired signals of the cutting forces, machine vibrations and emitted sound, a method involving a set of features for the detection of chatter in a cutting regime has been defined. The proposed method is not affected by the workpiece geometry or the process parameters. Analysis of the individual features extracted from the various process signals has been performed for chatter and chatter-free band sawing regime classification. The paper presents the results obtained using a cross-validation approach, and summarizes the most informative extracted features with respect to the various process signals.
Tool damage due to chatter poses harmful economic impact in modern machining production therefore it is important to avoid or suppress chatter during the production process. In order to establish ...automated chatter-free cutting conditions, the methods for online recognition of chatter and chatter-free cutting should be developed. It this paper a band sawing cut-off process is considered where a combination of selected workpiece properties and cutting parameters result in chatter. A method for online chatter detection based on processing of acoustic signals is proposed. The method consists of pre-processing sound signals with Short-Time Fourier Transform (STFT), extracting frequency invariant features, and finally applying Quadratic Discriminant Analysis (QDA) for classification. The proposed method, tested with two-fold cross validation on experimental data, yields high recognition rate (over 96%).
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