Lane M. D. Owsley

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Vibrations produced by the use of industrial machine tools can contain valuable information about the state of wear of tool cutting edges. However, extracting this information automatically is quite difficult. It has been observed that certain structures present in the vibration patterns are correlated with dullness. In this paper, we present an approach to(More)
Automatic feature extraction is a need in many current applications, including the monitoring of industrial tools. Currently available approaches suffer from a number of shortcomings. The Kohonen self -organizing neural network (SOW) has the potential to act as a feature extractor, but we find it benefits from several modifications. The purpose of these(More)
There are many applications for classification of acoustic transients produced by supersonic projectile fire. Analysis of existing models for such transients suggests they have properties which may be well-captured by a transform of a signal into joint acoustic and modulation frequency: a modulation spectral representation. Simple features are extracted(More)
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