Abstract
This paper describes a new approach for classifying NDE waveforms. Using this approach a set of matched filters is constructed one for each category of waveform, based on parameters from autoregressive models. The method offers advantages in terms of hardware implementation over conventional pattern recognition approaches. Feasibility is shown using computer generated data. Results are then presented for real data from acoustic emission experiments.
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© 1983 Plenum Press, New York
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Melton, R.B. (1983). Classification of NDE Waveforms with Autoregressive Models. In: Thompson, D.O., Chimenti, D.E. (eds) Review of Progress in Quantitative Nondestructive Evaluation. Library of Congress Cataloging in Publication Data, vol 2A. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-3706-5_72
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DOI: https://doi.org/10.1007/978-1-4613-3706-5_72
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