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Grinding is a complex machining process because of the cutting edges and their randomly distributed shapes. Due to insufficient knowledge of process state and tool wear during machining, process performance often does not achieve an optimum level. Acoustic emission sensors can be used to monitor the process in order to optimise performance. A neural network technique is used to remove unwanted signal disturbances and to give the best possible analysis of the signal and classification of the resulting information.

Additional information

Authors: HUNDT W, Eidgenössische Technische Hochschule Zürich, Institut für Werkzeugmaschinen und Fertigung (CH);BRANCI S, Ecole des Mînes d'Alés (FR)
Bibliographic Reference: Paper presented: SENSOR 95, Nürnberg (DE), May 9-11, 1995
Availability: Available from (1) as Paper EN 38845 ORA
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