Several sensing systems such as cutting force and torque, motor current and effective power, vibrations, acourstinc emission or audible energy sound have been analysed in recent years. Audible sound signals emitted during machining processes is one of the most practical techniques. The aim of this work is to characterise the audible sound signals from milling processes with different cutting parameters as a first approach to study of audible sound based monitoring systems. The classification of audible sound signal features for aprocess conditions monitoring has been carried out using graphical analysis and neural network data processing.

Monitoring of Machining Processes through NN Analysis of Audible Sound Signals

TETI, ROBERTO;
2004

Abstract

Several sensing systems such as cutting force and torque, motor current and effective power, vibrations, acourstinc emission or audible energy sound have been analysed in recent years. Audible sound signals emitted during machining processes is one of the most practical techniques. The aim of this work is to characterise the audible sound signals from milling processes with different cutting parameters as a first approach to study of audible sound based monitoring systems. The classification of audible sound signal features for aprocess conditions monitoring has been carried out using graphical analysis and neural network data processing.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/8193
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