The work summaries the most diffused acoustic emission (AE) signal analysis methods in the monitoring systems of the machining processes. Concretely, pattern recognition, group method of data handling, fuzzy classifier, neural network and, sensor and data fusion methodologies, since they can be used as decision making procedures for process assessment. Besides, some works showing the mentioned signal analysis methods have been shown. In partiuclar, the most used ones in the detection of the progressive tool wear, the catastrophic tool failure and the chip formation.
Main decision making procedures used in the monitoring systems of machining processes based on acoustic emission sensors / E. M., Rubio; Teti, Roberto; Baciu, IOAN LIVIU. - STAMPA. - 5:(2006), pp. 189-192.
Main decision making procedures used in the monitoring systems of machining processes based on acoustic emission sensors
TETI, ROBERTO;BACIU, IOAN LIVIU
2006
Abstract
The work summaries the most diffused acoustic emission (AE) signal analysis methods in the monitoring systems of the machining processes. Concretely, pattern recognition, group method of data handling, fuzzy classifier, neural network and, sensor and data fusion methodologies, since they can be used as decision making procedures for process assessment. Besides, some works showing the mentioned signal analysis methods have been shown. In partiuclar, the most used ones in the detection of the progressive tool wear, the catastrophic tool failure and the chip formation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
