n the cutting zone of a machining process, several variables are influenced by process conditions: cutting force, vibrations, temperature, acoustic emission, power absorption. Some variables, useful for process monitoring, can be measured by sensors installed on the machine tool. However, when assessing a particular process variable, a single sensory source may not be able to meet all the requirements. A solution is sensor data fusion, the purpose of which is to combine sensory information from disparate sources so that the resulting intelligence is reinforced. Multi-sensor signal processing provides for the extraction and selection of signal features, relevant for the machining monitoring scope,. Application cases of multi-sensor monitoring of machining process conditions investigated at the Fh-J_LEAPT Naples are reported with reference to: (a) workpiece residual stress assessment in turning of nickel base alloys; (b) tool wear state identification in machining of fiber reinforced composites; (c) chip form control in turning of C steel.
Advanced IT methods of signal processing and decision making for zero defect manufacturing in machining / Teti, R.. - 28:(2015), pp. 3-15. (Intervento presentato al convegno 3rd CIRP Global Web Conference on Production Engineering Research: Advancement Beyond State of the Art, CIRPe 2014 tenutosi a Italia nel 2014) [10.1016/j.procir.2015.04.003].
Advanced IT methods of signal processing and decision making for zero defect manufacturing in machining
Teti, R.
2015
Abstract
n the cutting zone of a machining process, several variables are influenced by process conditions: cutting force, vibrations, temperature, acoustic emission, power absorption. Some variables, useful for process monitoring, can be measured by sensors installed on the machine tool. However, when assessing a particular process variable, a single sensory source may not be able to meet all the requirements. A solution is sensor data fusion, the purpose of which is to combine sensory information from disparate sources so that the resulting intelligence is reinforced. Multi-sensor signal processing provides for the extraction and selection of signal features, relevant for the machining monitoring scope,. Application cases of multi-sensor monitoring of machining process conditions investigated at the Fh-J_LEAPT Naples are reported with reference to: (a) workpiece residual stress assessment in turning of nickel base alloys; (b) tool wear state identification in machining of fiber reinforced composites; (c) chip form control in turning of C steel.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
