Segreto, Tiziana and Caggiano, Alessandra and Karam, Sara and Teti, Roberto (2017) Vibration sensor monitoring of nickel-titanium alloy turning for machinability evaluation. Sensors (Switzerland), 17 (12). ISSN 1424-8220
Full text not available from this repository. (Request a copy)Abstract
Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.
Item Type: | Article |
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Additional Information: | Funding Information: Acknowledgments: This research work has received funding support from the “Programma per il finanziamento della ricerca di Ateneo” funded by the University of Naples Federico II under grant agreement n. 41_1458046376—CLOUD Manufacturing for On-Demand manufacturing sErvices (CLOUD MODE). The Fraunhofer Joint Laboratory of Excellence for Advanced Production Technology (Fh-J_LEAPT) at the Publisher Copyright: © 2017 by the authors. Licensee MDPI, Basel, Switzerland. |
Uncontrolled Keywords: | /dk/atira/pure/subjectarea/asjc/1600/1602 |
Departments or Groups: | |
Depositing User: | Admin SSL |
Date Deposited: | 19 Oct 2022 23:12 |
Last Modified: | 22 Jul 2023 19:20 |
URI: | http://repository-testing.wit.ie/id/eprint/4670 |
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