CINECA IRIS Institutional Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishThis paper presents a multi-sensor approach for the bearings diagnostics of induction motors. The physical quantities taken into account are vibrations (acceleration signals), stator current, axial and radial external leakage fluxes. The fault to detect is a “cyclic” localized crack on the external ring of the drive-end bearing. At first, piezoelectric and MEMS accelerometers are compared, showing that a cheap sensor could give sufficient diagnostic information. Subsequently, the analysis of the electromagnetic signals’ spectra is used to detect the fault. In order to facilitate this analysis, the exact characteristic fault frequency is obtained from the vibration spectra and identified in the current and flux signatures. This method avoids the slippage uncertainty on the electromagnetic spectra’s fault peaks detection. Further tests with oscillation load torque show new signatures in the spectra and tests with inverter highlight the peculiar issues coming from this supply condition.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
| Titolo: | A Multisensor Induction Motors Diagnostics Method for Bearing Cyclic Fault | |
| Autori: | ||
| Data di pubblicazione: | 2020 | |
| Abstract: | This paper presents a multi-sensor approach for the bearings diagnostics of induction motors. The physical quantities taken into account are vibrations (acceleration signals), stator current, axial and radial external leakage fluxes. The fault to detect is a “cyclic” localized crack on the external ring of the drive-end bearing. At first, piezoelectric and MEMS accelerometers are compared, showing that a cheap sensor could give sufficient diagnostic information. Subsequently, the analysis of the electromagnetic signals’ spectra is used to detect the fault. In order to facilitate this analysis, the exact characteristic fault frequency is obtained from the vibration spectra and identified in the current and flux signatures. This method avoids the slippage uncertainty on the electromagnetic spectra’s fault peaks detection. Further tests with oscillation load torque show new signatures in the spectra and tests with inverter highlight the peculiar issues coming from this supply condition. | |
| Handle: | http://hdl.handle.net/11571/1360214 | |
| ISBN: | 978-1-7281-9944-3 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
http://hdl.handle.net/11571/1360214
Copyright © 2021