Permanent magnet synchronous machine stator windings fault detection by Hilbert–Huang transform
| Autor: | Fernando Alvarez-Gonzalez, Antonio Griffo, Bo Wang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
machine bearings
fault diagnosis statistical analysis time-frequency analysis Hilbert transforms stators synchronous machines HHT permanent magnet synchronous machine stator windings fault detection Hilbert–Huang transform time-frequency signal analysis method empirical mode decomposition reliable fault detection induction machines stator short-circuit faults online statistical analysis Engineering (General). Civil engineering (General) TA1-2040 |
| Zdroj: | The Journal of Engineering (2019) |
| Druh dokumentu: | article |
| ISSN: | 2051-3305 |
| DOI: | 10.1049/joe.2018.8173 |
| Popis: | The Hilbert–Huang transform (HHT) is a time-frequency signal analysis method based on empirical mode decomposition and the Hilbert transform. It is well suited for reliable fault detection since it is unaffected by transient conditions which might cause false alarms. The method has been demonstrated in recent years for bearing fault detection of induction machines (IM). This study explores the possibility of applying the technique to the detection of stator short-circuit faults in permanent magnet synchronous machine (PMSM). A method based on the online statistical analysis of the instantaneous frequency calculated by the HHT is proposed and demonstrated through real-time hardware-in-the-loop simulation and experimental results. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|
Plný text