Comparison between the efficiency of L.M.D and E.M.D algorithms for early detection of gear defects
| Autor: | El Badaoui Mohamed, Kidar Thameur, Thomas Marc, Guilbault Raynald |
|---|---|
| Přispěvatelé: | Ecole de Technologie Supérieure [Montréal] (ETS), Université de Lyon |
| Rok vydání: | 2013 |
| Předmět: |
02 engineering and technology
01 natural sciences Signal Industrial and Manufacturing Engineering Hilbert–Huang transform Fault detection and isolation Hilbert transform 010309 optics symbols.namesake 0203 mechanical engineering local mean decomposition 0103 physical sciences Decomposition (computer science) General Materials Science Sensitivity (control systems) empirical mode decomposition Mathematics Mechanical Engineering gear defect [SPI.MECA.STRU]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of the structures [physics.class-ph] Vibration 020303 mechanical engineering & transports Kurtosis symbols defect descriptor Algorithm |
| Zdroj: | Mechanics & Industry Mechanics & Industry, EDP Sciences, 2013, 14 (2), pp.121-127. ⟨10.1051/meca/2012037⟩ |
| ISSN: | 2257-7750 2257-7777 |
| DOI: | 10.1051/meca/2012037 |
| Popis: | International audience; In recent years, the adaptive decomposition methods have become the center of interest of researchers in many fields and especially in the vibration diagnosis of rotating machines. This paper compares the sensitivity of defect detection of two adaptive methods: local mean decomposition (L.M.D) and empirical mode decomposition (E.M.D). The efficiency of L.M.D and E.M.D methods for detecting defects is investigated for two cases, one from numerical signals and the other from signals recorded during a fatigue test on gear bench. The time descriptors Kurtosis, Thalaf and Thikat are applied on the signal and on its Hilbert transform. The results reveal that both techniques seem to be suitable and have good efficiency for the fault detection. From experimental signals, the comparative results reveal that both methods allow for monitoring wear, but that L.M.D is more sensitive to detect rapid changes of degradation than E.M.D method for the considered case. Consequently these features have potential to become powerful tools for the monitoring of rotating machinery. |
| Databáze: | OpenAIRE |
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