Gear fault diagnosis under non-stationary operating mode based on EMD, TKEO, and Shock Detector
| Autor: | Fakher Chaari, Ahmed Hammami, Ahmed Felkaoui, Ridha Ziani, Mohamed Haddar |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Marketing
Signal processing Computer science Strategy and Management Acoustics Shock detector Condition monitoring 02 engineering and technology Signal Bevel Hilbert–Huang transform Shock (mechanics) Vibration 020303 mechanical engineering & transports 0203 mechanical engineering Media Technology General Materials Science |
| Zdroj: | Comptes Rendus Mécanique. 347:663-675 |
| ISSN: | 1631-0721 |
| Popis: | Condition monitoring of gearboxes running under non-stationary operating conditions is a very difficult task. In this study, a signal processing technique is developed for damage detection of a bevel gearbox running under variable load and speed conditions. The proposed technique is applied on simulated vibration data computed through a dynamic model of bevel gearbox. The procedure used in this technique is based on the extraction of the shock related to the defect using the Shock Detector (SD) method. Firstly, vibration signals are decomposed into IMFs using Empirical Mode Decomposition (EMD). Then, the Teager–Kaiser Energy Operator (TKEO) is used to assess the instantaneous energy of the signal. Afterwards, SD is applied to examine and quantify the shock contents of the TKEO signal, which reflect the effect of the defect. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|