A computationally efficient algorithm devoted to gear tooth localized fault detection in induction machine-based systems
| Autor: | Humberto Henao, Gerard-Andre Capolino, S. Hedayati Kia, Giansalvo Cirrincione |
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| Rok vydání: | 2016 |
| Předmět: |
Engineering
Signal processing business.industry Stator Computation 020208 electrical & electronic engineering Bandwidth (signal processing) 02 engineering and technology Fault (power engineering) Fault detection and isolation law.invention law 0202 electrical engineering electronic engineering information engineering Electronic engineering business Algorithm Energy (signal processing) Induction motor |
| Zdroj: | 2016 XXII International Conference on Electrical Machines (ICEM). |
| DOI: | 10.1109/icelmach.2016.7732819 |
| Popis: | This paper presents a fast and computationally efficient algorithm based on the combination of both zoom-MUSIC and zoom-FFT methods for gear tooth localized fault detection in induction machine-based systems. This method relies mainly on the zoom-MUSIC technique for rotor speed estimation at a primary stage and the application of the zoom-FFT to notch filtered instantaneous frequencies of the stator current space vector for the computation of a fault index. It computes the energy of fault-related frequencies in a predefined bandwidth. It will be demonstrated that the fault can be well detected by using only 100 data samples associated with one second data collection of three stator currents. A test-rig based on a 250W three-phase squirrel-cage induction machine shaft-connected to a single-stage helical gearbox has been used for experimental verifications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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