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Communication Dans Un Congrès Année : 2016

A Computationally Efficient Algorithm Devoted to Gear Tooth Localized Fault Detection in Induction Machine-Based Systems

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Résumé

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.
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Dates et versions

hal-03629909 , version 1 (04-04-2022)

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  • HAL Id : hal-03629909 , version 1

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Shahin Hedayati Kia, G. Cirrincione, H. Henao, Gérard-André Capolino. A Computationally Efficient Algorithm Devoted to Gear Tooth Localized Fault Detection in Induction Machine-Based Systems. 2016 XXII INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES (ICEM), Sep 2016, Lausanne, Switzerland. pp.2144-2150. ⟨hal-03629909⟩

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