Eccentricity Fault Diagnosis in BLDC Motor using Finite Element and Frequency Research
Gunjan Sardana1, Neelam Turk2, Satvir Deswal3
1Gunjan Sardana, Department of Electronics, YMCAUST, Faridabad (Haryana), India.
2Dr. Neelam Turk, Department of Electronics, YMCAUST, Faridabad (Haryana), India.
3Satvir Deswal, Department of Electronics, MAIT, IP University, (Delhi), India.
Manuscript received on 10 October 2019 | Revised Manuscript received on 19 October 2019 | Manuscript Published on 02 November 2019 | PP: 9-14 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B10020982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1002.982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The present article examines how rotor, stator and eccentricity faults can be identified in a Brushless DC (BLDC) motor. For a defective BLDCM, a novel finite-element analysis (FEA) index is implemented for non-invasive detection of such faults. The selected index was the elements for amplitude/frequency modulation units with a specific pattern of frequency obtained from the stator current spectrum. The application of this index enables the incidence and type and the proportion of eccentricity to be accurately determined. A finite-element analysis (FEA) method that takes into consideration all the structural and physical features of the motor elements, nonuniform permanent-magnet (PM) features as well as nonuniform air gap permeance, is used to model the BLDC eccentricities. In an attempt to be processed accurately, this model employs tools such as FFT, STFT, Wigner-Ville, Choi Williams analysis and Gabor Transforms to the expected indicators. The suggested index is validated by comparing the simulation and experimentation outcomes of both healthy and faulty machines.
Keywords: Dynamic Eccentricity, BLDC Motor, Fault-Detection, FFT, SIFT, Wigner-Ville Analysis.
Scope of the Article: Frequency Selective Surface