Gearbox fault detection using spectrum analysis of the drive motor current signal

Mohamed Rgeai, Fengshou Gu, Andrew Ball, Mohamed Elhaj, Mohamed Ghretli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper investigates the application of spectrum analysis of the motor current signal to the detection of mechanical faults in a two-stage helical gearbox driven by an 11kW induction motor. The benefits of using the current signal of the drive motor to monitor downstream mechanical components include a non-intrusive approach, potentially applicable remotely from the machine, likely less costly to apply than more conventional approaches like vibration monitoring, and with scope for improved health and safety. Comparison of the spectral content of the motor current signal against the baseline is used for the purposes of detecting and assessing the severity of pinion gear faults in a multi-stage gearbox, and a method is established that quantifies spectral components and provides a basis for assessment of gearbox condition. The spectrum is dominated by the 50Hz mains frequency component in the motor current spectrum and families of sidebands are revealed which correlate with the shaft rotational frequencies (RF) around the gear meshing frequency (GMF). The number and the amplitude of the sidebands rise when a local tooth fault is introduced into the gear and the clear differences can be observed between the faulty and the healthy spectra. The work in this paper then confirms the abilities of motor current signal for fault detection of downstream machines.

LanguageEnglish
Title of host publicationEngineering Asset Lifecycle Management - Proceedings of the 4th World Congress on Engineering Asset Management, WCEAM 2009
Pages758-769
Number of pages12
Publication statusPublished - 2009
Event4th World Congress on Engineering Asset Management: Engineering Asset Lifecycle Management - Ledra Marriot Hotel, Athens, Greece
Duration: 28 Sep 200930 Sep 2009
Conference number: 4
http://wceam.com/past-congresses/wceam-2009/ (Link to Conference Details )

Conference

Conference4th World Congress on Engineering Asset Management
Abbreviated titleWCEAM 2009
CountryGreece
CityAthens
Period28/09/0930/09/09
Internet address

Fingerprint

Fault detection
Spectrum analysis
Gears
Gear teeth
Induction motors
Health
Monitoring
Fault

Cite this

Rgeai, M., Gu, F., Ball, A., Elhaj, M., & Ghretli, M. (2009). Gearbox fault detection using spectrum analysis of the drive motor current signal. In Engineering Asset Lifecycle Management - Proceedings of the 4th World Congress on Engineering Asset Management, WCEAM 2009 (pp. 758-769)
Rgeai, Mohamed ; Gu, Fengshou ; Ball, Andrew ; Elhaj, Mohamed ; Ghretli, Mohamed. / Gearbox fault detection using spectrum analysis of the drive motor current signal. Engineering Asset Lifecycle Management - Proceedings of the 4th World Congress on Engineering Asset Management, WCEAM 2009. 2009. pp. 758-769
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Rgeai, M, Gu, F, Ball, A, Elhaj, M & Ghretli, M 2009, Gearbox fault detection using spectrum analysis of the drive motor current signal. in Engineering Asset Lifecycle Management - Proceedings of the 4th World Congress on Engineering Asset Management, WCEAM 2009. pp. 758-769, 4th World Congress on Engineering Asset Management, Athens, Greece, 28/09/09.

Gearbox fault detection using spectrum analysis of the drive motor current signal. / Rgeai, Mohamed; Gu, Fengshou; Ball, Andrew; Elhaj, Mohamed; Ghretli, Mohamed.

Engineering Asset Lifecycle Management - Proceedings of the 4th World Congress on Engineering Asset Management, WCEAM 2009. 2009. p. 758-769.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Rgeai M, Gu F, Ball A, Elhaj M, Ghretli M. Gearbox fault detection using spectrum analysis of the drive motor current signal. In Engineering Asset Lifecycle Management - Proceedings of the 4th World Congress on Engineering Asset Management, WCEAM 2009. 2009. p. 758-769