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Advanced signal processing techniques for wind turbine gearbox bearing failure detection

Advanced signal processing techniques for wind turbine gearbox bearing failure detection
Advanced signal processing techniques for wind turbine gearbox bearing failure detection
Premature wind turbine gearbox failure has been observed to occur after periods as short as 5 years, while the design life of a gearbox is expected to exceed 20 years. Most wind turbine failures have been found to be initiated at the bearings. The formation of white etching cracks (WECs) on the subsurface of bearings can occur after 6 months to 2 years of operation. WECs, which can eventually lead to spallation and catastrophic failure of the wind turbine gearbox, have been identified as one of the most severe damaging causes of failure in bearings. Recent research has suggested that electrical load is one of the key parameters affecting the formation of WECs. To investigate the characteristics and formation of WECs, a test rig was designed at the University of Erlangen-Nuremberg. The rig facilitated the simultaneous data capture of vibration, electrostatic and acoustic emission through dedicated sensors. Signal processing techniques have been utilised to process and correlate sensor data in order to detect WECs before the final failure occurs and trace back to earlier stages of propagation. This conference paper demonstrates the effectiveness of the suggested signal processing techniques, using multiple sensors, to detect and monitor bearing crack initiation and propagation.
acoustic emission, Electrostatic sensing, Signal Processing, Bearing failure, rolling element bearing, wind turbine
Esmaeili, Kamran
99ab4049-5a0c-46dd-9478-91fc9c82f711
Zuercher, Manuel
787dbb36-ab4b-4dfc-99c0-5b6ec2a87a1b
Wang, Ling
c50767b1-7474-4094-9b06-4fe64e9fe362
Harvey, Terence
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Holweger, Walter
97dc70d7-c418-430b-8f43-424983c07e8d
White, Neil
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
Schlücker, Eberhard
637c5ed0-5a20-4a9a-9a4e-9f289453109c
Esmaeili, Kamran
99ab4049-5a0c-46dd-9478-91fc9c82f711
Zuercher, Manuel
787dbb36-ab4b-4dfc-99c0-5b6ec2a87a1b
Wang, Ling
c50767b1-7474-4094-9b06-4fe64e9fe362
Harvey, Terence
3b94322b-18da-4de8-b1af-56d202677e04
Holweger, Walter
97dc70d7-c418-430b-8f43-424983c07e8d
White, Neil
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
Schlücker, Eberhard
637c5ed0-5a20-4a9a-9a4e-9f289453109c

Esmaeili, Kamran, Zuercher, Manuel, Wang, Ling, Harvey, Terence, Holweger, Walter, White, Neil and Schlücker, Eberhard (2017) Advanced signal processing techniques for wind turbine gearbox bearing failure detection. First World Congress on Condition Monitoring 2017: Condition monitoring (CM) methods and technologies, ILEC Conference Centre, United Kingdom. 13 - 16 Jun 2017. 13 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Premature wind turbine gearbox failure has been observed to occur after periods as short as 5 years, while the design life of a gearbox is expected to exceed 20 years. Most wind turbine failures have been found to be initiated at the bearings. The formation of white etching cracks (WECs) on the subsurface of bearings can occur after 6 months to 2 years of operation. WECs, which can eventually lead to spallation and catastrophic failure of the wind turbine gearbox, have been identified as one of the most severe damaging causes of failure in bearings. Recent research has suggested that electrical load is one of the key parameters affecting the formation of WECs. To investigate the characteristics and formation of WECs, a test rig was designed at the University of Erlangen-Nuremberg. The rig facilitated the simultaneous data capture of vibration, electrostatic and acoustic emission through dedicated sensors. Signal processing techniques have been utilised to process and correlate sensor data in order to detect WECs before the final failure occurs and trace back to earlier stages of propagation. This conference paper demonstrates the effectiveness of the suggested signal processing techniques, using multiple sensors, to detect and monitor bearing crack initiation and propagation.

Text
Esmaeili-Advanced signal processing techniques for wind turbine gearbox bearing failure detection - Accepted Manuscript
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More information

Accepted/In Press date: 28 April 2017
Venue - Dates: First World Congress on Condition Monitoring 2017: Condition monitoring (CM) methods and technologies, ILEC Conference Centre, United Kingdom, 2017-06-13 - 2017-06-16
Keywords: acoustic emission, Electrostatic sensing, Signal Processing, Bearing failure, rolling element bearing, wind turbine
Organisations: EEE, nCATS Group, Education Hub

Identifiers

Local EPrints ID: 411707
URI: http://eprints.soton.ac.uk/id/eprint/411707
PURE UUID: f8458d26-e838-48c9-be88-4b9a74192882
ORCID for Ling Wang: ORCID iD orcid.org/0000-0002-2894-6784
ORCID for Neil White: ORCID iD orcid.org/0000-0003-1532-6452

Catalogue record

Date deposited: 22 Jun 2017 16:31
Last modified: 02 May 2020 00:28

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Contributors

Author: Kamran Esmaeili
Author: Manuel Zuercher
Author: Ling Wang ORCID iD
Author: Terence Harvey
Author: Walter Holweger
Author: Neil White ORCID iD
Author: Eberhard Schlücker

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