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Integrated smart bearings for next generation aero-engines Part 1: Development of a sensor suite for automatic bearing health monitoring

Integrated smart bearings for next generation aero-engines Part 1: Development of a sensor suite for automatic bearing health monitoring
Integrated smart bearings for next generation aero-engines Part 1: Development of a sensor suite for automatic bearing health monitoring
The development of smart bearing solutions will contribute to increased aircraft engine reliability, allowing the early detection of bearing failure through robust health monitoring. This project aims to develop intelligent bearing systems for an Ultra High Propulsion Efficiency (UHPE) ground test demonstrator, where a fully integrated self-powered wireless sensing system will be developed for future aircraft. This paper provides a comprehensive review of the state-of-the-art smart bearing technologies and presents the structure of the integrated sensing system focusing on the parameters to be monitored and the sensor technology selection methods for the aircraft engine. Currently, most of the existing smart bearings have been developed for automobile and railway industries with very limited availability for the harsh environment a jet engine experiences, such as high temperatures and vibration levels. Initially monitoring will involve vibration, temperature, load, shaft movement, rotating speed and wear debris. Suitable sensing techniques will be selected using a rating method based on their survivability under the extreme environment inside the engine, as well as their size, weight, sensitivity, operating bandwidth, mounting methods, data processing demand and power consumption for energy harvesting and wireless transmission
Bashir, Imran
e7bed382-cefa-4a4b-a2e2-253ef98a963a
Wang, Ling
c50767b1-7474-4094-9b06-4fe64e9fe362
Harvey, Terence
3b94322b-18da-4de8-b1af-56d202677e04
Zaghari, Bahareh
a0537db6-0dce-49a2-8103-0f4599ab5f6a
Weddell, Alexander
3d8c4d63-19b1-4072-a779-84d487fd6f03
White, Neil
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
Bashir, Imran
e7bed382-cefa-4a4b-a2e2-253ef98a963a
Wang, Ling
c50767b1-7474-4094-9b06-4fe64e9fe362
Harvey, Terence
3b94322b-18da-4de8-b1af-56d202677e04
Zaghari, Bahareh
a0537db6-0dce-49a2-8103-0f4599ab5f6a
Weddell, Alexander
3d8c4d63-19b1-4072-a779-84d487fd6f03
White, Neil
c7be4c26-e419-4e5c-9420-09fc02e2ac9c

Bashir, Imran, Wang, Ling, Harvey, Terence, Zaghari, Bahareh, Weddell, Alexander and White, Neil (2017) Integrated smart bearings for next generation aero-engines Part 1: Development of a sensor suite for automatic bearing health monitoring. In WCCM2017. 12 pp.

Record type: Conference or Workshop Item (Paper)

Abstract

The development of smart bearing solutions will contribute to increased aircraft engine reliability, allowing the early detection of bearing failure through robust health monitoring. This project aims to develop intelligent bearing systems for an Ultra High Propulsion Efficiency (UHPE) ground test demonstrator, where a fully integrated self-powered wireless sensing system will be developed for future aircraft. This paper provides a comprehensive review of the state-of-the-art smart bearing technologies and presents the structure of the integrated sensing system focusing on the parameters to be monitored and the sensor technology selection methods for the aircraft engine. Currently, most of the existing smart bearings have been developed for automobile and railway industries with very limited availability for the harsh environment a jet engine experiences, such as high temperatures and vibration levels. Initially monitoring will involve vibration, temperature, load, shaft movement, rotating speed and wear debris. Suitable sensing techniques will be selected using a rating method based on their survivability under the extreme environment inside the engine, as well as their size, weight, sensitivity, operating bandwidth, mounting methods, data processing demand and power consumption for energy harvesting and wireless transmission

Text Bashir-WCCM2017 - Author's Original
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Published date: 25 April 2017
Organisations: EEE, nCATS Group

Identifiers

Local EPrints ID: 411589
URI: https://eprints.soton.ac.uk/id/eprint/411589
PURE UUID: 6af59c20-cf18-4ae7-9a2d-97ba0d7e73ba
ORCID for Ling Wang: ORCID iD orcid.org/0000-0002-2894-6784
ORCID for Alexander Weddell: ORCID iD orcid.org/0000-0002-6763-5460
ORCID for Neil White: ORCID iD orcid.org/0000-0003-1532-6452

Catalogue record

Date deposited: 21 Jun 2017 16:31
Last modified: 20 Dec 2017 17:31

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Contributors

Author: Imran Bashir
Author: Ling Wang ORCID iD
Author: Terence Harvey
Author: Bahareh Zaghari
Author: Alexander Weddell ORCID iD
Author: Neil White ORCID iD

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