Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Liner condition monitoring of self-lubricating plain bearings

Monteil, Adrien 2023. Liner condition monitoring of self-lubricating plain bearings. PhD Thesis, Cardiff University.
Item availability restricted.

[thumbnail of Final Thesis Copy.pdf] PDF - Accepted Post-Print Version
Restricted to Repository staff only until 22 November 2025 due to copyright restrictions.

Download (92MB)
[thumbnail of Cardiff University Electronic Publication Form] PDF (Cardiff University Electronic Publication Form) - Supplemental Material
Restricted to Repository staff only

Download (724kB)

Abstract

Due to the safety critical nature of the pitch control links on helicopters,it is essential to ensure that the wear of a composite liner within two embedded spherical bearings is not above a specified threshold. Failing to replace the bearings once they have reached this safety critical threshold means running the risk of failure with potential catastrophic consequences. Currently, these are controlled via regular maintenance checks which are costly and timeconsuming due to the lack of a reliable monitoring method. In this thesis, a method of condition monitoring is investigated using a conductive sensor embedded within the liner, with a signal measurement allowing to correlate the threshold wear depth being reached. The composition and structure of the liner had to be analysed to develop a method to integrate the sensor within the liner, with different sensing materials and structures being compared. It was shown that a layer of metallic fibres could be woven into the fabric part of the liner to create a sensing layer with a measurable resistance value. The fibres used for this purpose were brass, stainless steel, bronze and copper, with varying diameters. Two of the proposed smart liners (stainless steel and brass) were tested on a reciprocating test bench to have an initial assessment of their tribological performances, with the comparison of their wear rates and coefficients of friction being drawn against those of the standard SKF liner. The functionality of the sensor was also verified and validated, with a clear and distinct change in the resistance measurement due to the sensing layer being worn through. An initial assessment on the positioning of the sensing layer within the liner was provided to allow future iterations to adjust the wear depth at which the signal is triggered. The integration of the smart liner into a bearing and its production line was evaluated, as well as the requirements for the connecting components to be manufactured successfully. Two methods of implementation were tested. The first one demonstrated through bespoke prototypes that the manufacture of bearings with a fully integrated and wired connection sensing system was feasible. The second, showing the preliminary feasibility study for using a wireless method to connect the sensing layer of the liner to an external receiver. The main benefits and challenges of both methods were presented and compared to allow the creation of a route to implementation for SKF. Overall, it was shown that conductive liners could be manufactured with various materials and structures, with the sensing functionality validated on test samples. The research undertook for this thesis is the foundation block for establishing a condition monitoring method in a plain self-lubricating bearing, with successful steps having been achieved in terms of establishing a reliable wear detection method and developing implementation

Item Type: Thesis (PhD)
Date Type: Completion
Status: Unpublished
Schools: Engineering
Uncontrolled Keywords: Tribology, Condition Monitoring, Plain Bearings, Conductive sensor, Wear Testing, Sensor Integration
Funders: SKF Ltd, College of Physical sciences and Engineering
Date of First Compliant Deposit: 22 November 2024
Last Modified: 25 Nov 2024 10:52
URI: https://orca.cardiff.ac.uk/id/eprint/172090

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics