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Title: Tribology and condition monitoring of composite bearing liners for intelligent aerospace bearings
Author: Karras, Konstantinos
ISNI:       0000 0004 7962 152X
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2018
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This thesis sets out to develop a condition monitoring technique for self-lubricating composite liner bearings. Self-lubricating bearings have been widely employed within the Aerospace industry since the 1950s. The focus of this thesis is primarily on helicopter main rotor applications, where self-lubricating bearings are located within the pitch-control link rodends. Such bearings are designed to be subjected to reciprocating motions and, due to their conformal geometry, they are able to handle high magnitude loads. Through the use of coupon and full-bearing test benches, an understanding of the wear characteristics of the liner composite was achieved, leading to the development of a series of condition monitoring techniques. Temperature and Acoustic Emission (AE) were chosen as the two focal points for experimental data gathering. Within a helicopter's main rotor pitch control system, it can be assumed that all pitch-control bearings function at near-identical operating conditions. This assumption gave rise to a comparative condition monitoring technique being developed. Methods such as cross-sample correlation and creation of control charts were employed with successful outcomes. Acoustic Emission monitoring was successfully utilised in order to identify tribological condition changes with respect to the sliding contact surface. Such changes occur, as the liner material is consumed and in time transitions from a PTFE rich to a glass fibre rich composition. The wear depth of such transition is always constant and its detection can therefore be employed as a condition monitoring technique. A self-developed Acoustic Emission analysis technique was also successfully created, where the reciprocating nature of the sliding contact is exploited. Outcomes from this technique are compared with conventional methods such as RMS.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available