The Application of Multifactorial Diagnostic Criteria for Early Vibration Diagnostics of Aircraft Gas Turbine Engine Bearings
The paper proposes basic approaches and results of working out and application of early vibration diagnostics of gas turbine engine bearings using multifactorial diagnostic criteria.
Fatigue spalling, not detected at an early stage on working surfaces of ring raceways and rollers of a turbine bearing subsequently leads to its failure and considerable expenses for regenerative engine repairing. Thus the regular alarm system detecting debris presence in oil due to insufficient sensitivity and selectivity gives an alarm signal too late, at a high stage of damage that excludes the possibility of malfunction elimination without the engine withdrawing from the operation. The vibrations generated by a bearing at its work in the aircraft GTE structure, mostly, have a very low intensity in relation to the noise level and consequently, for working out of an early and reliable diagnostics, it is necessary on the one hand, to take measures in decreasing the levels of external and internal noise, on the other hand, to develop reliable diagnostic criteria on the basis of multifactorial models, allowing to minimize a zone of uncertainty of diagnostic parameters, to lift their diagnostic sensitivity by taking into account various influencing additional parameters such as shaft speed, ambient temperature, etc.
How to Cite
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.