Monitoring Material Degradation in Aircraft Turbine Blades: A Comprehensive Survey on Current Techniques
AbstractAn aircraft turbine is the power harness of the engine. It however, operates under intense mechanical, extreme aerodynamic and severe temperature loading. The extremes of these environments renders turbine blade material to be vulnerable to attacks by: corrosion, erosion, oxidation, fretting, crack formation, crack propagation, creep, fatigue, or even microstructure damage. It is prudent to monitor degradation resulting from the above cited factors lest the long-term effect be grounding of aircrafts for unscheduled maintenance. Grounded aircrafts are a loss of revenue, yet again unplanned maintenance is an unplanned maintenance expense. This paper seeks, therefore, to analyze the modern methods used in the aviation industry for monitoring turbine blade material degradation. Literature on sampled techniques have been compiled and analyzed. Key approaches in the study range from; optical, microstructural change observations, metallurgical approaches, reliability testing, statistical methods, simulation, probabilistic algorithms and use of sensors. Identification of gaps in these techniques has been done. Impacts of the study range from informing of real-time degradation monitoring approaches, proposition of adoptable ones, from ease of learning, administering and teaching. Questions left unanswered by existing methods will form a debate platform for further research to increase accuracy and reliability in newer to be developed techniques.
May 4, 2016
How to Cite
NGORET, Joshua K.; KOMMULA, Venkata P.. Monitoring Material Degradation in Aircraft Turbine Blades: A Comprehensive Survey on Current Techniques. Proceedings of Sustainable Research and Innovation Conference, [S.l.], p. 21-29, may 2016. ISSN 2079-6226. Available at: <http://sri.jkuat.ac.ke/ojs/index.php/proceedings/article/view/393>. Date accessed: 23 nov. 2017.
Material degradation; Turbine Blade; Probabilistic- Simulation Approach; Microstructural Approach; Reliability Approach ; Algorithmic Approach
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