Review for State-of-the-Art Health Monitoring Technologies on Airframe Fuel Pumps
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Published
Jun 10, 2022
Tedja Verhulst
David Judt
Craig Lawson
Yongmann Chung
Osama Al-Tayawe Geoff Ward
https://orcid.org/0000-0002-6969-312X
Craig Lawson
Yongmann Chung
Osama Al-Tayawe Geoff Ward
Abstract
Aircraft maintenance is an essential cost borne by the airline. Improving maintenance practices for day-to-day operations can lead to significant financial savings. The benefits of effective maintenance are derived from the avoided costs caused by unexpected breakdowns and from maximising aircraft flight time transporting passengers. The fuel system is a crucial part of the entire aircraft as it ensures delivery of the fuel to the engine and a key component within this system are the fuel pumps. These airborne fuel pumps are classified between the pumps installed in the airframe fuel system and in the engine fuel system. Past works have investigated the performance characteristics of these pumps during flight, however there are no reviews related to the present Health Monitoring (HM) capabilities under flight conditions. HM refers to the field of diagnosing faults or predicting the remaining useful life (RUL) of the pump and the focus of this review is to highlight the HM technologies suitable for aircraft fuel pumps. This is done by first reviewing the technologies and concepts related to HM of fuel pumps. Second a literature review is carried out on pump and motor faults is carried out, drawing on examples from aerospace and other relevant industries. Section 6: Conclusion, discusses the HM technologies have been applied to aerospace fuel pumps and highlights the gaps in capabilities, based on the findings of the literature review carried out in Section 4: Common Faults and Section 5: HM Sensing Methods to suggest future developments in this field. It was found that there is a large scope for development for the HM airframe fuel pumps, based on reviewing the present state of the art. Furthermore, there are no clear strategies formulated by airframe manufacturers and equipment suppliers to test and implement existing HM solutions to operate under flight conditions. This highlights the need to develop HM in this field and a requirement for further research to allow this technology to be a part of routine aircraft
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Keywords
Wear, Health Monitoring, Condition Monitoring, Cavitation, Fault, Motor, Centrifugal Pump, Hydraulic Pump
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De Martin, A., Jacazio, G., & Vachtsevanos, G. (2020). Windings Fault Detection and Prognosis in Electro-Mechanical Flight Control Actuators Operating in Active-Active Configuration. International Journal of Prognostics And Health Management, 8(2), 1-13. https://doi.org/10.36001/ijphm.2017.v8i2.2633
Delaloye, J. (2022). Electric Motor Driven Lubrication Pump and Lubrication System Prognostic and Health Management System and Method. 20090299535A1: USPTO. Retrieved from
https://patents.google.com/patent/US20090299535A1/
en?oq=20090299535
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Djamaï, A., Brunetière, N., & Tournerie, B. (2010). Numerical Modeling of Thermohydrodynamic Mechanical Face Seals. Tribology Transactions, 53(3), 414-425. https://doi.org/10.1080/10402000903350612
Du, J., Wang, S., & Zhang, H. (2013). Layered clustering multi-fault diagnosis for hydraulic piston pump. Mechanical Systems and Signal Processing, 36(2), 487-504. https://doi.org/10.1016/j.ymssp.2012.10.020
Dular, M., & Osterman, A. (2008). Pit clustering in cavitation erosion. Wear, 265(5-6), 811-820. https://doi.org/10.1016/j.wear.2008.01.005
Dular, M., Bachert, B., Stoffel, B., & Širok, B. (2004). Relationship between cavitation structures and cavitation damage. Wear, 257(11), 1176-1184. https://doi.org/10.1016/j.wear.2004.08.004
Dular, M., Stoffel, B., & Širok, B. (2006). Development of a cavitation erosion model. Wear, 261(5-6), 642-655. https://doi.org/10.1016/j.wear.2006.01.020
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Fang, J., Li, W., Li, H., & Xu, X. (2015). Online Inverter Fault Diagnosis of Buck-Converter BLDC Motor Combinations. IEEE Transactions on Power Electronics, 30(5), 2674-2688. https://doi.org/10.1109/tpel.2014.2330420
Feng, K., Borghesani, P., Smith, W., Randall, R., Chin, Z., Ren, J., & Peng, Z. (2019). Vibration-based updating of wear prediction for spur gears. Wear, 426-427, 1410-1415. https://doi.org/10.1016/j.wear.2019.01.017
Flint, P. (2007). Engine Fuel System Health Monitoring. (EP1801391A2). EPO. Retrieved from https://patents.google.com/patent/EP1801391A2/en?oq=EP1801391A2
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