Networked Modular Technology for Integrated Aircraft Health Monitoring: Application to Rotary Structures

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Jul 8, 2014
Hamza Boukabache Vincent Robert Christophe Escriba Jean-Yves. Fourniol Jean-Philippe Furlan

Abstract

The largest variable cost to aircraft’s manufacturers and flying companies is unscheduled maintenance. Therefore, developing efficient and modular PHM system capable to scale different architectures topologies for in flight and on ground health monitoring could be cost effective, since it brings indication and warning prior to damage occurring.
In this paper, we propose an innovative diagnostic and prognostic health system based on a combination of modular acquisitions interfaces and processing units.
An embedded JTFA (Joined Time-Frequency Analysis) method based on STFT (Short-Time Fourier Transform) or Wigner-Ville transforms are used to extract a relevant signature. The proposed algorithms and PHM system technology are applied for diagnosis of mechanical flows in a high speed rotating gear of a demonstrator machine. A detailed description of data management and rooting from vibration sensors to the processing unit will be exposed.
Finally, a proof-of-concept experiment will be designed to demonstrate the integration of all the described system elements to detect any damage or anomaly into the monitored structure.

How to Cite

Boukabache, H., Robert, V., Escriba, C., Fourniol, J.-Y., & Furlan, J.-P. (2014). Networked Modular Technology for Integrated Aircraft Health Monitoring: Application to Rotary Structures. PHM Society European Conference, 2(1). https://doi.org/10.36001/phme.2014.v2i1.1540
Abstract 20468 | PDF Downloads 291

##plugins.themes.bootstrap3.article.details##

Keywords

SHM, Avionics Systems, diagnosis, prognosis, fault-tolerant control, reconfigurable control, PHM, PHM sensors and detection methodologies, Aircraft Avionics, Electronic PHM

References
Vachtsevanos, G., Lewis, F. L., Roemer, M., Hess, A., & Wu, B. (2006). Intelligent fault diagnosis and prognosis for engineering system. Hoboken, NJ: John Wiley & Sons, Inc
Bechhoefer, E., He, D., and Dempsey P., (2011). Gear Health Threshold Setting Based On a Probability of
False Alarm. Annual Conference of the Prognostics and Health Management
Dempsey, P.,Lewicki. D, Le. D,. (2007). Investigation of Current Methods to Identify Helicopter Gear Health. NASA archive
Lewicki, D., Dempsey, P., Heath, G., and Shanthakumaran P. (2010), Gear Fault Detection Effectiveness as Applied to Tooth Surface Pitting Fatigue Damage, Gear Technology, November/December 2010.
Escriba, C.,Fourniols, J., Lastapis, M., Boizard, J., Auriol, G., Andrieu, S., (2012) New real-time structural health monitoring microsystem for aircraft propeller blades, Aerospace and Electronic Systems Magazine, IEEE, Vol.27 , Issue: 2, 10.1109/MAES.2012.6163611
Boukabache, H., Escriba, C., Zedek, S., Fourniols, (2013) J. Wavlet Decomposition based Diagnostic for Structural Health Monitoring on Metallic Aircrafts: Case of Crack Triangulation and Corrosion Detection, International Journal of Prognostics and Health Management, ISSN 2153-2648, 2013 003
Klein, R. (2013) A Method for Anomaly Detection for Non-stationary Vibration Signatures, Annual Conference of the Prognostics and Health Management Society, 2013
Byington, C., Watson, J., Sheldon, J., Lee H., Mott G., (2011) Joint Time Frequency Vibration Diagnostics of Main and Engine Accessory Gearboxes, AIAC14 Fourteenth Australian International Aerospace Congress, 2011 Heng, A., Zhang, S., Tan, A. C., & Mathew, J. (2009). Rotating machinery prognostics: State of the art, challenges and opportunities. Mechanical Systems and Signal Processing, 23(3), 724-739.
Cohen L., (1966) Generalized Phase-Space Distribution Functions, Journal of Mathematical Physics, Volume 7, Issue 5, May 1966
Lazorenko, O.V. (2006), Ultrawideband Signals and Choi-Williams Transform, Ultrawideband and Ultrashort Impulse Signals, The Third International Conference, Sept. 2006 P300 -302.
Boashash B., Black P.,(1987) An Efficient Real-Time Implementation of the Wigner-Ville Distribution, IEEE transactions on acoustics, speech, and signal processing, Vol assp35, No11
Rajagopalan, S., Habetler, T.G., et al (2006)., Non-Stationary Motor Fault Detection Using Recent Quadratic Time-Frequency Representations, Industry Applications Conference, 2006, 41st IAS Annual Meeting, Conference Record of the 2006 IEEE, Volume 5, Oct. 8-12, 2006 P:2333 - 2339.
PIPAME report : Maintenance et réparation aéronautique, base de connaissances et évolution. Online
Richter, B., Ridenour-Bender, M., Tsao, M., Aircraft Turbine Engine Reliability and Inspection Investigations, Report No. DOR/FAA/CT-92/29, October 1993.
Qian, S.; Sapang, C.(1999) Joint Time Frequency Analysis, Signal Processing Magazine, IEEE, Volume 16, Issue 2
Section
Technical Papers