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No AccessFull-Length Papers

Performance-Based Ice Detection Methodology

Published Online:29 Jan 2020https://doi.org/10.2514/1.C034828

Abstract

A novel robust ice detection methodology for the early detection of icing-related flight performance degradation is presented. Based on data of 75,689 flights with modern commercial airliners, a maximum aircraft fleet’s performance variation has been estimated. The evaluation of results indicates that an expected influence of icing could be clearly separated. The developed methodology is energy based and fuses aircraft body and engine influences on flight performance, which allows to reliably calculate a deviation from an available reference. This difference in flight performance is consequently used to detect an aerodynamic degradation. The novel methodology provides large capabilities and shows a good detection reliability with no false alarm even within maneuvering flight, wind shear, turbulence, and sideslip as well as for several sensor error cases. The methodology was evaluated during various simulator trials. The results show a very high potential in supporting pilots with adequate information about the current aircraft status in icing conditions.

References

  • [1] Green S. D., “A Study of U.S. Inflight Icing Accidents and Incidents, 1978 to 2002,” 44th AIAA Aerospace Sciences Meeting and Exhibit, AIAA Paper  2006-82, Jan. 2006.https://doi.org/10.2514/6.2005-6220 LinkGoogle Scholar

  • [2] Final Report (BFU 5X011-0/98), Bundesstelle für Flugunfalluntersuchung, Braunschweig, Germany, April 2001. Google Scholar

  • [3] Aircraft Accident Report (NTSB/AAR-96/01, DCA95MA001), Safety Board Report, National Transportation Safety Board (NTSB), Washington, DC, July 1996. Google Scholar

  • [4] “Ice Accretion Simulation,” Advisory Group for Aerospace Research & Development (AGARD) - Fluid Dynamics Panel Working Group 20, North Atlantic Treaty Organization (NATO), AGARD, Advisory Rept.  344, Neuilly-Sur-Seine, France, Dec. 1997. Google Scholar

  • [5] Gray V. H., “Prediction of Aerodynamic Penalties Caused by Ice Formations on Various Airfoils,” NASA TN D-2166, Feb. 1964. Google Scholar

  • [6] Broeren A. P., Whalen E. A., Busch G. T. and Bragg M. B., “Aerodynamic Simulation of Runback Ice Accretion,” Journal of Aircraft, Vol. 47, No. 3, May–June 2010, pp. 924–939. https://doi.org/10.2514/1.46475 LinkGoogle Scholar

  • [7] Ranuado R. J., Batterson J. G., Reehorst A. L., Bond T. and O’Mara T. M., “Determination of Longitudinal Aerodynamic Derivatives Using Flight Data from an Icing Research Aircraft,” 27th AIAA Aerospace Science Meeting, AIAA Paper  1989-0754, Jan. 1989.https://doi.org/10.2514/6.1989-754 LinkGoogle Scholar

  • [8] Ratvasky T. P. and Ranuado R. J., “Icing Effects on Aircraft Stability and Control Determined from Flight Data. Preliminary Results,” 31st AIAA Aerospace Science Meeting and Exhibit, AIAA Paper  1993-0398, Jan. 1993. https://doi.org/10.2514/6.1993-398 LinkGoogle Scholar

  • [9] Lee S., Barnhart B. P. and Ratvasky T. P., “Dynamic Wind-Tunnel Testing of a Sub-Scale Iced S-3B Viking,” AIAA Atmospheric and Space Environments Conference, AIAA Paper  2010-7986, Aug. 2010. https://doi.org/10.2514/6.2010-7986 LinkGoogle Scholar

  • [10] Gingras D. R., “Requirements and Modeling of In-Flight Icing Effects for Flight Training,” AIAA Modeling and Simulation Technologies (MST) Conference, AIAA Paper  2013-5075, Aug. 2013.https://doi.org/10.2514/6.2013-5075 LinkGoogle Scholar

  • [11] Federal Regulation Title 14.I.C Part 25—Airworthiness Standards: Transport Category Airplanes, Federal Aviation Administration, Washington, D.C. Google Scholar

  • [12] Bragg M. B., Başar T., Perkins W. R., Selig M. S., Voulgaris P. G., Melody J. W. and Sater N. B., “Smart Icing Systems for Aircraft Icing Safety,” 40th AIAA Aerospace Sciences Meeting and Exhibit, AIAA Paper  2002-813, Jan. 2002. https://doi.org/10.2514/6.2002-813 LinkGoogle Scholar

  • [13] Bragg M. B., Perkins W. R., Sarter N. B., Başar T., Voulgaris P. G., Gurbacki H. M., Melody J. W. and McCray S. A., “An Interdisciplinary Approach to Inflight Aircraft Icing Safety,” 36th AIAA Aerospace Sciences Meeting and Exhibit, AIAA Paper  1998-95, Jan. 1998. https://doi.org/10.2514/6.1998-95 LinkGoogle Scholar

  • [14] Myers T. T., Klyde D. H. and Magdaleno R. E., “The Dynamic Icing Detection System (DIDS),” 38th AIAA Aerospace Science Meeting and Exhibit, AIAA Paper  2000-364, Jan. 1999. Google Scholar

  • [15] Melody J. W., Başar T., Perkins W. R. and Voulgaris P. G., “Parameter Identification for Inflight Detection and Characterization of Aircraft Icing,” Control Engineering Practice, Vol. 8, No. 9, Sept. 2000, pp. 985–1001. https://doi.org/10.1016/S0967-0661(00)00046-0 CrossrefGoogle Scholar

  • [16] Aykan R., Hajiyev C. and Caliskan F., “Aircraft Icing Detection, Identification and Reconfigurable Control Based on Kalman Filtering and Neural Networks,” AIAA Atmospheric Flight Mechanics Conference and Exhibit, AIAA Paper  2005-6220, Aug. 2005. https://doi.org/10.2514/6.2005-6220 LinkGoogle Scholar

  • [17] Gingras D. R., Barnhart B. P., Ranuado R. J., Ratvasky T. P. and Morelli E. A., “Envelope Protection for In-Flight Ice Contamination,” 47th Aerospace Science Meeting, AIAA Paper  2009-1458, Jan. 2009. https://doi.org/10.2514/6.2009-1458 LinkGoogle Scholar

  • [18] Jackson D., Owens D., Cronin D. and Severson J., “Certification and Integration Aspects of a Primary Ice Detection System,” 39th AIAA Aerospace Sciences Meetings and Exhibit, AIAA Paper  2001-0398, Jan. 2001. https://doi.org/10.2514/6.2001-398 LinkGoogle Scholar

  • [19] Spriggs T. J., “An Ice Detection System for Helicopters,” Digital Avionics Systems Conference, AIAA Paper  1988-3949, Oct. 1988. https://doi.org/10.2514/6.1988-3949 LinkGoogle Scholar

  • [20] Gao H. and Rose J. L., “Ice Detection and Classification on an Aircraft Wing with Ultrasonic Shear Horizontal Guided Waves,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 55, No. 2, Feb. 2009, pp. 334–344. https://doi.org/10.1109/TUFFC.2009.1042 Google Scholar

  • [21] Liu Y., Bond L. J. and Hu H., “Ultrasonic-Attenuation-Based Technique for Ice Characterization Pertinent to Aircraft Icing Phenomena,” AIAA Journal, Vol. 55, No. 5, May 2017, pp. 1602–1609. https://doi.org/10.2514/1.J055500 LinkGoogle Scholar

  • [22] 14 CFR Parts 25 and 33 Airplane and Engine Certification Requirements in Supercooled Large Drop, Mixed Phase, and Ice Crystal Icing Conditions; Final Rule (Federal Register, Vol. 79, No. 213), Federal Aviation Administration, Nov. 2014 Google Scholar

  • [23] Certification Specifications and Acceptable Means of Compliance for Large Aeroplanes CS-25, Amendment 16, European Aviation Safety Agency (EASA), Brussels, March 2016. Google Scholar

  • [24] Barnhart B. P., Dickes E. G., Gingras D. R. and Ratvasky T. P., “Simulation Model Development for Icing Effects Flight Training,” General Aviation Technology Conference and Exhibition, Soc. of Automotive Engineers (SAE), Wichita, KA, April 2002.https://doi.org/10.4271/2002-01-1527 Google Scholar

  • [25] Gingras D. R., Dickes E. G., Ratvasky T. P. and Barnhart B. P., “Modeling of In-Flight Icing Effects for Flight Training,” AIAA Modeling and Simulation Technologies Conference and Exhibit, AIAA Paper  2002-4605, Aug. 2002.https://doi.org/10.2514/6.2002-4605 LinkGoogle Scholar

  • [26] Deters R. W., Dimock G. A. and Selig M. S., “Icing Encounter Flight Simulator,” Journal of Aircraft, Vol. 43, No. 5, Sept. 2006, pp. 1528–1537. https://doi.org/10.2514/1.20364 LinkGoogle Scholar

  • [27] Ratvasky T. P., Barnhart B. P., Lee S. and Cooper J., “Flight Testing an Iced Business Jet for Flight Simulation Model Validation,” 45th AIAA Aerospace Science Meeting and Exhibit, AIAA Paper  2007-0089, Jan. 2007. https://doi.org/10.2514/6.2007-89 LinkGoogle Scholar

  • [28] Deiler C., “Aerodynamic Modeling, System Identification, and Analysis of Iced Aircraft Configurations,” Journal of Aircraft, Vol. 55, No. 1, Jan.–Feb. 2018, pp. 145–161. https://doi.org/10.2514/1.C034390 LinkGoogle Scholar

  • [29] Deiler C., “Time Domain Output Error System Identification of Iced Aircraft Aerodynamics,” CEAS Aeronautical Journal, Vol. 8, No. 2, June 2017, pp. 231–244. https://doi.org/10.1007/s13272-016-0231-2 CrossrefGoogle Scholar

  • [30] Jategaonkar R., ldentification of the Aerodynamic Model of the DLR Research Aircraft ATTAS from Flight Test Data, Deutsche Forschungsanstalt für Luft- und Raumfahrt e. V. (DLR), Köln, Germany, Sept. 1990. Google Scholar

  • [31] Moennich W., “Ein 2-Punkt-Aerodynamikmodell für die Identifizierung,” Symposium ‘Systemidentifizierung in der Fahrzeugdynamik’, Deutsche Forschungs- und Versuchsanstalt für Luft- und Raumfahrt Mitteilung 87-22, 1987, Paper 3.1 (in German). Google Scholar

  • [32] Fischenberg D. and Jategaonkar R. V., “Identification of Aircraft Stall Behavior from Flight Test Data,” RTO Systems Concepts and Integration Panel (SCI) Symposium, NATO Research and Technology Organisation, Madrid, May 1998, Paper 17. Google Scholar

  • [33] Fischenberg D., “Identification of an Unsteady Aerodynamic Stall Model from Flight Test Data,” AIAA Atmospheric Flight Mechanics Conference, AIAA Paper  1995-3438-CP, Aug. 1995, pp. 138–146. https://doi.org/10.2514/6.1995-3438 LinkGoogle Scholar

  • [34] Bragg M. B., Hutchison T., Merret J., Oltman R. and Pokhariyal D., “Effect of Ice Accretion on Aircraft Flight Dynamics,” 38th AIAA Aerospace Science Meeting and Exhibit, AIAA Paper  2000-0360, Jan. 2000. https://doi.org/10.2514/6.2000-360 LinkGoogle Scholar

  • [35] Krajěk K., Nikolić D. and Domitrović A., “Aircraft Performance Monitoring from Flight Data,” Technical Gazette, Vol. 22, No. 5, Oct. 2015, pp. 1337–1344. Google Scholar

  • [36] Lombaerts T., Schuet S., Acosta D., Kaneshige J. and Martin L., “Piloted Simulator Evaluation of Maneuvering Envelope Information for Flight Crew Awareness,” AIAA SciTech—AIAA Guidance, Navigation, and Control Conference, AIAA Paper  2015-1546, Jan. 2015. https://doi.org/10.2514/6.2015-1546 LinkGoogle Scholar

  • [37] Dong Y. and Ai J., “Research on Inflight Parameter Identification and Icing Location Detection of the Aircraft,” Aerospace Science and Technology, Vol. 29, No. 1, Aug. 2013, pp. 305–312. https://doi.org/10.1016/j.ast.2013.03.012 CrossrefGoogle Scholar

  • [38] Fujita T. T., “Downbursts and Microbursts—An Aviation Hazard,” Preprints, 19. Conference on Radar Meteorology, American Meteorological Soc., Miami Beach, FL, April 1980, pp. 94–101. Google Scholar

  • [39] Air Data Computer—Minimum Performance Standard (Aerospace Standard AS8002), SAE International, Warrendale, PA, Sept. 1996. Google Scholar

  • [40] Duda H., Gerlach T., Advani S. K. and Potter M., “Design of the DLR AVES Research Flight Simulator,” AIAA Modeling and Simulation Technologies (MST) Conference, AIAA Paper  2013-4737, Aug. 2013. https://doi.org/10.2514/6.2013-4737 LinkGoogle Scholar

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