Skip to main content
Article
Comparison of immunity-based schemes for aircraft failure detection and identification
Engineering Applications of Artificial Intelligence (2016)
  • Dia Al Azzawi, West Virginia University
  • Hever Moncayo, Embry-Riddle Aeronautical University, Daytona Beach
  • Mario G. Perhinschi, West Virginia University
  • Andres Perez, Embry-Riddle Aeronautical University, Daytona Beach
  • Adil Togayev, West Virginia University
Abstract
In this paper, two approaches are proposed and compared for the detection and identification of aircraft subsystem failures based on the artificial immune system paradigm combined with the hierarchical multiself strategy. The first approach relies on the heuristic ranking of lower order self/non-self projections and the generation of selective immunity identifiers through structuring of the non-self. The second approach is based on an information processing algorithm inspired by the functionality of the dendritic cells. The artificial dendritic cell is defined as a computational unit that centralizes, fuses, and interprets information from the multiple selves to produce a unique detection and identification outcome. A hierarchical multi-self strategy is used with both approaches considering 2-dimensional self/non-self projections or subselves. A mathematical formulation of the concepts and detailed implementation algorithms are presented. The proposed methodologies are demonstrated and compared using simulation data for a supersonic fighter from a motion-based flight simulator at nominal conditions, under failures of actuators, malfunction of sensors, and wing damage. In all cases considered, both detection and identification schemes achieve excellent detection and identification rates with practically no false alarms.
Keywords
  • Bioinspired failure detection,
  • Fault identification,
  • Artificial intelligence,
  • Aircraft subsystems failures,
  • Artificial immune system
Publication Date
June 1, 2016
DOI
https://doi.org/10.1016/j.engappai.2016.02.017
Citation Information
Dia Al Azzawi, Hever Moncayo, Mario G. Perhinschi, Andres Perez, et al.. "Comparison of immunity-based schemes for aircraft failure detection and identification" Engineering Applications of Artificial Intelligence Vol. 52 (2016) p. 181 - 193 ISSN: 0952-1976
Available at: http://works.bepress.com/hever_moncayo/58/