Integrated Framework for Artificial Immunity-Based Aircraft Failure Detection, Identification, and Evaluation
作者： Mario G. Perhinschi , Hever Moncayo , Jennifer Davis
DOI: 10.2514/1.45718
关键词: Artificial immune system 、 Process (engineering) 、 Flight envelope 、 Reliability engineering 、 Context (language use) 、 Engineering 、 Flight simulator 、 Identification (information) 、 Simulation 、 Fault detection and isolation 、 Identification scheme
摘要: This paper presents a novel conceptual framework for an integrated set of methodologies the detection, identification, and evaluation wide variety failures aircraft subsystems based on artificial immune system paradigm. The detection represents capability to declare that failure within any has occurred. identification process determines which element failed. addresses three aspects: type failure, its magnitude, reassessment generalized flight envelope. Failure schemes are included using bioimmune metaphor combined with other intelligence techniques. immunity-based fault operates in similar manner as does when it distinguishes between entities belong organism do not. proposed approach directly complexity multidimensionality dynamic response context abnormal conditions provides adequate tools solve problem comprehensive manner. A multiself scheme is presented actuator, sensor, engine, structural failures/damages, was developed tested motion-based simulator. achieves excellent rates low number false alarms demonstrates effectiveness framework.
sci-hub.se 参考文章(48)
Dipankar Dasgupta, Fabio A. Gonzalez, An Imunogenetic Technique To Detect Anomalies In Network Traffic genetic and evolutionary computation conference. pp. 1081- 1088 ,(2002)
Karen Gundy-Burlet, K. KrishnaKumar, John Kaneshige, Daniel Clancy, Don Soloway, Intelligent Control Approaches for Aircraft Applications ,(2001)
Christopher D. Wickens, Colin Kessel, Failure Detection in Dynamic Systems Springer, Boston, MA. pp. 155- 169 ,(1981) , 10.1007/978-1-4615-9230-3_11
Fabio González, Dipankar Dasgupta, Jonatan Gómez, The Effect of Binary Matching Rules in Negative Selection Genetic and Evolutionary Computation — GECCO 2003. pp. 195- 206 ,(2003) , 10.1007/3-540-45105-6_25
David L. Iverson, Inductive System Health Monitoring international conference on artificial intelligence. pp. 605- 611 ,(2004)
D. Dasgupta, K. KrishnaKumar, D. Wong, M. Berry, Negative Selection Algorithm for Aircraft Fault Detection international conference on artificial immune systems. pp. 1- 13 ,(2004) , 10.1007/978-3-540-30220-9_1
Albert Ko, H. Y. K. Lau, T. L. Lau, An immuno control framework for decentralized mechatronic control international conference on artificial immune systems. pp. 91- 105 ,(2004) , 10.1007/978-3-540-30220-9_8
Fabio A. González, Dipankar Dasgupta, Anomaly Detection Using Real-Valued Negative Selection Genetic Programming and Evolvable Machines. ,vol. 4, pp. 383- 403 ,(2003) , 10.1023/A:1026195112518
Michel Verleysen, Damien François, The Curse of Dimensionality in Data Mining and Time Series Prediction Computational Intelligence and Bioinspired Systems. ,vol. 3512, pp. 758- 770 ,(2005) , 10.1007/11494669_93
Hever Moncayo, Mario G. Perhinschi, Jennifer Davis, Artificial Immune System – Based Aircraft Failure Evaluation over Extended Flight Envelope Journal of Guidance Control and Dynamics. ,vol. 34, pp. 989- 1001 ,(2010) , 10.2514/1.52748