Particle filter based anomaly detection for aircraft actuator systems

IEEE Aerospace Conference Proceedings

Volumn , Issue , 2009, Pages

  Brown, D ^a   Georgoulas, G ^a   Bae, H ^a   Vachtsevanos, G ^a   Chen, R ^b   Ho, Y H ^b   Tannenbaum, G ^c   Schroeder, J B ^d  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b NORTHROP GRUMMAN CORPORATION   (United States)

^c MOOG INC   (United States)

^d AIR FORCE RESEARCH LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AIRCRAFT ACTUATORS; ANOMALY DETECTION; ANOMALY DETECTOR; BAYESIAN ESTIMATION THEORY; BRUSHLESS DC; COMPUTATIONALLY EFFICIENT; CONFIDENCE LEVELS; DIAGNOSTIC FEATURES; ELECTRO-MECHANICAL ACTUATOR; EXPERIMENTAL DATA; EXPERIMENTAL EVALUATION; EXPERIMENTAL TEST; FALSE ALARM RATE; FAULT DIMENSION; FAULT MODEL; HILBERT TRANSFORM; INTERNAL FAILURE; LABVIEW; MANAGEMENT OF UNCERTAINTY; MONITORING PARAMETERS; PARTICLE FILTER; PHYSICS-OF-FAILURE; PRIMARY MECHANISM; REAL TIME PERFORMANCE; SIMULINK; SIMULINK MODELS; WINDING FAULTS;

ACTUATORS; AIR FILTERS; AIRCRAFT; BAYESIAN NETWORKS; BRUSHLESS DC MOTORS; DC GENERATOR MOTORS; DC MOTORS; ELECTROMECHANICAL DEVICES; ERROR DETECTION; FAULT DETECTION; FEATURE EXTRACTION; MOTORS; NONLINEAR FILTERING; QUALITY ASSURANCE; SAFETY FACTOR; WINDING;

FAILURE ANALYSIS;

EID: 70349142281     PISSN: 1095323X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AERO.2009.4839659     Document Type: Conference Paper

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