Application of likelihood ratio methods to failure detection and identification in the NASA F-8 DFBW aircraft

A system for on-line detection and identification of aircraft sensor and effector failures is developed. The heart of the system is a state estimator which provides accurate, real time estimates of the aircraft states. These estimates are used both to provide failure analysis and as inputs to the flight control system. Because the sensors measure functions of the aircraft state, the state estimator also provides running estimates of what it believes each sensor output ought to be, based upon the previous history of sensor outputs and commanded control inputs. Because of the relatively large number of sensors, of various types, that are available; there is an abundance of observability. Thus, failure of a single sensor will not greatly degrade the state estimates and in the event of a sensor failure the output of the failed sensor will diverge from the estimated value. The divergence is monitored and decision logic, based upon likelihood ratio tests, is employed for sensor failure detection and identification (FDI). The likelihood ratio methods provide a systematic, quantitative means for design of the decision logic. This FDI technique is in direct contrast to techniques which employ voting among like sensors and therefore require three sensors of every type in order to identify the single failure of any one of them. The present technique, employing likelihood ratio methods, requires fewer sensors because of its utilization of the redundant information available from sensors of different types which are coupled through the dynamics of the aircraft.