Fault detection, isolation and reconfiguration process has a vital importance especially in aviation sector. In this sector, health fault diagnosis can avoid systems abnormal situations and provides operational continuity of the aircraft system. In this study, a model-based fault detection-isolation- reconfiguration process is offered for finding faulty sensor using an engine model. 'Unknown Input Observer (UIO)' is used for fault detection, 'Generalized Observer Scheme (GOS)' is used for fault isolation and finally 'Hamming Neural Network' is used as a decision maker in the reconfiguration of faulty sensor. © 2013 IEEE.