Centered on NI (National Instruments) CompactRIO

a real-time simulation platform with rapid prototyping was built to validate the fault diagnosis approaches for turbo-fan engine sensors rapidly and efficiently. Based on a bank of Kalman filters

an turbo-fan engine sensor fault diagnostics system was developed in LabVIEW environments. Extensive experiments were conducted for the fault detection

isolation and restructuring of individual sensor faults

at both steady state and dynamic conditions. The accuracy of the proposed algorithm was thus verified. Experimental results showed that Kalman filter algorithm could ensure safe operation of engine control system even in the case of sensor failures

the best accuracy of diagnosis reached 1.4%

and the effectiveness of this rapid prototype real-time platform for sensor fault diagnosis was also shown. Consequently

the developed platform could be taken as the foundation for semi-physical tests.