In this paper, the design and the prototype implementation of a wireless SHM system capable of autonomously detecting and isolating various types of sensor faults are shown.
The effect of smearing on the isolation performance of single and multiple sensor faults of various magnitudes is studied and illustrated using a simulation case study.
The sensor faults are detected and isolated by several observers using different sensor signals.
For multiple sensor faults, univariate fault isolation exhibits a significantly larger correct fault isolation rate.
Considering sources from various fault occurrences, the local actuator model and the global aircraft model are used in observer estimation schemes to estimate simultaneously the ADIRS yaw rate sensor faults and the abnormal aircraft configurations.
Different sensor faults are simulated by modifying a single sensor.
For sensor faults, the smallest reliably detectable sensor fault is determined.
In generally, faults are unavoidable under practical conditions, such as hotspot faults, sensor faults and short circuits faults [1 3].
The sensor fault studies include the sensor faults due to drift in calibration and drift in sensor degradation anomalies.
Furthermore, contribution plots only outperform univariate fault isolation for single sensor faults with small magnitudes.
