Mean value test for FDI in redundant sensor configurations

In this paper, a mean value test (MVT) is proposed to detect and isolate failures. Non-linear filtering is used to estimate the combinations of sensor errors affecting the parity vector, the estimates are used to form a compensated parity vector. The compensated parity vector is used to make an FDI decision for improving FDI performance. To illustrate its application, the MVT approach is used to detect and isolate the failure in an optimal mounting configuration of five single-degree-of-freedom sensors. Some results are obtained by comparing the MVT method with the generalized likelihood test (GLT) method. Simulation results prove that MVT method can detect and isolate the failure effectively when two sensors fail simultaneously