Fault diagnosis using a combined parametric and non-parametric approach

A fault detection and isolation (FDI) scheme is proposed which combines the detection filter, parity equation and parameter estimation approaches with a view to obtain a faster and a more reliable fault detection and isolation. A fault is defined to be a deviation in a parameter (termed physical parameter) associated with a device whose fault is to be detected and isolated. The feature vector which is a vector formed of the coefficients of the system transfer function is assumed to be multilinear in the physical parameters. The influence of these physical parameters on the feature vector is captured in a vector, termed the influence vector. The feature vector and the influence vector are estimated off-line, and are used to construct a detection filter and a parity equation. In real time, a fault is detected from the statistical analysis of the residual generated by the detection filter, and it is isolated using the parity equation which relates the residual, the input and the physical parameter deviations. Thanks to the multilinear relationship, the off-line parameter estimation need not be repeated every time a physical parameter varies: the initial estimates are merely updated. The proposed scheme is evaluated on a number of simulated examples