Abstract
A novel fault detection/diagnosis technique for linear dynamic systems is proposed. In comparison with existing schemes, the proposed method achieves fault detection/diagnosis using neither observer residuals nor parameter estimation errors; instead, it relies on the estimation of the underlying modal parameters of the system. The estimated modal parameters are compared with pre-calculated characteristic patterns of the system, which are represented as a set of root loci in terms of the physical system parameters. The modal parameter estimation is carried out using a numerically robust least-squares algorithm based on singular value decomposition. A pattern recognition technique employing linear multiprototype distance functions is used to classify the faults according to the variations of physical parameters. The proposed method has been applied to a simulated DC servo system where faults are introduced as abrupt changes in physical system parameters. It is shown that the proposed scheme is capable of di...
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