Abstract:

For the complex control systems，it is too hard to model precisely，so model-based fault detection methods are
not efficacious in application.A fault detection method based on parameter estimation of Symmetric Alpha-Stable distributions
for a class of model-unknown nonlinear system is proposed.Firstly，the output series is predicted，and the prediction error signal
with obvious abrupt impulses is obtained.Then the value of parameter alpha can be estimated through the method of parameter
estimation of Symmetric Alpha-Stable distributions.Therefore，the curse of parameter alpha is established.It is explicit
to detect system fault on the basis of this curse.The proposed method still has good robustness for signals corrupted by
large amplitude colored noise.The proposed method is applied to fault detection of bearing system.The fault state of bearing
can be detected exactly.The simulation result indicates that the method mentioned above is effective and feasible.