In order to solve particle degeneracy problem

we present an improved particle filter algorithm based on unscented Kalman filter and partial resampling algorithm.By using unscented Kalman filter to generate importance distribution function and partial resampling algorithm to resample particles

the method enriches the diversity of the particles.Furthermore

to solve the problem which likelihood detection statistics is obtained with difficulty in typically nonlinear and non-Gaussian

a fault diagnosis method based on the multiple model and the likelihood is proposed.Simulation results show the precision of the presented filter algorithm outperforms that of the standard particle filter and the improved particle filter existed in the filter system

and the proposed fault diagnosis method can detect fault quickly and isolate accurately.