Fault prediction method of improving particle filter with support vector regression

Aiming at the problem of particle degeneracy and sample impoverishment in fault prediction, an improving particle filter with support vector regression was proposed. The no-linear function of particle state and its weight was established by using support vector regression to estimate the particle's posterior probability density model. Based on this model, the new particle was obtained and weights of particles were updated by resampling, and the diversity and effectiveness of samples were improved. Thus the ability to control and predict the fault was raised. Simulation result demonstrated that the method was feasible and system fault could be predicted correctly.