Step-by-step Linearized Kalman Filter-Based Fault Detection of Workpiece Machining

This paper is concerned with step-by-step linearized Kalman filter to deal with multiplicative faults diagnosis problem for class of nonlinear systems. Multiplicative fault variables are defined as parameter variables to be estimated, and linear dynamic models between fault variables and all variables are established. The indirect linear state and measurement models of fault variables and the corresponding step-by-step linearized Kalman filters are established based on current estimated values of all variable and some obtained estimated values of future variables; further, combined with fault variables, a filter is designed for state variables in the linearized system. On basis of EKF, the redisual generation is obtained. The effectiveness of the novel filter is verified in workpiece machining process.