Fault detection based on adaptive parity equations and single-parameter tracking

Faults which appear in technical processes can often be described as additive or multiplicative faults with respect to the process model. To perform fast detection of these faults, continuous-time parity equations are used. Parameter deviations are estimated directly from residuals, providing information about their size. The combined method enables one to distinguish between additive and parametric faults. In case of time-variant processes with slow parameter changes, the coefficients of the parity equations can also be adapted with respect to the tracked parameters. The problem of persistent process excitation for estimation is by-passed. The fault-detection scheme is demonstrated on a permanently excited d.c. motor on a laboratory rig. Its properties, and the experimental results, are discussed.