A New Nonlinear Model-Based Fault Detection Method Using Mann-Whitney Test

A well-established theory of statistical inference enables the generation of statistical fault detection approaches. Previous works mainly focus on parametric tests that assume that probabilistic distributions of both healthy and faulty residuals can be parameterized. However, such assumptions may be quite limited for general nonlinear stochastic systems because those residuals are usually with unknown distribution. In this article, a new fault indicator is defined to replace the traditional residual, and a multistep fault detection method is developed via the standard Mann-Whitney (MW) test. Moreover, with weak assumptions on faults and systems, a one-step fault detection approach is proposed by means of the modified MW test. Finally, the effectiveness of the proposed fault detection method is verified by a simulation of three water tank system.