A sub-grouping methodology and non-parametric sequential ratio test for signal validation

On-line signal validation is essential for safe and economic operations of a complicated industrial system such as a nuclear power plant. Various signal validation methods based on empirical signal estimation have been developed and successfully used. The first part of the thesis addresses a common and unavoidable problem for these methods---fault propagation, which causes false identification of healthy signals as faulty ones because of the faults existing in other signals. This effect is especially serious when faults occur in multiple signals and/or during system transient. A sub-grouping technique is presented in the thesis to prevent the effect of fault propagation in general signal validation methods. Specifically, two methods, Subgroups Consistency Check (SCC) and Subgroups Voting (SV), are developed. Their effectiveness is demonstrated by using a well-known Multivariate State Estimation technique (MSET) as a general method of signal estimation. To further improve the performance of MSET estimation, a procedure called Feedback Once (FBO) is also developed. All these new methods are tested and compared with MSET by using real transient data from a reactor startup process in a nuclear power plant. The results show that false identification of signals caused by fault propagation is significantly reduced by the two sub-grouping methods and the FBO method is able to improve the performance of MSET estimation to some extent. The results demonstrate that implementation of these new methods can lead to an improved signal validation technique that remains effective even when faults occur in multiple signals during system transients.;The other major contribution is on the improvement of statistical test used for signal validation. Sequential Probability Ratio Test (SPRT) is a popular method that has been widely used in many signal validation methods. However, the assumption of SPRT is too stringent to satisfy in practice, which may cause the false identification rate exceeding the preset tolerance. In this thesis, a Sequential Rank-sum Probability Ratio Test (SRPRT) method is developed. This method is similar to SPRT in procedure but is based on a much weaker assumption that can be easily satisfied. The demonstrations show that SRPRT yields a smaller false identification rate than SPRT and is always below the preset tolerance.