Outliers detection method of multiple measuring points of parameters in power plant units

Abstract A novel outlier detection method known as modified Grubbs method, which is based on median and median absolute deviation, is proposed to solve outlier detection in multiple measuring points' parameters. Weights are introduced to modify median absolute deviation and the test criterion. In the paper, a comparative study of the proposed method and the original Grubbs method in outlier detection on simulated data is presented. Due to the shortcomings of the original Grubbs method, the modified Grubbs method is a more robust alternative. The performances of the proposed method are illustrated by main steam temperature data set with and without outliers. The obtained results demonstrate that the proposed method can be used in outlier detection in thermal power plants and it is highly efficient and robust.

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