Industrial data characterization for an autonomous valve stiction detection system

This paper proposes a valve stiction detection system which selects valve stiction detection algorithms based on characterizations of the data. For this purpose, five data feature indexes are introduced, which quantify the presence of oscillations, mean-nonstationarity, noise and nonlinearities in a given data sequence. The selection is then performed according to the conditions on the index values in which each method can be applied successfully. Finally, the stiction detection decision is given by combining the detection decisions made by the selected methods. The paper ends demonstrating the effectiveness of the proposed valve stiction detection system with benchmark industrial data.