Detection of Correlated Alarms Based on Similarity Coefficients of Binary Data

This paper studies the statistical analysis for alarm signals in order to detect whether two alarm signals are correlated. First, a similarity measurement, namely, Sorgenfrei coefficient, is selected among 22 similarity coefficients for binary data in the literature. The selection is based on the desired properties associated with specialities of alarm signals. Second, the distribution of a so-called correlation delay is shown to be indispensable and effective for the detection of correlated alarms. Finally, a novel method for detection of correlated alarms is proposed based on Sorgenfrei coefficient and distribution of the correlation delay. Numerical and industrial examples are provided to illustrate and validate the obtained results.