Abstract
Alarm systems are crucial to the safety and efficiency of industrial processes, but they may be contaminated by massive nuisance alarms. Alarm deadbands and delay timers with their connections are often used to remove nuisance alarms. However, different process variables are with different characteristics of alarm events, so that it is necessary to determine which one of these alarm systems is the most appropriate for a given process variable. This paper proposes a method to select the most suitable alarm system for a given process variable, by formulating an indicator to evaluate the risk of missed abnormality detections. The technical challenge is about how to calculate the uncertainty of the risk indicator. The Bayesian estimation approach is utilized to yield confidence intervals of the risk indicator for addressing the technical challenge. The alarm system with the lowest risk indicator is chosen as the most appropriate one. Numerical and industrial examples are presented to support the proposed method.
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