A New Approach to Design Alarm Filters Using the Plant and Controller Knowledge

Abstract

Alarm systems are of paramount importance to the safety and proficiency of process industries. These systems aim to notify the plant operators of any possible equipment malfunction or undesired situation. An imperfect alarm system may announce false alarms in the normal operation mode or fail to raise alarms in case of some abnormalities. One mechanism for improving alarm systems is alarm filtering, which has already been addressed in the literature owing to its popularity in industries. The focus of previous research was mostly on process variables with statistically independent variables. This, however, is not aligned with many practical situations where the acquired variables are originated from closed-loop control systems. In this paper, we propose a new method for obtaining optimal filter coefficients by incorporating the knowledge of plant and control systems while relaxing the independence assumption. The design objective is to minimize the rates of missed and false alarms, which are commonly used measures for performance evaluation of alarm systems. The superiority of the proposed method over the conventional one is demonstrated via a simulation case study.