Integrating probabilistic signed digraph and reliability analysis for alarm signal optimization in chemical plant

• A plant alarm signal optimization strategy is set up to control alarm floods.
• This strategy is based on the PSDG model with reliability analysis.
• The criteria of observability and identifiability are discussed based on PSDG model.
• A reliability formulation for selecting alarm signals is presented and solved by ROC.
• The Tennessee Eastman process is applied to reveal the advantages of the method.

The alarm system given in industrial plants are massive and complex. Under such condition, critical alarms are overwhelmed by false and unnecessary alarms and thus result in severe safety issues. To address the problem, this paper proposes a probabilistic signed digraph (PSDG) based alarm signal selection method that requires achieving maximal system reliability. In this method, a PSDG model is firstly constructed to visualize the causal relations between process variables. Then the criteria of observability and identifiability are imposed to determine the candidate alarm variables that can qualitatively distinguish all assumed faults. Instead of selecting the minimum number of combinations of candidate variables, the alarm variables are optimized by a reliability formulation that takes into account the missed alarm and false alarm probabilities of the system; this formulation is solved by the receiver operating characteristic (ROC) graph. Finally, the developed methodology is illustrated using a Tennessee Eastman process.