Application of Alarm Correlations in Root Cause Diagnosis of Plant-wide Oscillations*

Abstract

Plant-wide oscillations are common types of disturbances in industrial processes, whose effects propagate to multiple process units through material and/or information flow paths. Such oscillations cause poor controller performance and thus can impact product quality and overall plant performance. Early detection of oscillations and root cause diagnosis is essential. Constructing an adjacency matrix is an efficient method to locate the root cause of oscillations and uses control loop digraphs to capture controller interactions from the process flowsheet. However, constructing an adjacency matrix is time-consuming and resource-intensive, especially when dealing with complex industrial facilities. This paper proposes an alternative data-driven method to construct an adjacency matrix using alarm correlations extracted from historical Alarm & Event (A&E) data. A component-level adjacency matrix is constructed by consolidating process unit information from alarm configuration attributes. Potential root causes of oscillations are shortlisted for further investigations using a process knowledge-based method. This preliminary diagnosis tool can reduce the computational complexity of the subsequent knowledge-driven stage. The applicability and effectiveness of the proposed method are demonstrated via a case study using a benchmark industrial dataset.