Abstract
In continuous chemical processes, disturbances in the process conditions can propagate widely and cause secondary upsets in remote locations. The aim of this paper is to apply some recent data-driven methods for detection and diagnosis of process disturbances using historical process data that have been proving successful in a range of applications. An industrial case study is presented in which a plant-wide control system disturbance caused by the presence of a recycle was successfully located and then verified by further plant testing.
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