Alert Systems for production Plants: A Methodology Based on Conflict Analysis

We present a new methodology for detecting faults and abnormal behavior in production plants. The methodology stems from a joint project with a Danish energy consortium. During the course of the project we encountered several problems that we believe are common for projects of this type. Most notably, there was a lack of both knowledge and data concerning possible faults, and it therefore turned out to be infeasible to learn/construct a standard classification model for doing fault detection. As an alternative we propose a method for doing on-line fault detection using only a model of normal system operation, i.e., it does not rely on information about the possible faults. We illustrate the proposed method using real-world data from a coal driven power plant as well as simulated data from an oil production facility.