Abstract
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.
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Nielsen, T.D., Jensen, F.V. (2005). Alert Systems for Production Plants: A Methodology Based on Conflict Analysis. In: Godo, L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2005. Lecture Notes in Computer Science(), vol 3571. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11518655_8
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DOI: https://doi.org/10.1007/11518655_8
Publisher Name: Springer, Berlin, Heidelberg
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