Introduction
Contemporary SCADA systems allow collecting huge amounts of data that originates from diverse data sources. There are at least two groups of such sources:
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measuring systems installed on the object (machine or installation) that permit the acquisition of data that are instant values of sampled analogue signals or numeric/functional values of features of such signals;
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sources of messages which can be either automatic systems (e.g., systems for assessing residuals in a model-based diagnostic system, supervisory systems generating warnings and/or alarms etc.), or process operators and other managing personnel.
Data acquired from the enumerated data sources can be the carrier of important information on the process state. During the realization of the DiaSter project, particular meaning is assigned to the issue that these data can be the source of diagnostic knowledge that might be used for automatic detection, localization and diagnostics of faults in dynamic industrial processes.
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© 2010 Springer-Verlag Berlin Heidelberg
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Moczulski, W., Szulim, R., Tomasik, P., Wachla, D. (2010). Knowledge Discovery in Databases. In: Korbicz, J., Kościelny, J.M. (eds) Modeling, Diagnostics and Process Control. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16653-2_4
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DOI: https://doi.org/10.1007/978-3-642-16653-2_4
Publisher Name: Springer, Berlin, Heidelberg
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