Data-driven Methods for Fault Localization in Process Technology
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Beschreibung
Control systems at production plants consist of a large number of process variables. When detecting abnormal behavior, these variables generate an alarm. Due to the interconnection of the plant\'s devices the fault can lead to an alarm flood. This again hides the original location of the causing device. In this work several data-driven approaches for root cause localization are proposed, compared and combined. All methods analyze disturbed process data for backtracking the propagation path.
Control systems at production plants consist of a large number of process variables. When detecting abnormal behavior, these variables generate an alarm. Due to the interconnection of the plant\'s devices the fault can lead to an alarm flood. This again hides the original location of the causing device. In this work several data-driven approaches for root cause localization are proposed, compared and combined. All methods analyze disturbed process data for backtracking the propagation path.
Autor*in
Christian Kühnert
Themen in »Data-driven Methods for Fault Localization in Process Technology«
System identification Time series Causality Signal processing Data Mining