Data-driven Methods for Fault Localization in Process Technology

By: Material type: ArticleArticleLanguage: English Publication details: KIT Scientific Publishing 2013Description: 1 electronic resource (XVIII, 194 p. p.)ISBN:
  • KSP/1000036427
  • 9783731500988
Subject(s): Online resources: Summary: 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.
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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.

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