Data-driven Methods for Fault Localization in Process Technology
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...
| Format: | eBook |
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| Language: | English |
| Published: |
KIT Scientific Publishing
2013
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| Series: | Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe
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| Online Access: | Open Access: DOAB: description of the publication Open Access: DOAB, download the publication |
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| 720 | 1 | |a Kühnert, Christian |4 aut | |
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| 506 | 0 | |a Open Access |f Unrestricted online access |2 star | |
| 520 | |a 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. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-sa/4.0/ |2 cc |u https://creativecommons.org/licenses/by-sa/4.0/ | ||
| 546 | |a English | ||
| 653 | |a Causality | ||
| 653 | |a Data Mining | ||
| 653 | |a Signal processing | ||
| 653 | |a System identification | ||
| 653 | |a Time series | ||
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| 856 | 4 | 0 | |u https://www.ksp.kit.edu/9783731500988 |7 0 |z Open Access: DOAB, download the publication |