LEADER 01783nam  2200361z- 450 
001 9910347060203321
005 20231214132819.0
010   $a1000036427
035   $a(CKB)4920000000101914
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/44557
035   $a(EXLCZ)994920000000101914
100   $a20202102d2013      |y             0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aData-driven Methods for Fault Localization in Process Technology
210   $cKIT Scientific Publishing$d2013
215   $a1 electronic resource (XVIII, 194 p. p.)
225 1 $aKarlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe
311   $a3-7315-0098-1 
330   $aControl 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.
610   $aTime series
610   $aSignal processing
610   $aData Mining
610   $aSystem identification
610   $aCausality
700   $aKühnert$b Christian$4auth$0754943
906   $aBOOK
912   $a9910347060203321
996   $aData-driven Methods for Fault Localization in Process Technology$93031981
997   $aUNINA