LEADER 04858nam 22008055 450 001 9910299715503321 005 20200701072541.0 010 $a3-319-05380-9 024 7 $a10.1007/978-3-319-05380-6 035 $a(CKB)2560000000148716 035 $a(EBL)1698355 035 $a(OCoLC)876368073 035 $a(SSID)ssj0001204823 035 $a(PQKBManifestationID)11787169 035 $a(PQKBTitleCode)TC0001204823 035 $a(PQKBWorkID)11179768 035 $a(PQKB)10474492 035 $a(MiAaPQ)EBC1698355 035 $a(DE-He213)978-3-319-05380-6 035 $a(PPN)178318892 035 $a(EXLCZ)992560000000148716 100 $a20140401d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aCapturing Connectivity and Causality in Complex Industrial Processes$b[electronic resource] /$fby Fan Yang, Ping Duan, Sirish L. Shah, Tongwen Chen 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (99 p.) 225 1 $aSpringerBriefs in Applied Sciences and Technology,$x2191-530X 300 $aDescription based upon print version of record. 311 $a3-319-05379-5 320 $aIncludes bibliographical references. 327 $aIntroduction -- Examples of Applications for Connectivity and Causality Analysis -- Description of Connectivity and Causality -- Capturing Connectivity and Causality from Process Knowledge -- Capturing Causality from Process Data -- Case Studies. 330 $aThis brief reviews concepts of inter-relationship in modern industrial processes, biological and social systems. Specifically ideas of connectivity and causality within and between elements of a complex system are treated; these ideas are of great importance in analysing and influencing mechanisms, structural properties and their dynamic behaviour, especially for fault diagnosis and hazard analysis. Fault detection and isolation for industrial processes being concerned with root causes and fault propagation, the brief shows that, process connectivity and causality information can be captured in two ways: ˇ      from process knowledge: structural modeling based on first-principles structural models can be merged with adjacency/reachability matrices or topology models obtained from process flow-sheets described in standard formats; and ˇ      from process data: cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian networks can be used to identify pair-wise relationships and network topology. These methods rely on the notion of information fusion whereby process operating data is combined with qualitative process knowledge, to give a holistic picture of the system. 410 0$aSpringerBriefs in Applied Sciences and Technology,$x2191-530X 606 $aComputational complexity 606 $aMathematical models 606 $aControl engineering 606 $aChemical engineering 606 $aStatistics  606 $aComplexity$3https://scigraph.springernature.com/ontologies/product-market-codes/T11022 606 $aMathematical Modeling and Industrial Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M14068 606 $aControl and Systems Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/T19010 606 $aIndustrial Chemistry/Chemical Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/C27000 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 615 0$aComputational complexity. 615 0$aMathematical models. 615 0$aControl engineering. 615 0$aChemical engineering. 615 0$aStatistics . 615 14$aComplexity. 615 24$aMathematical Modeling and Industrial Mathematics. 615 24$aControl and Systems Theory. 615 24$aIndustrial Chemistry/Chemical Engineering. 615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 676 $a670.42 700 $aYang$b Fan$4aut$4http://id.loc.gov/vocabulary/relators/aut$0721285 702 $aDuan$b Ping$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aShah$b Sirish L$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aChen$b Tongwen$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299715503321 996 $aCapturing Connectivity and Causality in Complex Industrial Processes$91979674 997 $aUNINA