000 03993nam a22005535i 4500
001 978-3-319-74014-0
003 DE-He213
005 20220801220451.0
007 cr nn 008mamaa
008 180327s2018 sz | s |||| 0|eng d
020 _a9783319740140
_9978-3-319-74014-0
024 7 _a10.1007/978-3-319-74014-0
_2doi
050 4 _aTK5101-5105.9
072 7 _aTJK
_2bicssc
072 7 _aTEC041000
_2bisacsh
072 7 _aTJK
_2thema
082 0 4 _a621.382
_223
245 1 0 _aFault Diagnosis of Hybrid Dynamic and Complex Systems
_h[electronic resource] /
_cedited by Moamar Sayed-Mouchaweh.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aVIII, 286 p. 97 illus., 59 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
520 _aOnline fault diagnosis is crucial to ensure safe operation of complex dynamic systems in spite of faults affecting the system behaviors. Consequences of the occurrence of faults can be severe and result in human casualties, environmentally harmful emissions, high repair costs, and economical losses caused by unexpected stops in production lines. The majority of real systems are hybrid dynamic systems (HDS). In HDS, the dynamical behaviors evolve continuously with time according to the discrete mode (configuration) in which the system is. Consequently, fault diagnosis approaches must take into account both discrete and continuous dynamics as well as the interactions between them in order to perform correct fault diagnosis. This book presents recent and advanced approaches and techniques that address the complex problem of fault diagnosis of hybrid dynamic and complex systems using different model-based and data-driven approaches in different application domains (inductor motors, chemical process formed by tanks, reactors and valves, ignition engine, sewer networks, mobile robots, planetary rover prototype etc.). These approaches cover the different aspects of performing single/multiple online/offline parametric/discrete abrupt/tear and wear fault diagnosis in incremental/non-incremental manner, using different modeling tools (hybrid automata, hybrid Petri nets, hybrid bond graphs, extended Kalman filter etc.) for different classes of hybrid dynamic and complex systems. Synthesizes the state of the art in the domain of fault diagnosis of hybrid dynamic systems; Studies the complementarities and the links between the different methods and techniques of fault diagnosis of hybrid dynamic systems; Includes the required notions, definitions and background to understand the problem of fault diagnosis of hybrid dynamic systems and how to solve it; Uses multiple examples in order to facilitate the understanding of the presented methods.
650 0 _aTelecommunication.
_910437
650 0 _aSecurity systems.
_931879
650 0 _aControl engineering.
_931970
650 0 _aComputational intelligence.
_97716
650 0 _aComputer networks .
_931572
650 1 4 _aCommunications Engineering, Networks.
_931570
650 2 4 _aSecurity Science and Technology.
_931884
650 2 4 _aControl and Systems Theory.
_931972
650 2 4 _aComputational Intelligence.
_97716
650 2 4 _aComputer Communication Networks.
_950468
700 1 _aSayed-Mouchaweh, Moamar.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_950469
710 2 _aSpringerLink (Online service)
_950470
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319740133
776 0 8 _iPrinted edition:
_z9783319740157
776 0 8 _iPrinted edition:
_z9783030089016
856 4 0 _uhttps://doi.org/10.1007/978-3-319-74014-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c78597
_d78597