000 | 03993nam a22005535i 4500 | ||
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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 |
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024 | 7 |
_a10.1007/978-3-319-74014-0 _2doi |
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050 | 4 | _aTK5101-5105.9 | |
072 | 7 |
_aTJK _2bicssc |
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072 | 7 |
_aTEC041000 _2bisacsh |
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_aTJK _2thema |
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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. |
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300 |
_aVIII, 286 p. 97 illus., 59 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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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 |
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_aSecurity systems. _931879 |
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_aControl engineering. _931970 |
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_aComputational intelligence. _97716 |
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_aComputer networks . _931572 |
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650 | 1 | 4 |
_aCommunications Engineering, Networks. _931570 |
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_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 |
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_aSpringerLink (Online service) _950470 |
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773 | 0 | _tSpringer Nature eBook | |
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_iPrinted edition: _z9783319740133 |
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_iPrinted edition: _z9783319740157 |
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_iPrinted edition: _z9783030089016 |
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-74014-0 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
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