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008			161004s2016 gw | s |||| 0|eng d
020			_a9783658159719
040			_aES-MaUEC
050		4	_aTA169.6 _bZ436 2016
082	0	4	_a005.55
100	1		_aZhang, Kai. _921935 _0comprobar BNE19980973571
245	1	0	_aPerformance Assessment for Process Monitoring and Fault Detection Methods _cby Kai Zhang
260			_aWiesbaden _bSpringer Fachmedien Wiesbaden Vieweg _c2016
300			_a1 recurso en línea (XXI, 153 páginas) _b55 ilustraciones
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aAssessing the performance of T2 and Q fault detection statistics -- Proposing a new performance evaluation index called expected detection delay (EDD) -- Assessing the performance of different PM-FD methods using EDD when applied to detecting different types of faults -- Assessing the state-space-based PM-FD methods when applied to a real hot strip mill process.
520	3		_aThe objective of Kai Zhang and his research is to assess the existing process monitoring and fault detection (PM-FD) methods. His aim is to provide suggestions and guidance for choosing appropriate PM-FD methods, because the performance assessment study for PM-FD methods has become an area of interest in both academics and industry. The author first compares basic FD statistics, and then assesses different PM-FD methods to monitor the key performance indicators of static processes, steady-state dynamic processes and general dynamic processes including transient states. He validates the theoretical developments using both benchmark and real industrial processes. Contents Assessing the performance of T2 and Q fault detection statistics Proposing a new performance evaluation index called expected detection delay (EDD) Assessing the performance of different PM-FD methods using EDD when applied to detecting different types of faults Assessing the state-space-based PM-FD methods when applied to a real hot strip mill process Target Groups Scientists and students in the field of process control and statistical quality control Electrical engineers, chemical engineers, hot strip steel mill engineers About the Author Kai Zhang has just finished his PhD defense. His research area covers multivariate statistical process monitoring (PM) methods, data-driven fault detection (FD) methods and performance evaluation for PM-FD methods.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, asignarmaterias , EBSPRINGER
650	0	7	_aIngeniería química _2embne _9492897
650		7	_aEstadística matemática _0comprobar BNE19900966258 _2embne _9138936
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-658-15971-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783658159719
907			_a.b12957045 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0
945			_aTA169.6 Z436 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11598840 _z06-04-17
999			_c86426 _d86426 _x1