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001			298682
003			MX-SnUAN
005			20160429155515.0
007			cr nn 008mamaa
008			150903s2008 gw | o |||| 0|eng d
020			_a9783540792246 _99783540792246
024	7		_a10.1007/9783540792246 _2doi
035			_avtls000351820
039		9	_a201509030450 _bVLOAD _c201405060256 _dVLOAD _y201402171146 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
100	1		_aChoudhury, Shoukat M. A. A. _eautor _9335211
245	1	0	_aDiagnosis of Process Nonlinearities and Valve Stiction : _bData Driven Approaches / _cby Shoukat M. A. A. Choudhury, Sirish L. Shah, Nina F. Thornhill.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2008.
300			_brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aAdvances in Industrial Control, _x1430-9491
500			_aSpringer eBooks
505	0		_aHigher-Order Statistics -- Higher-Order Statistics: Preliminaries -- Bispectrum and Bicoherence -- Data Quality – Compression and Quantization -- Impact of Data Compression and Quantization on Data-Driven Process Analyses -- Nonlinearity and Control Performance -- Measures of Nonlinearity – A Review -- Linear or Nonlinear? A Bicoherence-Based Measure of Nonlinearity -- A Nonlinearity Measure Based on Surrogate Data Analysis -- Nonlinearities in Control Loops -- Diagnosis of Poor Control Performance -- Control Valve Stiction~– Definition, Modelling, Detection and Quantification -- Different Types of Faults in Control Valves -- Stiction: Definition and Discussions -- Physics-Based Model of Control Valve Stiction -- Data-Driven Model of Valve Stiction -- Describing Function Analysis -- Automatic Detection and Quantification of Valve Stiction -- Industrial Applications of the Stiction Quantification Algorithm -- Confirming Valve Stiction -- Plant-wide Oscillations – Detection and Diagnosis -- Detection of Plantwide Oscillations -- Diagnosis of Plant-wide Oscillations.
520			_aIn this book, Higher Order Statistical (HOS) theory is used to develop indices for detecting and quantifying signal non-Gaussianity and nonlinearity. These indices, together with specific patterns in the mapping of process output and controller output are used to diagnose the causes of poor control loop performance. Often valve stiction is the main cause of poor control performance. A generalized definition of valve stiction based on the investigation of real plant data is proposed. A simple data-driven model of valve stiction is developed. The model is simple, yet powerful enough to properly simulate the complex valve stiction phenomena. Both open and closed loop results have been presented and validated to show the capability of the model. Conventional invasive methods such as the valve travel test can detect stiction easily. However, they are expensive, time consuming and tedious to use for examining thousands of valves in a typical process industry. A non-invasive method that can simultaneously detect and quantify control valve stiction is presented. The method requires only routine operating data from the process. Over a dozen industrial case studies have demonstrated the wide applicability and practicality of this method. In chemical industrial practice, data are often compressed for archival purposes, using various techniques. Compression degrades data quality and induces nonlinearity in the data. The issues of data quality degradation and nonlinearity induction due to compression are investigated in this book. An automatic method for detection and quantification of the compression present in the archived data is discussed. Compelling and quantitative analyses have been recommended to end the practice of process data compression.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aShah, Sirish L. _eautor _9335212
700	1		_aThornhill, Nina F. _eautor _9335213
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783540792239
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-79224-6 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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