000			04018nam a22005295i 4500
001			978-1-84996-106-6
003			DE-He213
005			20140220084515.0
007			cr nn 008mamaa
008			100820s2010 xxk| s |||| 0|eng d
020			_a9781849961066 _9978-1-84996-106-6
024	7		_a10.1007/978-1-84996-106-6 _2doi
050		4	_aTJ212-225
072		7	_aTJFM _2bicssc
072		7	_aTEC004000 _2bisacsh
082	0	4	_a629.8 _223
100	1		_aSbárbaro, Daniel. _eeditor.
245	1	0	_aAdvanced Control and Supervision of Mineral Processing Plants _h[electronic resource] / _cedited by Daniel Sbárbaro, René del Villar.
264		1	_aLondon : _bSpringer London, _c2010.
300			_aXX, 312 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aAdvances in Industrial Control, _x1430-9491
505	0		_aProcess Observers and Data Reconciliation Using Mass and Energy Balance Equations -- Multivariate Image Analysis in Mineral Processing -- Soft Sensing -- Dynamic Simulation and Model-based Control System Design for Comminution Circuits -- Automatic Control of Flotation Columns -- Industrial Products for Advanced Control of Mineral Processing Plants.    .
520			_aModern mineral processing plants are required to be safe and profitable and to minimize their environmental impact. The consequent quest for higher operational standards at reduced cost is leading the industry towards automation technologies as capital-effective means of attaining these objectives. Advanced Control and Supervision of Mineral Processing Plants describes the use of dynamic models of major items of mineral processing equipment in the design of control, data reconciliation and soft-sensing schemes; through examples, it illustrates tools integrating simulation and control system design for comminuting circuits and flotation columns. Full coverage is given to the design of soft sensors based on either single-point measurements or more complex measurements like images. The chief issues concerning steady-state and dynamic data reconciliation and their employment in the creation of instrument architecture and fault diagnosis are surveyed. In consideration of the widespread use of distributed control and information management systems in mineral processing, the book describes the current platforms and toolkits available for implementing such advanced systems. Applications of the techniques described in real mineral processing plants are used to highlight their benefits; information for all of the examples, together with supporting MATLAB® code can be found at www.springer.com/978-1-84996-105-9. The provision of valuable tools and information on the use of modern software platforms and methods will benefit engineers working in the mineral processing industries, and control engineers and academics interested in the real industrial practicalities of new control ideas. The book will also be of interest to graduate students in chemical, metallurgical and electronic engineering looking for applications of control technology in the treatment of raw materials.
650		0	_aEngineering.
650		0	_aChemical engineering.
650		0	_aMines and mineral resources.
650		0	_aStructural control (Engineering).
650		0	_aMaterials.
650	1	4	_aEngineering.
650	2	4	_aControl.
650	2	4	_aMineral Resources.
650	2	4	_aIndustrial Chemistry/Chemical Engineering.
650	2	4	_aOperating Procedures, Materials Treatment.
650	2	4	_aMetallic Materials.
700	1		_adel Villar, René. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781849961059
830		0	_aAdvances in Industrial Control, _x1430-9491
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-84996-106-6
912			_aZDB-2-ENG
999			_c110969 _d110969