Advanced Control and Supervision of Mineral Processing Plants describes the use of dynamic models 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. Coverage is given to the design of soft sensors based on either single-point measurements or more complex measurements like images. Issues concerning data reconciliation and its 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 platforms and toolkits available for implementing such systems

Advanced Control and Supervision of Mineral Processing Plants describes the use of dynamic models 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. Coverage is given to the design of soft sensors based on either single-point measurements or more complex measurements like images. Issues concerning data reconciliation and its 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 platforms and toolkits available for implementing such systems.

Applications of the techniques described in real 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.

Provides the reader with up-to-date information on the application of modern control methods in the mineral processing industries Readers can investigate the benefits of this book further using the examples and MATLAB® code available from the book's website Includes supplementary material: sn.pub/extras

Klappentext
Modern 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 rawmaterials.

Inhalt
Process 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.