
An Advanced Control System for Fine Coal Flotation. Sixth quarter, technical progress report, July 1-September 30, 1997
Author(s) -
G.T. Adel,
G.H. Luttrell
Publication year - 1997
Language(s) - English
Resource type - Reports
DOI - 10.2172/620677
Subject(s) - froth flotation , process engineering , coal , process (computing) , process control , instrumentation (computer programming) , control (management) , engineering , computer science , operations research , industrial engineering , waste management , chemistry , artificial intelligence , organic chemistry , operating system
Over the past thirty years, process control has spread from the chemical industry into the fields of mineral and coal processing. Today, process control computers, combined with improved instrumentation, are capable of effective control in many modem flotation circuits. Unfortunately, the classical methods used in most control strategies have severe limitations when used in froth flotation. For example, the nonlinear nature of the flotation process can cause single-input, single-output lines to battle each other in attempts to achieve a given objective. Other problems experienced in classical control schemes include noisy signals from sensors and the inability to measure certain process variables. For example, factors related to ore type or water chemistry, such as liberation, froth stability, and floatability, cannot be measured by conventional means. The purpose of this project is to demonstrate an advanced control system for fine coal flotation. The demonstration is being carried out at an existing coal preparation plant by a team consisting of Virginia Polytechnic Institute and State University (VPI&SU) as the prime contractor and J.A. Herbst and Associates as a subcontractor. The objectives of this work are: (1) to identify through sampling, analysis, and simulation those variables which can be manipulated to maintain grades, recoveries, and throughput rates at levels set by management; (2) to develop and implement a model-based computer control strategy that continuously adjusts those variables to maximize revenue subject to various metallurgical, economic, and environmental constraints; and (3) to employ a video-based optical analyzer for on-line analysis of ash content in fine coal slurries