Abstract
An intelligent sensor for estimating the coal powder rate injected into a slag-cleaning furnace (SCF) was developed at Caletones Smelter, Chile. At present the estimation algorithms are only based on discharged cycle average information, leading to large prediction errors. In this paper an improved estimation of the current coal rate is presented, based on the instant tank weights, the tank pressure and the position of the control valves, among other variables. Better control of coal addition into the batch process increases copper recovery from slags and reduces the particulate material pollution. An hybrid expert and fuzzy supervisory control is proposed.
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