Estimation of Phases Levels in a Teniente Converter Using Machine Vision

Abstract

Abstract The Teniente converter (TC) is used for smelting and converting copper concentrates. The TC process is very complex given that it combines continuous input flows with intermittent product extraction in an autogenous operation. Liquid levels inside the converter are important variables for deciding the operation of the overall process, but in the high-temperature environment of the TC, their measurement presents a challenge. Although various measuring techniques have been employed for the task, the traditional approach using a test bar remains the established one. This article describes an instrument for estimating the phase levels in a TC based on machine vision. The method employs a digital camera to capture images of the test bar. A video image processing algorithm extracts several of the surface characteristics of the bar in order to make the estimate. The main contribution of this work is to estimate criteria free of human intervention and directly connect the image processing algorithm to the smelter's control network.