Computer vision for automatic opening of fuming slag-furnace

Abstract: This thesis covers the implementation of visual algorithms for a robot that is to operate at a smelter furnace. The goal is for the robot to replace a human in the opening, closing and flow regulation process as danger can arise when 1300°C slag flows out of the furnace. A thermal lance is used for opening the furnace which means the robot also has to understand if the lance is burning or not. A heat camera with temperature intervals 0-660°C and 300-2000°C was used to record the furnace during these critical moments which has been used to test different vision and tracking algorithms, such as mean shift and continuously adaptive mean shift. The heat images were filtered to extract only the relevant slag flow part, which then were used to track if slag was flowing, and see how large the slag flow was. Opening of the furnace was possible to identify for both temperature intervals. For the closing of the furnace both intervals were also successful, but the lower interval used a different algorithm for this case to be successful. A relative slag flow has been identified which looks promising for further real life studies. The ignition of the lance result is inconclusive as the data recorded was not fit for analysing this case, though a few conclusions could be made indicating a thermal camera may be unfit to track the thermal lance state.