Browsing by Author "Rabie, Johannes Kasselman"
Now showing 1 - 1 of 1
Results Per Page
Sort Options
- ItemPellet-size estimation of a ferrochrome pelletizer circuit using Computer Vision techniques(Stellenbosch : Stellenbosch University, 2018-03) Rabie, Johannes Kasselman; Auret, Lidia; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.ENGLISH SUMMARY: Agglomerate pellet size plays an integral part in the safe and stable operation of a submerged arc furnace (SAF), and the efficiencies and yields achieved within the ferrochrome refining processes. For effective process control that ensures constant and optimal pellet size production, the continuous monitoring of pellet size distribution produced by the agglomeration circuit becomes imperative. Traditional size estimation methods tend to be labour intensive and time consuming, and cannot provide feedback in real time. The need therefore exists for automated, real time, and non-intrusive industrial size estimation systems. Despite major advances in the field and proven advantages with regards to object identification and analysis, image analysis-based size estimation systems have not experienced widespread implementation in the mineral processing environment. Cost and problem specific implications have been cited as the main factors inhibiting implementation. In an attempt to prove its viability, this study was aimed at developing a Digital Image Processing (DIP) and Digital Image Analysis (DIA) based particle size estimation algorithm that is suitable for implementation as part of a conceptual particle size distribution estimation sensor at a FeCr pelletizing plant, specifically at Glencore Plc‘s Bokamoso Pelletizing Plant. Additionally it had to explore the viability of the implementation of the sensor as part of a continuous monitoring and control system for a FeCr pelletizing process. This would be done through the development of a conceptual control framework for a FeCr pelletizing circuit. The algorithm was tested and validated on both simulated pelletizer circuit footage and actual process footage, with the former being made possible by the construction of a lab-scale set-up of a section of a FeCr pelletizing circuit. Estimated pellet size distributions were compared to sieve size distributions and a pixel to mm ratio. Results of analyses of both types of footage showed that the algorithm was capable of accurately estimating particle size distribution of moving FeCr pellets. In terms of industry application, the results point to a solution that analyses sintered pellet on conveyor footage as opposed to pellets on roller footage. Furthermore, the conceptual control framework suggests that the output of the algorithm can be successfully utilised in a control system that aims to control the size of FeCr pellets produced by a FeCr pelletizing circuit. The use of problem specific filters aided in the accuracy of the algorithm in terms of identifying and delineating objects of interest, and thus ensured its applicability. It is however recommended that future studies investigate methods in which size estimation error associated with irregularly shaped particles is mitigated. Furthermore, it is also recommended to investigate and apply methods that would enable the algorithm to correctly interpret surface pellet data, in terms of pellet on conveyor footage, and subsequently correctly infer information regarding the entire population.