Investigation of the Possibilities for Infrared Diagnosis of Peirce–Smith Converters in Non-Ferrous Metallurgy

To implement predictive maintenance of units in the practice of metallurgical manufacturers, computer information and diagnostic systems are being developed to assess the current state of individual units throughout their entire life cycle. This publication presents the results of a study on developing an infrared diagnostic system for predictive maintenance of converter units in the non-ferrous metallurgy industry. A 3D mathematical model of the transient heat transfer in the wall of a real operating unit has been developed and numerically implemented to study, analyze, and diagnose surface temperature fields resulting from wear and local damage. To adjust the operation of the mathematical model, the design parameters and the results for operating and technological parameters from an industrial experiment are taken into consideration. Using the model, a full-factor experiment was simulated to study the surface temperature fields resulting from the erosion wear of the wall and the presence of local damage. Based on the simulation results, the optimal time range for thermographic monitoring is determined. A regression dependence was derived to predict the refractory wall wear as a function of the outer surface temperature of the converter unit. The results are part of a comprehensive investigation aimed at developing thermal imaging techniques for converter units in non-ferrous metallurgy.