Analysis of cracks and coating in iron ore pellets by digital image processing

Abstract

The pelletizing process agglomerates ore fines previously considered as tailings and makes its application possible in the form of pellets. During the process, the pellets are subjected to various compressive forces and temperature changes, which cause ruptures in their surface. These ruptures (cracks) impair the performance of the pellets in the reduction furnaces and affect their strength. In addition to cracking, the formation of clusters inside the furnaces is also a problem for the reduction process because they compromise the flow of gases inside the furnaces. This bonding phenomenon occurs from the formation of iron bridges between pellets subjected to high temperatures. This problem can be minimized by coating the pellets with a mixture of magnesium oxides that inhibits bridging. The present study considered the importance of characterizing cracks and coating on the pellet surface and developed methodologies for the acquisition, processing and digital analysis of images acquired with a stereoscope. Adjustable sample holders were developed which made it possible to cover most of the surface area of the spherical object avoiding overlapping of analysis regions. The crack analysis routine used semantic segmentation and provided attributes such as mean thickness, area fraction and length. The coating analysis routine used color threshold segmentation and measured the fraction of the area occupied by the coating in the samples. The use of the sample holders was essential for the success of the acquisition procedure. The analysis routines were robust for different samples.

Application of Digital Image Processing Technology in Textile and Garment Field

“…e mean filtering algorithm is relatively simple, and the calculation speed is very fast [17]. However, the smoothing effect of mean filtering is mainly determined by the neighborhood radius used.…”