The use of multivariate data analysis methods in corrosion monitoring data interpretation

The chlorine dioxide bleaching process is an environment where high corrosion resistivity is required of the construction materials. In order to follow the corrosion behaviour of process equipment construction materials and their weldments, corrosion monitoring systems were applied. The test material was the highly alloyed stainless steel UNS S31254 and its weldments. Corrosion potential measurements were used as the primary corrosion monitoring tool and the environmental parameters were obtained from the process automation system of the plant. The results obtained were analysed by using multivariate data analysis methods. The principal component analysis (PCA) projection method was used for process condition examinations. To determine quantitative relationships between process conditions and corrosion monitoring results, the projections to latent structures (PLS) method was used. The results showed that not only a few but many process variables affect the corrosiveness of the process solution. By using the PLS method we found that there is a clear correlation between the process conditions and the corrosion potential values. The production rate, factors related to the pulp pH and to the brightness values, among others, were significant variables when evaluating the corrosion behaviour of the highly alloyed stainless steel UNS S31254 and its weldments.