Smelting process smoke detection using multivariate image analysis

To solve the problems that available technology was difficult to detect smoke concentration in the smelting process, this paper presented investigations into the smoke detection using multivariate image analysis. Firstly, smoke image matrix was transformed to a new one with single row and high dimension columns. Then the transformed matrix was processed by principal components analysis (PCA) to extract principal components (PCs). Finally, smoke concentration was detected by the two extracted PCs and threshold values. The correlations between PCs and smoke concentration were also identified and analyzed. The results of industrial application show that the proposed method could detect the smoke concentration effectively.