FUZZY ESTIMATION PROCEDURE OF THE CONCENTRATION OF THE COMPONENTS OF A SULFURIC ACID PICKLING SOLUTION

The article is devoted to the issue of determining the level of concentration of individual components of working solutions. The relevance of the topic lies in the fact that some impurities in solutions (for example, when pickling steel) cannot be measured automatically, which reduces the efficiency of the process and increases the load on the solution regeneration section. Also, impurities are hazardous waste for the environment and humans. The development of a method for the operational control of the composition of the pickling solution components in pickling baths is the main task of the work. A detailed substantiation of the choice of the mathematical apparatus of the method is given. The process of fuzzy identification of the composition of the components is carried out by the number of pixels with certain digital color RGB codes from digital images of the control doses of the solution. A set of technical means for providing the method for practical implementation in the technological process is described. A prototype of a graphical user interface (GUI) for the proposed method for identifying the composition of technological liquid solutions, developed in the Processing 3.0 integrated environment using applications from the Open Source Computer Vision Library, is presented. A technique for extracting experimental data for filling the base of a fuzzy classifier with model reference points is proposed. Its essence lies in simultaneous measurements of the concentration of the components of the pickling solution by classical methods of titration and dry residues and the proposed method with a step equal to the regulated accuracy. The results of approbation of the proposed method are presented. The presented technique for obtaining a fuzzy classifier can be used to develop IT tools for the operational control of the composition of various liquid solutions with opaque colored components and color identification of defects in various flat surfaces, provided that they are color distinguishable and determine the boundaries of RGB - intervals for assessing the color of individual component (defects).