It is well known that a crushing process is one of the most energy intensive technological processes in mineral processing. The aim of this process is to achieve the required size of the processed raw material. The course of the crushing process is characterized by the influence of a number of basic factors: multidimensionality, multiple connections, nonlinearity, physical and mechanical properties of the mineral, shape and size of rock lumps, position of the crushing material inside the crushing chamber, lumps movement speed, wear of a liner and elements of the crusher, as well as design parameters of the crusher. Efficiency of the crushing process in the process flow of solid mineral processing is achieved by applying reasonable operation parameters of crushing equipment, ensuring the set performance and particle size distribution of the crushed ore at minimum electricity consumption. When processing minerals, the size is often monitored between individual operations. Objective. The objective is to provide an innovative solution in developing intelligent systems for automatic control, resulting in adaptive control, depending on changes of the material size distribution by making measurements “inside” the technological equipment. Methods Applied. Methodology of fuzzy logic theory and fuzzy sets was used. Originality. We made it possible to distinguish frame differences in a video stream to detect defects and wear of a crusher liner. Result. The paper identifies an approach to monitoring the discharge slot width for crushing and milling complexes using intelligent control methods.