Predictive Method for Determining the Operating Condition of Big-Blaster Air Cannons Using Automatic Classification of Critical Discharge of Compressed Air

Starting from the current requirements in industrial applications regarding the characterization and classification of the phenomenology of compressed air flow to sonic velocities in big-blaster type equipment, used for unblocking or cleaning of bunkers and silos with bulk/powder materials in cement and building material factories, coal-fired power plants, mining and steel industry, this paper presents a theoretical study of the discharge process of big-blaster equipment together with the automatic classification of each discharge by comparison with the presented theoretical results. The paper also describes the hardware and software structures of the automatic classification system, which additionally provides an automatic report and storage of the obtained results in special TDMS files or in MySQL database. Thus, we present a predictive maintenance method, which determines the operating condition of each big-blaster pneumatic cannon. The classification categories of the discharge phenomenon of big-blaster equipment obtained theoretically are validated by practical tests on a relatively large number of pieces of equipment from the range of air cannons mentioned above.