Digitalizace údržby parního ofukovače

Abstract

This thesis addresses the design and development of a monitoring system for steam blowers, which are crucial for the effective cleaning of heat exchange surfaces in power plant boilers. The aim of the work was to develop a system that, by using modern data collection and analysis technologies, would improve maintenance processes and reduce costs associated with the operation of steam blowers. The implementation of edge computing and IoT technologies for real-time data collection and processing enables more efficient fault prevention and maintenance optimization. Through the integration of hardware and software components, a prototype was created and tested in an industrial environment. The system demonstrated the ability to improve fault prediction and prevention, contributing to extended equipment life and minimizing unplanned downtime. The work also identified key areas for future development, including improvements in data security and user interface. The results of this thesis demonstrate the potential for the digitalization of maintenance in the industrial sector and provide important insights for further development in the field of industrial monitoring systems. The thesis confirms that an innovative approach to monitoring and maintenance can significantly contribute to the efficiency and economic sustainability of industrial operations.