Data collection and intelligent data analysis system for performance analysis of boiler systems

In this study, It is aimed to create the most efficient product by performing all the tests required before the preparation of a new model combi boiler to be created on the field as fast and reliable as possible. For this purpose, software was created, and the connection with the PCB microprocessor was established, and instant data collection Since the collected data set is very large, it will be very difficult to analyze and deduce from its results. Rough set theory (Rough set theory) has been utilized and uncertain and fuzzy information has been overcome. In this project, the Rough set Theorem was applied to the data set we obtained with the created program through the Rose program and a reduction was made on the data. As a result of the reduction, the critical values for the test have been halved. This decrease has provided a very serious service to our goal both in terms of numbers and in terms of the relationship between parameters. With the reduced data, the tests have been carried out in many conditions, the most critical areas have been determined and the necessary arrangements have been made in the boiler operating logic. The most efficient product was created. In the first simulations examined, it was determined that the dhw temperature increased to a maximum of 62 °C in the simulations performed after the improvements made. After the improvements, the Ch temperature increased to 102 °C, and it was measured as 62 °C. In addition, the flue gas temperature was measured as 123 °C instantaneously, and after the work, it was measured as 67 °C, thus eliminating the errors and obtaining safer combi boilers.