PREDICTIVE MAINTENANCE THROUGH VIBRATION ANALYSIS IN BOILER EXHAUST ROTOR

Abstract

The condition of a machine affects the quality and efficiency of its work and allowing a problem to reach a critical state results in negative consequences, potentially causing equipment loss and extensive downtime in a factory. Machine maintenance, therefore, is a concern that came into existence along with the creation of the industry. The expansion of industries has made it necessary to carry out constant maintenance. This fact made the planning areas realize that there were better ways to carry out maintenance, other than just when the equipment was defective (corrective maintenance) or simply changing everything to avoid defects (preventive maintenance). Bearing in mind that predictive maintenance, based on vibration analysis, is extremely important to detect defects imperceptible to the naked eye or audible tests. The objective of this work is a case study that shows that with the implementation of a predictive maintenance system that uses vibration analysis, it is possible to prevent failures and breakdowns in equipment, thus reducing the time and cost for identification and repair. of failures. For this purpose, an exhaust fan rotor from a boiler located in the industrial area of ​​a company that generates energy was studied using the steam generated by burning sugarcane bagasse. Throughout the case study of boiler exhaust vibrations, two faults due to dynamic unbalance in the rotor were identified. In short, the objective of the work was achieved, as it was possible to perceive the efficiency of the method, given that the fault was intercepted before causing further damage, giving the maintenance team the chance to prepare for the repair.