Metodologia de acompanhamento e identificação de falha em transformadores (MAIFT): contribuição da identificação da causa raiz aliada à manutenção preditiva

Abstract

Power transformers are generally the most expensive assets in an electrical system, in addition to being critical to the operation of the system or an industry in which an unscheduled shutdown can bring enormous economic damage. Thus, the detection of incipient failures and the verification of the condition of the equipment to avoid untimely stops are essential and can be achieved through periodic tests. The preventive and predictive maintenance of electrical transformers with the application of conventional techniques for analysis of gases dissolved in insulating oil are capable of indicating the types of failures: overheating, low intensity partial discharges, among others, however they do not identify the root cause of the diagnosed effects. Given this, there is the possibility of greater gains combining the predictive diagnosis with the technique of searching for the root cause of the failure, aiming at obtaining more in-depth diagnoses, allowing the blocking of the root cause. For this purpose, this dissertation proposes a methodology for monitoring and investigating failures in transformers. Therefore, it is expected that the use of the proposed tool will avoid the repetition of the problem or allow the anticipation of failure in other similar equipment. The proposed methodology is used in real cases, which demonstrates its great efficiency compared to conventional diagnostic techniques.