Sistemas inteligentes para monitoramento e diagnostico de falhas em motores de indução IEC 60034 / ISO 20816

Abstract

In industrial plants, engines are subject to failures that can cause production downtime causing economic losses. Predictive monitoring identifies these failures and reduces maintenance and operating costs. In this work, systems for monitoring and diagnosing faults in three-phase induction motors were developed based on the IEC 60034 and ISO 20816 standards. Through a pattern recognition neural network, the Operating Regions Diagnostic System classifies the region of operation of the motor. The Rotor Broken Bar Diagnostic System monitors the machine’s state through a recurring neural network of short-term long memory, identifying the number of broken bars on the rotor and the operating zone according to ISO 20816. Finally, the Diagnosis Fuzzy uses a neuro- fuzzy system to predict the motor reduction factor, predicting possible failures that occur due to voltage imbalance.