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Article - Main Track Intelligent Fault Diagnosis in Industrial Equipment Author: VAREJÃO, F. M. Abstract: Companies in the industrial sector generally have large investments in modern production equipment, as well as high maintenance costs for these units. Fast and accurate detection of failures and problems in industrial equipment makes a crucial contribution to reducing maintenance costs and improving confidence in production. Fault diagnosis consists of monitoring the operation of equipment in order to identify the occurrence of a failure. With the increase in the number of sensors installed on board in equipment, they have been more used to monitor the status of these equipment and diagnose their failures or malfunctions. Advances in research in the area of Artificial Intelligence, especially in the area of Machine Learning, provide ways to increase the reliability of intelligent fault diagnosis systems and result in a more reliable performance of equipment and industry. This paper presents an overview of learning techniques for the intelligent diagnosis of failures in industrial equipment that have been used in the last 12 years on the Laboratory of the Nucléo de Inferência and Algoritmos at the Universidade Federal do Espírito Santo, as well as points of future research on this topic. Keywords: Fault Diagnosis, Industrial Equipment, Sensor Data, Time Series, Machine Learning, Real World Applications Full Reference: Varaejão, F. M., "Diagnóstico Inteligente de Falhas em Equipamentos Industriais", Revista de Sistemas de Informação da FSMA n 28(2021) pp. 15-26 |