Predictive maintenance oriented neural network system - PREMON

Abstract

The cost of equipment maintenance represents an important budgetary item in industrial and commercial applications. Smart machines are able to evaluate online a number of its own vitalities helping operators to diagnose faults. Most often the origins of the problems are buried into intractable and not usually relevant data. Some neural architectures are presented for recognizing those operational trajectories that are the early symptoms of faults in these smart machines. In order to cope with such classification problem, a neural architecture defined as PREMON (predictive maintenance oriented network) is designed. The main advantage of the system is its brain-inspired philosophy that allow it to be applied to a great deal of systems that are degraded or damaged because of their interaction with its environment.