SEMIGROUP BASED NEURAL NETWORK ARCHITECTURE FOR EXTRAPOLATION OF MASS UNBALANCE FOR ROTATING MACHINES IN POWER PLANTS

In this paper we focus on an investigation of a mathematical approach to extrapolation, using a combination of a modified neural network architecture and the semigroup theory. Semigroup theory provides a unified and powerful tool for the study of differential equations, partial differential equations and combinations thereof. The target of this investigation will be the prediction (by way of extrapolation) of the mass unbalance of the rotating component in a power plant. Simple mass unbalance system is considered for the simulation purpose. A new technique is proposed for measurement of vibration directly from rotating component using extrapolation.