Using Artificial Neural Network with Genetic Algorithm to Estimate the Relationship between Operational Variables in Hydrodynamic Bearing and Acoustic Emission Features

Artificial neural network (ANN) with genetic algorithm (GA) method is used to find the correlation between operational values as an input (Speed, oil type and load) and extracted outputs (RMS, power loss and shear stress) these data have reached in an experimental Examination for understanding the effect of the operational variables on generation of acoustic emission in hydraulic bearing ,Results show that ANN with GA with an error of 12% can estimate the relation between input and output data. Also the existence relationship from ANN can be used by GA in order to obtain optimal amount. Such a relationship will go some way in further developing the applicability of AE technology to monitoring rotating machinery.

Keywords:

Acoustic emission , Genetic algorithm , Hydrodynamic bearing , Neural network