Controlling the Twin Wire Arc Spray Process Using Artificial Neural Networks (ANN)

One approach for controlling the TWAS process is to use optical properties of the particle beam as input parameters for a process control. The idea is that changes in the process can be detected through observation of the particle beam. It can be assumed that if beam properties deviate significantly from those obtained from a beam recorded for an optimal process spray particle and so coating properties change significantly. The goal is to detect these deviations and compensate occurring errors by adjusting appropriate process parameters. One method for monitoring is to apply the diagnostic system PFI: PFI fits an ellipse to an image of a particle beam thereby defining easy to analyze characteristical parameters. Using artificial neural networks (ANN) mathematical relations between ellipse and process parameters can be defined. In case of disturbance through the use of an ANN-based control process parameters can be computed to compensate particle beam deviations.