A fast test and compensation system for optical encoders based on extreme learning machine — Fourier Neural Network

This paper describes fast test and compensation system for optical encoders. The resolution of system is 0.375", and it can measure the actual accuracy of an optical encoder in four minutes. Furthermore, a method called Extreme Learning Machine - Fourier Neural Network (ELM-FNN) are proposed to compensate the error. Fourier neural network (FNN) is chosen to fit the curve of the optical encoder's output, and the weights of FNN is calculated by Extreme Learning Machine (ELM). Experimental results demonstrate that ELM-FNN effectively improve the accuracy of the optical encoder. Compared to a back propagation neural network (BP net) and a standard FNN, ELM-FNN has advantages of higher accuracy and less training time.