Corning Incorporated
PREDICTING OPTICAL FIBER MANUFACTURING PERFORMANCE USING NEURAL NETWORK

Abstract:

A machine accesses a stored dataset comprising, for each of multiple optical fiber preforms, a plurality of images of each optical fiber preform coupled with an indication of a number of fiber kilometers lost due to diameter upset of a cable built using optical fiber drawn from the optical fiber preform. Each image represents a portion of the optical fiber preform. The machine preprocesses the stored dataset to generate a training dataset. The machine trains, using the training dataset, a convolutional neural network (CNN) to predict diameter upset performance of an optical fiber preform based on visual information representing the optical fiber preform. The CNN comprises an input layer, a plurality of hidden layers, and an output layer. Each of the input layer and the plurality of hidden layers comprises a plurality of artificial neurons. The machine provides an output representing the trained CNN.