Application of fuzzy neural network in optical fiber fusion defect recognition system by AS1773 protocol

Because of having many advantages, optical fiber network is applied widely in high-tech fields. But the existence of optical fiber fusion defects will debase the quality of message transmission. A set of defect recognized system is established based on the compensatory fuzzy neural network of using wavelet and with fast algorithm in this paper. The `energy-defect' method to extract eigenvalue is used firstly, then defect classification is recognized by fuzzy neural network. The results of simulation show that the model established by making use of this algorithm has higher efficiency, and the possibility of wrap in local minimum value of the network during the training process is smaller, which can compare to approach the precision utmost steadily and classification recognize the defect precision. The experiment result can verify this system have very high accurate rate to forecast the fusion defects and satisfy the demand of the engineering application based on AS1773 protocol, which provide the technique guarantee for further realizing the optical fiber fusion quantity monitor system.