Design and Implementation of Damage Assessment System for Optical Fiber Intelligent Structure Based on RBF Neural Network

The safety and reliability of optical fiber structure are the key factors to ensure the normal operation of the whole system, and slight damage can potentially cause catastrophic accidents. In order to avoid this situation, structural damage must be identified. At present, academic circles are actively developing new methods for structural health monitoring and damage analysis. In recent years, the intelligent method represented by RBFNN (RBF neural network) has been applied to structural damage diagnosis. In this paper, the damage assessment of optical fiber intelligent structure based on RBFNN is studied. Experiments show that the average time of the system in this paper is the shortest, with an average time of 24.09min, followed by the system in literature [5] with an average time of 71.03min, and finally the system in literature [8] with an average time of 75.90min. Therefore, the system established in this paper is more suitable for damage assessment of optical fiber intelligent structures. Therefore, it is an ideal method to apply RBFNN to signal processing in optical fiber intelligent structure.