Research on fault location technology based on BP neural network in DWDM optical network

BP neural network is introduced to the fault location field of DWDM optical network in this paper. The alarm characteristics of the optical network equipments are discussed, and alarm vector and fault vector diagrams are generated by analyzing some typical instances. A 17 × 14 × 18 BP neural network structure is constructed and trained by using MATLAB. By comparing the training performances, the best training algorithm of fault location among the three training algorithms is chosen. Numerical simulation results indicate that the sum squared error （SSE） of fault location is less than 0.01, and the processing time is less than 100 ms. This method not only well deals with the missing alarms or false alarms, but also improves the fault location accuracy and real-time ability.