Fault Diagnosis of Telecommunications Base Station Equipments Based on Neural Network

This article uses sensor analysis results as the basis for judging the signal status of base station equipments, and combines BP neural network to establish a base station equipment fault diagnosis model. Firstly, the preliminary established diagnostic model is optimized, and then the diagnostic effect of the optimized model is tested, and the test results of the model are analyzed. The analysis results show that the diagnostic model has performed well in the effectiveness test, confirming the feasibility of the diagnostic model in engineering applications.