Optimization Design and Implementation of Intelligent Diagnosis System for AFC Equipment Fault Detection

Abstract

In view of the problems faced by the operation and maintenance of subway AFC system, such as the distribution of stations, the large number of equipment repairs and the difficulty of fault analysis and diagnosis. On the basis of the research and analysis, taking the operation and maintenance services as the main line, taking the parameters such as influencing the service life and maintenance cycle of the main equipment components of AFC as the characteristic data, and based on the optimization model of the combination of BP neural network and genetic algorithm. After simulation verification, an intelligent fault detection diagnosis system is designed and implemented. It has high application value in system optimization design, equipment physical quantity characteristic detection and intelligent diagnosis, and also has a certain reference guidance role in other design of preventive operation and maintenance systems related to equipment failure.