The Research of Fault Diagnosis for Gasoline Engine Based on RS-ANN

Considering the reduction ability of rough set theory and the classification ability of fuzzy neural network, a rough set-neural network combinatorial fault-diagnosing model is constructed. The model enjoys a better topological structure and greatly increased speed for learning. The practical application to fault diagnosis for gasoline engine verifies that the model has comparably fast and accurate diagnosing abilities.