Research on Wear Debris Recognition Algorithm Based on IFNN
According to the qualitative characterization of the morphological features of the wear debris, Feature vector mathematics model of wear debris are built,which are based on Foruier parameter refining methord.Then the advantages of fuzzy system and neural network are taken to establish a kind of improved fuzzy neural network (IFNN) models and algorithm.which is used to realize the automatic classification and recognition of wear debris. An improved learning algorithm with the modified fuzzy weight is proposed on the basis of the fuzzy neurons model for the max-min fuzzy operator. The amount of calculation for the improved FNN model is reduced greatly and the convergence velocity is improved. At last ,the experiment results show that the recognition method based on the IFNN is good at algorithm convergence speed and recognition accuracy.
Dongye Sun, Wen-Pei Sung and Ran Chen
X. Wang "Research on Wear Debris Recognition Algorithm Based on IFNN", Applied Mechanics and Materials, Vols. 121-126, pp. 4043-4047, 2012