A improved back propagation(BP) neural network by Genetic algorithm was introduced to realize the automatic classification and recognition of wear debris, based on the qualitative characterization of the morphological features of the wear debris making use of the characteristic parameters of wear debris shape, color, and surface texture. A neural network model based on the improved back propagation (BP) neural network by Genetic algorithm was established to classify and recognize the wear debris using those parameters as the input vectors. The algorithm of the established model was detailed. By comparing the results of automatic recognizing the wear debris by the improved BP neural network and the presented BP neural network, it shows that the improved back propagation (BP) neural network combines the global optimization feature of genetic algorithm and the fast speed feature in local search of BP algorithm, which has a high recognition rate and better global search feature.
.[J]. Lubrication Engineering,2014,39(1):24-28.