Abstract:Abstract:Through the pattern recognition of ferrograghy wear particle, the wear condition of mechanical equipment can be monitored effectively to prevent the malfunction problems. In this paper, the raditional particle swarm optimization algorithm is improved, in addition, the improved pso is used to optimize the error punish modulus and kernel function parameter, and the slf-adapting recogniyion model for wear particle was established. The method is applied in simulation , and the classification accuracy rate is 98% . The method is compared with the BP neural network, the results show superiority and effectivity of the new method.