Study of self-learning method based genetic programming

Appropriate symptom parameters used in the fault diagnosis expert system are not being selected fast and truly enough because the diagnosis knowledge of some of the diagnosed-objects is insufficient. In this paper the genetic programming is considered and used to self-reorganize the effective symptom parameters, a self-learning function of the system is achieved, and the precision and efficiency of diagnosis are improved. The obvious effect is proved by the experiment of fault diagnosis for the conic-form bearing