Research on the detection information intelligent fusion of oil equipment

Abstract

By analyzing the character of oil equipment detection, the intelligent fusion model of detection information of oil equipment has been established. The feature-level fusion algorithm based on fuzzy neural network and expert system has been proposed, in which the expert system has been embedded into fuzzy neural network so that it could choose the membership function and adjust the network structure. The improved PSO algorithm has been adopted to train fuzzy neural network and prune fuzzy rules. Evidence theory has been applied to achieve the decision-making level fusion. Then, the results of feature-level fusion have been taken as the evidences to construct the frame of discernment. On the basis of the generalized evidence combination rule, the conflict evidence combination rule based on the weighted averaging method is proposed, and the prior knowledge in expert system has been utilized to adjust the evidence weights. The research results show that the process of detection information fusion has abilities of adapting and self-learning. This research has significant importance on reliability of improving oil equipment.