Abstract: In some large intelligent mechanical equipment environment,the fault data increases variety,forms a strong redundant interference environment,and in the environment,mining is time-consuming,because of the existence of unassociation rules．On the basis of full research of association mining algorithm, strong redundant data mining algorithm based on a prediction of the theory of decision homomorphism was proposed which constructs homomorphisms interval by the redundancy of the data with punish factor,constraints the interval of the huge redundant associated data correlation,ensures related data in the distance nears the homomorphism interval,and in the nearby interval,uses prediction methods of operation decision-making to make fault final confirmation．Experiments show that the method can improve the redundant environment,the accuracy of fault data mining,the calculation cost is not high,and it has a good robustness.

Key words: Forecast decision,Homomorphisms interval,Data mining