The clustering rule based data mining fault diagnosis in internet based Virtual Hospital for power equipment

In internet based Virtual Hospital for power equipment, it is not easy to use the rules of power equipment fault diagnosis from the resources by traditional expert system. Data mining technique opens a new window for the utilization of the abundant and chaotic data in VH. In this paper, the clustering rule and Radial Basis Function Neural Network based data mining fault diagnosis method for power equipment is proposed. Furthermore, using rough sets method to pretreat the input of Neural Network, the training time can be decreased quite more. All these will offer the quite significant reference information for fleetly and drastically excluding the fault.