**5. Conclusions**

In this chapter, a hybrid intelligent method based on fuzzy inference system is proposed for intelligent fault diagnosis of rotating machinery. In the method, several preprocessing methods, like empirical mode decomposition (EMD), filtration and demodulation, are utilized to mine fault information from vibration signals. In order to remove the redundant and irrelevant information, an improved distance evaluation technique is presented and used to select the sensitive features. Multiple fuzzy inference systems are combined using genetic algorithms (GAs) to enhance fault identification accuracy. The experimental results show that the hybrid intelligent method enables the identification of incipient faults and at the same time recognition of compound faults.
