The development of techniques in diagnosing the state of the system is one of the essential tools in establishing the automation and unmanned manufacturing system for the realization of CIM/FMS in the fields. In this paper, we developed various diagnostic schemes for the journal bearing supported rotor system. Up to now, vibration of the shaft, measurement of the displacement and the temperature have been used for diagnostic tools, however, the statistical features only could not differentiate the state from states. Thus, we identified the sensor data f3r the steady state in the signal processing and then applied the fuzzy c-mean technology to cope with the nonlinear characteristics of the system. This will, in return, establish a possible diagnostic system for the rotor system in the fields.