NOVELTY - The method involves tracking time characteristics of specific sensor data, during monitoring operating phase. The first diagnosis SOM with subset of specific sensor data is prepared in reference operating phase. Three-dimensional (3D) graph of first diagnosis SOM is evaluated to identify a fault cause. The second diagnosis SOM is prepared, when identification of fault cause is unsuccessful. Second diagnosis SOM is evaluated to identify the fault cause for checking a starting model. The rule set is modified based on evaluations of reference and diagnosis SOMs.    USE - Method for monitoring rotating machine such as wind power plant. Can also be used in dragline excavator such as scraper excavator and bucket dragline excavator, marine engine, thruster drives, crushing mill, thruster, industrial turbine, pumping, fan and hydroelectric power plant.    ADVANTAGE - The diagnosis SOM is evaluated to identify the fault cause for checking the starting model, and rule set is modified based on evaluations of reference and diagnosis SOM, so that the current machine state and the risk of failure can be evaluated reliably. The vibration-diagnostic condition monitoring is established, and vibrations of the individual components are continuously recorded, hence several plants regardless of their locations can be monitored effectively. The incipient component damage can be detected reliably. The initialization of the monitoring process can be made simply and efficiently. The efficiency and reliability of the statistical evaluation can be greatly improved. The statistical analysis can be improved with increasing length of plant operation. The turbulence-induced vibration excitations can be recognized and analyzed reliably. Amplitude SOM graphs and pertinent frequencies can be evaluated, so that expected degrees of damage and reductions of the service life can be estimated efficiently. The remaining service lives can be estimated and predictions of remaining utility can be derived. The turbulence actions and effects can be determined by comparisons of graphs. Selective vibration and diagnosis characteristics can be used in SOM graphs for systematic machine analysis and can be automatically monitored based on diagnosis/vibrations coding.    DESCRIPTION OF DRAWING(S) - The drawing shows a block diagram illustrating monitoring process of rotating machine. (Drawing includes non-English language text)