The properties of grinding wheel condition for the hard and brittle material thinning equipment (Vertical Wheel Grinder) can be estimated based on the analysis of acoustic emission (AE) signals during grinding process. In this paper, a study on the frequency content of the raw AE signals is carried out to determine the features of frequency bands from three grinding wheels with different grades. The signal characteristics of the surface condition change affected by different wheel grades are obtained from the root mean square (RMS) and ratio of power (ROP) statistics at frequency bands selected from AE spectra. The analyze results indicate that the proposed methodology can distinguish different grades of grinding wheel condition from each raw AE signals segment using the ROP statistics. Thus, based on AE spectra analysis, the raw AE signals contain most of grinding information at the frequency bands of 600900 kHz. Discrete wavelet transform and RMS statistics are able to describe the change of grinding-wheel-surface condition during grinding process. The findings of this paper proves that this research can be applied to the intelligent grinding monitoring systems in the future .