In this paper, there are two kinds of material (cermet and cemented carbide) to be used. Different grinding conditions were performed for evaluation of RMS of acoustic emission(AE) signals and understanding the effect of each grinding parameter on AE RMS during grinding process. A kind of on-line monitoring method based on wavelet analysis and acoustic emission was raised and the nonlinear relation model between AE RMS,wavelet energy coefficients and wheel passivation state was built. During the process,the wavelet analysis method was used to decompose the original signals for extracting wavelet energy coefficients. The results of experiments indicates that AE RMS increases with increasing table speed;The corresponding relation between AE RMS and table speed is good and could take the table speed as the main parameter for studying wheel passivation state. As a result, the nonlinear relation model can monitor the wheel passivation degree on-line accurately through training. This provides a kind of viable method which has very high practical value for confirming the wheel dressing cycle.