This paper presents study of efficiency of wavelet transformation for on-line chatter detection during hard fuming process. From comparison with other time series and statistical methods such as fast fourier transformation (FFT), Kurtosis and standard deviation (STD), wavelet transform is better than others in on-line chatter detection. With using wavelet function with pseudo frequency corresponding to chatter frequency, chatter could be detected more sensitively. And for both force signal from dynamometer and displacement signal from capacitance type cylindrical sensor (CCS), wavelet transform with DB2 function on level 4 could be well used for chatter detection in hard turning process.