Abstract: To overcome the shortages of IEC method of wind turbine noise tonality evaluating, an improved methodology is proposed. Firstly, the tonal signal generated from wind turbine (WT) is extracted from the captured noises in operating conditions, taking use of Gabor order component exaction technology. It is beneficial to eliminate the tonality evaluating errors caused by using background masking noises level of shutdown WT to correct that of running WT. Secondly, one minute WT noise was divided into some relatively stationary sub-segments, in order to suppress the frequency aliasing phenomenon in FFT analysis of non-stationary signal. Thirdly, the tonality identification method based on spectral flatness measure replaces that based on psychoacoustic model in the IEC standard. This replacement can eliminate the deviation brought by forecast of initial tone frequency and simplify the procedure of tonality identification to a great degree. The experiments in Danbancheng of Xinjiang province have verified that the improved methodology is able to eliminate the uncertainty and inconsistency of WT noise tonality evaluating with the IEC method, and has a good prospect in the application of WT noise tonality assessment.