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A wavelet transform based method is proposed in the paper for harmonic analysis. The research is motivated by the authors’ project about power quality monitoring. In the project, a classifier for recognizing power quality disturbances has been developed. The classifier adopts wavelet transform to extract features of various distorted waveforms including those containing harmonics. Obviously, it is no longer necessary or economic to use Fourier transform for evaluating harmonics that are retrievable from the transformed data. Thus a number of algorithms have been developed to estimate the distortion contributions from different sub-band coefficients. By employing techniques of neural networks, furthermore, each harmonic component is directly retrieved. Both the distortion estimation and the harmonics evaluation have achieved a high accuracy.