Visibility graph method is used to map multifractal series to complex networks.Intrinsic traits of multifractal series generated by different dynamical mechanisms were compared.It is found that mixture series constructed by superposition of several monofractal Brownian motions behave generally with multifractal character and the corresponding networks are scalefree.While for the multifractal series generated by theoretical models,the corresponding visibility graphs display complicated behaviors rather than scalefree.In order to distinguish between these different generators,joint use of wavelet analysis and visibility graph is required to make clear the dynamical mechanisms embedded in multifractal time series.Visibility graph method is a necessary complement to traditional time series analysis approaches,which has potential use in detecting dynamical mechanisms of complex systems from output series.