Based on the parameter optimized variational mode decomposition (POVMD) and envelope order spectrum, a new fault diagnosis method is proposed to extract the fault features of rolling bearing under variable speed condition. First, the vibration signal of rolling bearing is decomposed into several intrinsic mode functions (IMFs) by POVMD. Second, each IMF is resampled in the angular domain and transformed into stationary signals. Then, the Hilbert transform is used to estimate the envelope function of the resampled signals. The obtained envelope functionsare are analyzed using the order tracking technology and the fault feature information is read from the order spectrum. The comparisons show the superiority of POVMD over empirical mode decomposition by analyzing the simulation signals. Finally, the proposed fault diagnosis method for rolling bearing with variable speed is applied on the experimental data analysis and the results show that the propose method can effectively achieve the fault diagnosis of rolling bearing in variable speed.