The occurrence of inter-turn faults in the electric motor of the fuel pump in new energy vehicles cannot guarantee fuel supply, pressure control, lubrication, and cooling, which poses a threat to driving safety. To address this issue, this article proposes an online monitoring method for winding inter-turn faults by combining electromagnetic parameters and vibration signals. Firstly, the electromagnetic force model containing fault current harmonics is formulated according to the Maxwell tensor method. Then, a multisensor motor signal acquisition circuit is designed. Finally, the improved adaptive empirical mode decomposition method is applied to adaptively decompose the denoised vibration signals, and a set of intrinsic mode functions is selected and reconstructed by using the correlation coefficient method. The comprehensive evaluation of the kurtosis-to-root mean square ratio and envelope spectrum feature factor results in 52. 3% improvement in the fault characteristic indicator. This indicates that the reconstructed signal has higher sensitivity. The consistency between the reconstructed signal and fault characteristics is further evaluated through analysis of current waveforms. This research holds important engineering significance for the fault diagnosis and state prediction of oil pump motors.