In the process of real-time monitoring of fatigue crack growth by adopting direct current potential drop method (DCPD), multiple noises interference make the potential drop signal of fatigue crack propagation inaccurate. To improve the accuracy and stability of signal, the optimal smoothing noise reduction model based on variational mode decomposition (VMD) is established. The sample entropy, correlation coefficient, and mean square error of each intrinsic mode function (IMF) are calculated to eliminate the interference source in the original signal, and the effective components are selected to reconstruct new potential drop signal. Comparing different signal reconstruction schemes to select the optimal reconstructed signal. Finally, different smoothing noise reduction models are established for the optimal reconstructed signal, and the optimal smoothing noise reduction model is obtained by comparing smoothness, mean square error, signal-to-noise ratio and other indicators. The analysis results show that the smooth noise reduction model has excellent noise reduction effect, the noise reduction error ratio of the optimal smooth model is 0. 122 050, and improves the smoothness and accuracy of the monitoring signal.