Aiming at the problem that the feature extraction performance of variational modal decomposition (VMD) is affected by its parameters and the poor real-time performance of fault state tracking, an early warning approach and adaptive VMD method are proposed and applied to mechanical part fault detection. Firstly, the degradation characteristics of the full-life vibration signal of mechanical parts are extracted, and then the state warning line is constructed based on the 2σ criterion. Through the early warning line, the degradation state of mechanical parts can be tracked and the fault early warning points can be detected. Then, the energy entropy and mutual information are introduced to construct the fitness function, and an adaptive VMD model is constructed by grasshopper optimization algorithm (GOA) to detect the fault state of mechanical parts near the early warning point. The results show that the proposed state early warning line can detect the fault early warning points timelier and more effectively, and the adaptive VMD can detect the faults of mechanical parts more accurately, which have good application value.