To address issues in gearbox fault diagnosis of doubly-fed wind turbines, such as the lack of coverage of doubly-fed grid-connected conditions in existing stator current methods and the difficulty in comparing frequency band aliasing under variable operating conditions, this article proposes a gearbox condition monitoring method based on stator current signals from doubly-fed wind turbines. Firstly, a phenomenological model is formulated based on the stator current signal of the generator of the doubly-fed wind turbine physical simulation platform, and the composition and law of the stator current signal were determined. Then, the stator current signal phenomenological model is used to link the mechanical part of the fan with the electrical characteristics and determine the influence of the mechanical side of the fan on the electrical side. The current-energy ratio algorithm was proposed. For the problems of frequency band overlap and inability to compare caused by variable working conditions, the method of segmentation and reorganization is used to avoid it. Rotor speed estimation is achieved by leveraging motor cogging harmonics, enabling the calculation of the current energy ratio using only stator current signals, with a mean relative error of 0.277 2 and a mean squared error of 0.114 6. To validate the feasibility of the method, stator current signals under various operating conditions are collected from a physical doubly-fed wind turbine simulation platform for both normal and multiple fault states of the gearbox. The results show that the current energy ratio under gearbox fault conditions is significantly higher than that in the normal state, and the severity of faults in the same component is positively correlated with the current energy ratio—specifically, more severe faults correspond to higher current energy ratios. Comparative analysis of the current energy ratio between the parallel stage and the secondary planetary stage further shows that the algorithm maintains strong universality even when wind turbine parameters change. It can effectively monitor faults in both the parallel and secondary planetary stages of the gearbox.