As a key component of the main power output of harvester, the fault performance of the spiral bevel gear is usually the excitation impulse. To monitor and diagnose the faults of the main transmission gearbox of agricultural harvester timely and effectively, an improved wavelet packet decomposition ( WPD) method based on dynamic model driven optimization is proposed in this paper. Aiming at the multi-component modulation phenomenon of gear damage and the characteristics of wavelet basis function specific timefrequency window to analyze the signal, the proposed method establishes the physical model of gear dynamic damage to assist in screening of wavelet packet decomposition coefficients that adapt to the gear damage characteristics. Thus, the wavelet basis function selected for the decomposed signal is optimized, so that it has a better ability to extract feature information of gear fault. Through the envelope spectrum analysis of the experimental signal and fault signal of the Chinese onion harvester gear, it is verified that the proposed method can be effectively applied to the fault diagnosis of the harvester gear.