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Helicopter rotor system consists of a large number of dynamic components, and works in a single-channel and complex environment, which is a critical system that ensures the helicopter reliability and security. Because the data on the rotating parts is not easy to measure, and the noise environment is complex, the rotor fault detection capacity is limited, thus seriously affecting the reliability and safety of the helicopter as a whole. This paper firstly presents the simulation of neural network prognostic method based on the rotor system failure mechanism and failure mode analysis (FMA), which can effectively use the failure mode for the modeling of the prediction method combined with the test and simulation data of key components, and greatly improved the effectiveness of fault detection. Besides, a general, open architecture of an advanced health usage and management system (A-HUMS) is proposed, and the overall structure, hierarchy and functions are elaborated. Finally, taking the helicopter rotor system components as the research object, the validation system of the helicopter HUMS system has been planned and designed. The analysis results show that the proposed method can effectively predict to preset a variety of fault conditions and solve the low predictive ability of key components of the rotor system failure problems.