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Aiming at the problem that the fuel flow sensor of a certain type of aircraft is susceptible to the external environment when recording, which results in a large amount of noise and non-monotonicity in the recorded signal, and lacks the recording of fuel flow parameters, an improved Complete Ensemble Empirical Empirical Mode Decomposition (CEEMDAN) method is proposed, which corrected the recording of sensor data and realized the extraction of fuel flow characteristic on the premise of monotonicity. Firstly, extracted the residual fuel volume recorded in the Flight Data Recorder (FDR). Secondly, the improved CEEMDAN method was used to extract the intrinsic mode function (IMF) and residual components and reconstructed them. Finally, the fuel consumption rate of the engine can be obtained by calculating the first derivative of the residual fuel volume. Experiments show that the SNR of the improved CEEMDAN method is 48.6% higher than that of the CEEMDAN method, and the RMSE is reduced by 69.9%.