| Citation: | ZHANG Zhen, LIU Baoguo, ZHOU Wanchun, et al. Composite fault signal feature extraction method for aero-engine based on maximum correlation Rényi entropy and phase space reconstruction[J]. Journal of Aerospace Power, 2023, 38（4）：889-900 doi: 10.13224/j.cnki.jasp.20220609
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In order to solve the problem of complex fault signal feature extraction under the condition of low signal-to-noise ratio (SNR) and complex noise, a feature extraction method based on phase space reconstruction and maximum correlation Rényi entropy deconvolution was proposed. Rényi entropy was taken as the performance index, and the maximum correlation Rényi entropy deconvolution was taken as the basic method, and the phase space reconstruction technique was incorporated with the characteristics of noise suppression and decomposition. Results showed that the sensitivity of Raney entropy was only 18.4% of the kurtosis when the fault sensitivity was equal to and slightly better than that of kurtosis. Through simulation, experimental data and bench test, this method was proved superior to existing comparison methods in extracting the features of composite fault signals.
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