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Considering difficulty in choice of fault feature and deficiency of principal component analysis for helicopter rotor, an effective fault feature choice method based on kernel principal component analysis is presented and realized. A nonlinear mapping from original feature space into high dimensional feature space is realized by calculating inner product kernel function in original feature space....
Considering difficulty in extracting feature and localizing fault for helicopter rotor, a new method based on wavelet energy spectrum and phase spectrum is presented. The wavelet package analysis is adopted to eliminate the noise in the actual signals to increase signal-to-noise ratio, and to extract energy feature vector in various frequency bands through signal decomposition and single reconfiguration...
Considering the drawbacks of traditional adjustment method without calculating possible nonlinear between rotor adjustments and fuselage vibration signals, a new rotor adjustment method based on general regression neural network (GRNN) and genetic algorithm is presented. GRNN network is employed to model the relationship of the rotor adjustments and fuselage vibrations, whose input parameters are...
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