Recognition and location of rotor–stator rub-impact failure of aircraft engine with periodicity feature of vibration signals

To precisely recognize and locate a rub-impact fault of aircraft engine, an approach combining Hilbert envelope (HE), adaptive motion window (AMW), and margin factor (MF) (HE-AMW-MF) was presented. HE can reflect the change rule and tendency of vibration signals and simplify the complexity of calculation of fault diagnosis. Therefore, the paper starts with the calculation of HE of signal and takes it in place of original signal for subsequent analysis. As vibration signal caused by rub-impact fault is often accompanied by periodic impact, the paper takes advantage of the characteristic of periodic impact (collision period instead of rotation period) to adaptively determine a length and step size of motion window and exactly distills the rub-impact fault characteristics of each period. Due to the sensitivity of margin factor (MF) to the trait of wearing and impact, it is brought in to represent the fault feature information contained in signal in each motion window. Equally, mean value of all MFs is calculated and built into feature vector to reduce an interference of noise. Finally, the feature vector is combined with classification algorithms (k-nearest neighbor, KNN; support vector machine, SVM; convolutional neural network, CNN) to recognize a rub-impact fault and its location. After comparative analysis with typical method, the result indicates that the proposed HE-AMW-MF method can identify and locate the rub-impact fault more precisely, and the precision is 32.0% and 36.2%, 22.5% higher than typical comparison method.