Diagnostic des defauts de fissures d'engrenages par l'analyse cyclostationnaire.

摘要

The gear crack is considered as the most complicated failure to diagnose because its vibration signature is not really known. In addition, the integration of crack defect in numerical models is not a simple task. On the other hand, gears diagnosis can be done in the time domain through statistical descriptors or in the frequency domain using spectral analysis or cepstral analysis. During the appearance of a crack defect, nonlinear and non-stationary phenomena occur which makes the classical tools of signal processing unreliable. In this manuscript, we respond to these challenges by developing a gear model of 6 DOF that has a crack that breathes. This allows us to study the signature of the defect in the resulting vibrations with a flexible way away from external vibrations. The results showed that the crack leads to a fall in the mesh stiffness. In addition, the opening and closing of the crack causes a fatigue in the material which generates a random term in the vibration signal. The combination of the random term with periodic component due to the rotation of the shafts leading to the appearance of second-order cyclostationary. A comparative study of sensitivity and robustness between the fast Fourier transform, second-order cyclostationary and estimators of instantaneous phase (the Hilbert transform, Estimation of Signal Parameters via Rotational Invariance Techniques with a sliding window, Weighted Least Squares Estimation and phase scalogramme) is performed for the early detection of cracks. In addition, experimental tests were carried out on a test-bench with different sizes of crack. The theoretical and experimental results showed that the cyclostationary analysis is the most sensitive and most robust method for the early detection of cracks in comparison with the other evaluated methods. Furthermore, the analysis of the instantaneous phase also gives good results in the case of crack defects. We have shown that the phase scalogramme is a priori more efficient than other approaches.;Keywords: Gears, crack, vibration analysis, cyclostationnarity, spectral analysis.