Condition monitoring of fatigue cracks in machinery blades

A novel generic approach to fatigue crack diagnostics in machinery blades is employed. The approach consists of simultaneously using two new diagnostic features: the real and imaginary parts of the Fourier transform of vibroacoustical signals generated from a blade. This approach is more generic than traditional approaches based on the power spectral density, phase spectrum and Hartley transform; the power spectral density, phase spectrum and Hartley approaches are particular cases of the proposed approach. Numerical examples are given based on the processing of signals generated using a nonlinear model of a blade. The signals generated are the resonant vibroacoustical oscillations of cracked and uncracked blades under narrowband exitation. The numerical examples show that the crack detection is more effective when using the new diagnostic features than when using the power spectral density feature. The presented experimental results are matched with the numerical results. The proposed approach offers an effectiveness improvement over the traditional approach based on power spectral density.