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In this work, the effect of a crack on the vibrational properties of a shaft-disc system has been studied applying a generalized harmonic balance method. In the reviewed literature, the reported methods to find the unbalance response of a continuous shaft-disc system provide only the first harmonic component of the response; whereas, the presented method gives the super-harmonic components as well. The shaft-disk system consists of a flexible shaft with a single rigid disc mounted on rigid short bearing supports. The shaft contains a transverse breathing crack (fatigue crack). The main concept for crack detection in vibration-based methods is basically the investigation of crack-induced changes in the selected vibrational properties. Shaft critical speeds and harmonic and super-harmonic components of the unbalance lateral response have been used as typical vibrational properties for crack detection in a rotating shaft system. A generalized harmonic balance method has been developed to efficiently investigate changes in vibrational properties due to the effect of crack properties, depth and location. The results of the developed analytical model have been compared with those obtained from the finite element model and close agreement has been observed.

The crack-induced changes in the vertical transient response of a rotating shaft–disc system, Jeffcott rotor, are investigated for transverse crack detection. The crack is considered as a breathing crack. A novel breathing function is proposed, in which the partially open–closed crack breathing behavior is interpolated between the fully open and closed crack behaviors. The breathing crack excites superharmonic response components of the transient as well as the subharmonic components. A Hilbert–Huang transform based on an improved empirical mode decomposition algorithm is subsequently formulated to evaluate the time–frequency representation of the vertical transient response of the rotor to detect the crack. The results show that the proposed breathing function can effectively reduce the computational effort without sacrificing the accuracy of the crack breathing behavior in the presence of small cracks. It is shown that time–frequency representations based on an improved empirical mode decomposition algorithm can lead to the detection of smaller cracks compared with those based on the empirical mode decomposition algorithm.