Experimental Analysis and Validation of a Vibration-Based Technique for Crack Detection in a Shaft

Abstract

Detection of cracks in shafts plays a critical role in maintenance. A crack can cause a catastrophic failure with costly processes of reparation. The aim of condition monitoring and fault diagnostics is to detect and to distinguish different kinds of faults. In this work vibration signals are obtained from an analytical Jeffcott rotor model and a real rotating machine during working. The aim was to identify indicators of the presence of a crack, to allow the inverse process of detecting a crack and its size for the machine tested. Signals were processed using the Wavelet Packets Transform. In signals obtained from the analytical model, the best indicators of crack were frequencies related to the first's harmonics of the rotation speed. However, when matching the theoretical results with the experimental ones, only harmonics higher than the 2× component of the rotation speed seemed to feel that changes in practice.

Review of Recent Advances in the Application of the Wavelet Transform to Diagnose Cracked Rotors

“…Specifically, in crack detection, the maximum cross-correlation coefficients computed between the fault signal and the different wavelet functions from the library will give the optimal wavelet function, as shown in [68]. The Daubechies family, and more specifically the Daubechies order six has been widely used for crack detection due to its proven effectiveness in this field [33,57,69].…”