Identification of Breathing Cracked Shaft Models from Measurements

  • Michael I. Friswell
  • Ralston Fernandes
  • Nidhal Jamia
  • Sami El-Borgi
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)


Cracks in the shafts of rotating machinery are a serious problem that can lead to significant costs. Condition monitoring is required to identify the presence of cracks before the machine fails. However, methods based on linear models and low frequency dynamics are very insensitive because the local stiffness reduction leads to only small changes in critical speeds. Cracks in a shaft are often breathing; they open and close depending on the local curvature of the shaft. In the general case this makes the crack nonlinear, and leads to the presence of harmonics. In larger rotating machines the cracks will open and close because the self weight of the rotor; for a constant rotor spin speed this leads to a parametric variation in stiffness. There are various breathing crack models, many of which model the stiffness as a truncated Fourier series. However the parameters of this series are estimated based on an idealized model of the crack front. This paper suggests a method to directly estimate the breathing crack stiffness using the measured synchronous response and its harmonics. The approach is demonstrated on a simple laboratory test rig. These improved models are vital to enable accurate model based condition monitoring of rotating machines.


Rotating machine Breathing crack Condition monitoring 



The authors gratefully acknowledge the support of the Qatar National Research Fund through grant number NPRP 7-1153-2-432.


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Copyright information

© The Society for Experimental Mechanics, Inc. 2016

Authors and Affiliations

  • Michael I. Friswell
    • 1
  • Ralston Fernandes
    • 2
  • Nidhal Jamia
    • 1
  • Sami El-Borgi
    • 2
  1. 1.College of EngineeringSwansea UniversitySwanseaUK
  2. 2.Department of Mechanical EngineeringTexas A&M University at QatarDohaQatar

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