Identification of breathing cracked shaft models from measurements

Michael I. Friswell, Ralston Fernandes, Nidhal Jamia, Sami El-Borgi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationRotating Machinery, Hybrid Test Methods, Vibro-Acoustics
PublisherSpringer New York LLC
Pages537-543
Number of pages7
Volume8
ISBN (Print)9783319300832
DOIs
Publication statusPublished - 2016
Event34th IMAC, A Conference and Exposition on Structural Dynamics, 2016 - Orlando, United States
Duration: 25 Jan 201628 Jan 2016

Other

Other34th IMAC, A Conference and Exposition on Structural Dynamics, 2016
CountryUnited States
CityOrlando
Period25/1/1628/1/16

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Keywords

  • Breathing crack
  • Condition monitoring
  • Rotating machine

ASJC Scopus subject areas

  • Engineering(all)
  • Computational Mechanics
  • Mechanical Engineering

Cite this

Friswell, M. I., Fernandes, R., Jamia, N., & El-Borgi, S. (2016). Identification of breathing cracked shaft models from measurements. In Rotating Machinery, Hybrid Test Methods, Vibro-Acoustics (Vol. 8, pp. 537-543). Springer New York LLC. https://doi.org/10.1007/978-3-319-30084-9_47