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Crack Localization in Operating Rotors Based on Multivariate Higher Order Dynamic Mode Decomposition.

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Summary
This summary is machine-generated.

A new method uses enhanced higher-order dynamic mode decomposition (HODMD) to accurately locate cracks in rotating machinery. This technique identifies crack-induced vibrations without needing data from undamaged rotors.

Keywords:
crack localizationhigher-order dynamic mode decompositionnonlinearrotors

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Area of Science:

  • Mechanical Engineering
  • Vibration Analysis
  • Non-destructive Testing

Background:

  • Operating rotors are susceptible to cracks, which can lead to catastrophic failures.
  • Existing crack localization methods often require baseline data from intact rotors or struggle with complex operating conditions.

Purpose of the Study:

  • To propose a novel output-only crack localization method for operating rotors.
  • To enhance Higher-Order Dynamic Mode Decomposition (HODMD) for improved crack detection.
  • To develop a robust method for multi-crack localization without baseline data.

Main Methods:

  • Utilizing an enhanced Higher-Order Dynamic Mode Decomposition (HODMD) for multivariate signals.
  • Incorporating the total least square method into standard HODMD.
  • Adaptively selecting the Koopman approximation order parameter by optimizing the super-harmonic frequency vector.
  • Deriving damage indexes based on super-harmonic transmissibility and fractal dimension.

Main Results:

  • Successfully extracted nonlinear breathing crack-induced super-harmonic components from multiple vibration points.
  • Demonstrated accurate and robust multi-crack localization for running rotors using numerical simulations and experiments.
  • Showcased the method's effectiveness in the absence of baseline information from intact rotors.
  • Confirmed the elimination of interferences from steps and misalignment.

Conclusions:

  • The proposed HODMD-based method is effective for output-only crack localization in operating rotors.
  • The technique provides accurate and robust multi-crack identification even with environmental interferences.
  • This approach offers a valuable tool for the condition monitoring and health assessment of rotating machinery.