Damage localization of closing cracks using a signal decomposition technique

Authors

  • J. Prawin CSIR STRUCTURAL ENGINEERING RESEARCH CENTRE
  • Rama Mohan Rao A CSIR STRUCTURAL ENGINEERING RESEARCH CENTRE

DOI:

https://doi.org/10.3221/IGF-ESIS.48.49

Keywords:

Pairwise eigenvalues, Singular spectrum analysis, Closing crack, Damage localization, Nonlinearity, Bilinear

Abstract

Fatigue cracks are a common occurrence in engineering structures subjected to dynamic loading and need to identify at its earliest stage before it leads to catastrophic failure. The presence of fatigue-breathing crack or closing cracks is usually characterised by the presence of sub, super-harmonics, and inter-modulation in the response of the structure subjected to harmonic excitation. It should be mentioned here that the amplitude of nonlinear harmonics are of very less order in magnitude when compared to linear or excitation component. Further, these nonlinear components often get buried in noise as both are having matched (low) energy levels. The present work attempts to decompose the acceleration time history response using singular spectrum analysis and propose a strategy to extract the nonlinear components from the residual noisy time history component. A new damage index based on these extracted nonlinear features is also proposed for closing crack localization. The effectiveness of the proposed closing crack localization approach is illustrated using detailed numerical studies and validated with lab level experimentation on the simple beam-like structure. It can be concluded from the investigations that the proposed signal decomposition based damage localization technique can detect and locate more than one crack present in the structure.

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Published

05-03-2019

Issue

Section

SI: Showcasing Structural Integrity Research in India

Categories

How to Cite

Damage localization of closing cracks using a signal decomposition technique. (2019). Frattura Ed Integrità Strutturale, 13(48), 513-522. https://doi.org/10.3221/IGF-ESIS.48.49