Highly Sensitive Nonlinear Identification to Track Early Fatigue Signs in Flexible Structures

Ed Habtour*, Dario Di Maio, Thijs Masmeijer, Laura Cordova Gonzalez, Tiedo Tinga

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
72 Downloads (Pure)

Abstract

This study describes a physics-based and data-driven nonlinear system identification (NSI) approach for detecting early fatigue damage due to vibratory loads. The approach also allows for tracking the evolution of damage in real-time. Nonlinear parameters such as geometric stiffness, cubic damping, and phase angle shift can be estimated as a function of fatigue cycles, which are demonstrated experimentally using flexible aluminum 7075-T6 structures exposed to vibration. NSI is utilized to create and update nonlinear frequency response functions, backbone curves and phase traces to visualize and estimate the structural health. Findings show that the dynamic phase is more sensitive to the evolution of early fatigue damage than nonlinear parameters such as the geometric stiffness and cubic damping parameters. A modified Carrella-Ewins method is introduced to calculate the backbone from nonlinear signal response, which is in good agreement with the numerical and harmonic balance results. The phase tracing method is presented, which appears to detect damage after approximately 40% of fatigue life, while the geometric stiffness and cubic damping parameters are capable of detecting fatigue damage after approximately 50% of the life-cycle.

Original languageEnglish
Article number021005
Number of pages12
JournalJournal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems
Volume5
Issue number2
Early online date13 Oct 2021
DOIs
Publication statusPublished - May 2022

Keywords

  • detection
  • diagnostics
  • early fatigue
  • high-order
  • nonlinear dynamics
  • phase tracing
  • signal processing
  • system identification
  • 22/3 OA procedure

Fingerprint

Dive into the research topics of 'Highly Sensitive Nonlinear Identification to Track Early Fatigue Signs in Flexible Structures'. Together they form a unique fingerprint.

Cite this