A New Nonlinear Damage Indicator Based on Spectral Correlation for Identification of Multiple Breathing Cracks in Beam-Like Structures

PurposeIdentification of fatigue-breathing cracks at an early stage offers critical information about the health of structures, aiding in the prevention of catastrophic failure and saving human lives. Localization of multiple breathing cracks is a highly challenging inverse problem, as all these breathing cracks (more than two) might be in a similar state (either opening or closing state) at any particular time instant or in contrasting states (while some breathing cracks are opening, others in closing state) during vibration. This paper presents a spectral correlation approach for the localization of multiple breathing cracks on beams exploiting the modulation effect on the vibration data with bitone harmonic excitation.Contribution and MethodA new nonlinear damage indicator based on cyclic spectral energy is developed for breathing crack identification in beams. Effects of the varied spatial location of multiple breathing cracks, different crack depths, measurement noise, and limited sensors are studied numerically. The superiority and the uniqueness of the proposed spectral correlation approach are verified by comparing it to other popular breathing crack diagnosis algorithms, including singular spectrum analysis (SSA) and weighting function augmented curvature approach.Results and ConclusionThe results of both numerical and experimental investigations in this paper reveal that the proposed spectral correlation algorithm can effectively localize the multiple breathing cracks with different severities present at various spatial positions in the beam. Studies also indicate that the proposed cyclic spectral energy-based nonlinear damage indicator can effectively localize closely spaced or sparsely spaced (i.e., spatially far apart) cracks in the beam.

Automated summary

This paper presents a spectral correlation approach for the localization of multiple breathing cracks on beams using vibration data. Numerical and experimental results show that the proposed method can effectively localize multiple breathing cracks with different severities at various spatial positions in the beam.