Abstract
This paper presents a damage detection technique which uses change in Frequency Response Function (FRF) and Modal Strain Energy (MSE) for damage detection in beam and truss like structures. It’s a robust approach for Structural Health Monitoring (SHM) using natural frequency for structural damage assessment. This technique couples FRF with Iterative Modal Strain Energy (IMSE) method to accurately localize and quantify the damage with only few frequencies, overcoming the limitation of mode shape based damage detection methods which requires mode shapes at full coordinates but damage is either over/underestimated. In the current approach, a damage detection algorithm is developed and validated by conducting numerical studies for a Fixed-Fixed beam, both noise-free and noise-effected cases are simulated. The numerical studies reveal that proposed algorithm is capable of identifying, localizing and quantifying the damage accurately at reduce computational cost.
Highlights
Structural Health Monitoring (SHM) finds its application in mechanical, civil and aerospace Engineering
Many structural damage detection techniques are proposed in the recent decades which use the measured mode shapes and natural frequencies in the damaged structure to localize and estimate the damage
For beam structure single and multiple damage cases Frequency Response Function (FRF) indicate the presence of damage in all three damage cases
Summary
SHM finds its application in mechanical, civil and aerospace Engineering. Damage in any structure is result of deterioration, degradation or any natural disaster in a structure during its service life. DI & MSEC methods require paired modes of intact and damaged structures, as correct modal identification is practically difficult in some cases. Considering this limitation, Cross Modal Strain Energy (CMSE) method is developed by hu et al to quantify the damage accurately [10]. Pan and Zhang et al Formulated a Noise Response Rate (NRR) in an inverse problem to select the specific mode shape for damage detection based on mode shape sensitivity to noise This method improves the accuracy for prediction of size and location of damage [14].
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