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In this paper a technique for detecting multiple delamination in a weakly damaged composite beam is presented. The conventional techniques have been successfully used to detect single delamination in composite beams. However, these techniques were not as successful in detecting multiple delaminations particularly with measurement noise in the data. Moreover, the effectiveness of these techniques relies on the reference data with which the information is compared to discriminate the damage. The proposed technique uses the perturbation in the strain measurements along the beam axis to localize multiple delaminations. A Bayesian data fusion technique developed previously is used here with strain measurements to localize the delaminations by suppressing the noise. The smart statistical fusion of several likelihood functions screens out the false noisy peaks from the damage indices and accurately highlights the delamination locations. The simulation results in this paper indicate that the proposed technique accurately detects both delaminations with severity as small as 4% even when the data are contaminated with noise level up to 20% of the measured time response signal. For further smaller delaminations, the proposed technique was able to detect one damage clearly with 5% noise level.
Saad Zafar, Ummul Baneen, Ayisha Nayyar. (2020) Damage detection in composite beam type structure by strain measurements, Pakistan Journal of Engineering and Applied Sciences, Volume 27, Issue 1.
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