کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6702571 1428505 2018 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Damage identification for plate-like structures using ultrasonic guided wave based on improved MUSIC method
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
Damage identification for plate-like structures using ultrasonic guided wave based on improved MUSIC method
چکیده انگلیسی
The ultrasonic guided wave has emerged as one of the most prominent and promising tools for metal and composite structures in the fields of structural health monitoring (SHM) and nondestructive testing (NDT). This paper presents a novel model-based 2D multiple signal classification (MUSIC) damage identification algorithm for plate-like structures. Unlike the conventional MUSIC algorithm, the proposed model-based 2D MUSIC damage identification algorithm is deduced based on the assumption of near-field according to the propagation model of guided waves. Since scattered signals contain the location information of damage, the cross-correlation function of residual signals received by experiment and scattered signals received by damage scattering model are developed for spatial spectrum estimation MUSIC algorithm. Due to the uncorrelation of signal and noise, the damage can be successfully identified by searching the peak point of spatial spectrum in the monitored area employing the orthogonality of signal subspace and noise subspace. The accuracy and effectiveness of the proposed method are firstly validated by numerical simulation on aluminum plate, and the general applicability is further verified by experiments for the damage identification of laminated composite plate. The numerical and experimental results demonstrate the proposed damage identification algorithm is appropriate for damage identification of plate-like structures with high estimation accuracy and resolution.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Composite Structures - Volume 203, 1 November 2018, Pages 164-171
نویسندگان
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