کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
567166 1452124 2016 18 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An improved hybrid optimization algorithm for vibration based-damage detection
ترجمه فارسی عنوان
یک الگوریتم بهینه سازی ترکیبی بهبود یافته برای تشخیص آسیب بر اساس ارتعاش
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزار
چکیده انگلیسی


• A modification of the P-NMA algorithm is proposed for damage detection.
• IP-NMA speeds up the convergence of the damage detection problem.
• IP-NMA is more accurate than its original version and the harmony search algorithm.
• The results encourage its application for optimization based damage identification.

In this paper, an improvement in the hybrid stochastic/deterministic Pincus-Nelder-Mead optimization algorithm (P-NMA) which enables to solve the target optimization problem of vibration-based damage detection is proposed. The proposed modification consists in reducing the sampling domain of the Pincus formula by assigning a maximum number of damaged elements, i.e., by allowing only a few elements of the sampling vector to be different from 1. Consequently, a new parameter which determines the maximum number of damaged elements (npmax) is introduced and must be choose by the designer. Such a modification attempts to speed up the convergence of the original version of the P-NMA and thus, reducing its computational cost. A series of numerical examples, all selected from literature, was performed. To test the accuracy and efficiency of the proposed improved optimization algorithm (IP-NMA), its results were compared to those obtained by the P-NMA and the metaheuristic harmony search algorithm (HS). A statistical analysis was also performed in order to test the robustness of the three algorithms. The proposed improved optimization algorithm showed better performance (more accurate and required lower computational cost than the original version of the P-NMA and the metaheuristic HS), emphasizing its capacity in damage diagnosis and assessment.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Engineering Software - Volume 93, March 2016, Pages 47–64
نویسندگان
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