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دسته بندی:
تشخیص الگو - Pattern recognition
سال انتشار:
2019
عنوان انگلیسی مقاله:
An algorithmic framework for reconstruction of time-delayed and incomplete binary signals from an energy-lean structural health monitoring system
ترجمه فارسی عنوان مقاله:
یک چارچوب الگوریتمیک برای بازسازی سیگنالهای باینری با تأخیر زمان و ناقص از یک سیستم نظارت بر سلامت ساختاری کم انرژی
منبع:
Sciencedirect - Elsevier - Engineering Structures, 180 (2019) 603-620: doi:10:1016/j:engstruct:2018:11:072
نویسنده:
Hadi Salehia, Saptarshi Dasb, Shantanu Chakrabarttyc, Subir Biswasb, Rigoberto Burgueñoa,d,⁎
چکیده انگلیسی:
Recent advances in energy harvesting technologies have led to the development of self-powered structural health
monitoring (SHM) techniques that are power-efficient. Energy-aware data transmission protocols, on the other
hand, have evolved due to the emergence of self-powered sensing. The pulse switching architecture is among
such protocols employing ultrasonic pulses for event reporting through the substrate material. However, the
noted protocol raises the necessity for new types of signal/data interpretation methods for SHM purposes. This is
because a system using such technology demands dealing with power budgets for sensing and communication of
binary signals that leads to unique time delay constraints. This study presents a novel computational approach to
reconstruct delayed and incomplete binary signals provided by a through-substrate ultrasonic self-powered
sensor network for SHM of plate-like structures. An algorithmic framework incorporating low-rank matrix
completion, a data fusion model, and a statistical approach is proposed for damage identification. Performance
and effectiveness of the proposed method for the case of dynamically loaded plates was evaluated using finite
element simulations and experimental vibration tests. Results demonstrate that the energy-lean damage identification
methodology employing the proposed algorithmic framework enables dependable detection of damage
using reconstructed time-delayed binary signals.
Keywords: Structural health monitoring | Matrix completion | Pattern recognition | Self-powered sensor network | Time-delayed binary signals
قیمت: رایگان
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