کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
11003631 1461461 2018 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Identification of structural dynamic characteristics based on machine vision technology
ترجمه فارسی عنوان
شناسایی ویژگی های پویایی ساختاری بر اساس تکنولوژی بینایی ماشین
کلمات کلیدی
نظارت بر سلامت سازمانی، فن آوری مبتنی بر دید، الگوریتم پردازش تصویر دیجیتال، پاسخ پویای سازه، شناسایی پارامتر مودال،
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
چکیده انگلیسی
As a convenient and effective tool for monitoring of the structural behaviors of civil infrastructure, the machine vision-based sensing technology integrated with digital image processing algorithm has achieved great progress in the field of structural health monitoring (SHM). The prominent advantages of this kind of measurement technology mainly include non-contact, long-distance and high-resolution. Up to now, various types of vision-based systems have been developed and applied in structural performance monitoring of engineering structures, however, seldom investigations are relevant to monitoring of structural dynamic characteristics. In this paper, the method for multi-point synchronous measurement of structural dynamic displacement is proposed. The structural modal parameters are identified using measured multi-point dynamic displacements and fast Fourier transform. A simple-supported rectangle steel beam model is established for conducting experiments to investigate (i) comparison study on the measurement results obtained by the vision-based system and the accelerometer, (ii) the effect of the measurement distance on the accuracy of the vision-based system, and (iii) the feasibility of different types of targets (LED lamp and black spot). The experimental results show that the proposed vision-based method is effective, accurate and stable for structural dynamic response monitoring and modal parameter identification.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Measurement - Volume 126, October 2018, Pages 405-416
نویسندگان
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