On the Use of Acoustic Emission and Digital Image Correlation for Welded Joints Damage Characterization

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
A series of tests have been conducted to investigate fatigue damage characterization in corroded welded steel plates using structural health monitoring (SHM) techniques. Acoustic Emission (AE) is a non-destructive testing (NDT) technique with potential applications for locating and monitoring fatigue cracks in service. In the present work, AE is implemented to characterize damage during crack evolution. It is considered to be based on the relationship between RA value (the rise time divided by the amplitude) and the average frequency of the recorded data. Results are confirmed by visual observation of the crack geometry at the end of the test and by Digital image correlation (DIC) measurements. It is seen that the obtained results allow a better understanding of such damage mechanisms, and enabling an early warning against final failure. Thus, ensuring the safety and integrity of the structures is feasible.
Language:
English
Published:
Journal of Applied and Computational Mechanics, Volume:5 Issue: 2, Spring 2019
Pages:
381 to 389
magiran.com/p1954391  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!