تشخیص و تخمین خسارات ریز و کوچک در تیرهای فولادی با استفاده از روش های المان محدود طیفی، شاخص انرژی کرنشی مودال و رگرسیون بردار پشتیبان

وحیدی, محمد; عظیمی نژاد, آرمین; فیروزی نظام آبادی, مریم; هریسچیان, محمود

doi:10.22065/jsce.2022.346306.2842

تشخیص و تخمین خسارات ریز و کوچک در تیرهای فولادی با استفاده از روش های المان محدود طیفی، شاخص انرژی کرنشی مودال و رگرسیون بردار پشتیبان

نوع مقاله : علمی - پژوهشی

نویسندگان

¹ دانشجوی دکتری ، گروه مهندسی عمران، دانشکده فنی و مهندسی ،واحد تهران جنوب، دانشگاه آزاد اسالمی، تهران، ایران

² استادیار گروه مهندسی عمران، دانشکده عمران معماری و هنر، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران

³ استادیار، گروه مهندسی عمران،دانشکده فنی و مهندسی، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران

⁴ دانشیار، گروه مهندسی عمران،دانشکده فنی و مهندسی، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران ، ایران

10.22065/jsce.2022.346306.2842

چکیده

سازه هایی نظیر پلها در طول عمر بهره برداری خود در معرض انواع خسارات ریز و کوچک قرار می گیرند. با توجه به اهمیت و نقش این دسته از سازه ها در حوزه حمل و نقل ، تشخیص به موقع خسارت در آنها از جایگاه ویژه ای برخوردار است. از این رو در این تحقیق یک روش نوین و کارآمد برای تشخیص و تخمین خسارات ریز و کوچک در پل ها ارائه گردیده است. روش ارائه شده بر مبنای ترکیب المان محدود طیفی و شاخص انرژی کرنشی مودال برای تشخیص موقعیت خسارت بوده و از تکنیک رگرسیون بردار پشتیبان جهت تخمین میزان شدت خسارت استفاده شده است. برای مدلسازی المان هشت گره ای جدید که دارای ویژگی های المان محدود طیفی می باشد در نرم افزارOpenSees تعریف گردید. سپس جهت مدلسازی خسارات ریز و کوچک به ترتیب از یک تیر یک دهانه و یک تیر دو دهانه فولادی با تکیه گاه های ارتجاعی استفاده شده است. جهت تشخیص خسارات در گام اول پس از تحلیل مودال سازه ها به محاسبه شاخص انرژی کرنشی مودال پرداخته تا موقعیت خسارات در سازه تشخیص داده شود. در گام دوم با استفاده از شاخص های انرژی کرنشی مودال محاسبه شده در گام قبل به آموزش شبکه های رگرسیون بردار پشتیبان برای تخمین میزان شدت خسارات پرداخته می شود. نتایج کاربرد روش دو مرحله ای ارائه شده نشان دهنده دقت مناسب و عملکرد مطلوب آن می باشد

کلیدواژه‌ها

موضوعات

روش های عددی در مهندسی سازه

عنوان مقاله [English]

Detection of the micro and small scale damages in steel beams using spectral finite element methods, modal strain energy-based damage index, and support vector regression

نویسندگان [English]

Mohammad Vahidi ¹
Armin Aziminejad ²
Maryam Firoozi Nezamabadi ³
Mahmoud Heristchian ⁴

¹ PhD candidate, Department of Civil Engineering,,Faculty of Engineering,, South Tehran Branch, Islamic Azad University, Tehran, Iran

² Assistant professor, Department of Civil Engineering, ,Faculty of civil engineering, architecture and art, Science and Research Branch, Islamic Azad University, Tehran, Iran

³ Assistant professor, Department of civil engineering and research center for modeling and optimization in science and engineering, , Faculty of engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.

⁴ Associate professor, Department of Civil Engineering, Faculty of engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

چکیده [English]

Bridges are exposed to various micro and small damages during their service life. Due to the importance and role of these structures in transportation on roads, timely detection of damages in them has a special place. This research presents an innovative and efficient method for diagnosing and estimating micro and small damages to bridges. The proposed method is based on the combination of spectral finite element and modal strain energy-based damage index to determine the location of damages in the first step. Then the support vector regression technique is used to estimate the severity of damages in the second step. A new eight-node element with spectral finite element characteristics is defined in OpenSees software. Then, micro and small damages are modeled in a single-span beam and a double-span steel beam with spring supports. In the first step, after modal analysis of the structures, the modal strain energy-based damage index is calculated to determine the location of the damages. In the second step, using the modal strain energy-based damage indices calculated in the previous step, the support vector regression networks are trained to estimate the severity of the damages. The results show very high accuracy and optimal performance of the proposed method.

کلیدواژه‌ها [English]

Damage detection
Spectral finite element
Modal strain energy index
Steel beam
Support vector regression

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