شناسایی خسارت با هزینه کم پل‌های کابلی با استفاده از پردازش سیگنال و فراگیری ماشین

نوع مقاله : مقاله پژوهشی

نویسنده

استادیار، گروه عمران، واحد رودهن، دانشگاه آزاد اسلامی، رودهن، ایران،

چکیده

امروزه با کمک روش های پایش سالمت سازه ها می توان وقوع خسارت را در همان مراحل اولیه شناسایی کرد و از وقوع خسارت های مالی و جانی جلوگیری کرد. با این حال، یکی از موانع بر سر راه متداول شدن این روش ها در کشور گران قیمت بودن سیستم های پایش سالمت است. هدف از این پژوهش، ارائه یک روش شناسایی خسارت با هزینه کم برای پل ها با استفاده از تکنیک های پردازش سیگنال و فراگیری ماشین است. جهت کاهش هزینه ها تعداد سنسورها جهت پایش ارتعاش سازه به یک سنسور کاهش یافته است. از آنجا که کاهش تعداد سنسورها ممکن است از دقت پایش سالمت سازه ها بکاهد، از بروزترین روش های پردازش سیگنال استفاده شده است. در مرحله اول چند روش پردازش سیگنال دامنه زمان-فرکانس با یکدیگر مقایسه شده اند و روش تبدیل موجک تجربی به عنوان بهترین روش از میان آن ها انتخاب شده است. در مرحله بعد پس از تجزیه سیگنال ها، یک شاخص خسارت جدید بر مبنای تبدیل موجک متقاطع معرفی شده و سپس با استفاده از ماشین بردار پشتیبان شاخص های خسارت طبقه بندی شده اند تا قابلیت تفکیک حالت سالم و خسارت فراهم شود. نتایج نشان می دهد روش فوق با دقت باال می تواند خسارت را در سازه شناسایی کند.

کلیدواژه‌ها

عنوان مقاله [English]

Low-Cost Damage Detection of Cable-Stayed Bridges Using Signal Processing and Machine Learning

نویسنده [English]

  • Ehsan Darvishan
Assistant Professor, Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran
چکیده [English]

Today, it is possible to detect damage in the early stages with the aim of structural health monitoring (SHM) techniques and prevent financial losses and loss of lives. However, high prices of SHM systems has caused that such systems do not gain popularity in our country. The aim of this study is providing a low-cost damage detection technique for bridges based on signal processing and machine learning. In order to reduce expenses, the number of sensors to monitor the vibration of the structure was decreased. Since sensor number reduction can lead to a drop in damage detection accuracy, most up to date signal processing methods were used. In the first step of the paper, several time-frequency signal processing techniques were compared and EWT was selected as the best method. In the next step, after decomposition of signals by time-frequency techniques, a new damage index was introduced base on cross wavelet transform (CWT) and then calculated damaged indices were classified using support vector machine (SVM) to be able to distinguish healthy and damage states. Results showed that the proposed method can detect damage with high accuracy.

کلیدواژه‌ها [English]

  • Damage detection
  • Structural health monitoring
  • Signal processing
  • Cross wavelet
  • Support vector machine

مراجع

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نشریه مهندسی عمران امیرکبیر
دوره 52، شماره 1
فروردین 1399
صفحه 257-274

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