شبیه‌سازی شتاب‌نگاشت مصنوعی زلزله سازگار با طیف ساختگاه با استفاده از تحلیل سری‌های زمانی

نوع مقاله: علمی - پژوهشی

نویسندگان

1 دانشجوی دکتری مهندسی کامپیوتر، دانشکده مهندسی کامپیوتر و فناوری اطلاعات، دانشگاه صنعتی شاهرود، شاهرود، ایران

2 دانشیار، دانشکده مهندسی برق، دانشگاه صنعتی شاهرود، شاهرود، ایران

3 استاد، دانشکده مهندسی کامپیوتر و فناوری اطلاعات، دانشگاه صنعتی شاهرود، شاهرود، ایران

4 استادیار، دانشکده مهندسی عمران، دانشگاه صنعتی شاهرود، شاهرود، ایران

چکیده

در طراحی سازه‌های مهم و حیاتی مانند سدها، نیروگاه‌ها و پل‌ها، لزوم انجام تحلیل تاریخچه زمانی لرزه‌ای یکی از مهم‌ترین نیازهای مهندسی می‌باشد. با توجه به اینکه شتاب‌نگاشت­های واقعی مربوط به ساختگاه این سازه‌ها در بسیاری از موارد وجود ندارد و یا به تعداد کافی در دسترس نیست، لذا تولید شتاب‌نگاشت مصنوعی یکی از موضوعات مهم پژوهشی و کاربردی در این زمینه می‌باشد. این مقاله به ارائه روشی نوین برای تولید شتابنگاشت‌های مصنوعی منطبق با طیف ساختگاه سازه با استفاده از تحلیل سری‌های زمانی، شبکه­های عصبی مصنوعی، تبدیل موجک و الگوریتم ژنتیک می‌پردازد. در روش پیشنهادی ابتدا تعدادی شتاب‌نگاشت ثبت شده در ایستگاه‌های شتاب‌نگاری و بر اساس نوع خاک انتخاب می‌شوند. این خاک‌ها با توجه به سرعت موج برشی ایستگاه‌های ثبت کننده به دو گروه خاک و سنگ تقسیم می‌شوند و سپس با استفاده از تبدیل موجک به تحلیل  و پردازش  آنها پرداخته می‌شود. در قدم بعدی از توانایی یادگیری شبکه­های عصبی برای نگاشت معکوس از طیف پاسخ این شتابنگاشت‌ها به ضرایب تبدیل ویولتی استفاده می‌گردد.  به موازات استفاده از الگوریتم­های آموزشی موجود برای شبکه­های عصبی، از توانایی الگوریتم ژنتیک برای جستجو در یک فضای گسترده کمک گرفته می‌شود تا ماتریس‌های وزن و بایاس شبکه­ها بهینه گردند و از محبوس شدن شبکه­ها در نقاط بهینه محلی جلوگیری به عمل آید. در نهایت شتابنگاشت‌های سازگار با طیف ساختگاه تولید می‌شود. در این مقاله با ارائه مثال‌هایی از شتابنگاشت­های ثبت شده در ایران، به آزمایش الگوریتم پیشنهادی پرداخته شده و کارایی موثر آن نشان داده می­شود. استفاده ترکیبی از شبکه عصبی مصنوعی، تبدیل موجک، الگوریتم ژنتیک و تحلیل سری‌های زمانی موجب ارتقاء توانایی روش از نظر سرعت و دقت در تولید شتاب‌نگاشت مصنوعی سازگار با طیف برای شرایط ساختگاهی مختلف می‌شود

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Simulation of artificial earthquake records compatible with site specific response spectra using time series analysis

نویسندگان [English]

  • Mohammad Reza Fadavi Amiri 1
  • Sayed Ali Soleymani Eyvari 2
  • Hamid Hasanpoor 3
  • Mohammad Shamekhi Amiri 4
1 PhD Student of Computer Engineering, School of Computer and Information Technology, Shahrood University of Technology, Shahrood, Iran
2 Associate Professor,School of Electrical Engineering, Shahrood University of Technology, Shahrood, Iran
3 Professor, School of Computer & Information Technology, Shahrood University of Technology, Shahrood, Iran
4 Assistant Professor, School of Civil Engineering, Shahrood University of Technology, Shahrood, Iran
چکیده [English]

Time history analysis of infrastructures like dams, bridges and nuclear power plants is one of the fundamental parts of their design process. But there are not sufficient and suitable site specific earthquake records to do such time history analysis; therefore, generation of artificial accelerograms is required for conducting research works in this area.  Using time series analysis, wavelet transforms, artificial neural networks and genetic algorithm, a new method is introduced to produce artificial accelerograms compatible with response spectra for the specified site condition. In the proposed method, first, some recorded accelerograms are selected based on the soil condition at the recording station. The soils in these stations are divided into two groups of soil and rock according to their measured shear wave velocity. These accelerograms are then analyzed using wavelet transform. Next, artificial neural networks ability to produce reverse signal from response spectra is used to produce wavelet coefficients. Furthermore, a genetic algorithm is employed to optimize the network weight and bias matrices by searching in a wide range of values and prevent neural network convergence on local optima. At the end site specific accelerograms are produced. In this paper a number of recorded accelerograms in Iran are employed to test the neural network performances and to demonstrate the effectiveness of the method. It is shown that using synthetic time series analysis, genetic algorithm, neural network and wavelet transform will increase the capabilities of the algorithm and improve its speed and accuracy in generating accelerograms compatible with site specific response spectra for different site conditions.

کلیدواژه‌ها [English]

  • Spectrum Compatible Records
  • time series analysis
  • Genetic algorithm
  • Artificial Neural Network
  • wavelet transform

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