پیش بینی عمر مفید اعضای سکوی فراساحل با الگوریتم جنگل تصادفی

نوع مقاله : مقاله کامل پژوهشی

نویسندگان

1 گروه زلزله، دانشکده مهندسی عمران و محیط زیست، دانشگاه صنعتی امیرکبیر

2 گروه آب، دانشکده مهندسی عمران و محیط زیست، دانشگاه صنعتی امیرکبیر

چکیده

پایداری و سلامت سکوهای دریایی به دلایل مسائل زیست ­محیطی، هزینه نصب زیاد و ارزشمندی این نوع سازه ­ها در وضعیت اقتصاد کشور، حائز اهمیت می‌باشد. مهم‌ترین خرابی ­های سازه ­های دریایی از نوع خستگی و خوردگی می‌باشند، پایش و بازرسی این سازه ­ها در درازمدت برای تشخیص و شناسایی چنین خرابی­ هایی به ­همراه پیش ­بینی عمر مفید اعضای سازه برای مدیریت سکوها، امری لازم و ضروری می‌باشد. در این مقاله به بررسی روشی هوشمند برای پیش ­بینی عمر مفید اعضا در سکوهای دریایی به ­کمک روش یادگیری ماشین پرداخته می ­شود. به این منظور سکویی واقعی درمحیط خلیج ­فارس در نرم ­افزار SACS مدل ­سازی شده و با ایجاد سناریوهای مختلف خرابی در آن با استفاده ازنتایج آنالیز خستگی طیفی در نرم ­فزار SACS، به پیش ­بینی عمر مفید اعضای سازه به ­کمک الگوریتم های یادگیری ماشین پرداخته می­ شود و رویکردهای مدیریتی با توجه به آنالیزهای صورت گرفته ارائه می­ گردد. نتایج ارزیابی الگوریتم به کارگرفته شده بر روی 20 درصد از نمونه­ هایی که آموزش داده نشده بودند نشان می ­دهد که دقت این الگوریتم در تخمین عمر مفید خستگی اعضای حساس معادل 94 درصد می­ باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Predicting the Remaining Life of Offshore Structure Members with Random Forest Algorithm

نویسندگان [English]

  • Touraj Taghikhany 1
  • Mohammad Nabi Nazari Ghalati 2
1 Faculty of Civil Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
2 Faculty of Civil Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
چکیده [English]

Introduction

     Considering the importance and high cost of construction and maintenance of offshore platforms for the purpose of oil and gas extraction, and considering the fact that in case of failure, they can cause many environmental disasters, technical inspection of their structural condition is of serious importance. In addition to the high cost, this does not cover all aspects and it is very difficult to detect the failure in this case. Due to the repetitive nature of most of the environmental loads in the seas, these structures are constantly exposed to multiple and repetitive loadings. The phenomenon of fatigue is one of the effective factors in the health of these types of structures, so that during the past decades, the offshore industry has witnessed unfortunate events that often occurred due to the phenomenon of fatigue. One of the unpleasant cases can be mentioned the disaster of the Norwegian semi-submerged oil platform in the North Sea, named as the Kyland Alexandria, in which 123 people of the platform's crew lost their lives. One of the main braces connected to the base of the pontoon was completely broken and separated from the platform, causing the platform to completely overturn. The semi-submersible rig Sedo 135, which began operating in the Gulf of Mexico in 1965, suffered a fatigue failure in one of its rigs in 1967 after two years. One of the most widely used platforms in the Persian Gulf is the fixed platform of the stencil or jacket type, which is a steel structure that has braces and a deck, and foundations that are fixed on the sea floor by numerous piles. Fatigue cracks are the main failure factor in fixed jacket platforms (Ibrion et al., 2020).

کلیدواژه‌ها [English]

  • Remaining life
  • Health monitoring
  • Offshore structures
  • Random forest
  • Fatigue spectral analysis

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