Damage localization and quantification by direct structural dynamic parameters updating method
Publish place: international conference on civil engineering, architecture and Urban Sustainable Development
Publish Year: 1392
نوع سند: مقاله کنفرانسی
زبان: English
View: 843
This Paper With 13 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICCAU01_3057
تاریخ نمایه سازی: 29 تیر 1393
Abstract:
The objective of this paper is detecting the location and extent of structural damage from measured vibration test data based on direct structural finite element model updating. The method is based upon a mathematical model representing the undamaged vibrating structure and a local description of the damage and introduces a new finite element model updating approach for damage detection. The problem of modeling errors and their influence to damage localization accuracy is discussed and an approach to obtain reliable results in this case is presented. The concept of direct updating of individual dynamic parameters is used and according to that algorithms the mathematical function for damage assessment are defined. Then, error matrix of dynamic properties of healthy and damaged structures is established to detect the damage location and severity. For validation of damage detection approaches, two numerical examples are utilized. At the all examples, consider the modal data are incomplete and inverse of rectangular matrices is accomplished by Moore–Penrose inverse matrix without using any multipliers. It will be shown that the proposed procedure is simple to implement and may be useful for structural damage identification.
Keywords:
Damage localization and quantification , Direct optimization functions , Updating of mass and stiffness , Moore-Penrose inverse method
Authors
Alireza Entezami
M.Sc. of Structural Engineering, Department of Civil Engineering, Ferdowsi University of Mashhad,
Hashem Shariatmadar
Associate Professor, Department of Civil Engineering, Ferdowsi University of Mashhad, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :