Structural damage localization using probabilistic neural networks
نویسندگان
چکیده
منابع مشابه
Structural damage localization using probabilistic neural networks
In this paper, the structural damage localization on a simple composite plate specimen is identified using probabilistic neural networks. First, the category to be identified is defined according to the structural location, and the number of categories is reduced by grouping neighboring elements to one category. Second, the state data of damaged structure are collected by a data collection syst...
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In this paper, the damage location of a bridge is identified using probabilistic neural networks. At first, modal parameters are identified from the ambient vibration data, and are utilized as the feature vectors for probabilistic neural networks. The class to be identified is defined according to the location of damaged structural members. To deal with a lot of structural members, the number o...
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در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...
Damage Identification with Probabilistic Neural Networks
Efforts to optimize the design of mechanical systems for preestablished use environments and to extend the durations of use cycles establish a need for in-service health monitoring. Numerous studies have proposed measures of structural response for the identification of srrucrural damage, buf few have suggested systematic techniques to guide the decision es to whether or not damage has occurred...
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A computationally method on damage detection problems in structures was conducted using neural networks. The problem that is considered in this works consists of estimating the existence, location and extent of stiffness reduction in structure which is indicated by the changes of the structural static parameters such as deflection and strain. The neural network was trained to recognize the beha...
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ژورنال
عنوان ژورنال: Mathematical and Computer Modelling
سال: 2011
ISSN: 0895-7177
DOI: 10.1016/j.mcm.2010.11.023