Damage Identification for Large Span Structure Based on Multiscale Inputs to Artificial Neural Networks

المؤلفون المشاركون

Lu, Wei
Teng, Jun
Cui, Yan

المصدر

The Scientific World Journal

العدد

المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-12، 12ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2014-05-25

دولة النشر

مصر

عدد الصفحات

12

التخصصات الرئيسية

الطب البشري
تكنولوجيا المعلومات وعلم الحاسوب

الملخص EN

In structural health monitoring system, little research on the damage identification from different types of sensors applied to large span structure has been done in the field.

In fact, it is significant to estimate the whole structural safety if the multitype sensors or multiscale measurements are used in application of structural health monitoring and the damage identification for large span structure.

A methodology to combine the local and global measurements in noisy environments based on artificial neural network is proposed in this paper.

For a real large span structure, the capacity of the methodology is validated, including the decision on damage placement, the discussions on the number of the sensors, and the optimal parameters for artificial neural networks.

Furthermore, the noisy environments in different levels are simulated to demonstrate the robustness and effectiveness of the proposed approach.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Lu, Wei& Teng, Jun& Cui, Yan. 2014. Damage Identification for Large Span Structure Based on Multiscale Inputs to Artificial Neural Networks. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1050050

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Lu, Wei…[et al.]. Damage Identification for Large Span Structure Based on Multiscale Inputs to Artificial Neural Networks. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1050050

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Lu, Wei& Teng, Jun& Cui, Yan. Damage Identification for Large Span Structure Based on Multiscale Inputs to Artificial Neural Networks. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1050050

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1050050