Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks

المؤلفون المشاركون

Chun, Pang-jo
Yamashita, Hiroaki
Furukawa, Seiji

المصدر

Shock and Vibration

العدد

المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-11، 11ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2015-09-30

دولة النشر

مصر

عدد الصفحات

11

التخصصات الرئيسية

هندسة مدنية

الملخص EN

The deterioration of bridges as a result of ageing is a serious problem in many countries.

To prevent the failure of these deficient bridges, early damage detection which helps us to evaluate the safety of bridges is important.

Therefore, the present research proposed a method to quantify damage severity by use of multipoint acceleration measurement and artificial neural networks.

In addition to developing the method, we developed a cheap and easy-to-make measurement device which can be made by bridge owners at low cost and without the need for advance technical skills since the method is mainly intended to apply to small to midsized bridges.

In addition, the paper gives an example application of the method to a weathering steel bridge in Japan.

It can be shown from the analysis results that the method is accurate in its damage identification and mechanical behavior prediction ability.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Chun, Pang-jo& Yamashita, Hiroaki& Furukawa, Seiji. 2015. Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks. Shock and Vibration،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1078337

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Chun, Pang-jo…[et al.]. Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks. Shock and Vibration No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1078337

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Chun, Pang-jo& Yamashita, Hiroaki& Furukawa, Seiji. Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks. Shock and Vibration. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1078337

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1078337