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Improved Continuous Wavelet Transform for Modal Parameter Identification of Long-Span Bridges
المؤلفون المشاركون
Li, Yongle
Zhang, Mingjin
Huang, Xu
Sun, Hao
Zhang, Jingyu
Huang, Bin
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-01-27
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Accurate and timely identification of modal parameters of long-span bridges is important for bridge health monitoring and wind tunnel tests.
Wavelet analysis is one of the most advantageous methods for identification because of its good localization characteristics in both time and frequency domain.
In recent years, the wavelet method has been applied more frequently in parameter identification of linear and nonlinear systems.
In this article, based on wavelet ridges and wavelet skeleton, the improved modal parameter identification method was studied.
To find the appropriate time-frequency resolution, an optimal wavelet basis design principle based on minimum Shannon entropy was proposed.
Aiming at endpoint effect in wavelet transform, a prediction continuation method based on support vector machine (SVM) was proposed, which can effectively suppress the endpoint effect of the extended samples.
In view of the fact that the ridges of metric matrices obtained by the traditional crazy climber algorithm cannot fully reflect the distribution of ridges of modulus value matrices of wavelet coefficients, an improved high-precision crazy climber algorithm was put forward to accurately identify the position of the ridge of wavelet coefficients.
Finally, taking a long-span cable-stayed bridge and a long-span suspension bridge as the engineering background, improved continuous wavelet transform (CWT) was applied to modal parameter identification of bridge under ambient excitation.
The modal parameters such as modal frequency, damping ratio, and mode shape were obtained.
Compared with the calculation value of the numerical simulation of long-span cable-stayed bridge and wind tunnel test of long-span suspension bridge, the reliability of CWT for modal parameter identification of long-span bridges under ambient excitation was verified.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhang, Mingjin& Huang, Xu& Li, Yongle& Sun, Hao& Zhang, Jingyu& Huang, Bin. 2020. Improved Continuous Wavelet Transform for Modal Parameter Identification of Long-Span Bridges. Shock and Vibration،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1209926
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhang, Mingjin…[et al.]. Improved Continuous Wavelet Transform for Modal Parameter Identification of Long-Span Bridges. Shock and Vibration No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1209926
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhang, Mingjin& Huang, Xu& Li, Yongle& Sun, Hao& Zhang, Jingyu& Huang, Bin. Improved Continuous Wavelet Transform for Modal Parameter Identification of Long-Span Bridges. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1209926
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1209926
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