Bridge moving load identification based on improved fractional Tikhonov regularization

Home > Archive>Volume 46, Issue 15, 2023 >59-66

Bridge moving load identification based on improved fractional Tikhonov regularization
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                        Li MingqiangLi Mingqiang
1.Hubei Key Laboratory of Hydropower Machinery Design and Maintenance, China Three Gorges University，Yichang 443002, China； 2.School of Mechanical and Power Engineering, China Three Gorges University，Yichang 443002, China
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Wang LinjunWang Linjun
1.Hubei Key Laboratory of Hydropower Machinery Design and Maintenance, China Three Gorges University，Yichang 443002, China； 2.School of Mechanical and Power Engineering, China Three Gorges University，Yichang 443002, China
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Luo ChengshengLuo Chengsheng
1.Hubei Key Laboratory of Hydropower Machinery Design and Maintenance, China Three Gorges University，Yichang 443002, China； 2.School of Mechanical and Power Engineering, China Three Gorges University，Yichang 443002, China
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Chen BaojiaChen Baojia
1.Hubei Key Laboratory of Hydropower Machinery Design and Maintenance, China Three Gorges University，Yichang 443002, China； 2.School of Mechanical and Power Engineering, China Three Gorges University，Yichang 443002, China
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Affiliation:1.Hubei Key Laboratory of Hydropower Machinery Design and Maintenance, China Three Gorges University，Yichang 443002, China; 2.School of Mechanical and Power Engineering, China Three Gorges University，Yichang 443002, China
Clc Number:UU411+.2
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Abstract:

Aiming at the problem of poor identification accuracy of bridge moving load by integer Tikhonov regularization method (Tik), a bridge moving load identification method based on improved fractional Tikhonov regularization method (IFTik) is proposed. According to the theory of time domain method, the bridge moving load identification model is established to simulate the driving process of two axle vehicles on the bridge. The moving load is expressed as the differential form of moment response and acceleration response kernel function by kernel function method. The differential equation is transformed into linear equations by discretization method, which is solved by improved fractional Tikhonov regularization method. The results show that compared with FTik and Tik methods, IFTik method has certain advantages in recognition accuracy and noise resistance, and IFTik method has higher recognition accuracy at low noise level, and the recognition error is only 15% of FTik method; The identification result is less affected by the moment response, and has good robustness, which is more suitable for the field identification of bridge moving load.

Key words:bridge;moving load;load identification;identification accuracy;improved fractional Tikhonov regularization

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Online: January 08,2024
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