Time-variant Extreme Value Prediction of Vehicle Load Effect Based on Long-term Monitoring

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Time-variant Extreme Value Prediction of Vehicle Load Effect Based on Long-term Monitoring

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[1]JIAO Meiju,HAO Jianming,CHEN Ludan,et al.Time-variant Extreme Value Prediction of Vehicle Load Effect Based on Long-term Monitoring[J].Journal of Zhengzhou University (Engineering Science),2023,44(06):105-111.[doi:10.13705/j.issn.1671-6833.2023.03.020]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 44卷 Number of periods: 2023 06 Page number: 105-111 Column: Public date: 2023-12-25

Title:: Time-variant Extreme Value Prediction of Vehicle Load Effect Based on Long-term Monitoring

Author(s):: JIAO Meiju; HAO Jianming; CHEN Ludan; ZHENG Yuanxun; School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China

Keywords:: extreme value theory; monitoring information; block over-threshold model; vehicle load; model verification

CLC:: U441+. 2U448. 22

DOI:: 10.13705/j.issn.1671-6833.2023.03.020

Abstract:: In order to establish an accurate and reasonable probability model for extreme value of vehicle load (VL) effect, based on the existing extreme value theories and models of VL effect, a novel prediction model named block over-threshold model was proposed. Firstly, the over-threshold model was established by making full use of the existing monitoring information according to POT method; and then the parameter correlation between the overthreshold model and the block maximum model was studied. A bridge was constructed for their conversion through a point process,afterward the block maximum model was derived from established GPD model. Thus the maximum distribution of VL effect in any T period was predicted. Finally, the established block over-threshold model was tested, and the probability density of VL strain in 10, 40, 70 and 100 a was extrapolated by using the model in combination with bridge design service life. The data collected by five steel longitudinal sensors in mid-span section of a cable-stayed bridge were analyzed and modeled. The results showed that the P-P diagram and Q-Q diagram in the model diagnostic plots all had very good linearity, the points described by the empirical recurrence level were within the 95% confidence interval of the recurrence level, and the empirical probability density histogram also fitted perfectly with the corresponding GP distribution. They all proved that the model could well simulate and predict the extreme value of VL effect with actual traffic flow.

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Last Update: 2023-10-22