Application of Stress GM (1,1) Residual Error Model with New Equal Dimension Information on Bridge Construction Control

Tian Zhi Hao; Xiao Li Xie; Jun Xie

doi:10.4028/www.scientific.net/AMR.538-541.2153

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Research on the Sampling Frequency’s Range to Improve the Precision of All-Phase FFT Phase Measurement
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Application of Stress GM (1,1) Residual Error Model with New Equal Dimension Information on Bridge Construction Control
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Monocyclic Aromatic Compounds Detection with High Field Asymmetry Waveform Ion Mobility Spectrometry
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Hawking Radiation of Charged Particles as Tunneling from Kim Black Hole
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 538-541Application of Stress GM (1,1) Residual Error...

Application of Stress GM (1,1) Residual Error Model with New Equal Dimension Information on Bridge Construction Control

Abstract:

Stress is affected by many factors in the course of bridge construction, which is introduced in this paper. The stress changes are affected by a lot of uncertain factors that can’t use mechanical method for clear calculation, so that make prediction of stress becomes very difficult in the period of practical engineering, in order to solve this problem, the grey theory and the wide applicability in bridge construction monitoring are introduced in this paper. The stress data processing method, data generation method of the new equal dimension information are defined and researched, which combine with the introduction of GM (1,1) residual error model of grey equation solution, stress development and trend are forecasted precisely in the practical experience in the process of control, so the problem which can’t be solved by the complicated mechanics is solved by mathematical method. And set the Baise zhuzhou bridge as an example, practice has proved that stress GM (1,1) residual error model with the new equal dimension information can be applied for bridge construction monitoring with a higher prediction accuracy. Suggestion of stress forecast are proposed for bridge construction monitoring according to the actual control experience.