Total stress computing method and safety pre-warning method of large-span steel box girder bridge based on monitored data and temperature stress analysis

Abstract

The invention discloses a total stress computing method and safety pre-warning method of a large-span steel box girder bridge based on monitored data and temperature stress analysis. The total stress computing method comprises a step 1 of acquiring the strain and the temperature of the bridge by using a health monitoring system; a step 2 of separating temperature strain from the actually measured strain; a step 3of computing the uniform temperature and gradient temperature on the upper cross section of the steel box girder; a step 4 of computing axial restraint stress; a step 5 of computing bending restraint stress; a step 6 of computing temperature self-stress; a step 7 of acquiring geostatic stress from a finite element model; and a step 8 of computing the total stress of the large-span bridge in operation. Compared with a conventional early warning method, the early warning method is clear in early warning index and clear in mechanical model, takes account of the influence of temperature load on the large-span bridge structure, and is applicable to popularization in engineering field.

Description

technical field [0001] The invention relates to the field of monitoring data early warning of long-span bridges in civil engineering and traffic engineering. Background technique [0002] The safety early warning of bridge structures is a complex research topic, which not only involves professional knowledge in the field of bridges, but also involves many disciplines such as system science, management science, and decision science. In order to have a more in-depth and comprehensive understanding of the early warning problems of bridge structures. In recent years, early warning methods based on vibration modal analysis and parameter identification have been widely studied, but due to the complex characteristics of bridge structures, there are still many problems in applying these technologies to large bridge structures. With the advancement of social informatization and the increasingly widespread application of computer and network technologies, especially the installation ...

AI Technical Summary

Problems solved by technology

[0005] These early warning methods have the following disadvantages: 1. Traditional early warning parameters (such as structural frequency, etc.) are easily affected by the environment, especially temperature changes; 2. Traditional early warning parameters are often macro indicators (such as structural deflection), macro indicators It only reflects the overall condition of the structure. In fact, the damage of structural areas or components is the direct cause of structural damage or even collapse. These macro indicators cannot reflect the local characteristics of the structure; 3. The theory of traditional early warning methods is complex and difficult to promote in the engineering field

Compared with early warning based on structural stress, its physical concept and mechanical model are clearer, and it is suitable for engineering personnel to operate. However, there are still some problems in this method for early warning of long-span bridges as mentioned above.

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