Bridge damage rapid identification method based on macro strain energy under random traffic flow

Abstract

The invention discloses a bridge damage rapid identification method based on macro strain energy under random traffic flow. The method comprises the following steps: continuously installing n macro strain sensors below a bridge along a bridge span direction; collecting a macro strain response of the bridge when a section of random traffic flow passes; integrating the macro strain response acquiredby each sensor in a time domain to obtain a macro strain energy vector; regularizing the macro strain energy vector by using the infinite norm of the macro strain energy vector to obtain a regularized macro strain energy vector; and comparing the identified regularized macro strain energy vector RMEV with a standard value to obtain the bridge damage position and degree. The structural damage position and degree can be effectively, accurately and rapidly judged under the random traffic flow working condition, and traffic interruption or traffic condition limitation is not needed.

Description

technical field [0001] The invention relates to the technical field of bridge damage identification, in particular to a bridge damage rapid identification method based on macro-strain energy under random traffic flow. Background technique [0002] Because the long-term reciprocating upper vehicle load will cause the gradual decline of bridge performance, in order to avoid potential accidents and ensure the safety of the upper passers-by and vehicles, it is necessary to carry out real-time detection of the bridge. However, the current commonly used method is to complete the load test. However, in practice, it is found that the load test is inefficient, takes a long time, and needs to interrupt traffic, which will seriously affect normal vehicle traffic. Therefore, a rapid damage identification algorithm for bridges based on health monitoring is particularly necessary. At present, many scholars have developed many damage identification algorithms, but a large part of them are...

AI Technical Summary

Problems solved by technology

At present, many scholars have developed many damage identification algorithms, but a large part of them are limited in working conditions, and have strict restrictions on the traffic flow conditions on the upper part of the bridge, and can only be applied to simple working conditions similar to the sports car test in the load test , but cannot directly work under random traffic conditions, so the application scenarios are limited

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