A bridge damage detection method

Abstract

The invention provides a bridge damage detection method. Through field experiments, the bridge bottom testing point flexibility response due to bridge passing by a vehicle can be obtained through test; then, the vehicle axle information is combined; a multi-section function model is introduced; a flexibility influence line (the influence line includes relevant information of the bridge damage) ofthe test point through mathematical inversion; on the basis of the test point position, the base function-non-damaged base function capable of reflecting non-damaged state is built; the damage index is built by combining the flexibility influence line and the non-damaged base function; the damage positioning can be performed through the damage index curve local peak value point. The base functioncapable of describing the damage degree is built according to the recognized damage position information, and is called as the damage base function; the bridge practical flexibility influence line andthe non-damaged base function and the damage base function are built in a combined way; through the least square fitting collation, the effective recognition on the damage degree is realized. The problem of non-damaged state information requirement of the exiting bridge damage detection method is solved. The test is simple; the test data information quantity is great; high practical significanceand values are realized.

Description

Technical field [0001] The invention relates to a bridge damage detection method; it belongs to the technical field of civil engineering application. Background technique [0002] Understanding the changes in the damage state of the structure, so that the damage accumulation can be detected before it reaches the level of threatening the safety of the structure. It is not only related to the safety of the structure, but also has important significance for deciding whether to repair the structure and when. In the field of bridge health monitoring, the most concerned is the extraction of damage features. Structural damage detection is the core issue related to its safety. [0003] Damage detection methods based on structural dynamic characteristics (based on vibration) have been widely used in the past two decades. Typical examples include damage detection based on modal parameters (frequency, mode shape, damping ratio, strain mode, etc.) and its branches. . These vibration-based no...

AI Technical Summary

Problems solved by technology

[0004] Most of the above methods need to compare with the information in the undamaged state of the structure to identify the damage, but for the existing structure, it is difficult to obtain the structural feature information in the undamaged state, and it is not feasible

For this problem, some filtering methods are used to process the existing modal data information to obtain undamaged information, but there is no substantial breakthrough in the quality of damage detection results, and accurate modal information of the actual structure needs to be obtained

[0005] Generally speaking, due to the limited impact of local damage on the overall characteristics of the structure, the damage detection effect is very sensitive to small changes in structural characteristic parameters, and test errors, recognition errors, test noise, etc. are often unavoidable, which leads to the current damage detection The following two problems generally exist in the method: 1) The characteristic parameter information in the undamaged state is required for reference comparison; 2) Most methods are only feasible in the stage of numerical simulation and model test, and the effect of applying to the actual structure is often unsatisfactory

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