Method and system for identifying damage of bridge structure

Abstract

The invention discloses a method and system for identifying damage of a bridge structure. The method comprises the steps of arranging sensors on a target bridge, collecting pulse signals, collecting pulse signals of the target bridge structure under natural excitement with the sensors, obtaining high-precision impulse signals, acquiring incomplete modal parameters, conducting modal identification on the high-precision pulse signals through an improved NExT-ERA method, acquiring high-precision incomplete modal parameters, identifying the damage and establishing change rate indexes and indexes of incomplete modal strain energy, wherein the change rate indexes of the incomplete modal strain energy are used for representing damage positions, and the indexes of the incomplete modal strain energy are used for representing damage degrees. With the method for identifying the damage of the bridge structure, the damage positions and damage degrees of the target bridge structure can be obtained accurately, therefore, sudden disasters are prevented effectively, defect development is controlled timely, losses are cut, casualties are avoided, and the safety of the structure and users is guaranteed.

Description

technical field [0001] The invention relates to the technical field of bridge structure damage identification, in particular to a bridge structure damage identification method and system for pulse response on limited measuring points. Background technique [0002] In recent years, frequent bridge collapse accidents have caused serious economic losses and social adverse effects, and the safety of bridge structures has attracted widespread attention. Among many infrastructures, bridge structures play an extremely important role in the national economy. Especially large bridges have high engineering cost and large traffic flow, and they are also important transportation hubs for maintaining economic operation between regions and cities. The design life of long-span bridges is as long as decades or hundreds of years. The coupling effect of unfavorable factors such as long-term environmental corrosion, material aging, long-term effects of load, fatigue and mutation effects will ...

AI Technical Summary

Problems solved by technology

[0004] First, due to the impact on traffic, the artificial static and dynamic loading tests of large bridges are more difficult, and it is impossible to monitor in real time. Therefore, natural excitation measurement methods are often used at present

However, natural excitation has many disadvantages; such as weak excitation, small response, and low signal-to-noise ratio; such as narrow bandwidth, some modes cannot be excited; or only the output can be measured, but the input cannot be measured; and only the modal frequency, vibration model and damping ratio, parameters such as modal stiffness and mass cannot be obtained

These shortcomings will lead to low precision and large errors in the modal parameters obtained during damage identification of bridge structures, resulting in inaccurate final damage identification results.

[0005] Second, the response of bridge structures to damage is generally relatively small, and it can be said that the sensitivity of the structural response is low

In many cases, the damage may only be a local phenomenon. At this time, the local damage may not have a significant impact on the overall stiffness of the structure, but may be weaker related to the bearing capacity, so the modal parameters obtained on this basis are also low in accuracy. big error

In addition, for stiffened beams with complex shapes, different damages lead to different changes in different elements of the stiffness matrix, which will also lead to excessive errors in the obtained modal parameters

[0006] Third, due to operability and economical reasons, the number of sensors installed on a long-span bridge is limited. In order to obtain as much structural damage information as possible through a limited number of sensors, the optimal arrangement of a limited number of sensors can However, the current damage identification method has not been able to optimize the arrangement of sensors

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