Bridge damage identification method based on multiple cross validation

A cross-validation, damage identification technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of limited confidence in identification results, external environment interference, and difficulty in finding damage, and achieve low-cost and large-scale Application, accident avoidance, high precision effect

Active Publication Date: 2019-05-14
SOUTHEAST UNIV
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Problems solved by technology

In practical engineering applications, it is found that these methods are not sensitive to local damage of the structure, and it is difficult to detect damage
In order to solve such problems, a damage identification method based on

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  • Bridge damage identification method based on multiple cross validation
  • Bridge damage identification method based on multiple cross validation
  • Bridge damage identification method based on multiple cross validation

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Embodiment Construction

[0033] The present invention will be further described below in conjunction with accompanying drawing.

[0034] like figure 1 Shown, the present invention comprises following implementation steps:

[0035] S1: Arrange n distributed long-gauge fiber grating sensors continuously along the extension direction of the bridge under the bridge, such as figure 2 As shown in , the n long-gauge fiber grating sensors should be connected at the first place to cover the whole span of the bridge in the most ideal situation, as shown in figure 2 , Figure 4 As shown, 10 sensors are arranged continuously under the bridge. When the cost is limited, long-gauge fiber grating sensors should also be arranged in the key areas of the structure;

[0036] S2: Connect all the sensors to the demodulation equipment to collect the long-gage strain response of the bridge when the vehicle passes by. At the same time, it should be noted that the acquisition frequency of the demodulator should not be low...

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Abstract

The invention discloses a bridge damage identification method based on multiple cross validation. The method comprises the following steps that: continuously arranging n pieces of distributed long-gauge-length fiber grating sensors along a bridge extension direction below a bridge; connecting all sensors to demodulation equipment to collect the long-gauge-length strain response of the bridge whena vehicle passes; carrying out permutation and combination on all sensors, taking any three sensors as a group, and carrying out intra-class second order difference on the correspondingly obtained long-gauge-length strain; solving an area surrounded by each group of strain difference curves and a time horizontal axis; carrying out statistics on the number of the sensor related to an exceptional damage index S* out of a threshold value range; and substituting the number into a damage calculation formula to obtain a structure damage degree [Beta]. By use of the method, through the multiple crossvalidation, the exception and the randomness of an individual sensor are avoided, an obtained result has a high confidence coefficient, and meanwhile, the sensor is higher in durability and accuracy.The method is suitable for the bridges of a simply supported beam and continuous beam structure, low cost and large range application can be realized, the potential damage of the bridge is found in time, and accidents are avoided.

Description

technical field [0001] The invention relates to a bridge damage identification method, in particular to a bridge damage identification method based on multiple cross validation. Background technique [0002] Due to the long-term reciprocating upper vehicle load, the bridge performance will gradually decline. 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 maintenance of the bridge. At present, the commonly used method is to complete by manual inspection. Practice has found that manual inspection is inefficient, takes a long time, and is highly subjective. It can only find structural surface damage and cannot effectively distinguish internal damage. Therefore, the damage identification algorithm based on bridge health monitoring is particularly necessary. [0003] At present, many scholars have developed many damage identification algorithms, but a large part of them are based on structu...

Claims

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Application Information

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IPC IPC(8): G01N21/88G06F17/50
Inventor 陈适之吴刚冯德成
Owner SOUTHEAST UNIV
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