A rapid detection method for bridge damage

Abstract

The invention discloses a rapid damage detection method for bridges. When a moving vehicle passes through a damaged area of ​​a bridge, some local cracks in concrete that are closed under the condition of no load on the bridge will open in a short time. Variation of bridge frequency over time. The bridge state can be judged by the relative change of the response frequency of the bridge before and after the excitation of the moving vehicle, and the three-stage signal analysis of the environmental vibration before the vehicle goes on the bridge in a short period of time, the coupled vibration of the bridge after the bridge goes on, and the bridge residual vibration after the bridge goes off, can be judged by the reasonable selection of the vehicle model. The influence of factors such as vehicle, temperature and boundary conditions on the frequency required for damage detection is avoided. This method does not require reference prior data, is insensitive to the location of the measuring point, and can effectively identify damage. Has a good application prospect.

Description

technical field [0001] The invention belongs to the technical field of civil engineering applications, and in particular relates to a bridge rapid damage detection method based on structural frequency changes before and after the excitation of a moving vehicle. Background technique [0002] Rapid bridge damage detection based on bridge dynamic characteristics has been widely studied due to its non-destructiveness, economy and convenience. Related methods are usually based on damage-induced changes in structural modal parameters such as natural frequencies, mode shapes, and damping ratios. Among them, the method based on modal mode requires more measuring points, the testing process is cumbersome, and the testing accuracy is lower than the natural frequency due to incomplete testing information and testing noise. The method based on damping ratio also has problems such as low test accuracy and sensitivity to environmental factors. In contrast, the damage detection method ba...

AI Technical Summary

Problems solved by technology

Finally, it relies on a complete structural model or complete structural feature data. Most of the above methods, especially the location and quantification of damage, require accurate prior data. Damage identification based on optimization methods such as neural networks requires a large amount of prior training data. This is obviously inconvenient in practical applications

However, a small number of damage detection methods that do not require prior data are often based on the singularity of the signal or its derived characteristic indicators. For example, wavelet transform and other methods are used to extract the mutation value from the characteristic frequency curve. Such methods are extremely vulnerable to environmental noise and Effects of uneven road surfaces

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