Early warning method for bridge structure strain response exception

Abstract

The invention discloses an early warning method for a bridge structure strain response exception. The method comprises the following steps that: utilizing a wavelet packet decomposition method to separate a bridge structure strain response; (2) utilizing a principal component analysis method to extract the principal component of a bridge ambient temperature field; (3) on the basis of an adaptive neural network fuzzy inference system, establishing a complex nonlinear relationship between an actual measurement load factor and corresponding strain data; (4) identifying the position information ofa vehicle on a bridge; (5) identifying the geometric parameter and the axle load of the vehicle; (6) on the basis of the adaptive neural network fuzzy inference system, establishing a complex nonlinear relationship between an actual measurement vehicle load parameter and corresponding strain data; (7) solving a bridge structure strain response theoretical value; and (8) comparing a theoretical solving result of the bridge structure strain response and the actual measurement result of the theoretical solving result, and updating the adaptive neural network fuzzy inference system. By use of themethod, effectively according to the actual measurement load parameter, the bridge structure strain response can be accurately predicted.

Description

Technical field: [0001] The present invention relates to a bridge structure strain response abnormal early warning method, in particular to a bridge structure strain response abnormal early warning method using an adaptive neural network fuzzy reasoning system, which is applicable to various civil engineering structures such as bridges and building structures under complex load excitation Under the strain response abnormal warning. Background technique: [0002] The number of bridges in my country is large and widely distributed. According to the "2017 Statistical Bulletin on the Development of Highway and Waterway Transportation Industry", there are 832,500 highway bridges nationwide, including 4,646 large bridges, 91,777 large bridges, and 736,100 small and medium bridges. With the rapid development of the economy and the construction of the national transportation network, the traffic volume has increased significantly, the traffic density and vehicle load have continued ...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a bridge structure strain response abnormal early warning method, which solves the problem that the working environment of the bridge structure is complex and changeable, and it is difficult to establish a clear relationship between the measured load parameters and the structural response

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