A Bridge Random Excitation Identification Method Based on Power Spectrum Propagation

Abstract

The invention discloses a bridge random excitation identification method based on power spectrum propagation, comprising the following steps: a bridge random excitation identification method based on power spectrum propagation, including: obtaining the bridge displacement response power spectrum S in the operating environment yy ; From the bridge displacement response power spectrum S yy Extract two main sub-matrices from the method as the known response power spectrum and the unknown response power spectrum respectively, and locate the random excitation position by minimizing the prediction error; use the random excitation position to reconstruct the virtual excitation; use the virtual excitation to calculate the random excitation power spectrum S ff . The present invention adopts a new positioning method of random excitation, without assuming the position of the random excitation, and directly locates the random excitation through the displacement response power spectrum, which is more in line with engineering practice, effectively solves the situation that the excitation position is unknown, and provides a basis for subsequent bridges. Random incentive refactoring provides the basis.

Description

technical field [0001] The invention relates to the field of bridges, in particular to a bridge random excitation identification method based on power spectrum propagation. Background technique [0002] Random excitation is the most common form of load acting on the bridge structure, such as the vehicle load on the main girder, the wind and rain induced vibration on the suspension cable, etc. Because it is necessary to obtain the action position and amplitude information of random excitations in the optimal design and reliability evaluation of bridge structures, the identification of random loads acting on bridges has important scientific research significance and engineering application value. [0003] Existing bridge stochastic excitation identification methods can be roughly divided into two categories, time-domain methods and frequency-domain methods. Specifically, the time-domain method uses Duhamel integration or Kalman filtering to perform random excitation recogniti...

AI Technical Summary

Problems solved by technology

However, in actual engineering, for random excitations such as vehicle loads, wind loads, etc., it is very difficult to obtain the excitation positions of these loads in advance, which will make random excitation identification impossible

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