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Bridge modal parameter intelligent updating method based on cross-modal confidence criterion matrix

A cross-modal and modal parameter technology, applied in neural learning methods, complex mathematical operations, biological neural network models, etc., can solve the problem of failing to make full use of MAC modal information, and achieve the effect of enhancing modal response information

Active Publication Date: 2021-07-23
SOUTHEAST UNIV
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AI Technical Summary

Problems solved by technology

However, in previous studies, MAC was often used as a single value, and the modal information contained in MAC was not fully utilized.

Method used

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  • Bridge modal parameter intelligent updating method based on cross-modal confidence criterion matrix
  • Bridge modal parameter intelligent updating method based on cross-modal confidence criterion matrix
  • Bridge modal parameter intelligent updating method based on cross-modal confidence criterion matrix

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Embodiment Construction

[0032] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0033] Such as figure 1 with 2 Shown, the present invention mainly comprises the following steps:

[0034]Step 1: Construct finite element models of various bridge structures with different modal parameters, and simulate random loads with Gaussian white noise to calculate structural acceleration response data, and add 0-70% Gaussian white noise to the response data respectively, Analog signal test noise; the generated sample data is divided into 10 sections to calculate its average power spectral density (PSD) matrix (set the sample size of each section as N), thereby reducing the dimension of the CMAC matrix and the dispersion between elements; the average Singular value decomposition is performed on the PSD matrix, and the eigenvector u corresponding to the largest singular value of each average PSD matrix is ​​retained i (The s...

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Abstract

The invention discloses a bridge modal parameter intelligent updating method based on a cross-modal confidence criterion (CMAC) matrix, and the method comprises the steps: taking a CMAC matrix as a basis, combining an adaptive convolution operation layer and a full-connection classification layer to form a modal spectrum response intelligent extraction neural network, and carrying out the classification reconstruction of the CMAC matrix; extracting a bridge structure physical modal spectrum response interval; furthermore, establishing an agent model of bridge vibration data power spectral density and modal information intensity based on the initial modal spectral response interval and a finite element model modal parameter theoretical value, so that a maximum modal information spectral response interval is determined, and bridge structure modal parameter identification is carried out accordingly. According to the method, the CMAC matrix and the adaptive convolutional neural network are combined to carry out intelligent analysis and identification of the structural modal parameters, the network training efficiency is high, the response of the weak excitation modal can be well extracted, and the method can be applied to bridge structure health state monitoring to carry out automatic updating of the modal parameters.

Description

technical field [0001] The invention relates to an intelligent updating method of bridge modal parameters based on a cross-modal confidence criterion (CMAC) matrix, which can be used for automatic analysis and extraction of structural modal spectral responses, thereby realizing intelligent identification and updating of bridge structural modal parameters. [0002] technical background [0003] With the substantial improvement of my country's economic and technological strength and the rapid development of the transportation industry, the level of bridge structure design and construction in my country has been continuously improved, and the bridge span has gradually moved from a hundred meters to a kilometer. As of 2019, my country has built about 880,000 highway bridges, including 5,716 super-large bridges. Such as the Hong Kong-Zhuhai-Macao Bridge and the Wufengshan Bridge, a number of super-large bridges representing the world's top level have been built in my country one a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06F17/16
CPCG06N3/08G06F17/16G06N3/045
Inventor 茅建校杨朝勇宗海梁瑞军王浩
Owner SOUTHEAST UNIV
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