Semi-supervised synergistic evaluation method for static parameter of health monitoring of bridge structure

Abstract

The invention relates to a semi-supervised synergistic evaluation method for the static parameter of the health monitoring of a bridge structure. The characteristic sample sets of a bridge structure are formed by preprocessing the static data of the health of the bridge structure, which are collected at real time. Three sample subsets which are already marked are obtained by the self-help sampling of the sample sets which are already marked, three initial base classifiers based on different supervised learning algorithms are trained by utilizing the three sample subsets, then the marking of samples which are not marked in the characteristic sample sets is realized by a synergistic action among the three classifiers, and the classifiers are also updated simultaneously. After the operation of synergistic training iteration is finished, the operation of weighted voting is carried out on the three base classifiers by the marking result of each base classifier on test samples so as to obtain a final classifying result. According to the semi-supervised synergistic evaluation method for the static parameter of the health monitoring of the bridge structure, a great number of marking requirements on the health data of the bridge structure can be reduced, the manual marking cost is lowered, the classifying accuracy of the health data of the bridge structure can also be enhanced, and the analysis and the evaluation of the health condition on the bridge structure are realized by the classifying result of the health data of the bridge structure.

Description

technical field [0001] The invention provides an analysis and evaluation method for bridge structure health monitoring static data, in particular to a semi-supervised collaborative method using a small amount of marked and a large amount of unmarked bridge structure static data, and belongs to the field of bridge structure health evaluation and analysis. Background technique [0002] The bridge structural health monitoring system is generally installed on important independent bridges or bridges with a low health level and a certain degree of risk. By monitoring and analyzing different parameters, the overall damage and local damage of the bridge can be judged to evaluate the structural health of the bridge. The bridge structural health monitoring system is mainly composed of sensor subsystems, data acquisition subsystems, data communication and transmission subsystems, data analysis and processing subsystems, and state evaluation and prediction subsystems. The bridge struct...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a semi-supervised collaborative method for bridge structure health monitoring static parameter data, by using a small amount of marked static data and a large amount of unmarked static data to establish a bridge structure health semi-supervised model, which not only solves the problem of bridge structure A large amount of manual labeling of data effectively ensures the accuracy of the classification. The health status of the bridge structure is analyzed and evaluated through the alert status classification of the bridge structure health data.

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