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馬耀華

 

（ 中化學(xué)建設(shè)投資集團(tuán)有限公司 ，北京 102300)

摘   要：為合理實(shí)現(xiàn)運(yùn)營橋梁的安全性預(yù)警分級，結(jié)合去噪處理的實(shí)測數(shù)據(jù)，以累計(jì)變形序列、速率序列和加速度序列分別構(gòu)建相應(yīng)的預(yù)警判據(jù)，實(shí)現(xiàn)運(yùn)營橋梁安全性預(yù)警分級的多源信息融合，充分保證分級結(jié)果的準(zhǔn)確性。結(jié)果表明：PSO - DVMD 模型可有效剔除橋梁變形數(shù)據(jù)中的隨機(jī)噪聲，適用于橋梁變形數(shù)據(jù)的去噪處理；不同監(jiān)測點(diǎn)或監(jiān)測項(xiàng)目在不同判據(jù)條件下的預(yù)警等級存在一定差異，按不利原則綜合確定橋梁的安全性預(yù) 警等級。運(yùn)營橋梁安全預(yù)警分級為運(yùn)營橋梁安全性評價(jià)提供了一種量化分級標(biāo)準(zhǔn)，值得進(jìn)一步推廣應(yīng)用研究。

關(guān)鍵詞：橋梁 ；去噪 ；安全性預(yù)警 ；相關(guān)向量機(jī) ；趨勢判斷

中圖分類號(hào)：U446           

文獻(xiàn)標(biāo)志碼：A            

文章編號(hào)： 1005- 8249   (2024)  05- 0162- 07 

DOI:10. 19860/j.cnki.issn1005 - 8249.2024.05 .029

 

MA Yaohua

(China National Chemical Construction Investment Group Co. ，Ltd . ,  Beijing 102300 ,  China)

Abstract:In order to reasonably realize the safety early warning classification of operating bridges, based on the monitoring results of operating bridges, this paper first carries out data denoising to eliminate the noise information in the data and lay a foundation for subsequent analysis; Secondly, from three aspects of cumulative deformation sequence, velocity sequence and acceleration sequence, corresponding early warning criteria are constructed respectively to achieve multi-source information fusion of early warning classification of operational bridge safety and fully ensure the accuracy of classification results. The case analysis results show that the PSO-DVMD model can effectively eliminate the random noise in the bridge deformation data, and there are certain differences in the early warning levels of different monitoring points or monitoring items under different criteria. According to the adverse principle, the safety early warning level of the example bridge in this paper is comprehensively determined as Level II - Yellow, which belongs to the basic safety state. The follow-up monitoring should be continued, and the maintenance and reinforcement plan should be prepared. Through this study, it provides a quantitative grading standard for the safety evaluation of operating bridges, which is worthy of further popularization and application.

Keywords :  bridges;  denoising;   security early warning;  correlation vector machine;  trend judgment

作者簡介： 馬耀華  (1973—) , 男，本科， 高級工程師 ，研 究方向： 土木工程。

收稿日期：2023- 05- 04