[1]吴睿,廖聿宸,宗周红,等.基于GNSS信号的随机子空间模态参数识别方法[J].东南大学学报(自然科学版),2020,50(6):1045-1051.[doi:10.3969/j.issn.1001-0505.2020.06.008]
 Wu Rui,Liao Yuchen,Zong Zhouhong,et al.Stochastic subspace modal parameter identification method based on GNSS signals[J].Journal of Southeast University (Natural Science Edition),2020,50(6):1045-1051.[doi:10.3969/j.issn.1001-0505.2020.06.008]
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基于GNSS信号的随机子空间模态参数识别方法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
50
期数:
2020年第6期
页码:
1045-1051
栏目:
交通运输工程
出版日期:
2020-11-20

文章信息/Info

Title:
Stochastic subspace modal parameter identification method based on GNSS signals
作者:
吴睿1廖聿宸1宗周红1张坤2
1东南大学爆炸安全防护教育部工程研究中心, 南京 211189; 2中交第二公路勘察设计研究院有限公司, 武汉430056
Author(s):
Wu Rui1 Liao Yuchen1 Zong Zhouhong1 Zhang Kun2
1Engineering Research Center of Safety and Protection of Explosion and Impact of Ministry of Education, Southeast University, Nanjing 211189, China
2 CCCC Second Highway Survey, Design and Research Institute Co., Ltd., Wuhan 430056, China
关键词:
GNSS 小波阈值降噪 随机子空间方法 模态参数识别
Keywords:
global navigation satellite system(GNSS) wavelet threshold noise reduction stochastic subspace method modal parameter identification
分类号:
U446.2
DOI:
10.3969/j.issn.1001-0505.2020.06.008
摘要:
为了从全球卫星定位系统(GNSS)监测信号中获得桥梁结构模态特性信息,提出了一种基于GNSS信号的随机子空间模态参数识别方法.通过小波分解将GNSS信号分频,对各频段信号采用小波阈值降噪方法进行处理,并采用数据驱动的随机子空间模态参数识别方法对处理后的信号进行结构模态参数识别.以灌河大桥健康监测为例,对比研究了基于GNSS信号和基于加速度信号的随机子空间模态参数识别方法的模态频率识别效果.结果表明:通过分频段小波阈值降噪可有效滤除GNSS信号噪声,所提方法可以识别出灌河大桥多阶模态频率,与基于加速度信号的随机子空间模态参数识别方法识别结果吻合良好,最大误差在3.44%以内.
Abstract:
To obtain the bridge structure modal characteristic information from the signals of the global navigation satellite system(GNSS), a stochastic subspace modal parameter identification method based on GNSS signals was proposed. The GNSS signals were divided by wavelet decomposition, and the wavelet threshold noise reduction method was used to deal with the signal in each dependent frequency band. Then, the data-driven stochastic subspace modal parameter identification method was applied to identify the structural modal parameters. Based on the health monitoring of the Guanhe Bridge, the modal frequency recognition results of the stochastic subspace modal parameter identification method based on the GNSS signals and those based on the acceleration signals were compared. The results indicate that the noise in the GNSS signals can be effectively filtered by the wavelet threshold noise reduction method in each frequency band. The proposed method can identify the multi-modal frequencies of the Guanhe Bridge. The recognition results of the proposed method are in good agreement with those of the stochastic subspace modal parameter identification method based on the acceleration signals, and the maximum error is within 3.44%.

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备注/Memo

备注/Memo:
收稿日期: 2020-05-07.
作者简介: 吴睿(1996—),女,硕士生;宗周红(联系人),男,博士,教授,博士生导师,zongzh@seu.edu.cn.
基金项目: 国家自然科学基金资助项目(51678141).
引用本文: 吴睿,廖聿宸,宗周红,等.基于GNSS信号的随机子空间模态参数识别方法[J].东南大学学报(自然科学版),2020,50(6):1045-1051. DOI:10.3969/j.issn.1001-0505.2020.06.008.
更新日期/Last Update: 2020-11-20