Vibration source identification method based on multisensor vibration signal fusion analysis

被引:0
|
作者
Yang, Yulong [1 ]
Wang, Jintao [1 ]
Wang, Peng [2 ]
Huang, Yong [3 ]
Shao, Xiaoguang [1 ]
Huang, Zheyu [1 ]
Xue, Fei [4 ]
Liang, Xu [4 ]
机构
[1] Zhejiang Univ, Coll Civil Engn & Architecture, Hangzhou 310058, Peoples R China
[2] China Railway Tunnel Grp Corp Ltd, Guangzhou 511458, Peoples R China
[3] Power China Huadong Engn Corp Ltd, Hangzhou 311100, Peoples R China
[4] Hangzhou Urban Infrastruct Construct Management Ct, Hangzhou 310006, Peoples R China
关键词
Multisource data; Correlation analysis; Signed time delay analysis; Vibration; Classification and identification; Vibration propagation correlation coefficient;
D O I
10.1016/j.istruc.2025.108604
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The accelerated development of urban areas has resulted in an increase in environmental vibration factors in the vicinity of buildings. For buildings, particularly ancient ones, vibrations that exceed their limits can potentially cause irreversible damage. The identification of the source of the vibrations and ensuring that the identification process and results are physically meaningful is necessary to implement timely and targeted measures to mitigate the impact of vibration and noise on the building structure. We proposed a vibration source identification method based on the correlation analysis of multi-source vibration response signals. This method uses two parameters, correlation coefficient and signed time delay, to describe the similarity and directionality of different vibration response signals propagating through various parts of the structure. Moreover, we innovatively integrate these two parameters into a new indicator vibration propagation correlation coefficient (VPCC), which could simultaneously quantify the similarity and direction of the propagation of different vibration response signals, thereby achieving vibration source identification through the quantification of intervals. With the intuitive index construction, the proposed method achieves clear physical interpretability while ensuring low computational complexity, providing an efficient and physically insightful solution for vibration source identification. The results of validation demonstrated that this method is an effective means of identifying single load vibration sources, whether originating from wind or construction activity. However, its efficacy is somewhat diminished when applied to mixed load vibration sources, consisting of a combination of wind and construction. In these instances, the overall identification accuracy reached 96.7 %.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] Fault Diagnosis Method of Escalator Step System Based on Vibration Signal Analysis
    You, Fuqiang
    Wang, Dianlong
    Li, Guanghai
    Chen, Chunhua
    INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2022, 20 (10) : 3222 - 3232
  • [32] Identification of power output of diesel engine by analysis of the vibration signal
    Gao, Zhilong
    Jiang, Zhinong
    Zhang, Jinjie
    MEASUREMENT & CONTROL, 2019, 52 (9-10): : 1371 - 1381
  • [33] Damage identification of heterogeneous materials based on vibration and information fusion
    Liu, T.
    Li, A. Q.
    Ding, Y. L.
    Zhao, D. L.
    ADVANCES IN HETEROGENEOUS MATERIAL MECHANICS 2008, 2008, : 1391 - 1394
  • [34] Identification of vibration signal in Φ-OTDR system
    Liu, Chenda
    Qin, Zujun
    Xiong, Xianming
    Zhang, Wentao
    2019 ASIA COMMUNICATIONS AND PHOTONICS CONFERENCE (ACP), 2019,
  • [35] Structural Damage Detection Based on Vibration Signal Fusion and Deep Learning
    Zhang, Jiqiao
    Zhang, Junwei
    Teng, Shuai
    Chen, Gongfa
    Teng, Zhiqiang
    JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES, 2022, 10 (04) : 1205 - 1220
  • [36] Structural Damage Detection Based on Vibration Signal Fusion and Deep Learning
    Jiqiao Zhang
    Junwei Zhang
    Shuai Teng
    Gongfa Chen
    Zhiqiang Teng
    Journal of Vibration Engineering & Technologies, 2022, 10 : 1205 - 1220
  • [37] Fault Diagnosis for Gear Pump Based on Feature Fusion of Vibration Signal
    Liu, Xiliang
    Chen, Guiming
    Li, Fangxi
    Zhang, Qian
    Dong, Zhenqi
    2012 INTERNATIONAL CONFERENCE ON QUALITY, RELIABILITY, RISK, MAINTENANCE, AND SAFETY ENGINEERING (ICQR2MSE), 2012, : 709 - 712
  • [38] Research on Identification Method of Multi-mixed Vibration Signal of Aeroengine
    Jin Xiang-yang
    Zhong Shi-sheng
    ADVANCED DESIGN AND MANUFACTURE II, 2010, 419-420 : 801 - 804
  • [39] Turbo generator vibration source identification based on operational transfer path analysis technology
    Yan, Wei
    Zhong, Shouping
    Li, Huazhong
    Chen, Jun
    Yang, Jiangang
    JOURNAL OF VIBROENGINEERING, 2023, 25 (07) : 1243 - 1256