A new damage detection method for bridge condition assessment in structural health monitoring

被引:8
|
作者
Miyamoto, Ayaho [1 ]
机构
[1] Yamaguchi Univ, Grad Sch Sci & Engn, 2-16-1 Tokiwadai, Ube, Yamaguchi 7558611, Japan
关键词
Bridge; Damage detection; Condition assessment; State representation methodology (SRM); Structural health monitoring (SHM); Frequency slice wavelet transform (FSWT);
D O I
10.1007/s13349-013-0058-z
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper introduces a newly proposed "state representation methodology (SRM)'' and its application to bridge condition assessment based on the bridge monitoring data. The SRM is a novel tool that can provide some ideas and algorithms for data mining in the bridge monitoring system. The state of a system such as bridge structure can be obtained by a state variable calculated from a state representation equation (SRE). A kernel function method which plays an important role in the support vector machines is applied to obtain solutions of the SRE. In the computation of the SRE, it needs to be changed into a large-scale linear constraint problem (LSLCP). Anew compatible algorithm is therefore proposed for solving technique of the LSLCP. Before using theSRM, it is necessary that the system features need to extract from the complex responses observed data in the system. Consequently, a new time-frequency analysis tool, called frequency slice wavelet transform (FSWT), will be able to powerfully reveal a change of the characteristics in vibration signal. The FSWT produces five new properties in contrast with the traditional wavelet transform. Therefore, the paper will show the new method that can be used widely in signal processing. In this paper, a general theory for the nonparametric description of the infrastructure system's state will also be introduced and will demonstrate how to apply the SRM to practical problems.
引用
收藏
页码:269 / 284
页数:16
相关论文
共 50 条
  • [31] Online fatigue damage assessment for bridges with structural health monitoring system
    Li, ZX
    Ko, JM
    Chan, THT
    ADVANCES IN STRUCTURAL DYNAMICS, VOLS I & II, 2000, 10 : 1053 - 1060
  • [32] Improved Shewhart Chart for Damage Detection of Structural Health Monitoring Systems
    Chaabane, Marwa
    Ben Hamida, Ahmed
    Mansouri, Majdi
    Nounou, Hazem
    Nounou, Mohamed
    2018 4TH INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP), 2018,
  • [33] Damage Detection and Evaluation in Wireless Sensor Network for Structural Health Monitoring
    Surya, S.
    Ravi, R.
    INTELLIGENT COMMUNICATION TECHNOLOGIES AND VIRTUAL MOBILE NETWORKS, ICICV 2019, 2020, 33 : 207 - 211
  • [34] Structural Health Monitoring and Damage Detection Using Neural Networks Technique
    Lin, Niu
    Qun, Cai
    2013 THIRD INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM DESIGN AND ENGINEERING APPLICATIONS (ISDEA), 2013, : 1302 - 1304
  • [35] Structural Health Monitoring and Damage Detection with Piezoelectric Wafer Active Sensors
    Giurgiutiu, Victor
    DYNAMICS FOR SUSTAINABLE ENGINEERING, VOL 1, 2011, : 329 - 337
  • [36] Personalised federated learning framework for damage detection in structural health monitoring
    Ali Anaissi
    Basem Suleiman
    Widad Alyassine
    Journal of Civil Structural Health Monitoring, 2023, 13 : 295 - 308
  • [37] Damage Detection for Structural Health Monitoring Using Ultrasonic Guided Waves
    Li, Hongyuan
    Xu, Hong
    ADVANCES IN FRACTURE AND DAMAGE MECHANICS XI, 2013, 525-526 : 433 - 436
  • [38] Personalised federated learning framework for damage detection in structural health monitoring
    Anaissi, Ali
    Suleiman, Basem
    Alyassine, Widad
    JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING, 2023, 13 (2-3) : 295 - 308
  • [39] Robust dimensionality reduction and damage detection approaches in structural health monitoring
    Khoa, Nguyen L. D.
    Zhang, Bang
    Wang, Yang
    Chen, Fang
    Mustapha, Samir
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2014, 13 (04): : 406 - 417
  • [40] Field investigation of bicycles for indirect bridge structural health monitoring
    May, Richard
    Chai, Hwa Kian
    Reynolds, Thomas
    Lu, Yong
    JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING, 2025, 15 (02) : 465 - 481