Dual-type sensor placement optimization by fully utilizing structural modal information

被引:6
|
作者
Pei, Xue-Yang [1 ]
Yi, Ting-Hua [1 ]
Li, Hong-Nan [1 ,2 ]
机构
[1] Dalian Univ Technol, Sch Civil Engn, Dalian 116023, Peoples R China
[2] Shenyang Jianzhu Univ, Sch Civil Engn, Shenyang, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
accelerometer; displacement mode shape estimation; optimal sensor placement; strain gauge; structural modal information; IDENTIFICATION; BRIDGE; METHODOLOGY; LOCATIONS;
D O I
10.1177/1369433218799151
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Strain gauges and accelerometers are widely used in bridge structural health monitoring systems. Generally, the strain gauges are placed on the key locations to obtain local structural deformation information; the accelerometers are used to obtain the structural modal information. However, the modal information contained in the measured strains is not taken into account. In this article, to fully utilize the modal information contained in strains, a mode shape estimation method is proposed that the strain mode shapes of the strain locations are used to obtain the displacement mode shapes of some positions without accelerometers. At first, to simulate the practical situation, some positions with large structural deformations are selected as the strain gauge locations. Using the proposed mode shape estimation method, the displacement mode shapes of some locations without accelerometers are estimated by the strain mode shapes using the least squares method, and the locations with the smallest estimation error are finally determined as the estimated locations. Then, accelerometers are added to the existing sensor placement. Here, the modal assurance criterion is used to evaluate the distinguishability of the displacement mode shapes obtained from the strain gauges and accelerometers. The accelerometer locations that bring the smallest modal assurance criterion values are selected. In addition, a redundancy can be set to avoid the adjacent sensors containing similar modal information. Through the proposed sensor placement method, the deformation and modal information contained in the strain gauges is fully utilized; the modal information contained in the strain gauges and accelerometers is comprehensively utilized. Numerical experiments are carried out using a bridge benchmark structure to demonstrate the sensor placement method.
引用
收藏
页码:737 / 750
页数:14
相关论文
共 50 条
  • [41] Optimal sensor placement in structural health monitoring using discrete optimization
    Sun, Hao
    Bueyuekoeztuerk, Oral
    SMART MATERIALS AND STRUCTURES, 2015, 24 (12)
  • [42] Optimization of Embedded Sensor Placement for Structural Health Monitoring of Composite Airframes
    Park, Chun
    Peters, Kara
    AIAA JOURNAL, 2012, 50 (11) : 2536 - 2545
  • [43] Distributed sensor placement optimization for computer aided structural health monitoring
    Ameduri, Salvatore
    Ciminello, Monica
    Dimino, Ignazio
    Concilio, Antonio
    Catignani, Alfonso
    Mancinelli, Raimondo
    ARCHIVE OF MECHANICAL ENGINEERING, 2019, 66 (01) : 111 - 127
  • [44] Deep generative Bayesian optimization for sensor placement in structural health monitoring
    Sajedi, Seyedomid
    Liang, Xiao
    COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2022, 37 (09) : 1109 - 1127
  • [45] A transient dual-type sensor based on MXene/cellulose nanofibers composite for intelligent sedentary and sitting postures monitoring
    Huang, Haizhou
    Dong, Yide
    Wan, Shu
    Shen, Jiaxin
    Li, Chen
    Han, Longxiang
    Dou, Guangbin
    Sun, Litao
    CARBON, 2022, 200 : 327 - 336
  • [46] Multi-type, multi-sensor placement optimization for structural health monitoring of long span bridges
    Soman, Rohan N.
    Onoufriou, Toula
    Kyriakides, Marios A.
    Votsis, Renos A.
    Chrysostomou, Christis Z.
    SMART STRUCTURES AND SYSTEMS, 2014, 14 (01) : 55 - 70
  • [47] Structural damage detection-oriented multi-type sensor placement with multi-objective optimization
    Lin, Jian-Fu
    Xu, You-Lin
    Law, Siu-Seong
    JOURNAL OF SOUND AND VIBRATION, 2018, 422 : 568 - 589
  • [49] Extraction of structural modal information using acoustic sensor measurements and machine learning
    Jiang, Zhaoshuo
    Zhang, Zhenyu
    Maxwell, Alec
    JOURNAL OF SOUND AND VIBRATION, 2019, 450 : 156 - 174
  • [50] Dual-Type Structural Response Reconstruction Based on Moving-Window Kalman Filter with Unknown Measurement Noise
    Zhang, X. H.
    Wu, Z. B.
    JOURNAL OF AEROSPACE ENGINEERING, 2019, 32 (04)