Multi-objective sensor placement optimization in SHM systems with Kriging-based mode shape interpolation

被引:14
作者
de Souza Mello, Felipe Martarella [1 ]
Pereira, Joao Luiz Junho [2 ]
Gomes, Guilherme Ferreira [1 ]
机构
[1] Fed Univ Itajuba UNIFEI, Mech Engn Inst, Itajuba, Brazil
[2] Aeronaut Inst Technol ITA, Comp Sci Div, Sao Jose Dos Campos, Brazil
基金
巴西圣保罗研究基金会;
关键词
Sensor placement optimization; Multiobjective; Mode shapes; Lichtenberg algorithm; TOPSIS;
D O I
10.1016/j.jsv.2023.118050
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Sensor location optimization plays a key role in the application and development of structural integrity monitoring methodologies, especially in large mechanical structures. Given the existence of an effective damage detection and identification procedure, the question of how many and where to place the acquisition points (sensors) so that the monitoring system operates at peak efficiency arises. In this study, an innovative methodology is proposed in order to maximize the quality of modal information and minimize the number of sensors in the SHM system. To maximize the quality of modal information, it considered the reconstruction of mode shapes using Kriging interpolation. The study was carried out on plate-type composite material structures for initial validation and later applied and validated on a main rotor blade of the AS-350 helicopter. The initial modal information (modal deformation) was obtained through the finite element method, and the multi-objective Lichtenberg algorithm was used in the complex optimization process. The proposed method presented in this work allows for the best possible distribution of a minimum and sufficient number of acquisition points in a structure in order to obtain more modal information for a better modal reconstruction from kriging interpolation of these minimum points. Numerical examples and test results show that the proposed method is robust and effective for distributing a reduced number of sensors in a structure and at the same time guaranteeing the quality of the information obtained, even in noisy situations. Numerical results considering both the simple and complex geometric cases show that the proposed combined FS-kriging method is effective in distributing a finite number of sensors on the structures and at the same time guaranteeing the quality of the modal information obtained. The results also indicate that the layout of sensors obtained by multi-objective optimization does not become trivial and symmetrical when a set of modes is considered in the objective function formulation. The proposed strategy is an advantage in modal testing as it is only necessary to acquire signals at a limited number of points, saving time and operating costs in vibration-based processes.
引用
收藏
页数:25
相关论文
共 48 条
[1]  
Allemang RJ, 2003, SOUND VIB, V37, P14
[2]   Effect and detection of cracks on small wind turbine blade vibration using special Kriging analysis of spectral shifts [J].
Awadallah, Mohammed ;
El-Sinawi, Ameen .
MEASUREMENT, 2020, 151
[3]  
Balageas D., 2010, STRUCT HEALTH MONIT, P1, DOI [10.1002/9780470612071, DOI 10.1002/9780470612071, DOI 10.1117/1.2819119]
[4]   The State of the Art of Data Science and Engineering in Structural Health Monitoring [J].
Bao, Yuequan ;
Chen, Zhicheng ;
Wei, Shiyin ;
Xu, Yang ;
Tang, Zhiyi ;
Li, Hui .
ENGINEERING, 2019, 5 (02) :234-242
[5]  
Barthorpe R., 2009, ENCY STRUCTURAL HLTH, DOI DOI 10.1002/9780470061626.SHM086
[6]   A rigorous framework for optimization of expensive functions by surrogates [J].
Booker A.J. ;
Dennis Jr. J.E. ;
Frank P.D. ;
Serafini D.B. ;
Torczon V. ;
Trosset M.W. .
Structural optimization, 1999, 17 (1) :1-13
[7]   Optimal Sensor Placement for Modal Identification of Bridge Systems Considering Number of Sensing Nodes [J].
Chang, Minwoo ;
Pakzad, Shamim N. .
JOURNAL OF BRIDGE ENGINEERING, 2014, 19 (06)
[8]  
Chang Minwoo, 2014, Special topics in structural dynamics, V6, P287
[9]   Putting Continuous Metaheuristics to Work in Binary Search Spaces [J].
Crawford, Broderick ;
Soto, Ricardo ;
Astorga, Gino ;
Garcia, Jose ;
Castro, Carlos ;
Paredes, Fernando .
COMPLEXITY, 2017,
[10]   S-shaped versus V-shaped transfer functions for binary Manta ray foraging optimization in feature selection problem [J].
Ghosh, Kushal Kanti ;
Guha, Ritam ;
Bera, Suman Kumar ;
Kumar, Neeraj ;
Sarkar, Ram .
NEURAL COMPUTING & APPLICATIONS, 2021, 33 (17) :11027-11041