Advances and prospects for optimal sensor placement of structural health monitoring

被引:0
作者
Yang C. [1 ]
机构
[1] Qian Xuesen Lab of Space Technology, China Academy of Space Technology, Beijing
来源
Zhendong yu Chongji/Journal of Vibration and Shock | 2020年 / 39卷 / 17期
关键词
Adjustment strategy; Evaluation criterion; Optimal sensor placement; Optimization method; Structural health monitoring;
D O I
10.13465/j.cnki.jvs.2020.17.012
中图分类号
学科分类号
摘要
Large scale, complex, long life and multi-functional modern engineering structures are exposed to severe service environment for a long time, their structural function and state can deviate from the initial design goal. Using structural health monitoring technology to do health diagnosis and performance evaluation is an important means to ensure structural safety, extend service life and reduce maintenance cost, while sensor system is the primary link of structural health monitoring to directly determine the correctness of structural safety diagnosis. With increasing demands for security and functionality of structures to be monitored, sensor placement is more and more complex, and the high efficiency and high precision data acquisition system of structural state change also poses a higher challenge to the optimization of sensor layout. Here, advances of optimal sensor placement method and evaluation method were reviewed and commented, respectively. Several key problems to be urgently solved including coupling relation between input parameters and performance, reliability analysis, and large scale of sensor placement optimization algorithm's precision, efficiency and evaluation in optimal sensor placement were extracted. Prospects to be developed in future were described including key development directions of optimal sensor placement method with incomplete information and optimal input parameters, multi-type optimal sensor placement method based on the information fusion technology, integrated design for multi-objective optimization sensor placement algorithm, optimal sensor placement algorithm strategy based on artificial intelligence, and adaptive vibration data sampling system under low signal-to-noise ratio and multiple working conditions. © 2020, Editorial Office of Journal of Vibration and Shock. All right reserved.
引用
收藏
页码:82 / 93
页数:11
相关论文
共 122 条
  • [101] YANG C, ZHANG X P, HUANG X Q, Et al., Optimal sensor placement for deployable antenna module health monitoring in ssps using genetic algorithm, Acta Astronautica, 140, pp. 213-224, (2017)
  • [102] YANG C, LIANG K, ZHANG X P, Et al., Sensor placement algorithm for structural health monitoring with redundancy elimination model based on sub-clustering strategy, Mechanical Systems and Signal Processing, 124, pp. 369-387, (2019)
  • [103] YANG C., Sensor placement for structural health monitoring using hybrid optimization algorithm based on sensor distribution index and FE grids, Structural Control and Health Monitoring, 25, 6, (2018)
  • [104] YANG C, ZHENG W Z, ZHANG X P., Optimal sensor placement for spatial lattice structure based on three-dimensional redundancy elimination model, Applied Mathematical Modelling, 66, pp. 576-591, (2019)
  • [105] SANTI L M, SOWERS T S, AGUILA R B., Optimal sensor selection for health monitoring systems, (2005)
  • [106] YI T H, LI H N., Methodology developments in sensor placement for health monitoring of civil infrastructures, International Journal of Distributed Sensor Networks, 8, pp. 601-617, (2012)
  • [107] YI Tinghua, LI Hongnan, GU Ming, Multiple optimization strategies based sensor placement method for structural health monitoring, Journal of Building Structures, 32, 12, pp. 217-223, (2011)
  • [108] ZHANG J, MAES K, ROECK G D, Et al., Optimal sensor placement for multi-setup modal analysis of structures, Journal of Sound and Vibration, 401, pp. 214-232, (2017)
  • [109] YANG W, SUN L, YU G., Optimal sensor placement methodology for uncertainty reduction in the assessment of structural condition, Structural Control and Health Monitoring, 24, 6, (2017)
  • [110] YUEN K, KUOK S., Efficient Bayesian sensor placement algorithm for structural identification: a general approach for multi-type sensory systems, Earthquake Engineering & Structural Dynamics, 44, 5, pp. 757-774, (2015)