Hong Yin This email address is being protected from spambots. You need JavaScript enabled to view it.1, Jie Zheng1, Xiaoxia Liu1 and Zhenrui Peng1

1School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou, P.R. China


 

Received: March 4, 2019
Accepted: July 22, 2019
Publication Date: December 1, 2019

Download Citation: ||https://doi.org/10.6180/jase.201912_22(4).0009 *Corresponding  

ABSTRACT


The modal test usually needs many measuring points to provide abundant information. Meanwhile, the placement of sensors is limited by cost and working environment, which can bring much inconvenience to the test work. An optimal selection method of exciting and measuring points is put forward. The model updating idea in the distribution estimation algorithm is introduced into the harmony search algorithm to form a new algorithm called distributed estimation harmony search algorithm. The new algorithm is applied to the optimal selection of measuring points, and modal participation theory is used to select the optimal exciting points. Optimal measuring points and exciting points are selected for modal test of a steel truss bridge model. The modal test result demonstrates the effectiveness of the distribution estimation harmony search algorithm for the optimal selection of exciting and measuring points.


Keywords: Modal Analysis, Distributed Estimation, Harmony Search, Participation Theory


REFERENCES


  1. [1] Chen, G., X. Zhang, and C. Zhong (2017) Design and experimental analysis of U-shaped flexure hinge with shearing damping, Journal of Vibration Measurement & Diagnosis 37, 978983. doi: 10.16450/j.cnki.issn.1004-6801.2017.05.019
  2. [2] Chen,W. H., Z. R. Lu,W. Lin, et al. (2011) Theoretical and experimental modal analysis of the Guangzhou new TV tower, Engineering Structures 33, 3628–3646. doi: 10.1016/j.engstruct.2011.07.028
  3. [3] Zhang, G. W., J. H. Ma, Z. Chen, et al. (2014) Automated eigen system realisation algorithm for operational modal analysis, Journal of Sound and Vibration 333, 3550–3563. doi: 10.1016/j.jsv.2014.03.024
  4. [4] Alvandi, A., and C. Cremona (2006) Assessment of vibration-based damage identification techniques, Journal of Sound and Vibration 292, 179–202. doi: 10.1016/j.jsv.2005.07.036
  5. [5] Penny, J. E. T., M. I. Friswell, and S. D. Garvey (1994) Automatic choice of measurement locations for dynamic testing, AIAA Journal 32, 407–414. doi: 10.2514/3.11998
  6. [6] Michael, I. F., andR.C. Triguero (2015)Clustering of sensor locations using the effective independence method, AIAA Journal 53, 13881390. doi: 10.2514/1.J053503
  7. [7] Zhan, J., and Y. U. Ling (2017) An effective independence-improved modal strain energy method for optimal sensor placement, Journal of Vibration & Shock 36, 8287. doi: 10.4028/www.scientific.net/amm.670-671.1252
  8. [8] Wu, Z. Y., F. J. Dai, J. Song, et al. (2007) Research on sensor optimization arrangement method in damage detection, Journal of North Western Polytechnical University 25, 503507.
  9. [9] Huang, M. S., H. P. Zhu, andW. M. Li (2008) Optimal sensor placement on bridge structure based on genetic algorithm, Journal of Vibration & Shock 27, 8286.
  10. [10] Tian, L., H. G. Chen, J. Zhu, et al. (2015) Optimal sensor configuration based on adaptive simulated annealing genetic algorithm, Journal of Vibration Engineering 16, 464477.
  11. [11] Li, D. C., L. J. He, Y. Y. Chen, et al. (2014) Optimal strain sensor placement based on an improved particle swarm optimization algorithm, Journal of Vibration Measurement & Diagnosis 34, 610615.
  12. [12] Yi, T. H., X. D. Zhang, and H. N. Li (2013) Optimal sensor placement based on adaptive monkey algorithm, Journal of Vibration & Shock 32, 5763.
  13. [13] Yong, L. Q. (2011) Advances in harmony search algorithm, Computer Systems&Applications 20, 244248.
  14. [14] Jin, H., J. Xia, and Y. Q. Wang (2015) Optimal sensor placement for space modal identification of crane structures based on an improved harmony search algorithm, Journal of Zhejiang University-SCIENCE A 16, 464477. doi: 10.1631/jzus.A1400363
  15. [15] Xia, H. G., H. B. Ouyang, L. Q. Gao, et al. (2016) Global competitive harmony search algorithm, Control & Decision 31, 310316. doi: 10.13195/j.kzyjc.2014.1742
  16. [16] Wang. J., K. Tang, J. A. Lozano, et al. (2016) Estimation of the distribution algorithm with a stochastic local search for uncertain capacitated arc routing problems, IEEE Transactions on Evolutionary Computation 20, 96109. doi: 10.1109/TEVC.2015.2428616
  17. [17] Zhang, J. P., Y. Tao, H. P. Zhu, et al. (2016) Optimal sensor configuration based on spectral finite elementmethod and information entropy, Journal of Vibration & Shock 35, 7681. doi: 10.13465/j.cnki.jvs.2016.02.013
  18. [18] Ouyang, H. B., L. Q. Gao, D. X. Zou, et al. (2014) Exploration ability study of harmony search algorithm and its modification, Control Theory & Applications 31, 5765. doi: 10.7641/CTA.2014.30217
  19. [19] Zhai, J. C., L. Q. Gao, H. B. Ouyang, et al. (2015) An adaptive global HS algorithm, Control & Decision 30, 19531959.
  20. [20] Derrac J., S. García, D. Molina, et al. (2011) A practical tutorial on the use of nonparametric statistical tests as amethodology for comparing evolutionary and swarm intelligence algorithms, Swarm & Evolutionary Computation 1(1), 318. doi: 10.1016/j.swevo.2011.02.002
  21. [21] Zhang, H., Y. S. He, Z. M. Xu, et al. (2017) Modal simulation and test analysis of a claw-pole alternator, Noise & Vibration Control 37, 5861.
  22. [22] Qiang, W., Y. Zhao, F. Lin, et al. (2017) Correlation between the finite element calculation and experimental mode of a mechanical elastic wheel, Journal of Harbin Engineering University 38, 8693. doi: 10.11990/jheu.201512067
  23. [23] Mbarek,A., A. F. D. Rincon, A. Hammami, et al. (2018) Comparison of experimental and operational modal analysis on a back to back planetary gear, Mechanism & Machine Theory 124, 226247. doi: 10.1016/j.mechmachtheory.2018.03.005
  24. [24] Xu, F., C. Li, T. Jiang, et al. (2013) Optimization of excitation and measurement location in experimental modal test, Journal of Beijing University of Aeronautics & Astronautics 39, 16541659. doi: 10.4028/www.scientific.net/AMR.765-767.1481
  25. [25] Zou, Q., Z. Li, and H. Wu (2017) Modal analysis of trough solar collector, Solar Energy 141, 8190. doi:10.1016/j.solener.2016.11.026