Comptes Rendus
no. 4
The application of Shuffled Frog Leaping Algorithm to Wavelet Neural Networks for acoustic emission source location
Xinmin Cheng1 ; Xiaodan Zhang2; Li Zhao2; Aideng Deng2; Yongqiang Bao2; Yong Liu3; Yunliang Jiang1
1 School of Information and Engineering, Huzhou Teachers College, Huzhou, Zhejiang, 313000, China
2 School of Information Science and Engineering, Southeast University, Nanjing, Jiangsu, 210096, China
3 Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, Zhejiang, 310027, China
Comptes Rendus. Mécanique, Volume 342 (2014) no. 4, pp. 229-233.

When using acoustic emission to locate the friction fault source of rotating machinery, the effects of strong noise and waveform distortion make accurate locating difficult. Applying neural network for acoustic emission source location could be helpful. In the BP Wavelet Neural Network, BP is a local search algorithm, which falls into local minimum easily. The probability of successful search is low. We used Shuffled Frog Leaping Algorithm (SFLA) to optimize the parameters of the Wavelet Neural Network, and the optimized Wavelet Neural Network to locate the source. After having performed the experiments of friction acoustic emission's source location on the rotor friction test machine, the results show that the calculation of SFLA is simple and effective, and that locating is accurate with proper structure of the network and input parameters.

Received:
Accepted:
Published online:
DOI: 10.1016/j.crme.2013.12.006
Keywords: Acoustic emission, Location, Wavelet Neural Network, Shuffled Frog Leaping Algorithm

Xinmin Cheng 1; Xiaodan Zhang 2; Li Zhao 2; Aideng Deng 2; Yongqiang Bao 2; Yong Liu 3; Yunliang Jiang 1

1 School of Information and Engineering, Huzhou Teachers College, Huzhou, Zhejiang, 313000, China
2 School of Information Science and Engineering, Southeast University, Nanjing, Jiangsu, 210096, China
3 Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, Zhejiang, 310027, China 
@article{CRMECA_2014__342_4_229_0,
     author = {Xinmin Cheng and Xiaodan Zhang and Li Zhao and Aideng Deng and Yongqiang Bao and Yong Liu and Yunliang Jiang},
     title = {The application of {Shuffled} {Frog} {Leaping} {Algorithm} to {Wavelet} {Neural} {Networks} for acoustic emission source location},
     journal = {Comptes Rendus. M\'ecanique},
     pages = {229--233},
     publisher = {Elsevier},
     volume = {342},
     number = {4},
     year = {2014},
     doi = {10.1016/j.crme.2013.12.006},
     language = {en},
}
TY  - JOUR
AU  - Xinmin Cheng
AU  - Xiaodan Zhang
AU  - Li Zhao
AU  - Aideng Deng
AU  - Yongqiang Bao
AU  - Yong Liu
AU  - Yunliang Jiang
TI  - The application of Shuffled Frog Leaping Algorithm to Wavelet Neural Networks for acoustic emission source location
JO  - Comptes Rendus. Mécanique
PY  - 2014
SP  - 229
EP  - 233
VL  - 342
IS  - 4
PB  - Elsevier
DO  - 10.1016/j.crme.2013.12.006
LA  - en
ID  - CRMECA_2014__342_4_229_0
ER  - 
%0 Journal Article
%A Xinmin Cheng
%A Xiaodan Zhang
%A Li Zhao
%A Aideng Deng
%A Yongqiang Bao
%A Yong Liu
%A Yunliang Jiang
%T The application of Shuffled Frog Leaping Algorithm to Wavelet Neural Networks for acoustic emission source location
%J Comptes Rendus. Mécanique
%D 2014
%P 229-233
%V 342
%N 4
%I Elsevier
%R 10.1016/j.crme.2013.12.006
%G en
%F CRMECA_2014__342_4_229_0
Xinmin Cheng; Xiaodan Zhang; Li Zhao; Aideng Deng; Yongqiang Bao; Yong Liu; Yunliang Jiang. The application of Shuffled Frog Leaping Algorithm to Wavelet Neural Networks for acoustic emission source location. Comptes Rendus. Mécanique, Volume 342 (2014) no. 4, pp. 229-233. doi : 10.1016/j.crme.2013.12.006. https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.1016/j.crme.2013.12.006/

[1] G. Ma; H. Li; Z. Duan Repair effects and acoustic emission technique-based fracture evaluation for pre-damaged concrete columns confined with fiber-reinforced polymers, J. Compos. Constr., Volume 16 (2012) no. 6, pp. 626-639

[2] P. Sedlak; Y. Hirose; M. Enoki Acoustic emission localization in thin multi-layer plates using first-arrival determination, Mech. Syst. Signal Process., Volume 36 (2013) no. 2, pp. 636-649

[3] A. Perelli; L. De Marchi; A. Marzani; N. Speciale Acoustic emission localization in plates with dispersion and reverberations using sparse PZT sensors in passive mode, Smart Mater. Struct., Volume 21 (2012) no. 2 | DOI

[4] M.R. Gorman AE source orientation by plate wave analysis, J. Acoust. Emiss., Volume 10 (2000) no. 4, pp. 53-58

[5] M. Surgeon; M. Wevers Modal analysis of acoustic emission signals from CFRP laminates, Nondestruct. Test. Eval. Int., Volume 32 (1999) no. 6, pp. 311-322

[6] G.N. Morscher Modal acoustic emission of damage accumulation in a woven SIC/SIC composite, Compos. Sci. Technol., Volume 59 (1999) no. 6, pp. 687-697

[7] H.L. Bodine; R.L. Dawes; S. Henley; E.v.K. Hill Detecting crack growth in metal structures using temporal processing and the parametric avalanche stochastic filter neural network, Intelligent Engineering Systems Through Artificial Neural Networks, vol. 5, Fuzzy Logic and Evolutionary Programming, ASME Press, New York, NY, 1995, pp. 467-472

[8] Y. Hironobu; H. Kyoji Analysis of artificial acoustic emission waveforms using a neural network, Acoustic Emission, Volume 10 (1995) no. 5, pp. 35-41

[9] Y. Tian; P.L. Lewin; A.E. Davies PD pattern identification using acoustic emission measurement and neural networks, IEEE Conference Publication, vol. 5, 1999, pp. 541-543

[10] R.V. Alireza; M. Ali Hossein Solving a bi-criteria permutation flow-shop problem using shuffled frog-leaping algorithm, Soft Comput., Volume 12 (2008) no. 5, pp. 435-452

[11] M.M. Eusuff; K.E. Lansey Shuffled Frog-leaping Algorithm: A memetic meta-heuristic for discrete optimization, Eng. Optimiz., Volume 38 (2006) no. 2, pp. 129-154

[12] R.V. Alireza; M. Ali Hossein A hybrid multi-objective shuffled frog-leaping algorithm for a mixed-model assembly line sequencing problem, Comput. Ind. Eng., Volume 53 (2007) no. 4, pp. 642-666

[13] Q. Zhang; A. Benveniste Wavelet networks, IEEE Trans. Neural Network, Volume 3 (1992) no. 6, pp. 889-898

[14] H.-l. Bian; G.-j. Chen; T.-j. Du A method of time-varying harmonic detection based on the wavelet neural network, Proc. CSEE, Volume 28 (2008) no. 7, pp. 104-109

[15] F. Hu; R.Y. Liang; D.X. Li; L. Zhao Application of Shuffled Frog Leaping Algorithm and wavelet neural network in sound source location, Proc. 1st Int. Conf. on Information Science and Engineering (ICISE), 2009, pp. 3600-3604

Cited by Sources:

Comments - Policy