Steel and Composite Structures

  • 제19권3호
  • /
  • Pages.569-583
  • /
  • 2015
  • /
  • 1229-9367(pISSN)
  • /
  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

State detection of explosive welding structure by dual-tree complex wavelet transform based permutation entropy

  • Si, Yue (School of Mechanical Engineering, Xi'an Jiaotong University) ;
  • Zhang, ZhouSuo (School of Mechanical Engineering, Xi'an Jiaotong University) ;
  • Cheng, Wei (School of Mechanical Engineering, Xi'an Jiaotong University) ;
  • Yuan, FeiChen (School of Mechanical Engineering, Xi'an Jiaotong University)
  • 투고 : 2014.06.26
  • 심사 : 2015.01.31
  • 발행 : 2015.09.25
⟨ 이전 논문 다음 논문 ⟩

초록

Recent years, explosive welding structures have been widely used in many engineering fields. The bonding state detection of explosive welding structures is significant to prevent unscheduled failures and even catastrophic accidents. However, this task still faces challenges due to the complexity of the bonding interface. In this paper, a new method called dual-tree complex wavelet transform based permutation entropy (DTCWT-PE) is proposed to detect bonding state of such structures. Benefiting from the complex analytical wavelet function, the dual-tree complex wavelet transform (DTCWT) has better shift invariance and reduced spectral aliasing compared with the traditional wavelet transform. All those characters are good for characterizing the vibration response signals. Furthermore, as a statistical measure, permutation entropy (PE) quantifies the complexity of non-stationary signals through phase space reconstruction, and thus it can be used as a viable tool to detect the change of bonding state. In order to more accurate identification and detection of bonding state, PE values derived from DTCWT coefficients are proposed to extract the state information from the vibration response signal of explosive welding structure, and then the extracted PE values serve as input vectors of support vector machine (SVM) to identify the bonding state of the structure. The experiments on bonding state detection of explosive welding pipes are presented to illustrate the feasibility and effectiveness of the proposed method.

키워드

과제정보

연구 과제 주관 기관 : National Natural Science Foundation of China

참고문헌

  1. Acarer, M., Gulenc, B. and Findik, F. (2004), "The influence of some factors on steel/steel bonding quality on their characteristics of explosive welding joints", J. Mater. Sci., 39(21), 6457-6466. https://doi.org/10.1023/B:JMSC.0000044883.33007.20
  2. Akbari Mousavi, S.A.A., Al-Hassani, S.T.S. and Atkins, A.G. (2008), "Bond strength of explosively welded specimens", Mater. Des., 29(7), 1334-1352. https://doi.org/10.1016/j.matdes.2007.06.010
  3. Bandt, C. and Pompe, B. (2002), "Permutation entropy: A natural complexity measure for time series", Phys. Rev. Lett., 88(17), 174102. https://doi.org/10.1103/PhysRevLett.88.174102
  4. Cao, Y., Tung, W.W., Gao, J., Protopopescu, V. and Hively, L. (2004), "Detecting dynamical changes in time series using the permutation entropy", Phys. Rev. - SERIES E, 70(4; PART 2), 046217. https://doi.org/10.1103/PhysRevE.70.046217
  5. Chen, G. (2014), "Automatic EEG seizure detection using dual-tree complex wavelet-Fourier features", Expert Syst. Appl., 41(5), 2391-2394. https://doi.org/10.1016/j.eswa.2013.09.037
  6. Chen, G.Y., Bui, T.D. and Krzyżak, A. (2009), "Invariant pattern recognition using radon, dual-tree complex wavelet and Fourier transforms", Pattern Recogn., 42(9), 2013-2019. https://doi.org/10.1016/j.patcog.2008.10.008
  7. Chen, H.-L.R., Zhang, B., Alvin, M.A. and Lin, Y. (2012), "Ultrasonic detection of delamination and material characterization of thermal barrier coatings", J. Therm. Spray Techn., 21(6), 1184-1194. https://doi.org/10.1007/s11666-012-9811-9
  8. Durgutlu, A., Gulenc, B. and Findik, F. (2005), "Examination of copper/stainless steel joints formed by explosive welding", Mater. Des., 26(6), 497-507. https://doi.org/10.1016/j.matdes.2004.07.021
  9. Feng, Z. and Zuo, M.J. (2013), "Fault diagnosis of planetary gearboxes via torsional vibration signal analysis", Mech. Syst. Signal Process., 36(2), 401-421. https://doi.org/10.1016/j.ymssp.2012.11.004
  10. Findik, F. (2011), "Recent developments in explosive welding", Mater. Des., 32(3), 1081-1093. https://doi.org/10.1016/j.matdes.2010.10.017
  11. Gulenc, B. (2008), "Investigation of interface properties and weldability of aluminum and copper plates by explosive welding method", Mater. Des., 29(1), 275-278. https://doi.org/10.1016/j.matdes.2006.11.001
  12. Hanke, R., Fuchs, T. and Uhlmann, N. (2008), "X-ray based methods for non-destructive testing and material characterization", Nucl. Instrum. Meth. in Physics Research Section A, 591(1), 14-18. https://doi.org/10.1016/j.nima.2008.03.016
  13. He, Z.J., Chen, X.F. and Zhang, X.L. (2010), "Fault diagnosis based on support vector machines with parameter optimization by an ant colony algorithm", Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 224(1), 217-229. https://doi.org/10.1243/09544062JMES1731
  14. Hester, D. and Gonzalez, A. (2012), "A wavelet-based damage detection algorithm based on bridge acceleration response to a vehicle", Mech. Syst. Signal Process., 28, 145-166. https://doi.org/10.1016/j.ymssp.2011.06.007
  15. Hu, H. (2011), "Multiscale illumination normalization for face recognition using dual-tree complex wavelet transform in logarithm domain", Computer Vis. Image Und., 115(10), 1384-1394. https://doi.org/10.1016/j.cviu.2011.06.004
  16. Jayaswal, P., Verma, S.N. and Wadhwani, A.K. (2010), "Application of ANN, Fuzzy Logic and Wavelet Transform in machine fault diagnosis using vibration signal analysis", J. Qual. Maint. Eng., 16(2), 190-213. https://doi.org/10.1108/13552511011048922
  17. Kaya, Y. and Kahraman, N. (2013), "An investigation into the explosive welding/cladding of Grade A ship steel/AISI 316L austenitic stainless steel", Mater. Des., 52, 367-372. https://doi.org/10.1016/j.matdes.2013.05.033
  18. Kingsbury, N.G. (1998), "The dual-tree complex wavelet transform: a new technique for shift invariance and directional filters", Image Processing, 319-322.
  19. Kingsbury, N. (2001), "Complex wavelets for shift invariant analysis and filtering of signals", Appl. Comput. Harmon. Anal., 10(3), 234-253. https://doi.org/10.1006/acha.2000.0343
  20. Kahraman, N., Gulenc, B. and Findik, F. (2005), "Joining of titanium/stainless steel by explosive welding and effect on interface", J. Mater. Process. Techn., 169(2), 127-133. https://doi.org/10.1016/j.jmatprotec.2005.06.045
  21. Kahraman, N., Gulenc, B. and Findik, F. (2007), "Corrosion and mechanical-micro structural aspects of dissimilar joints of Ti-6Al-4V and Al plates", Int. J. Impact Eng., 34(8), 1423-1432. https://doi.org/10.1016/j.ijimpeng.2006.08.003
  22. Li, X., Ouyang, G. and Liang, Z. (2008), "Complexity measure of motor current signals for tool flute breakage detection in end milling", Int. J. Mach. Tools Manuf., 48(3), 371-379. https://doi.org/10.1016/j.ijmachtools.2007.09.008
  23. Lihong, Z., Ying, S., Yushi, Z., Cheng, Z. and Yi, Z (2009), "Face recognition based on multi-class SVM", Proceedings of Control and Decision Conference, CCDC'09, IEEE, pp. 5871-5873.
  24. Liu, T.Y., Chiang, W.L., Chen, C.W., Hsu, W.K., Lu, L.C. and Chu, T.J. (2010), "Identification and monitoring of bridge health from ambient vibration data", J. Vib. Control, 17(4), 589-603. https://doi.org/10.1177/1077546309360049
  25. Mousawi, S.A.A.A. and Sartangi, P.F. (2009), "Experimental investigation of explosive welding of cp-titanium/AISI 304 stainless steel", Mater. Des., 30(3), 459-468. https://doi.org/10.1016/j.matdes.2008.06.016
  26. Nair, U., Krishna, B.M., Namboothiri, V. and Nampoori, V. (2010), "Permutation entropy based real-time chatter detection using audio signal in turning process", Int. J. Adv. Manuf. Techn., 46(1-4), 61-68. https://doi.org/10.1007/s00170-009-2075-y
  27. Nicolaou, N. and Georgiou, J. (2012), "Detection of epileptic electroencephalogram based on Permutation Entropy and Support Vector Machines", Expert Syst. Appl., 39(1), 202-209. https://doi.org/10.1016/j.eswa.2011.07.008
  28. Ren, W.-X. and Sun, Z.-S. (2008), "Structural damage identification by using wavelet entropy", Eng. Struct., 30(10), 2840-2849. https://doi.org/10.1016/j.engstruct.2008.03.013
  29. Scholey, J.J., Wilcox, P.D., Wisnom, M.R. and Friswell, M.I. (2010), "Quantitative experimental measurements of matrix cracking and delamination using acoustic emission", Compos. Part A: Appl. Sci. Manuf., 41(5), 612-623. https://doi.org/10.1016/j.compositesa.2010.01.008
  30. Selesnick, I.W., Baraniuk, R.G. and Kingsbury, N.C. (2005), "The dual-tree complex wavelet transform", Signal Process. Magazine, IEEE, 22(6), 123-151. https://doi.org/10.1109/MSP.2005.1550194
  31. Sugumaran, V., Sabareesh, G. and Ramachandran, K. (2008), "Fault diagnostics of roller bearing using kernel based neighborhood score multi-class support vector machine", Expert Syst. Appl., 34(4), 3090-3098. https://doi.org/10.1016/j.eswa.2007.06.029
  32. Tang, X., Zhuang, L., Cai, J. and Li, C. (2010), "Multi-fault classification based on support vector machine trained by chaos particle swarm optimization", Knowledge-Based Syst., 23(5), 486-490. https://doi.org/10.1016/j.knosys.2010.01.004
  33. Tiwari, R., Gupta, V.K. and Kankar, P.K. (2013), "Bearing fault diagnosis based on multi-scale permutation entropy and adaptive neuro fuzzy classifier", J. Vib. Control.
  34. Wang, L., Yang, Z. and Waters, T.P. (2010a), "Structural damage detection using cross correlation functions of vibration response", J. Sound Vib., 329(24), 5070-5086. https://doi.org/10.1016/j.jsv.2010.06.020
  35. Wang, Y., He, Z. and Zi, Y. (2010b), "Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform", Mech. Syst. Signal Process., 24(1), 119-137. https://doi.org/10.1016/j.ymssp.2009.06.015
  36. Wronka, B. (2010), "Testing of explosive welding and welded joints: joint mechanism and properties of explosive welded joints", J. Mater. Sci., 45(15), 4078-4083. https://doi.org/10.1007/s10853-010-4494-4
  37. Yan, G., Duan, Z., Ou, J. and De Stefano, A. (2010), "Structural damage detection using residual forces based on wavelet transform", Mech. Syst. Signal Process., 24(1), 224-239. https://doi.org/10.1016/j.ymssp.2009.05.013
  38. Yan, R., Liu, Y. and Gao, R.X. (2012), "Permutation entropy: A nonlinear statistical measure for status characterization of rotary machines", Mech. Syst. Signal Process., 29, 474-484. https://doi.org/10.1016/j.ymssp.2011.11.022
  39. Zareie Rajani, H.R. and Akbari Mousavi, S.A.A. (2012), "The effect of explosive welding parameters on metallurgical and mechanical interfacial features of Inconel 625/plain carbon steel bimetal plate", Mater. Sci. Eng.: A, 556, 454-464. https://doi.org/10.1016/j.msea.2012.07.012

피인용 문헌

  1. Dual-Tree Complex Wavelet Transform and Twin Support Vector Machine for Pathological Brain Detection vol.6, pp.12, 2016, https://doi.org/10.3390/app6060169
  2. A novel method to aging state recognition of viscoelastic sandwich structures vol.21, pp.6, 2016, https://doi.org/10.12989/scs.2016.21.6.1183
  3. Mono-modal feature extraction for bonding quality detection of explosive clad structure with optimized dual-tree complex wavelet transform vol.392, 2017, https://doi.org/10.1016/j.jsv.2016.12.020
  4. A novel method for bonding state detection of explosive clad structure based on the Hilbert envelop energy ratio of mono-model signals vol.27, pp.11, 2018, https://doi.org/10.1088/1361-665X/aae124
  5. Feasibility study of bonding state detection of explosive composite structure based on nonlinear output frequency response functions vol.24, pp.4, 2015, https://doi.org/10.12989/scs.2017.24.4.391