Empirical Mode Decomposition And Rough Set Attribute Reduction For Ultrasonic Flaw Signal Classification

1K. Lee and V. Estivill Castro, “Feature extraction and gating techniques for ultrasonic shaft signal classification”, Applied Soft Computing, Vol. 7, No. 1, pp. 156-165, 2007.10.1016/j.asoc.2005.05.003Search in Google Scholar

2Kyungmi Lee, “Feature Extraction Schemes for Ultrasonic Non-destructive Testing Inspections”, Advances in Information Sciences and Service Sciences, Vol. 3, No. 3, pp. 125-135, 2011.10.4156/aiss.vol3.issue3.16Search in Google Scholar

3A.A. Anastassopoulos, V.N. Nikolaidis and T.P. Philippidis, “A Comparative Study of Pattern Recognition Algorithms for Classification of Ultrasonic Signals”, Neural Computing & Applications, Vol. 8, No. 1, pp. 53-66, 1999.10.1007/s005210050007Search in Google Scholar

4A. Shelke, T. Kundu, U. Amjad, K. Hahn and W. Grill, “Mode-selective excitation and detection of ultrasonic guided waves for delamination detection in laminated aluminum plates”, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 58, No. 3, pp. 567-577, 2011.10.1109/TUFFC.2011.183921429847Search in Google Scholar

5K. Lee, “A Hybrid Classification Approach to Ultrasonic Shaft Signals”, Lecture Notes in Computer Science, Vol. 3339, pp. 11-17, 2005.Search in Google Scholar

6K. Lee, “Feature extraction schemes for ultrasonic signal processing”, Proc. IEEE 5th International Conference on Computer Sciences and Convergence Information Technology, pp. 366-372, 2010.Search in Google Scholar

7M. Cacciola, S. Calcagno and F.C. Morabito, “Computational intelligence aspects for defect classification in aeronautic composites by using ultrasonic pulses”, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 55, No. 4, pp. 870-878, 2008.10.1109/TUFFC.2008.72218467232Search in Google Scholar

8Zhao Chihang, Zhong Xin, Dang Qian and Zhao Liye, “De-noising Signal of the Quartz Flexural Accelerometer by Multiwavelet Shrinkage”, International Journal on Smart Sensing and Intelligent Systems, Vol. 6, No. 1, pp. 191-208, 2013.10.21307/ijssis-2017-535Search in Google Scholar

9S. Sambath, P. Nagaraj and N. Selvakumar, “Automatic Defect Classification in Ultrasonic NDT Using Artificial Intelligence”, Journal of nondestructive evaluation, Vol. 30, No. 1, pp. 20-28, 2011.10.1007/s10921-010-0086-0Search in Google Scholar

10H. Hashim, S. Ramli, N. Wahi, M. S. Sulaiman and N. Hassan, “Recognition of Psioriasis Features via Daubechies D8 Wavelet Technique”, International Journal on Smart Sensing and Intelligent Systems, Vol. 6, No. 2, pp. 711-732, 2013.10.21307/ijssis-2017-562Search in Google Scholar

11G.P.P. Gunarathne and Y. Qureshi, “Development of a synthetic A-scan technique for ultrasonic testing of pipelines”, IEEE Transactions on Instrumentation and Measurement, Vol. 54, No. 1, pp. 192-199, 2005.10.1109/TIM.2004.839750Search in Google Scholar

12U.A. Qidwai, “Autonomous corrosion detection in gas pipelines: a hybrid-fuzzy classifier approach using ultrasonic nondestructive evaluation protocols”, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 56, No. 12, pp. 2650-2665, 2009.Search in Google Scholar

13N. Bochud, A.M. Gomez and G. Rus, “Robust parametrization for non-destructive evaluation of composites using ultrasonic signals”, Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1789-1792, 2011.Search in Google Scholar

14X.J. Zhou and T.S. Dillon, “A statistical-heuristic feature selection criterion for decision tree induction”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, No. 8, pp. 834-841, 1991.10.1109/34.85676Search in Google Scholar

15Sylvie Legendre, Daniel Massicotte, Jacques Goyette and Tapan K. Bose, “Wavelet Transform Based Method of Analysis for Lamb-Wave Ultrasonic NDE Signals”, IEEE Transactions on Instrumentation and Measurement, Vol. 49, No. 3, pp. 524-530, 2000.10.1109/19.850388Search in Google Scholar

16C. Damerval and S. Meignen, “A Fast Algorithm for Bidimensional EMD”, IEEE Signal Processing Letters, Vol. 12, No. 10, pp. 701-704, 2005.10.1109/LSP.2005.855548Search in Google Scholar

17Yanhua Zhang, Lu Yang and Jianping Fan, “Study on feature extraction and classification of ultrasonic flaw signals”, WSEAS Transactions on Mathmatics, Vol. 9, No. 7, pp. 529-538, 2010.Search in Google Scholar

18T. Chen, P. Que and Q. Zhang, “Ultrasonic signal identification by empirical mode decomposition and Hilbert transform”, Review of scientific instruments, Vol. 76, No. 8, pp. 1-6, 2005.10.1063/1.2006367Search in Google Scholar

19Kiran George and Chien-In Henry Chen, “Biologically-Inspired Signal Processor Using Lateral Inhibition and Integrative Function Mechanisms for High Instantaneous Dynamic Range”, International Journal On Smart Sensing and Intelligent Systems, vol. 4, no. 4, pp. 547-567, 2011.10.21307/ijssis-2017-456Search in Google Scholar

20Richard Jensen and Qiang Shen, “New Approaches to Fuzzy-Rough Feature Selection”, IEEE Transactions on Fuzzy Systems, Vol. 17, No. 4, pp. 824-838, 2009.10.1109/TFUZZ.2008.924209Search in Google Scholar

21Ye Hongxian, Li Wenchang and Hu Xiaoping, “A Blind Source Separation Method for Convolved Mixtures by Non-Stationary Vibration Signals”, International Journal On Smart Sensing and Intelligent Systems, Vol. 6, No. 3, pp. 973-992, 2013.10.21307/ijssis-2017-575Search in Google Scholar

22S. Iyer, S.K. Sinha and B.R. Tittmann, “Ultrasonic signal processing methods for detection of defects in concrete pipes”, Automation in Construction, Vol. 22, pp. 135-148, 2011.10.1016/j.autcon.2011.06.012Search in Google Scholar

23Zhao Chihang, Zhong Xin, Dang Qian, Zhao Liye, “De-noising Signal of the Quartz Flexural Accelerometer by Multiwavelet Shrinkage”, International Journal On Smart Sensing and Intelligent Systems, Vol. 6, No. 1, pp. 191-208, 2013.10.21307/ijssis-2017-535Search in Google Scholar