A Blind Source Separation Method for Convolved Mixtures by Non-Stationary Vibration Signals
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References
- A. Ypma, “Learning Methods for Machine Vibration Analysis and Health Monitoring”, Doctor of Engineering thesis, Pattern Recognition Group, Dept. of Applied Physics, Delft University of Technology, Netherlands, 1998.
- Z. N. Li, W. B. Liu and X. B. YI, “Underdetermined Blind Source Separation Method of Machine Faults Based on Local Mean Decomposition”, Chinese Journal of Mechanical Engineering, Vol. 47, No.7, pp. 97-102, Apr. 2011.
- W. F. Wu, X. H. Chen and X. J. SU, “Blind Source Separation of Single-channel Mechanical Signal Based on Empirical Mode Decomposition”, Chinese Journal of Mechanical Engineering, Vol. 47, No.4, pp. 12-16, Apr. 2011.
- G. Colas, “Blind Source Separation: a Tool for Rotating Machine Monitoring by Vibration Analysis” International Journal of Sound and Vibration, Vol. 248, No.5, pp. 865-885, Dec. 2001.
- G. Guillaume and S. Christine, “Blind Source Separation: A New Pre-Processing Tool for Rotating Machines Monitoring”? IEEE Transactions on Instrumentation and Measurement, Vol. 52, No.3, pp. 790-795, June. 2003.
- H. X. Ye, S. X. Yang and J. X. Yang, “Temporal Blind Source Separation Algorithm for Convolution Mixtures with Multi Vibration Sources”, Chinese Journal of Mechanical Engineering, Vol. 45, No. 1, pp.189-194,199, Jan. 2009.
- M. Parvaix and L.Girin, “Informed Source Separation of Linear Instantaneous UnderDetermined Audio Mixtures by Source Index Embedding”, IEEE Transactions on Audio, Speech and Language Processing, Vol. 19, No. 6, pp. 1721-1733, Aug. 2011.
- [8]P. Tichavsky and Z. Koldovsky, “Weight Adjusted Tensor Method for Blind Separation of Underdetermined Mixtures of Nonstationary Sources”, IEEE Transactions on Signal Processing, Vol. 59, No. 3, pp. 1037-1047, Mar. 2011.
- D. Farina, M. F. Lucas and C. Doncarli, “Optimized Wavelets for Blind Separation of Nonstationary Surface Myoelectric Signals”, IEEE Transactions on Biomedical Engineering, Vol. 55, No. 1, pp. 78-86, Jan. 2008.
- R. Guidara, S. Hosseini and Y. Deville, “Blind Separation of Nonstationary Markovian Sources Using an Equivariant Newton–Raphson Algorithm”, IEEE Signal Processing Letters, Vol. 16, No. 5, pp. 426-429, May. 2009.
- H. Rimminen, J. Lindstrom and R. Sepponen, “Positioning Accuracy and Multi-Target Separation With a Human Tracking System Using Near Field Imaging”, International Journal on Smart Sensing and Intelligent Systems, Vol. 2, No.1, pp. 156–175, Mar. 2009.
- B. Makkiabadi, D. Jarchi and S. Sanei, “A New Time Domain Convolutive BSS of Heart and Lung Sounds, Acoustics”, IEEE International Conference on Speech and Signal Processing (ICASSP), Vol. 25-30, pp. 605 – 608, Mar. 2012, Kyoto, Japan.
- G. P. Cedric, C. Marco and C. Brunner, C. Jutten and P. Gert, “Nonstationary Brain Source Separation for Multiclass Motor Imagery”, IEEE Transactions on Biomedical Engineering, Vol. 57, No. 2, pp.469-478, Feb. 2010.
- S. Choi and A. Cichocki, “Blind Separation of Nonstationary Sources in Noisy Mixtures”, International Journal of Electronics Letters, Vol. 36, No.9, pp. 848-849, Apr. 2000.
- T. Ishibashi, K. Inoue and H. Gotanda, “Studies on Estimation of the Sources Number in Blind Source Separation Problems”, International Joint Conference SICE-ICASE, pp. 5169-5174, Oct. 2006, Busan, Korea.
- N. Pan, X. Wu and Y. L. Chi, X. Q. Liu and C. Liu, “Machine Fault Diagnosis Based on Frequency-Domain Blind Deconvolution”. Proceedings of 2011 International Conference on Modeling, Identification and Control, pp. 63-68, June. 2011, Shanghai, China.
- Y. Y. Na and J. Yu, “Kernel and Spectral Methods for Solving the Permutation Problem in Frequency Domain BSS”, WCCI 2012 IEEE World Congress on Computational Intelligence, pp.1-8, June. 2012, Brisbane, Australia.
- S. M. Naqvi, Y. Zhang, T. Tsalaile, S. Saneiz and J. A. Chambers, “Evaluation of Emerging Frequency Domain Convolutive Blind Source Separation Algorithms Based on Real Room Recordings”, 5th IEEE Sensor Array and Multichannel Signal Processing Workshop, pp. 345 - 348, July. 2008, Darmstadt, Germany.
- T. T. Liu, X. M. Ren, “A Blind De-convolution Technique for Machine Fault Diagnosis”, 2009 Second International Conference on Information and Computing Science”, pp. 232-235, May. 2009, Manchester, England, UK.
- I. Russell, J. T. Xi and A. Mertins, “Blind Source Separation of Nonstationary Convolutively Mixed Signals in the Subband Domain”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vol. 5, pp. 481-484, May. 2004, Quebec, Canada.
- S. B. Han, J. Cui and P. Li, “Post-processing for Frequency-domain Blind Source Separation in Hearing Aids”, 7th International Conference on Information, Communications and Signal Processing, pp. 1 – 5, 8-10, Dec. 2009, Beijing, China.
- T. Nguyen and C. Jutten, “Blind Source Separation for Convolutive Mixtures”, IEEE Transactions on Signal Processing, Vol. 45, No. 2, pp. 209-229, July. 1995.
- Advantech CO. LTD, PCL-1800 Manual, 2005.
DOI: https://doi.org/10.21307/ijssis-2017-575 | Journal eISSN: 1178-5608
Language: English
Page range: 973 - 992
Submitted on: Nov 2, 2012
Accepted on: May 3, 2013
Published on: Jun 5, 2013
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year
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© 2013 Ye Hongxian, Li Wenchang, Hu Xiaoping, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.