Semi-supervised label consistent dictionary learning for machine fault classification

Proceeding - 2015 IEEE International Conference on Industrial Informatics, INDIN 2015

Volumn , Issue , 2015, Pages 1124-1129

  Jiang, Weiming ^a   Zhang, Zhao ^a,b   Li, Fanzhang ^a,b   Zhang, Li ^a,b   Zhao, Mingbo ^c  

^a SOOCHOW UNIVERSITY   (China)

^b NANJING UNIVERSITY   (China)

^c CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

label consistent K SVD; label propagation; Machine fault classification; semi supervised learning

Indexed keywords

INFORMATION SCIENCE; SUPERVISED LEARNING;

CLASS INFORMATION; COMPUTATIONALLY EFFICIENT; DICTIONARY LEARNING; DISCRIMINATIVE DICTIONARIES; LABEL PROPAGATION; MACHINE FAULTS; PRE-PROCESSING STEP; SEMI- SUPERVISED LEARNING;

CLASSIFICATION (OF INFORMATION);

EID: 84949513051     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/INDIN.2015.7281893     Document Type: Conference Paper

References (25)

1. H. Liu, C. Liu, Y. Huang, "Adaptive feature extraction using sparse coding for machinery fault diagnosis, " Mechanical Systems and SignalProcessing. vol. 25, pp. 558-574, 2011.
2. X. Jin, F. Yuan, T. W. S. Chow and M. Zhao "Weighted local and global regressive mapping: A new manifold learning method for machine fault classification, " Engineering Applications of Artificial Intelligence, pp. 118-128, 2014.
3. H. Liu, Y. Li, N. Li and C. Liu, "Robust Visual Monitoring of Machine Condition with Sparse Coding and Self-Organizing Map, " Intelligent Robotics and Applications, Lecture Notes in Computer Science, vol. 6424, pp. 642-653, 2010.
4. J. Yang, J. Wright, T. Huang, Y. Ma, "Image Superresolution as Sparse Representation of Raw Patches, " Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
5. M. Ranzato, C. Poultney, S. Chopra, and Y. LeCun, "Efficient Learning of Sparse Representations with an Energy-Based Model, " Proc. Conf. Neural Information Processing Systems, 2006.
6. J. Yang and M. Yang, "Top-Down Visual Saliency via Joint CRF and Dictionary Learning, " Proc. IEEE Conf. Computer Vision and PatternRecognition, 2012.
7. M. Elad and M. Aharon, "Image Denosing via Sparse and Redundant Representations over Learned Dictionaries, " IEEE Trans. ImageProcessing, vol. 54, no. 12, pp. 3736-3745, Dec. 2006.
8. J. Wright, M. Yang, A. Ganesh, S. Sastry, Y. Ma, "Robust Face Recognition via Sparse Representation, " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 2, pp. 210-227, Feb. 2009.
9. D. Bradley and J. Bagnell, "Differential Sparse Coding, " Proc. Conf. Neural Information Processing Systems, 2008.
10. Z. L. Jiang, Z. Lin, L. S. Davis, "Label Consistent K-SVD: Learning A Discriminative Dictionary for Recognition", IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 35, no. ll. pp. 2651-2664, 2013.
11. J. Mairal, F. Bach, and J. Ponce, "Task-Driven Dictionary Learning, " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 34, no. 4, pp. 791-804, Apr. 2012.
12. M. Aharon, M. Elad, A. Bruckstein, "K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation, " IEEE Trans. Signal Processing, vol. 54, no. 1, pp. 4311-4322, Nov. 2006.
13. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong, "Locality-Constrained Linear Coding for Image Classification, " Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2010.
14. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman, "Discriminative Learned Dictionaries for Local Image Analysis, " Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
15. D. Pham and S. Venkatesh, "Joint Learning and Dictionary Construction for Pattern Recognition, " Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
16. Q. Zhang and B. Li, "Discriminative K-SVD for Dictionary Learning in Face Recognition, " Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2010.
17. K. Engan, S. Aase, and J. Husoy, "Frame Based Signal Compression Using Method of Optimal Directions (mod), " Proc. IEEE Int'l Symp. Circuits and Systems, 1999.
18. T. Kohonen, "Self-Organizing Maps, " 3rd end. Springer, Heidelberg. 2001.
19. F. P. Nie, S. M. Xiang, Y. Liu, and C. S. Zhang, "A general graph-based semi-supervised learning with novle class discovery, " Neuaral ComputingApplications, vol. 19, no. 4, pp. 549-555, 2010
20. E. Achtert, C. Bohm, P. Kunath, A. Pryakhin, and M. Eenz, "Efficient reverse k-nearest neighbor search in arbitrary metric spaces, " SIGMOD, pp. 515-526, 2006.
21. G. Paul, K. Jan, M. Wojciech, and D. Fredo, "View-dependent precomputed light transport using nonlinear Gaussian function approximations, " ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, pp. 7-14, 2006.
22. M. B. Zhao, X. H. Jin, Z. Zhang, and B. Li, "Fault diagnosis of rolling element bearings via discriminative subspace learning: Visualization and classification, " Expert Systems with Applications, vol. 41, pp. 3391-3401, 2014.
23. S. Roweis and L. Saul, "Nonlinear dimensionality reduction by locally linear embedding, " Science, vol. 290, no. 5500, pp. 2323-2326. 2000.
24. J. Tropp and A. Gilbert, "Signal Recovery from Random Measurements via Orthogonal Matching Pursuit, " IEEE Trans. Information Theory, vol. 53, no. 12, pp. 4655-4666, Dec. 2007.
25. Y. F. Wang and P. J. Kootsookos, "Modeling of low shaft speed bearing faults for condition monitoring, " Mech. Syst. Sig. Process. vol. 12, no. 3, pp. 415-426, 1998.