Life grade recognition method based on supervised uncorrelated orthogonal locality preserving projection and K-nearest neighbor classifier

Neurocomputing

Volumn 138, Issue , 2014, Pages 271-282

  Li, Feng ^a   Wang, Jiaxu ^a   Tang, Baoping ^b   Tian, Daqing ^a  

^a SICHUAN UNIVERSITY   (China)

^b CHONGQING UNIVERSITY   (China)

Author keywords

Feature compression; K nearest neighbor classifier (KNNC); Life grade recognition; Rotating machine; Supervised uncorrelated orthogonal locality preserving projection (SUOLPP); Time frequency domain feature set

Indexed keywords

EIGENVALUES AND EIGENFUNCTIONS; FEATURE EXTRACTION; FREQUENCY DOMAIN ANALYSIS; SUPPORT VECTOR MACHINES;

FEATURE COMPRESSION; K-NEAREST NEIGHBOR CLASSIFIER; LIFE GRADE RECOGNITION; LOCALITY PRESERVING PROJECTIONS; ROTATING MACHINE; TIME FREQUENCY DOMAIN;

LEARNING ALGORITHMS;

ARTICLE; CALCULATION; CLASSIFICATION ALGORITHM; CLUSTER ANALYSIS; CONTROLLED STUDY; FUZZY C MEANS CLUSTERING; K NEAREST NEIGHBOR CLASSIFIER; LIFE GRADE RECOGNITION METHOD; MACHINE LEARNING; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MEASUREMENT ACCURACY; PRIORITY JOURNAL; SUPERVISED UNCORRELATED ORTHOGONAL LOCALITY PRESERVING PROJECTION; SUPPORT VECTOR MACHINE;

EID: 84899736273     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.01.037     Document Type: Article

References (31)

1. Zhang Y.W., Chai T.Y., Li Z.M. Modelling and monitoring of dynamic processes. IEEE Trans. Neural Networks Learn. System 2012, 23:277-284.
2. Zhang Y.W., Zhou H., Qin S.J., Chai T.Y. Decentralized fault diagnosis of large-scale processes using multiblock kernel partial least squares. IEEE Trans. Ind. Informatics 2010, 1:3-12.
3. Byon E., Ding Y. Season-dependent condition-based maintenance for a wind turbine using a partially observed Markov decision process. IEEE Trans. Power Syst. 2010, 1823-1834.
4. Nielsen J.J., Sørensen J.D. On risk-based operation and maintenance of offshore wind turbine components. Reliab. Eng. Syst. Saf. 2011, 96:218-229.
5. Zhang X.L., Chen X.F., Li B., He Z.J. Review of life prediction for mechanical major equipments. J. Mech. Eng. 2011, 47(11):100-116. (in Chinese).
6. Lei Y.G., He Z.J., Zi Y.Y. Fault diagnosis based on novel hybrid intelligent model. J. Mech. Eng. 2008, 44(7):112-117. (in Chinese).
7. Tang B.P., Li F., Qin Y. Fault diagnosis model based on feature compression with Orthogonal Locality Preserving Projection. Chin. J. Mech. Eng. 2011, 24(5):897-904.
8. Tang B.P., Liu W.Y., Song T. Wind turbine fault diagnosis based on Morlet wavelet transformation and Wigner-Ville distribution. Renew. Energy 2010, 35(12):2862-2866.
9. Qin Y., Tang B.P., Wang J.X. Higher-density dyadic wavelet transform and its application. Mech. Syst. Signal Process. 2010, 24(3):823-834.
10. Li F., Tang B.P., Yang R.S. Rotating machine fault diagnosis using dimension reduction with linear local tangent space alignment. Measurement 2013, 46:2525-2539.
11. J.P. Burg, Maximum Entropy Spectral Analysis (Ph.D. dissertation), Department of Geophysics, Stanford University, California, 1975.
12. Zhou Y.L., Liu C.X., Zhao P., Sun B., Hong W.P. Fault diagnosis methods for centrifugal pump based on autoregressive and continuous hidden Markov model. Proc. CSEE 2008, 28(20):88-93. (In Chinese).
13. Cox T.F., Cox M.A. Multi-dimensional Scaling 1994, Chapman & Hall, London.
14. Hyvarinen A., Oja E. Independent component analysis: algorithms and applications. Neural Networks 2000, 13(425):411-430.
15. Wong W.K., Zhao H.T. Supervised optimal locality preserving projection. Pattern Recognit. 2012, 45:186-197.
16. Li Y.Z., Luo D.Y., Liu S.Q. Orthogonal discriminant linear local tangent space alignment for face recognition. Neurocomputing 2009, 72:1319-1323.
17. Huang H., Li J.W., Liu J.M. Enhanced semi-supervised local Fisher discriminant analysis for face recognition. Future Gener. Comput. Syst. 2012, 28:244-253.
18. Jiang Q.S., Jia M.P., Hu J.Z., Xu F.Y. Machinery fault diagnosis using supervised manifold learning. Mech. Syst. Signal Process. 2009, 23:2301-2311.
19. Li M., Xu J.W., Yang J.H., Yang D.B., Wang D.D. Multiple manifolds analysis and its application to fault diagnosis. Mech. Syst. Signal Process. 2009, 23:2500-2509.
20. Belhumeur P.N., Hespanha J.P., Kriegman D.J. Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE. Trans. Pattern Anal. Mach. Intell. 1997, 19(7):711-720.
21. He X.F., Niyogi P. Locality preserving projections. Proceedings of the 17th Annual Conference on Neural Information Processing Systems 2003, 153-160. The MIT Press, Cambridge, USA.
22. X.M. Liu, J.W. Yin, Z.L. Feng, J.X. Dong, L. Wang, Orthogonal neighborhood preserving embedding for face recognition, in: Proceedings of the IEEE International Conference on Image Processing, ICIP 2007, New York, USA, 2007, pp.133-136.
23. Cai D., He X.F., Han J.W., Zhang H.J. Orthogonal laplacianfaces for face recognition. IEEE Trans. Image Process. 2006, 15(11):3608-3614.
24. X.P. Yu, X.G. Yu, Novel text classification based on k-nearest neighbor, in: Proceedings of Sixth International Conference on Machine Learning Cybernetics, Hong Kong, China, 2007, pp. 3425-3430.
25. Deng L., Hu X.L., Li F., Tang B.P. Support vector machines-based method for restraining end effects of B-spline empirical mode decomposition. J. Vib. Meas. Diagnosis 2011, 31(3):344-347. (+398 (in Chinese).
26. Andrejić M., Bojović N., Kilibarda M. Benchmarking distribution centres using principal component analysis and data envelopment analysis: a case study of Serbia. Exp. Syst. Appl. 2013, 40:3926-3933.
27. Bosch P., López J., Ramírez H., Robotham H. Support vector machine under uncertainty: an application for hydroacoustic classification of fish-schools in Chile. Exp. Syst. Appl. 2013, 40:4029-4034.
28. Park J.G., Kim K.J. Design of a visual perception model with edge-adaptive Gabor filter and support vector machine for traffic sign detection. Exp. Syst. Appl. 2013, 40:3679-3687.
29. Xu C., Zhang P.L., Ren G.Q., Fu J.P. Engine wear fault diagnosis based on improved semi-supervised fuzzy C-means clustering. J. Mech. Eng. 2011, 47(17):55-60. (in Chinese).
30. Ridder D.D., Duin R.P.W. Locally Linear Embedding for Classification 2002, Delft University of Technology, Delft, The Netherlands, (Technical Report PH-2002-01).
31. Pedrycz W. Algorithms of fuzzy clustering with partial supervision. Pattern Recognit. Lett. 1985, 3(1):13-20.