Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR: "References
1. Jack L.B., Nandi A.K., McCormick A.C. Diagnosis of rolling element bearing faults using radial basis function net works. Appl. Signal Process. 1999;6:25–32.
2. Li L.J., Zhang Z.S., He Z.J. Research of mechanical system fault diagnosis based on support vector data description. J. Xi’an Jiiaotong Univ. 2003;37:910–913.
3. Li G., Xing S.B., Xue H.F. Comparison on pattern analysis performance of SVM and RVM based on RBF kernel. Appl. Res. Comput. 2009;26:1782–1784.
4. Ezenwoye O., Sadjadi S.M. Robust BP EL2: Transparent autonomization in business processes through dynamic proxies. Proceedings of the 8th International Symposium on Autonomous Decentralized Systems; Sedona, AZ, USA. March 21–23, 2007; pp. 17–24.
5. Jack L.B., Nandi A.K. Support vector machines for detection and characterization of rolling element bearing faults. J. Mech. Eng. Sci. 2001;215:1065–1074"
'via Blog this'
No comments:
Post a Comment