Entwicklung von Datenanalyseverfahren für die Qualitäts - IAS ...

[43] Somervuo, P.: Experiments with linear and nonlinear feature transformations in HMM based phone
recognition. In Proceedings 2000 IEEE International Conference on Acoustics Speech and Signal Processing,
Band 1, S. 52-55, 2003.
[44] Somervuo, P; Chen, B; Zhu, Q.: Feature Transformations and Combinations for Improving ASR Performance.
In Proceedings of EUROSPEECH 2003, Geneva.
[45] Lee, J.-H.; Jung, H.-Y.; Lee T.-W.; Lee, S.-Y.: Speech feature extraction using independent component
analysis. In Proceedings 2000 IEEE International Conference on Acoustics Speech and Signal Processing
(ICASSP 2000), Band 3, S. 1631 - 1634, 2000.
[46] Smyth, P.: Hidden Markov models and neural networks for fault detection in dynamic systems. Neural
Networks for Signal Processing, 6-9 Sept. 1993, Proceedings of the 1993 IEEE-SP Workshop, Page(s): 582-
592.
[47] D. Zhang, Y. Zeng, X. Zhou, Cheng Y.: The pattern recognition of non-destructive testing based on hmm. in
Proc. 4 th World Congre World Congress on Intelligent Control and Automation (Cat. No. 02EX527), 2002, vol.
3, pp. 2198–2202, Piscataway, NJ, USA.
[48] P. Baruah und R. B. Chinnam: „Hmms for diagnostics and prognostics in machining processes,” in Proc. 57th
Meeting of the Society for Machinery Failure Prevention Technology, 2003, pp. 389–398, Virginia Beach,
USA.
[49] A. R. Taylor und S. R. Duncan: „A comparison of techniques for monitoring process faults,” in Proc. Conf.
Control Systems, 2002, pp. 323–327, Stockholm, SE.
[50] H. Y. K. Lau: „A hidden markov model-based assembly contact recognition system,” Mechatronics, vol. 13(8-
9), pp. 1001–1023, 2003, ISSN 0957-4158.
[51] Xiaodong Zhang, Xu, R., Chiman Kwan, Liang, S. Y., Quilin Xie, Haynes, L.: An integrated approach to
bearing fault diagnostics and prognostics. In Proc. American Control Conference, Bd. 4, S. 2750-2755, 2005.
[52] Roshan Rammohan et al.: "Exploratory Investigations for Intelligent Damage Prognosis using Hidden Markov
Models". In Proc. IEEE Int’l Conference on Systems, Man and Cybernetics, Bd. 2, S. 1524-1529, 2005.
[53] Kothamasu et al.: "Comparison of Selected Model Evaluation Criteria for Maintenance Applications", In
Structural Health Monitoring; 3: 213-224, 2004.
[54] Qiang Miao et al.: "A Novel Hybrid System with Neural Networks and Hidden Markov Models in Fault
Diagnosis". In Proc. MICAI: Advances in Artificial Intelligence, S. 513-521, 2006.
[55] Ming Dong et al.: "Equipment health diagnosis and prognosis using hidden semi-Markov models", 2006
[56] Qiang Miao et al.: "Condition monitoring and classification of rotating machinery using wavelets and hidden
Markov models". In: Mechanical Systems and Signal Processing, Bd. 21, Ausgabe 2, S. 840-855, 2007.
[57] Ocak, H.; K. A. Loparo K. A.; Discenzo, F. M.: “Online tracking of bearing wear using wavelet packet
decomposition and probabilistic modeling: A method for bearing prognostics”. In Journal of Sound and
Vibration, Band 302, Ausgabe 4-5, 22. Mai 2007, S. 951-961.
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