Paper Title:
Factorial Hidden Markov Model Recognition Method Based on Multi-Channel Information Fusion
  Abstract

Combining Self-organizing Feature Map (SOM) and Factorial hidden Markov model (FHMM), a new FHMM fault recognition method based on multi-sensor vibration information fusion is proposed. In the proposed method, the SOM neural network is used to reduce the information redundancy in feature vectors extracted from the multi-sensor’s vibration measurements, FHMM as a classifier. The fault recognition in the speed-up and speed-down process of rotating machinery was successfully completed. The experiment result shows that the proposed method is very effective.

  Info
Periodical
Advanced Materials Research (Volumes 291-294)
Chapter
Vibration, Noise Analysis and Control
Edited by
Yungang Li, Pengcheng Wang, Liqun Ai, Xiaoming Sang and Jinglong Bu
Pages
2027-2033
DOI
10.4028/www.scientific.net/AMR.291-294.2027
Citation
Z. N. Li, G. H. Wu, J. Jiang, F. Z. Feng, "Factorial Hidden Markov Model Recognition Method Based on Multi-Channel Information Fusion", Advanced Materials Research, Vols. 291-294, pp. 2027-2033, 2011
Online since
July 2011
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Price
$32.00
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