The Research of DHMM in Diagnosing Malfunction for the Closing down of Rotary Machine

Wei Hua Liu; Yu Bin Gao

doi:10.4028/www.scientific.net/AMR.546-547.182

Paper Titles

Fluid Structure Interaction Simulation on the Seagull Airfoil of the Small Wind Turbine
p.160

Static Analysis on Land Wheel of Vegetable Transplanter
p.166

Wet Modal Analysis of a Deep-Sea Autonomous Underwater Vehicle
p.171

Analysis of Hydrodynamic Noise around Acoustic Modem on the AUV Using Hybrid LES-Lighthill Method
p.176

The Research of DHMM in Diagnosing Malfunction for the Closing down of Rotary Machine
p.182

Vibration Signal Extraction of Rotating Machines Based on the Analysis of Degree of Cylcostationary
p.188

Research on the Electric Enclosed Loading Tester of Gearbox
p.194

Numerical Simulation on Aerodynamic of the Wing in Ground Effect
p.200

Numerical Simulation of Low Engine Order Excitation in a Transonic Compressor
p.206

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 546-547The Research of DHMM in Diagnosing Malfunction for...

The Research of DHMM in Diagnosing Malfunction for the Closing down of Rotary Machine

Abstract:

This paper proposes the basic concept of dynamical pattern recognition and introduces the implementation theories based on probability statistics .Based on the theory of the Discrete Hidden Markov Models (DHMM), the scalar quantization method of vibration spectrum vector of rotary machine is proposed, and then the fault diagnosis method based on DHMM is designed. The experiment of run-up process of rotor machine is made to verify the effect of the new fault diagnosis method.

You might also be interested in these eBooks

Electrical Insulating Materials and Electrical Engineering

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 546-547)

Pages:

182-187

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.546-547.182

Citation:

Cite this paper

Online since:

July 2012

Authors:

Wei Hua Liu, Yu Bin Gao

Keywords:

DHMM, Fault Diagnosis, Rotary Machine, Scalar Quantization, Vibration Analysis (VA)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] RabinerLRJuangBH. AnIntroduetiontoHiddenMarkovModels. IEEEASSPMagazine. 1986, 3(l): 4-6.

Google Scholar

[2] Puming Zhan. The improvement of Speech recognition hidden markov model. Acta Electronica Sinica. 1994，22(l): 9-15.

Google Scholar

[3] He Qiang, Youwei Zhang. No overflow parameters revaluation of more continuous observation sequence hidden markov model. Acta Electronica Sinica. 2000，28(l0)：98一101.

Google Scholar

[4] Qing Wang, Zheru Chi, Feng, D.D., Rongchun Zhao. Hidden Markov random field based approach for off-line handwritten Chinese character recognition. Pattern Recognition, 2000. Proceedings. 15th International Conference on, 2000, 2: 347-350.

DOI: 10.1109/icpr.2000.906084

Google Scholar

[5] Aitkin M. WiLson G. Mixture models, outline and the EM algorithm, Techno metrics, 1980, 22(3): 325-331.

Google Scholar