Method research of noise diagnosis based on fuzzy neural network

Author

Wu, Chang-Zhi ; Hua, Wu ; Ma, Yan Jian-Fen

Author_Institution

Comput. Center, Taiyuan Univ. of Technol., China

Volume

2

fYear

1998

fDate

1998

Firstpage

1370

Abstract

In this paper, a new noise diagnosis method is presented, and its algorithm deduced, based on a fuzzy neural network. As a practical example, the noise field intensity is diagnosed and the coupling noise is identified for the noise from a steam turbine unit. The results show that the fuzzy neural network has a good capacity for pattern recognition, fast convergence and good stability in dealing with uncertain or ambiguous data at the classification boundary. The noise radiated from the steam turbines unit is diagnosed accurately and the noise node is suppressed effectively and is restructured

Keywords

convergence; fault diagnosis; fuzzy neural nets; noise; pattern recognition; stability; steam turbines; classification boundary; coupling noise; fast convergence; fuzzy neural network; noise diagnosis; noise field intensity; nonlinear pattern classification; pattern recognition; stability; steam turbine unit; Active noise reduction; Computer networks; Fault diagnosis; Frequency; Fuzzy neural networks; Monitoring; Signal to noise ratio; Stability; Turbines; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Proceedings, 1998. ICSP '98. 1998 Fourth International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4325-5

Type

conf

DOI

10.1109/ICOSP.1998.770875

Filename

770875