Fundamental Study on Vibration Diagnosis for High Speed Rotational Machine using Wavelet Transform
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- Kawada Masatake
- Dept. of Electrical and Electronic Engineering, Faculty of Engineering, The University of Tokushima
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- Yamada Koji
- Electric Power R&D Center, Chubu Electric Power Co., Inc.
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- Yamashita Katsuya
- Vibration & Noise Control Laboratory, Takasago Research & Development Center, Mitsubishi Heavy Industries, LTD.
Bibliographic Information
- Other Title
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- ウェーブレヅト変換による高速回転機振動診断のための基礎研究
- ウェーブレット変換による高速回転機振動診断のための基礎研究
- ウェーブレット ヘンカン ニ ヨル コウソク カイテンキ シンドウ シンダン ノ タメ ノ キソ ケンキュウ
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Description
In this paper we presented results of fundamental study to introduce the wavelet transform to vibration diagnosis for high-speed rotational machine such as steam turbine, gas turbine, and generator and so on. It is required to detect and distinguish typical vibration of high-speed rotational machine accurately in order to diagnose the machine. The wavelet transform is used in many fields because it is able to visualize phenomenon in time-frequency domain and to detect the beginning time and the duration of it. <BR>We made a model rotor supported with two journal bearings to simulate contact vibration, clearance vibration, and oil whip. The vibration phenomena were measured with vertical and horizontal displacement meters at the rotor and vertical and horizontal accelerometers at the rotor bearing and visualized in the time-frequency domain by the wavelet transform. It is found that the dynamic spectra obtained by the wavelet transform of the vertical and horizontal components of displacement and acceleration signals are different for each vibration phenomenon, therefore, this method is able to distinguish each kind of vibration phenomenon. Each vibration phenomenon can be detected and distinguished at the early stage.
Journal
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- IEEJ Transactions on Power and Energy
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IEEJ Transactions on Power and Energy 123 (10), 1229-1241, 2003
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390282679580113792
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- NII Article ID
- 10011750861
- 10015576719
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- NII Book ID
- AN10136334
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- ISSN
- 13488147
- 03854213
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- NDL BIB ID
- 6720177
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed