Time-Frequency Visualization of Vibration Phenomena generated on Turbine Model using Wavelet Transform
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- Kawada Masatake
- Department 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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- Kaneko Yasutomo
- Vibration & Noise Control Laboratory, Takasago Research & Development Center, Mitsubishi Heavy Industries, LTD.
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- Isaka Katsuo
- Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Tokushima
Bibliographic Information
- Other Title
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- タービンモデルにおける振動現象のウェーブレット変換による時間周波数可視化
- タービン モデル ニ オケル シンドウ ゲンショウ ノ ウェーブレット ヘンカン ニ ヨル ジカン シュウハスウ カシカ
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Description
In this paper we presented results of fundamental study to introduce the wavelet transform to vibration diagnosis for a turbine. It is required to detect typical vibration of the turbine accurately. The wavelet transform is used in many fields because it is able to visualize a phenomenon in a time-frequency domain. Modern power plants usually use one-high pressure and one or two lower pressure turbines. We made a turbine model with 3 rotors supported with journal bearings to simulate contact vibration, oil whip, and clearance vibration. The vibration phenomena were measured with vertical and horizontal displacement meters at the rotors, and with vertical and horizontal accelerometers at the bearings. The vibration phenomena were visualized in the time-frequency domain by the wavelet transform. This paper especially shows the results of the acceleration signals. It is found that the dynamic spectra obtained by the wavelet transform of the acceleration signals are different for each vibration. Therefore, this method is able to distinguish the vibration phenomena. And furthermore, the contact point is localized by the proposed method.
Journal
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- IEEJ Transactions on Power and Energy
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IEEJ Transactions on Power and Energy 125 (4), 434-440, 2005
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
- 1390282679579502976
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- NII Article ID
- 10015576701
- 30011601596
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- NII Book ID
- AN10136334
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- ISSN
- 13488147
- 03854213
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- NDL BIB ID
- 7303901
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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