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Ultrasonic measurement of lubricant film thickness distribution of journal bearing.
Ouyang, Wu; Zhou, Zhenjiang; Jin, Yong; Yan, Xinping; Liu, Yuanchang.
Afiliação
  • Ouyang W; School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China.
  • Zhou Z; School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China.
  • Jin Y; School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China.
  • Yan X; School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China.
  • Liu Y; Department of Mechanical Engineering, University College London, London WC1E 7JE, United Kingdom.
Rev Sci Instrum ; 91(6): 065111, 2020 Jun 01.
Article em En | MEDLINE | ID: mdl-32611062
ABSTRACT
Most film thickness measurement methods damage the working surface of a bearing and cannot measure the minimum film thickness, making it difficult to reveal the lubrication state and warn of wear. Two non-intrusive ultrasonic methods were proposed for measuring the film thickness distribution of the bearing, i.e., the full circumferential measurement and the prediction based on limited measuring points. The ultrasonic recognition model of film thickness was built. A film thickness measuring device and its calibration device were constructed. A calibration experiment in the range of 1-150 µm and a measurement experiment of the bearing's film thickness distribution were carried out. The results showed that in the calibration range, the relative error of most recognition values was less than ±5%, and some are less than 3%. The identification accuracy of the spring model has a zoned phenomenon. The relative difference between the experimental and the simulated values of the film thickness was less than 8% under most working conditions. The predicted values of eccentricity, attitude angle, and minimum film thickness have a small difference from the simulated values, indicating that the accuracy of the measurement method is high.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article