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Automatic localization of the rotor-stator rubbing fault based on acoustic emission method and higher-order statistics

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Abstract

Localization to the rotor-stator rubbing fault of rotating machinery such as aero-engines has been attracting plenty of attentions in fault diagnosis field. Present study attempts to effectively and accurately localize such rubbing sources based on modal AE method automatically. In order to explore the propagation characteristic of rubbing signals, theoretical analysis and finite element simulation on a stator case are conducted. And the dependence of accuracy of time difference of arrival (TDOA) method on the propagation characteristic is investigated. Based on the analysis result, a higher-order statistics (HOS) algorithm is introduced into acoustic emission (AE) to automatically identify the arrival time of rubbing signals and localize the rubbing source via automatic threshold selection. To verify the effectiveness of the proposed AE method to recognize the rubbing fault, a series of rubbing tests are carried out. It is demonstrated by the experimental results that the accuracy of the proposed method is improved compared with conventional TDOA methods since more than half of the sources localized at the rubbing region can be identified in almost all cases and the identification accuracy is up to 80 % at threshold of 85 % of amplitude.

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Author information

Authors and Affiliations

  1. School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China

    Qiang Pan & Tian He

  2. School of Energy and Power Engineering, Beihang University, Beijing, 100191, China

    Rui Zhou

  3. AECC Hunan Aviation Powerplant Research Institute, Hunan, Zhuzhou, 412002, China

    Juying Su

  4. System Engineering Research Institute, Beijing, 100094, China

    Zebang Zhang

Authors
  1. Qiang Pan
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  2. Rui Zhou
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  3. Juying Su
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  4. Tian He
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  5. Zebang Zhang
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Corresponding author

Correspondence to Tian He.

Additional information

Recommended by Associate Editor Daeil Kwon

Qiang Pan received his B.S. degree in Jet Propulsion from Beijing University of Aeronautics & Astronautics in China in 2001 and completed his Ph.D. degree in Department of Mechanical Engineering from Inha University, South Korea in 2009. Presently he is a lecturer in School of Transportation Science and Engineering, Beihang University. His research interests include material and structure analysis of aircraft and aeroengines, aircraft airworthiness and fault diagnosis.

Rui Zhou received his B.S. degree in Aircraft Design Engineering from Nanchang Hangkong University in 2016. Now he is a graduate student in School of Energy and Power Engineering, Beihang University. His research interests include fault diagnosis, acoustic emission and signal processing.

Juying Su received his B.S. degree in Flight Vehicle Propulsion Engineering from Civil Aviation University of China in 2013 and completed his M.S. degree in Traffic and Transportation Engineering (Airworthiness) from Beihang University, China in 2017. Presently he is an engineer of airworthiness in AECC Hunan Aviation Powerplant Research Institute. His main research interests include aero-engine airworthiness and airworthiness management.

Tian He received his B.S. and M.S. degrees in Mechanical Engineering from Shijiazhuang Tiedao University, China, in 2001 and 2004, respectively, and his Ph.D. in Aerospace Propulsion Theory and Engineering from Beihang University, China, in 2008. He is an Associate Professor in School of Transportation Science and Engineering, Beihang University. His research interests include fault diagnosis, acoustic emission, vibration control and vibration signal processing.

Zebang Zhang received his B.S. and M.S. degrees in Jet Propulsion from Beijing University of Aeronautics & Astronautics in China in 2001 and 2004, respectively. Presently he is an engineer of System Engineering Research Institute. His research interest is structure analysis of ship equipment and fault diagnosis.

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Pan, Q., Zhou, R., Su, J. et al. Automatic localization of the rotor-stator rubbing fault based on acoustic emission method and higher-order statistics. J Mech Sci Technol 33, 513–524 (2019). https://doi.org/10.1007/s12206-019-0104-9

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  • DOI: https://doi.org/10.1007/s12206-019-0104-9

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