Orthogonal On-Rotor Sensing Vibrations for Condition Monitoring of Rotating Machines

Authors

  • Yuandong Xu Department of Mechanical Engineering, Imperial College London, London, UK https://orcid.org/0000-0003-4259-4727
  • Xiaoli Tang School of Engineering and Technology, Aston University, Birmingham, UK https://orcid.org/0000-0003-4428-0895
  • Guojin Feng School of Mechanical Engineering, Hebei University of Technology, Tianjin, China
  • Dong Wang State Key Laboratory of Mechanical Systems and Vibration, Shanghai Jiao Tong University, China https://orcid.org/0000-0003-4872-4860
  • Craig Ashworth Control System Integration Ltd, Littleborough, UK
  • Fengshou Gu Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield, UK https://orcid.org/0000-0003-4907-525X
  • Andrew Ball Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield, UK

DOI:

https://doi.org/10.37965/jdmd.v2i2.47

Keywords:

on-rotor sensing, vibration, condition monitoring, rotating machines

Abstract

Thanks to the fast development of micro-electro-mechanical systems (MEMS) technologies, MEMS accelerometers show great potentialities for machine condition monitoring. To overcome the problems of a poor signal to noise ratio (SNR), complicated modulation, and high costs of vibration measurement and computation using conventional integrated electronics piezoelectric accelerometers, a triaxial MEMS accelerometer-based on-rotor sensing (ORS) technology was developed in this study. With wireless data transmission capability, the ORS unit can be mounted on a rotating rotor to obtain both rotational and transverse dynamics of the rotor with a high SNR. The orthogonal outputs lead to a construction method of analytic signals in the time domain, which is versatile in fault detection and diagnosis of rotating machines. Two case studies based on an induction motor were carried out, which demonstrated that incipient bearing defect and half-broken rotor bar can be effectively diagnosed by the proposed measurement and analysis methods. Comparatively, vibration signals from translational on-casing accelerometers are less capable of detecting such faults. This demonstrates the superiority of the ORS vibrations in fault detection of rotating machines.

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Published

2021-12-21

How to Cite

Xu, Y., Tang, X., Feng, G., Wang, D., Ashworth , C. ., Gu, F., & Ball, A. (2021). Orthogonal On-Rotor Sensing Vibrations for Condition Monitoring of Rotating Machines. Journal of Dynamics, Monitoring and Diagnostics, 1(1), 29–36. https://doi.org/10.37965/jdmd.v2i2.47

Issue

Section

Regular Article