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Development and trend of condition monitoring and fault diagnosis of multi-sensors information fusion for rolling bearings: a review

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Abstract

A rolling bearing is an essential component of a rotating mechanical transmission system. Its performance and quality directly affects the life and reliability of machinery. Bearings’ performance and reliability need high requirements because of a more complex and poor working conditions of bearings. A bearing with high reliability reduces equipment operation accidents and equipment maintenance costs and achieves condition-based maintenance. First in this paper, the development of technology of the main individual physical condition monitoring and fault diagnosis of rolling bearings are introduced, then the fault diagnosis technology of multi-sensors information fusion is introduced, and finally, the advantages, disadvantages, and trends developed in the future of the detection main individual physics technology and multi-sensors information fusion technology are summarized. This paper is expected to provide the necessary basis for the follow-up study of the fault diagnosis of rolling bearings and a foundational knowledge for researchers about rolling bearings.

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Acknowledgments

The research work was supported by the Natural Science Foundation of China (NSFC) (grant numbers: 51675403, 51275381 and 51505475), National Research Foundation, South Africa (grant numbers: IFR160118156967 and RDYR160404161474), and UOW Vice-Chancellor’s Postdoctoral Research Fellowship.

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Authors and Affiliations

  1. Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, 710001, China

    Zhihe Duan, Tonghai Wu, Shuaiwei Guo & Tao Shao

  2. Department of Electrical, Electronic & Computer Engineering, University of Pretoria, Pretoria, 0002, South Africa

    Reza Malekian

  3. School of Mechatronics Engineering, China University of Mining & Technology, Xuzhou, 221110, China

    Zhixiong Li

  4. School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, 2522, Wollongong, NSW, Australia

    Zhixiong Li

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  1. Zhihe Duan
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  2. Tonghai Wu
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Correspondence to Tonghai Wu or Reza Malekian.

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Duan, Z., Wu, T., Guo, S. et al. Development and trend of condition monitoring and fault diagnosis of multi-sensors information fusion for rolling bearings: a review. Int J Adv Manuf Technol 96, 803–819 (2018). https://doi.org/10.1007/s00170-017-1474-8

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