Application of CYCBD for the planetary gearbox fault diagnosis based on encoder information
ID:145 View Protection:ATTENDEE Updated Time:2021-08-26 14:44:17 Hits:549 Oral Presentation

Start Time:Pending(Asia/Shanghai)

Duration:Pending

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Abstract
With more dynamic condition information, the built-in encoder signal is more superior and convenient than the traditional vibration signal in the mechanical system fault diagnosis. However, the early incipient fault features are apt to be submerged in the raw encoder signal due to the predominant feature of increasing. In this paper, the raw encoder signal is derived firstly to obtain the instantaneous angular speed. Then, IAS as the input series of the algorithm of maximum second-order cyclostationarity blind deconvolution (CYCBD), is used to enhance the fault features and identify the condition of the planetary gearbox. Through the simulation and experiment case, the feasibility of CYCBD in IAS signal can be verified.
Keywords
Encoder signal, Planetary gearbox, Feature enhancement, Maximum second-order cyclostationarity blind deconvolution (CYCBD)
Speaker
Boyao Zhang
Beihang University;School of Reliability and Systems Engineering

Submission Author
Boyao Zhang Beihang University;School of Reliability and Systems Engineering
Yonghao Miao School of Reliability and Systems Engineering, Beihang University, Beijing, China
Jing Lin School of Reliability and Systems Engineering, Beihang University, Beijing, China
Chenhui Li School of Reliability and Systems Engineering, Beihang University, Beijing, China
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Important Date
  • Conference Date

    Nov 01

    2022

    to

    Nov 03

    2022

  • Oct 30 2022

    Draft paper submission deadline

  • Nov 09 2022

    Registration deadline

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