Laser & Optoelectronics Progress, Volume. 59, Issue 23, 2312002(2022)

Gearbox Fault Detection Based on Self-Mixing Interference Technology and Hilbert-Huang Transform

Xuming Zhou*, Peng Xu, Fenni Zhao, and Pengfei Li
Author Affiliations
  • Logistics University of People’s Armed Police Force, Tianjin 300309, China
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    The vibration signal of the gearbox contains all the characteristic information during gear operation. The current running state of the equipment can be mastered by collecting and analyzing vibration signals. There are many methods for collecting gearbox vibration signals. The noncontact measurement method, based on the principle of laser self-mixing interference, has extremely unique advantages. First, this method can collect the early characteristic signals of gearbox fault and take corresponding measures in time. Second, the method can obtain the required characteristic information without damaging the gearbox’s surface. Third, compared with the installation of an acceleration sensor, the influence of this method on the reflector attached to the gearbox is very small and can be ignored. The planetary gear wear fault is artificially made, and the fault characteristic signal is collected during the experiment. Furthermore, the fault vibration signals of planetary gears are extracted and the intrinsic mode function (IMF) components of each order and Hilbert spectrum are analyzed using the Hilbert-Huang transform (HHT) signal processing method. The Hilbert spectrum can be analyzed during the period of gear wear fault. The results are in good agreement with the theoretical values, showing that this method can effectively detect gearbox vibration faults.

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    Xuming Zhou, Peng Xu, Fenni Zhao, Pengfei Li. Gearbox Fault Detection Based on Self-Mixing Interference Technology and Hilbert-Huang Transform[J]. Laser & Optoelectronics Progress, 2022, 59(23): 2312002

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Sep. 30, 2021

    Accepted: Nov. 15, 2021

    Published Online: Jan. 11, 2023

    The Author Email: Zhou Xuming (zhou05008@126.com)

    DOI:10.3788/LOP202259.2312002

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