4.7 Article

Nonlinear dynamic modeling and analysis of a helicopter planetary gear set for tooth crack diagnosis

Journal

MEASUREMENT
Volume 198, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2022.111347

Keywords

Fault dynamic modeling; Planetary gear set; Sweep-condition response analysis; Nonlinear characteristics analysis; Fault diagnosis

Funding

  1. National Key Research and Development Program of China [2018YFB1702401]
  2. Na-tional Natural Science Foundation of China [51975576, 52105133]
  3. Defense Industrial Technology Development Pro-gram [WDZC20205500301, WDZC20205250305]

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The planetary gearset is an essential component in helicopter transmission, and the nonlinear dynamic factors in the gearbox system greatly affect its vibration response characteristics and pose challenges to crack fault detection and diagnosis. This study establishes a 21 degrees of freedom model to analyze the nonlinear properties of the planetary gear set and identifies optimal fault detection indicators through analysis of natural frequency and statistical indicators. The study also uses time-domain waveform analysis and power spectrum analysis to point out crack fault symptoms, providing insights into the fault mechanism and achieving fault isolation. Experimental verification of the model's effectiveness with tooth crack in the planetary gear set is conducted.
Planetary gearset is a vital dynamic component in helicopter transmission. In the planetary gearbox, there are many nonlinear dynamic factors, such as time-varying meshing stiffness, bearing support stiffness, comprehensive transmission error and tooth backlash. These nonlinear factors will deeply affect the vibration response characteristics of the gearbox system, and bring new challenges to the crack fault detection and diagnosis. To unveil the nonlinear properties of planetary gear set, a 21 degrees of freedom translational-torsional model of the planetary gear set is established by integrating above-mentioned nonlinear factors. Analysis of the fault influence on natural frequency and statistical indicators of simulation responses, the optimal indicators for fault detection are found. Then, nonlinear dynamic characteristics of gear system under fault state are conducted, and crack fault symptoms are pointed out using time-domain waveform analysis and power spectrum analysis of response signals, which actively illustrates the system fault mechanism and achieves fault isolation. Finally, the effectiveness of the model for planetary gear set with tooth crack is verified by experiments.

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