access icon openaccess Research on gear crack diagnosis of the planet gear transmission

Objected to the planetary gear transmission, research on the fault diagnosis of gear cracks is mainly carried out with method of EEMD decomposition and Envelope demodulation. During the process, EEMD decomposition is used to the experiment data and continuously parameters of the root mean square (RMS) value, peak-to-peak (PtP) value, kurtosis (Kr), and other parameters of the IMF components are computed. According those parameters, the signal is reconstructed and after band-pass filtering the Hilbert transform and the envelope demodulation are carried out. The results showed that the power spectrum information obtained by using the EEMD decomposition and Hilbert transform could effectively response fault characteristics of the gear crack in the planetary transmission. The research is beneficial to the gear meshing fault diagnosis of the planetary transmission quickly and accurately and has a positive engineering value.

Inspec keywords: cracks; band-pass filters; fault diagnosis; Hilbert transforms; mean square error methods; gears; power transmission (mechanical)

Other keywords: IMF components; Hilbert transform; response fault characteristics; root mean square value; band-pass filtering; gear crack diagnosis; planetary transmission; kurtosis; EEMD decomposition; peak-to-peak value

Subjects: Fracture mechanics and hardness (mechanical engineering); Maintenance and reliability; Mechanical drives and transmissions; Numerical analysis; Mechanical components

References

    1. 1)
      • 13. Gao, J.H.: ‘Modeling and analysis on the vertical dynamics of an occupant and seat cushion system’, PhD thesis, Tsinghua University, 2014.
    2. 2)
      • 8. Liu, F.F., Li, J.G., Chen, G.Q., et al: ‘Biomechanical model of seated human body exposed to vertical vibration’, J. Shandong Univ. (Eng. Sci.), 2012, 42, (4), pp. 103107, 113.
    3. 3)
      • 4. Abbas, W., Abouelatt, O.B., ELazab, M., et al: ‘Optimal seat suspension design using genetic algorithms’, J. Mech. Eng. Autom., 2011, 1, (1), pp. 4452.
    4. 4)
      • 19. Inalat, M., Kahraman, A.: ‘A dynamic model to predict modulation sidebands of a planetary gear set having manufacturing errors’, J. Sound Vib., 2010, 329, pp. 49194939.
    5. 5)
      • 11. Zhang, Y.Q., Ma, Z., Jin, A., et al: ‘An improved human biodynamic model considering the interaction between feet and ground’, Sae Int. J. Commer. Veh., 2015, 8, pp. 1319.
    6. 6)
      • 20. Feng, Z.P., Zhao, L.L., Chu, F.L.: ‘Vibration spectral characteristics of localized gear fault of planetary gearboxes’, Proc. CSEE, 2013, 33(8), pp. 107111.
    7. 7)
      • 16. Divyaksh, S.C., Maria, P.: ‘Multi-directional one-handed strength assessments using AnyBody modeling systems’, Appl. Ergon., 2018, 67, pp. 225236.
    8. 8)
      • 5. Abbas, W., Abouelatt, O.B., ELazab, M., et al: ‘Optimization of bio-dynamic seated human models using genetic algorithms’, Engineering, 2010, 2, pp. 710719.
    9. 9)
      • 14. Pasha, Z.A.A., Mallakzadeh, M., Kalantarinejad, R.: ‘Optimal frame geometry of spacecraft seat based on multi-body dynamics modelling’, Acta Astronaut., 2015, 115, (4), pp. 5870.
    10. 10)
      • 17. Grabowski, A.M.: ‘Metabolic and bio-mechanical effects of velocity and weight support using a lower-body positive pressure device during walking’, Arch. Phys. Med. Rehab., 2010, 91, pp. 951957.
    11. 11)
      • 18. Feng, Z., Zuo, M.J., Hao, R., et al: ‘Gear damage assessment base cyclic spectral analysis’, J. Sound Vib., 2012, 331, pp. 49194939.
    12. 12)
      • 12. Ahmet, E., Scott, M., Walter, H., et al: ‘Model-based estimation of muscle forces exerted during movements’, Clin. Biomech., 2007, 22, pp. 131154.
    13. 13)
      • 6. Wu, Z.L.: ‘Equivalent dynamic model of vehicle-passenger and study on its dynamic response’, MD thesis, Southwest Jiaotong University, 2013.
    14. 14)
      • 10. Liu, J.J.: ‘Research in dynamic model and parameter identification of human-chair system for vehicle handling stability’, MD thesis, Chongqing University, 2014.
    15. 15)
      • 15. Ghezelbash, F., Eskandari, A.H., Shirazi-Adl, A., et al: ‘Effects of motion segment simulation and joint positioning on spinal loads in trunk musculoskeletal models’, J. Biomech., 2018, 70, pp. 149156.
    16. 16)
      • 3. Zhang, E., Li, Z.H., Shao, X.C.: ‘Simulation of human vibration characteristics based on 9-DOF riding dynamics model’, J. Traffic Transp. Eng., 2010, 10, (4), pp. 5864.
    17. 17)
      • 1. Zhang, E., Xu, L.A., Liu, Z.H.H., et al: ‘Dynamic modeling and vibration characteristics of multi-DOF upper part system of seated human body’, J. Eng. Des., 2008, 15, (4), pp. 244249.
    18. 18)
      • 9. Harsha, S., Desta, M., Prashanth, A., et al: ‘Measurment and bio-dynamical model development of seated human subjects exposed to low frequency vibration environment’, Int. J. Veh. Noise Vib., 2014, 10, (1), pp. 124.
    19. 19)
      • 7. Zhang, Z.F., Hu, Z.Q., Xu, Z.M., et al: ‘A dynamic model of a seated human body based on dynamic response’, J. Vib. Shock, 2016, 35, (4), pp. 104109.
    20. 20)
      • 2. Zhang, E., Liu, M.L., Shao, X.C., et al: ‘Study and simulation on human body vibration characteristics of human-vehicle system in dynamic environment’, J. Eng. Des., 2009, 16, (3), pp. 166171, 181.
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