A Novel Method to Improve Crack Detection Ability in Helical Gear

علوم کاربردی و محاسباتی در مکانیک

Article 1, Volume 31, Issue 1 - Serial Number 21, February 2020, Pages 1-12   

Document Type: Original Article

DOI: 10.22067/fum-mech.v31i1.78275

Authors

Mohsen Rezaei; Mehrdad Poursina; Farhad Haji Aboutalebi

Abstract

The helical gear systems have some distinctions such as more precision, long life and more applications in the industry, and less vibration, noise and transmission error compared to spur gear systems. One of the damages that can affect the operation of these systems is the gear tooth root crack. So, the crack detection in its early stages of growth and development is very important. The residual signal method is one of the common methods to extract the effect of crack from the system vibration signal. Since the residual signal calculation requires the information of the vibration response of the healthy state or the system initial parameters, providing a method to extract the effect of crack from the vibrating response without any more information is very helpful. In this research, at first the calculation of the helical gear pair mesh stiffness is explained, and the effect of tooth root crack is also described. Then, a single-stage helical gear system, with the motor and the load, is modeled and solved numerically to achieve the system dynamic response. Then, the effect of present method on the vibration signal obtained from the dynamic simulation of a system with a small crack is Shown and discussed. Finally, the proposed method is applied to the dynamic response signal of a system that presented in one of the previous researches, and its efficiency is illustrated.

Keywords

Helical Gear; Crack Detection; Transmission Error; Signal processing

Supplementary Files

EA1-poorsina-Nahayi.pdf

References

1. Mohammed, O.D., Rantatalo, M. and Aidanpää, J.-O., "Improving mesh stiffness calculation of cracked gears for the purpose of vibration-based fault analysis", Engineering Failure Analysis, Vol. 34, pp. 235–251, (2013).

2. Li, C.J. and Lee, H., "Gear fatigue crack prognosis using embedded model, gear dynamic model and fracture mechanics", Mechanical Systems and Signal Processing, Vol. 19, pp. 836–846, (2005).

3. Wan, Z., Cao, H., Zi, Y., He, W. and Chen, Y., "Mesh stiffness calculation using an accumulated integral potential energy method and dynamic analysis of helical gears", Mechanism and Machine Theory, Vol. 92, pp. 447–463, (2015).

4. McFadden, P.D., "Detecting fatigue cracks in gears by amplitude and phase demodulation of the meshing vibration", Journal of Vibration, Acoustics, Stress, and Reliability in Design, Vol. 108, pp. 165–170, (1986).

5. Stewart, R.M., "Some useful data analysis techniques for gearbox diagnostics", University of Southampton, (1977).

6. Randall, R.B., "Vibration-based condition monitoring: industrial, aerospace and automotive applications", John Wiley & Sons, (2011).

7. Wang, W. and Wong, A.K., "Autoregressive model-based gear fault diagnosis", Journal of Vibration and Acoustics, Vol. 124, pp. 172–179, (2002).

8. Endo, H., Randall, R.B., and Gosselin, C., "Differential diagnosis of spall vs. cracks in the gear tooth fillet region: Experimental validation", Mechanical Systems and Signal Processing, Vol. 23, pp. 636–651, (2009).

9. Zhou, X., Shao, Y., Lei, Y. and Zuo, M., "Time-varying meshing stiffness calculation and vibration analysis for a 16DOF dynamic model with linear crack growth in a pinion", Journal of Vibration and Acoustics, Vol. 134, pp. 11011, (2012).

10. Assaad, B., Eltabach, M. and Antoni, J., "Vibration based condition monitoring of a multistage epicyclic gearbox in lifting cranes", Mechanical Systems and Signal Processing, Vol. 42, pp.

351–367, (2014).

11. Elasha, F., Ruiz-Carcel, C., Mba, D. and Chandra, P., "A comparative study of the effectiveness of adaptive filter algorithms, spectral kurtosis and linear prediction in detection of a naturally degraded bearing in a gearbox", Journal of Failure Analysis and Prevention, Vol. 14, pp. 623–636, (2014).

12. Wu, S., Zuo, M.J. and Parey, A., "Simulation of spur gear dynamics and estimation of fault growth", Journal of Sound and Vibration, Vol. 317, pp. 608–624, (2008).

13. Sun, R., Yang, Z., Chen, X., Tian, S. and Xie, Y., "Gear fault diagnosis based on the structured sparsity time-frequency analysis", Mechanical Systems and Signal Processing, Vol. 102, pp. 346-363, (2018).

14. Buzzoni, M., D’Elia, G., Mucchi, E. and Dalpiaz, G., "A vibration-based method for contact pattern assessment in straight bevel gears", Mechanical Systems and Signal Processing, Vol. 120, pp.

693-707, (2019).

15. Mahgoun, H., Bekka, R.E. and Felkaoui, A., "Gearbox fault diagnosis using ensemble empirical mode decomposition (EEMD) and residual signal", Mechanics & Industry, Vol. 13, pp. 33–44, (2012).

16. Yu, W., Shao, Y. and Mechefske, C.K., "The effects of spur gear tooth spatial crack propagation on gear mesh stiffness", Engineering Failure Analysis, Vol. 54, pp. 103–119, (2015).

17. Mohammed, O.D., Rantatalo, M. and Aidanpää, J.-O.,: "Dynamic modelling of a one-stage spur gear system and vibration-based tooth crack detection analysis", Mechanical Systems and Signal Processing, Vol. 54, pp. 293–305, (2015).

18. Mohammed, O.D. and Rantatalo, M., "Gear tooth crack detection using dynamic response analysis", Insight (Northampton), Vol. 55, pp. 417–421, (2013).