"The Important Role of Gears in Mechanical Engineering"
Keywords:
gear, gear micro-geometry, profile modifications, transmission error, noise, finite-element method, gear bending and contact stressAbstract
Nowadays, the basic requirements of gear transmissions are not limited to resistance and reliability, but often include good efficiency and low vibration and noise emissions. This article investigates the role of tooth flank micro-geometry in fulfilling these needs. A non-linear finite element approach has been conceived and exploited to investigate in detail the influence of the shape of profile modifications (PMs) on transmission error, root stress, and contact pressure. In this approach, harmonic drive gears are widely used in space applications, robotics, and precision positioning systems because of their attractive attributes including near-zero backlash, high speed reduction ratio, compact size, and small weight. On the other hand, they possess an inherent periodic positioning error known as kinematic error responsible for transmission performance degradation. No definite understanding of the mechanism of kinematic error as well as its characterization is available in the literature. The numerical results are first assessed by comparison with experimental measurements and then a comparison of contact and bending stresses of the same gear with long linear and long circular PMs is presented and discussed. The results of these comparisons show that the optimal amount of PMs is not independent of PM shape; hence, the procedures used to design linear PMs cannot be directly applied to the design of non-linear PMs.
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References
W. T. Becker and R. J. Shipley, Failure analysis and prevention, ASM Handbook, ASM International, Ohio, 11 (2002).
H. Mahgoun, F. Chaari and A. Felkaoui, Detection of gear faults in variable rotating speed using variational mode decomposition (VMD), Mechanics & Industry, 17 (207) (2016) 1–14.
Q. Zhu, Y. Wang and G. Shen, Research and comparison of time-frequency techniques for nonstationary signals, J. of Computers, 7 (4) (2012) 954–958.
H. Li and Y. P. Zhang, Wear detection in gear system using Hilbert-Huang transform, J. of Mechanical Science and Technology, 20 (11) (2006) 1781–1789.
N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng and H. H. Liu, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proceedings: Royal Society London, Mathematical, Physical and Engineering Sciences, 454 (1996) 903–995.
Y. Lei, J. Lin, Z. He and M. J. Zuo, A review on empirical mode decomposition in fault diagnosis of rotating machinery, Mechanical Systems and Signal Processing, 35 (2013) 108–126.
A. Parey, M. E. Badaoui, F. Guillet and N. Tandon, Dynamic modelling of spur gear pair and application of empirical mode decomposition-based statistical analysis for early detection of localized tooth defect, J. of Sound and Vibration, 294 (2006) 547–561.
C. Junsheng, Y. Dejie and Y. Yu, Research on the intrinsic mode function (IMF) criterion in EMD method, Mechanical Systems and Signal Processing, 20 (4) (2006) 817–824.
R. Ricci and P. Pennacchi, Diagnostics of gear faults based on EMD and automatic selection of intrinsic mode functions, Mechanical Systems and Signal Processing, 25 (2011) 821–838.
S. Jin, J. S. Kim and S. K. Lee, Sensitive method for detecting tooth faults in gearboxes based on wavelet denoising and empirical mode decomposition, J. of Mechanical Science and Technology, 29 (8) (2015) 3165–3173.
J. Cheng, D. Yu, J. Tang and Y. Yang, Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis, Mechanism and Machine Theory, 43 (6) (2008) 712–723.
A. Parey and N. Tandon, Impact velocity modeling and signal processing of spur gear vibration for the estimation of defect size, Mechanical Systems and Signal Processing, 21 (2007) 234–243.
K. S. Wang and P. S. Heyns, An empirical resampling method on intrinsic mode function to deal with speed variation in machine fault diagnostics, Applied Soft Computing, 11 (2011) 5015–5027.
R. Shao, W. Hu and J. Cao, Gear damage detection and diagnosis system based on COM module, Procedia Engineering, 15 (2011) 2301–2307.
S. Singh and N. Kumar, Combined rotor fault diagnosis in rotating machinery using empirical mode decomposition, J. of Mechanical Science and Technology, 28 (12) (2014) 4869–4876.
D. Han, N. Zhao and P. Shi, Gear fault feature extraction and diagnosis method under different load excitation based on EMD, PSO-SVM and fractal box dimension, J. of Mechanical Science and Technology, 33 (2) (2019) 487–494.
Q. He, Y. Liu and F. Kong, Machine fault signature analysis by midpoint-based empirical mode decomposition, Measurement Science and Technology, 22 015702 (2011) 1–11.
B. Liu, S. Riemenschneider and Y. Xu, Gearbox fault diagnosis using empirical mode decomposition and Hilbert spectrum, Mechanical Systems and Signal Processing, 20 (2006) 718–734.
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