[1] Y. Fu, X. Chen, Y. Liu, C. Son, and Y. Yang. Gearbox fault diagnosis based on multi-sensor and multi-channel decision-level fusion based on SDP.
Applied Sciences, 12(15):7535, 2022. doi:
10.3390/app12157535.
[2] F. Xie, H. Liu, J. Dong, G. Wang, L. Wang, and G. Li. Research on the gearbox fault diagnosis method based on multi-model feature fusion.
Machines, 10(12):1186, 2022. doi:
10.3390/machines10121186.
[3] I. Komorska, K. Olejarczyk, A. Puchalski, M. Wikło, and Z. Wołczyński. Fault diagnosing of cycloidal gear reducer using statistical features of vibration signal and multifractal spectra.
Sensors, 23(3):1645, 2023. doi:
10.3390/s23031645.
[4] R. Król. Analysis of the backlash in the single stage cycloidal gearbox.
Archive of Mechanical Engineering, 69(4):693–711, 2022. doi:
10.24425/ame.2022.141521.
[5] R. Król. Resonance phenomenon in the single stage cycloidal gearbox. Analysis of vibrations at the output shaft as a function of the external sleeves stiffness.
Archive of Mechanical Engineering, 68(3):303–320, 2021. doi:
10.24425/ame.2021.137050.
[6] R. Król and K. Król. Multibody dynamics model of the cycloidal gearbox, implemented in Fortran for analysis of dynamic parameters influenced by the backlash as a design tolerance.
Acta Mechanica et Automatica, 17(2):272–280, 2023. doi:
10.2478/ama-2023-0031.
[7] R. Król. Cycloidal gearbox model for transient analysis implemented in Fortran with constant time step 2nd order integrator. In: A. Puchalski, B.E. Łazarz, F. Chaari, I. Komorska, Z. Zimroz (eds)
Advances in Technical Diagnostics II. ICTD 2022. Applied Condition Monitoring, pp. 63–74, vol. 21. Springer, Cham 2023. doi:
10.1007/978-3-031-31719-4_7.
[8] R. Król. Software for the cycloidal gearbox multibody dynamics analysis, implemented in Fortran. (Purpose: presentation of the results in the scientific article), 2023. doi:
10.5281/ZENODO.7729842.
[9] R. Król. Kinematics and dynamics of the two stage cycloidal gearbox.
AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe, . 19(6):523–527, 2018. doi:
10.24136/atest.2018.125.
[10] K.S. Lin, K. Y. Chan, and J. J. Lee. Kinematic error analysis and tolerance allocation of cycloidal gear reducers.
Mechanism and Machine Theory, 124:73–91, 2018. doi:
10.1016/j.mechmachtheory.2017.12.028.
[11] L.X. Xu, B.K. Chen, and C.Y. Li. Dynamic modelling and contact analysis of bearing-cycloid-pinwheel transmission mechanisms used in joint rotate vector reducers.
Mechanism and Machine Theory, 137:432–458, 2019. doi:
10.1016/j.mechmachtheory.2019.03.035.
[12] Y. Li, K. Feng, X. Liang, and M.J. Zuo. A fault diagnosis method for planetary gearboxes under non-stationary working conditions using improved Vold-Kalman filter and multi-scale sample entropy.
Journal of Sound and Vibration, 439:271–286, 2019. doi:
10.1016/j.jsv.2018.09.054.
[13] S. Schmidt, P.S. Heyns, and J.P. de Villiers. A novelty detection diagnostic methodology for gearboxes operating under fluctuating operating conditions using probabilistic techniques.
Mechanical Systems and Signal Processing, 100:152–166, 2018. doi:
10.1016/j.ymssp.2017.07.032.
[14] Y. Lei, D. Han, J. Lin, and Z. He. Planetary gearbox fault diagnosis using an adaptive stochastic resonance method.
Mechanical Systems and Signal Processing, 38(1):113–124, 2013. doi:
10.1016/j.ymssp.2012.06.021.
[15] Y. Chen, X. Liang, and M. . Zuo. Sparse time series modeling of the baseline vibration from a gearbox under time-varying speed condition.
Mechanical Systems and Signal Processing, 134:106342, 2019. doi:
10.1016/j.ymssp.2019.106342.
[16] G. D’Elia, E. Mucchi, and M. Cocconcelli. On the identification of the angular position of gears for the diagnostics of planetary gearboxes.
Mechanical Systems and Signal Processing, 83:305–320, 2017. doi:
10.1016/j.ymssp.2016.06.016.
[17] X. Chen and Z. Feng. Time-frequency space vector modulus analysis of motor current for planetary gearbox fault diagnosis under variable speed conditions.
Mechanical Systems and Signal Processing, 121:636–654, 2019. doi:
10.1016/j.ymssp.2018.11.049.
[18] S. Schmidt, P.S. Heyns, and K.C. Gryllias. A methodology using the spectral coherence and healthy historical data to perform gearbox fault diagnosis under varying operating conditions.
Applied Acoustics, 158:107038, 2020. doi:
10.1016/j.apacoust.2019.107038.
[19] D. Zhang and D. Yu. Multi-fault diagnosis of gearbox based on resonance-based signal sparse decomposition and comb filter.
Measurement, 103:361–369, 2017. doi:
10.1016/j.measurement.2017.03.006.
[20] C. Wang, H. Li, J. Ou, R. Hu, S. Hu, and A. Liu. Identification of planetary gearbox weak compound fault based on parallel dual-parameter optimized resonance sparse decomposition and improved MOMEDA.
Measurement, 165:108079, 2020. doi:
10.1016/j.measurement.2020.108079.
[21] W. Teng, X. Ding, H. Cheng, C. Han, Y. Liu, and H. Mu. Compound faults diagnosis and analysis for a wind turbine gearbox via a novel vibration model and empirical wavelet transform.
Renewable Energy, 136:393–402, 2019. doi:
10.1016/j.renene.2018.12.094.
[22] D. Abboud, S. Baudin, J. Antoni, D. Rémond, M. Eltabach, and O. Sauvage. The spectral analysis of cyclo-non-stationary signals.
Mechanical Systems and Signal Processing, 75:280–300, 2016. doi:
10.1016/j.ymssp.2015.09.034.
[23] J.M. Morris and R. Peravali. Minimum-bandwidth discrete-time wavelets, Signal Processing, vol. 76, no. 2, pp. 181–193, 1999. doi:
10.1016/S0165-1684(99)00007-9.
[24] R. Król. Software for the cycloidal gearbox multibody dynamics analysis, implemented in Fortran. (Purpose: presentation of the results in the scientific article), 2022. doi:
10.5281/ZENODO.7221146.
[25] P. Flores and H.M. Lankarani.
Contact Force Models for Multibody Dynamics, vol. 226, Springer, 2016. doi:
10.1007/978-3-319-30897-5.
[26] MATLAB documentation,
https://www.mathworks.com/help/signal/ref/mscohere.html.
[27] MATLAB documentation,
https://www.mathworks.com/help/wavelet/ug/wavelet-families-additional-discussion.html.
[28] X. Shi and A.A. Polycarpou. Measurement and modeling of normal contact stiffness and contact damping at the meso scale.
Journal of Vibration and Acoustics, 127(1):52–60, 2005. doi:
10.1115/1.1857920.
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