[1]COOLEY C G, PARKER R G.A review of planetary and epicyclic gear dynamics and vibrations research [J].Applied Mechanics Reviews, 2014, 66(4): 1-15.
[2]LIANG X H, ZUO M J, FENG Z P.Dynamic modelling of gearbox faults: A review [J].Mechanical Systems and Signal Processing, 2018, 98: 852-876.
[3]FENG Z P, CHEN X W, LIANG M.Time-frequency demodulation analysis based on iterative generalized demodulation for fault diagnosis of planetary gearbox under nonstationary conditions [J].Mechanical Systems and Signal Processing, 2015, 62/63: 54-74.
[4]FENG Z P, CHEN X W, LIANG M.Joint envelope and frequency order spectrum analysis based on iterative generalized demodulation for planetary gearbox fault diagnosis under nonstationary conditions [J].Mechanical Systems and Signal Processing, 2016, 76/77: 242-264.
[5]CHEN X W, FENG Z P.Iterative generalized time-frequency reassignment for planetary gearbox fault diagnosis under nonstationary conditions [J].Mechanical Systems and Signal Processing, 2016, 80: 429-444.
[6]CHEN X W, FENG Z P.Time-frequency analysis of torsional vibration signals in resonance region for planetary gearbox fault diagnosis under variable speed conditions [J].IEEE Access, 2017, 5: 21918-21926.
[7]FENG K, WANG K S, NI Q.A phase angle based diagnostic scheme to planetary gear faults diagnostics under non-stationary operational conditions [J].Journal of Sound and Vibration, 2017, 408: 190-209.
[8]GUAN Y P, LIANG M, NECSULESCU D S.A velocity synchro-squeezing transform for fault diagnosis of planetary gearboxes under nonstationary conditions [J].Journal of Mechanical Engineering Science, 2017, 231(15): 2868-2884.
[9]HU Y, TU X T, LI F C.Joint high-order synchro-squeezing transform and multi-taper empirical wavelet transform for fault diagnosis of wind turbine planetary gearbox under non-stationary conditions [J].Sensors, 2018, 18: 1-18.
[10]LI Y B, LI G Y, YANG Y T, et al.A fault diagnosis scheme for planetary gearboxes using adaptive multi-scale morphology filter and modified hierarchical permutation entropy [J].Mechanical Systems and Signal Processing, 2017, 105: 319-337.
[11]LIU L B, LIANG X H, ZUO M J.A dependence-based feature vector and its application on planetary gearbox fault classification [J].Journal of Sound and Vibration, 2018, 431: 192-211.
[12]ZHANG K, TANG B P, QIN Y, et al.Fault diagnosis of planetary gearbox using a novel semi-supervised method of multiple association layers networks [J].Mechanical Systems and Signal Processing, 2019, 131: 243-260.
[13]LI Q K, TANG B P, LEI D, et al.Deep balanced domain adaption neural networks for fault diagnosis of planetary gearboxes with limited labelled data [J].Measurement, 2020, 156:1-10.
[14]MAKHZANI A, SHLENS J, JAITLY N.Adversarial auto-encoders, arXiv:1511.05644v2 [cs.LG], 2016.
[15]HONG Y, HWANG U, YOO J.How generative adversarial networks and their variants work: An Overview [J].ACM Computing Surveys, 2019, 52(1): 1-10.
[16]WANG Z R, WANG J, WANG Y R.An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition [J].Neurocomputing, 2018, 310: 213-222.
[17]MAO W, LIU Y M, DING L.Imbalanced fault diagnosis of rolling bearing based on generative adversarial network: a comparative study [J].IEEE Access, 2019, 7: 9515-9530.
[18]WEN L, GAO L, LI X.A new deep transfer learning based on sparse auto-encoder for fault diagnosis [J].IEEE Transactions on Systems Man Cybernetics-systems, 2019, 7(1):136-144.
[19]冯志鹏, 赵镭镭, 褚福磊.行星齿轮箱齿轮局部故障振动频率特征[J].中国电机工程学报, 2013, 33(5):123-126.
FENG Zhipeng,ZHAO Leilei,CHU Fulei.Vibration spectral characteristics of localized gear fault of planetary gearboxes[J].Proc CSEE, 2013, 33(5):123-126.
[20]ZHAO C, FENG Z P.Application of multi-domain sparse features for fault identification of planetary gearbox [J].Measurement, 2017, 104: 169-179.