[1] 梅宏斌. 滚动轴承振动监测与诊断理论.方法.系统[M]. 北京:机械工业出版社, 1996. MEI Hongbin. Vibration monitoring and diagnosis of rolling bearing[M]. Beijing:China Machine Press, 1996. [2] 王天金,冯志鹏,郝如江,等. 基于Teager能量算子的滚动轴承故障诊断研究[J]. 振动与冲击, 2012, 31(2):1-5. WANG Tianjin, FENG Zhipeng, HAO Rujiang, et al. Fault diagnosis of rolling element bearings based on Teager energy operator[J]. Journal of Vibration and Shock, 2012, 31(2):1-5. [3] 雷亚国,韩冬,林京,等. 自适应随机共振新方法及其在故障诊断过程中的应用[J]. 机械工程学报, 2012, 48(7):62-67. LEI Yaguo, HAN Dong, LIN Jing, et al. New adaptive stochastic resonance method and its application to fault diagnosis[J]. Journal of Mechanical Engineering, 2012, 48(7):62-67. [4] LOH C, WU T, HUANG N. Application of the empirical mode decomposition-Hilbert spectrum method to identify near-fault ground-motion characteristics and structural responses[J]. Bulletin of the Seismological Society of America, 2001, 91(5):1339-1357. [5] 武哲,杨绍普,刘永强. 基于多元经验模态分解的旋转机械早期故障诊断方法[J]. 仪器仪表学报,2016,37(2):241-248. WU Zhe, YANG Shaopu, LIU Yongqiang. Rotating machinery early fault diagnosis method based on multivariate empirical mode decomposition[J]. Chinese Journal of Scientific Instrument, 2016, 37(2):241-248. [6] GILLES J. Empirical wavelet transform[J]. IEEE Transactions on Signal Processing, 2013, 61(16):3999-4010. [7] KEDADOUCHE M, THOMAS M, TAHAN A. A comparative study between empirical wavelet transforms and empirical mode decomposition methods:Application to bearing defect diagnosis[J]. Mechanical Systems and Signal Processing, 2016, 81:88-107. [8] 李志农,朱明,褚福磊,等. 基于经验小波变换的机械故障诊断方法研究[J]. 仪器仪表学报, 2014, 35(11):2423-2432. LI Zhinong, ZHU Ming, CHU Fulei, et al. Mechanical fault diagnosis method based on empirical wavelet transform[J]. Chinese Journal of Scientific Instrument, 2014, 35(11):2423-2432. [9] MAO J, LI H. Gear fault diagnosis Based on empirical wavelet transform[J]. Journal of Residuals Science and Technology, 2016, 13(5):152-157. [10] CAO H, FAN F, et al. Wheel-bearing fault diagnosis of trains using empirical wavelet transform[J]. Measurement, 2016, 82:439-449. [11] 陈学军, 杨永明. 基于经验小波变换的振动信号分析[J]. 太阳能学报, 2017, 38(2):339-346. CHEN Xuejun, YANG Yongming. Analysis of vibration signals based on empirical wavelet transform[J]. Acta Energiae Solaris Sinica, 2017, 38(2):339-346. [12] 陈志新,刘鑫,卢成林,等. 基于经验小波变换的复杂强噪声背景下弱故障检测方法[J]. 农业工程学报, 2016, 32(20):202-208. CHEN Zhixin, LIU Xin, LU Chenglin, et al. Weak fault detection method in complex strong noise condition based on empirical wavelet transform[J]. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(20):202-208. [13] CHEN J, PAN J. Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals[J]. Renewable Energy, 2016, 89:80-92. [14] SHI P, YANG W. An enhanced empirical wavelet transform for features extraction from wind turbine condition monitoring signals[J]. Energies, 2017, 10(7):972-984. [15] 祝文颖, 冯志鹏. 基于改进经验小波变换的行星齿轮箱故障诊断[J]. 仪器仪表学报, 2016, 37(10):2193-2201. ZHU Wenying, FENG Zhipeng. Fault diagnosis of planetary gearbox based on improved empirical wavelet transform[J]. Chinese Journal of Scientific Instrument, 2016, 37(10):2193-2201. [16] GAO Z, LIN J. Bearing fault detection based on empirical wavelet transform and correlated kurtosis by acoustic emission[J]. Materials, 2017, 10(6):571-581. [17] 苏文胜,王奉涛,张志新,等. EMD降噪和谱峭度法在滚动轴承早期故障诊断中的应用[J]. 振动与冲击, 2010, 29(3):18-21. SU Wensheng, WANG Fengtao, ZHANG Zhixin, et al. Application of EMD denoising and spectral kurtosis in early fault diagnosis of rolling element bearings[J]. Journal of Vibration and Shock, 2010, 29(3):18-21. [18] MCDONALD G, ZHAO Q, ZUO M. Maximum correlated kurtosis deconvolution and application on gear tooth chip fault detection[J]. Mechanical Systems and Signal Processing, 2012, 33:237-255. [19] HO D, RANDALL R. Optimisation of bearing diagnostic techniques using simulated and actual bearing fault signals[J]. Mechanical Systems and Signal Processing, 2000, 14(5):763-788. [20] ANTONI J, RANDALL R. A stochastic model for simulation and diagnostics of rolling element bearings with localized faults[J]. Transactions of the ASME, Journal of Vibration and Acoustics, 2003, 125(3):282-289. [21] RANDALL R, ANTONI J, CHOBSAARD S. The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals[J]. Mechanical Systems and Signal Processing, 2001, 15(5):945-962. [22] ANTONI J, RANDALL R. Differential diagnosis of gear and bearing faults[J]. Transactions of the ASME, Journal of Vibration and Acoustics, 2002, 124(2):165-171. |