·916· 工程科学学报，第39卷，第6期 方法的可行性和有效性，并成功诊断了滚动轴承故障， [8]Starck J L,Moudden Y,Bobin J,et al.Morphological component analysis.J Bra-ilian Comput Soe,2005,10(3):31 参考文献 [9]Bobin J,Starck JL,Fadili J M,et al.Morphological component [1]Wang P,Liao M F.Adaptive demodulated resonance technique analysis:an adaptive thresholding strategy.IEEE Trans Image for the rolling bearing fault diagnosis.J Aerospace Power,2005, Process,2007,16(11):2675 20(4):606 [10]Elad M,Starck J L,Querre P,et al.Simultaneous cartoon and (王平，廖明夫。滚动轴承故障诊断中的自适应共振解调技 texture image inpainting using morphological component analysis 术.航空动力学报，2005,20(4)：606) MCA).Appl Comput Harmonic Anal,2005,19(3):340 [2]Yang Y,Yu D J,Cheng JS.A fault diagnosis approach for roller [11]Starck J L,Elad M,Donoho D.Redundant multiscale transforms bearings based on EMD and envelope spectrum.China Mech Eng, and their application for morphological component separation 2004,15(16):1469 Ade Imaging Electron Phys,2004.132:287 (杨宇，于德介，程军圣.基于经验模态分解包络谱的滚动轴 [12]Abrial P,Moudden Y.Starck J L,et al.Morphological compo- 承故障诊断方法.中国机械工程，2004,15(16)：1469) nent analysis and inpainting on the sphere:application in physics [3]Zhao X N,Feng Z P.Fault diagnosis of rolling element bearing and astrophysics.J Fourier Anal Appl,2007,13(6):729 based on ensemble empirical mode decomposition and cross energy [13]Chen X M,Yu D J,Li R.Analysis of gearbox compound fault operator.Chin J Eng,2015,37(Suppl 1):65 vibration signal using morphological component analysis.J Mech (赵晓宁，冯志鹏.基于集合经验模式分解和交叉能量算子的 Eng,2014,50(3):108 滚动轴承故障诊断.工程科学学报，2015,37（增刊1）：65) (陈向民，于德介，李蓉.齿轮箱复合故障振动信号的形态 分量分析.机械工程学报.2014,50(3)：108) [4]Dwyer R.Detection of non-Gaussian signals by frequency domain kurtosis estimation /Acoustics,Speech,and Signal Processing, [14]Chen X M,Yu D J,Li R.Fault diagnosis of rolling bearings IEEE International Conference on ICASSP83.Boston,1983 based on morphological component analysis and envelope spec- [5]Antoni J.Fast computation of the kurtogram for the detection of trum.China Mech Eng,2014,25(8):1047 transient faults.Mech Syst Signal Process,2007,21(1):108 (陈向民，于德介，李蓉.基于形态分量分析和包络谱的轴 [6]Ding K,Huang Z D,Lin H B.A rolling bearing fault diagnosis 承故障诊断.中国机械工程，2014,25(8)：1047) method based on Morlet wavelet and spectral kurtosis.I Vib Eng, [15]Zhang H,Du Z H,Fang Z W,et al.Sparse decomposition 2014,27(1):128 based on aero-engine's bearing fault diagnosis.J Mech Eng, (丁康，黄志东，林慧斌.一种谱峭度和Molt小波的滚动轴 2015,51(1):97 承微弱故障诊断方法.振动工程学报，2014,27(1)：128) (张晗，杜朝辉，方作为，等.基于稀硫分解理论的航空发动 [7] Su W S,Wang F T.Zhang Z X,et al.Application of EMD de- 机轴承故障诊断.机械工程学报，2015,51(1)：97) noising and spectral kurtosis in early fault diagnosis of rolling ele [16]Chen S S,Donoho D L,Saunders M A.Atomic decomposition ment bearings.J Vib Shock,2010,29(3):18 by basis pursuit.SIAM Rev,2006,43(1)129 (苏文胜，王奉涛，张志新，等。ED降噪和谱峭度法在滚动 [17]Ho D,Randall R B.Optimisation of bearing diagnostic tech- 轴承早期故障诊断中的应用.振动与冲击，2010,29(3)： niques using simulated and actual bearing fault signals.Mech 18) Syst Signal Process,2000,14(5):763工程科学学报,第 39 卷,第 6 期 方法的可行性和有效性,并成功诊断了滚动轴承故障. 参 考 文 献 [1] Wang P, Liao M F. Adaptive demodulated resonance technique for the rolling bearing fault diagnosis. J Aerospace Power, 2005, 20(4): 606 (王平, 廖明夫. 滚动轴承故障诊断中的自适应共振解调技 术. 航空动力学报, 2005, 20(4): 606) [2] Yang Y, Yu D J, Cheng J S. A fault diagnosis approach for roller bearings based on EMD and envelope spectrum. China Mech Eng, 2004, 15(16): 1469 (杨宇, 于德介, 程军圣. 基于经验模态分解包络谱的滚动轴 承故障诊断方法. 中国机械工程, 2004, 15(16): 1469) [3] Zhao X N, Feng Z P. Fault diagnosis of rolling element bearing based on ensemble empirical mode decomposition and cross energy operator. Chin J Eng, 2015, 37(Suppl 1): 65 (赵晓宁, 冯志鹏. 基于集合经验模式分解和交叉能量算子的 滚动轴承故障诊断. 工程科学学报, 2015, 37(增刊 1): 65) [4] Dwyer R. Detection of non鄄Gaussian signals by frequency domain kurtosis estimation / / Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP蒺83. Boston, 1983 [5] Antoni J. Fast computation of the kurtogram for the detection of transient faults. Mech Syst Signal Process, 2007, 21(1): 108 [6] Ding K, Huang Z D, Lin H B. A rolling bearing fault diagnosis method based on Morlet wavelet and spectral kurtosis. J Vib Eng, 2014, 27(1):128 (丁康, 黄志东, 林慧斌. 一种谱峭度和 Morlet 小波的滚动轴 承微弱故障诊断方法. 振动工程学报, 2014, 27(1): 128) [7] Su W S, Wang F T, Zhang Z X,et al. Application of EMD de鄄 noising and spectral kurtosis in early fault diagnosis of rolling ele鄄 ment bearings. J Vib Shock, 2010, 29(3): 18 (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. 振动与冲击, 2010, 29 (3 ): 18) [8] Starck J L, Moudden Y, Bobin J, et al. Morphological component analysis. J Brazilian Comput Soc, 2005, 10(3): 31 [9] Bobin J, Starck J L, Fadili J M, et al. Morphological component analysis: an adaptive thresholding strategy. IEEE Trans Image Process, 2007, 16(11): 2675 [10] Elad M, Starck J L, Querre P, et al. Simultaneous cartoon and texture image inpainting using morphological component analysis (MCA). Appl Comput Harmonic Anal, 2005, 19(3): 340 [11] Starck J L, Elad M, Donoho D. Redundant multiscale transforms and their application for morphological component separation. Adv Imaging Electron Phys, 2004, 132: 287 [12] Abrial P, Moudden Y, Starck J L, et al. Morphological compo鄄 nent analysis and inpainting on the sphere: application in physics and astrophysics. J Fourier Anal Appl, 2007, 13(6): 729 [13] Chen X M, Yu D J, Li R. Analysis of gearbox compound fault vibration signal using morphological component analysis. J Mech Eng, 2014, 50(3): 108 (陈向民, 于德介, 李蓉. 齿轮箱复合故障振动信号的形态 分量分析. 机械工程学报, 2014, 50(3): 108) [14] Chen X M, Yu D J, Li R. Fault diagnosis of rolling bearings based on morphological component analysis and envelope spec鄄 trum. China Mech Eng, 2014, 25(8): 1047 (陈向民, 于德介, 李蓉. 基于形态分量分析和包络谱的轴 承故障诊断. 中国机械工程, 2014, 25(8): 1047) [15] Zhang H, Du Z H, Fang Z W, et al. Sparse decomposition based on aero鄄engine爷 s bearing fault diagnosis. J Mech Eng, 2015, 51(1): 97 (张晗, 杜朝辉, 方作为, 等. 基于稀疏分解理论的航空发动 机轴承故障诊断. 机械工程学报, 2015, 51(1): 97) [16] Chen S S, Donoho D L, Saunders M A. Atomic decomposition by basis pursuit. SIAM Rev, 2006, 43(1): 129 [17] Ho D, Randall R B. Optimisation of bearing diagnostic tech鄄 niques using simulated and actual bearing fault signals. Mech Syst Signal Process, 2000, 14(5): 763 ·916·