[1]陈雪峰, 张兴武, 曹宏瑞. 智能主轴状态监测诊断与振动控制研究进展[J]. 机械工程学报, 2018, 54(19):58-69.
CHEN Xuefeng, ZHANG Xingwu, CAO Hongrui. Advances in Condition Monitoring, Diagnosis and Vibration Control of Smart Spindles[J]. Journal of Mechanical Engineering, 2018, 54(19):58-69.
[2]CHEN Shiqian, DU Minggang, PENG Zhike, et al. Fault Diagnosis of Planetary Gearbox under Variable-speed Conditions Using an Improved Adaptive Chirp Mode Decomposition[J]. Journal of Sound and Vibration, 2020, 468:115065.
[3]张文颢, 李永健, 张卫华. 基于K-奇异值分解和层次化分块正交匹配算法的滚动轴承故障诊断[J]. 中国机械工程, 2019, 30(4):32-38.
ZHANG Wenhao, LI Yongjian, ZHANG Weihua. Bearing Fault Diagnosis Based on K-SVD and HBW-OOMP[J]. China Mechanical Engineering, 2019, 30(4):32-38.
[4]PACHORI R B, NISHAD A. Cross-terms Reduction in the Wigner-Ville Distribution Using Tunable-Q Wavelet Transform[J]. Signal Processing, 2016, 120:288-304.
[5]CHAUHAN K, REDDY M V, SODHI, R. A Novel Distribution-level Phasor Estimation Algorithm Using Empirical Wavelet Transform[J]. IEEE Transaction Industrial Electron, 2018,65(10):7984-7995.
[6]LIU Zhiliang, ZUO Mingjian, JIN Yaqiang, et al. Improved Local Mean Decomposition for Modulation Information Mining and Its Application to Machinery Fault Diagnosis[J]. Journal of Sound and Vibration, 2017, 397:266-281.
[7]JIANG Xingxing, SHEN Changqing, SHI Juanjuan, et al. Initial Center Frequency-guided VMD for Fault Diagnosis of Rotating Machines[J]. Journal of Sound and Vibration, 2018, 435:36-55.
[8]李心一, 谢志江, 罗久飞. 加窗插值快速傅里叶变换在滚动轴承故障诊断中的应用[J]. 中国机械工程, 2018, 29(10):1166-1171.
LI Xinyi, XIE Zhijiang, LUO Jiufei. Applications of Windowed Interpolation FFT Algorithm in Rolling Bearing Fault Diagnosis[J]. China Mechanical Engineering, 2018, 29(10):1166-1171.
[9]崔玲丽, 王鑫, 王华庆, 等. 基于改进开关卡尔曼滤波器的轴承特征提取方法[J]. 机械工程学报, 2019, 55(7):44-51.
CUI Lingli, WANG Xin, WANG Huaqing, et al. Feature Extraction of Bearing Fault Based on Improved Switching Kalman Filter[J]. Journal of Mechanical Engineering, 2019, 55(7):44-51.
[10]GU Fengshou, WANG Tie, ALWODAI A, et al. A New Method of Accurate Broken Rotor Bar Diagnosis Based on Modulation Signal Bispectrum Analysis of Motor Current Signals[J]. Mechanical Systems and Signal Processing, 2015, 50/51:400-413.
[11]ZHANG Ruiliang, GU Fengshou, HARAM M, et al. Gear Wear Monitoring by Modulation Signal Bispectrum Based on Motor Current Signal Analysis[J]. Mechanical Systems and Signal Processing, 2017, 94:202-213.
[12]TIAN Xiange, GU J X, REHAB I, et al. A Robust Detector for Rolling Element Bearing Condition Monitoring Based on The Modulation Signal Bispectrum and Its Performance Evaluation against the Kurtogram[J]. Mechanical Systems and Signal Processing, 2018, 100:167-187.
[13]WU Z H, HUANG N E, et al. Ensemble Empirical Mode Decomposition:a Noise-assisted Data Analysis Method[J]. Advances in Adaptive Data Analysis, 2011, 1(1):1-41.
[14]PARK S, KIM S, CHOI J H. Gear Fault Diagnosis Using Transmission Error and Ensemble Empirical Mode Decomposition[J]. Mechanical Systems and Signal Processing, 2018, 108:262-275.
[15]胡茑庆, 陈微鹏, 程哲, 等. 基于经验模态分解和深度卷积神经网络的行星齿轮箱故障诊断方法[J]. 机械工程学报, 2019, 55(7):9-18.
HU Niaoqing, CHEN Weipeng, CHENG Zhe, et al. Fault Diagnosis for Planetary Gearbox Based on EMD and Deep Convolutional Neural Networks[J]. Journal of Mechanical Engineering, 2019, 55(7):9-18.
[16]FU Qiang, JING Bo, HE Pengju, et al. Fault Feature Selection and Diagnosis of Rolling Bearings Based on EEMD and Optimized Elman_AdaBoost Algorithm[J]. IEEE Sensors Journal, 2018, 18(12):5024-5034.
[17]CHEN Xihui, CHENG Gang, SHAN Xianlei, et al. Research of Weak Fault Feature Information Extraction of Planetary Gear Based on Ensemble Empirical Mode Decomposition and Adaptive Stochastic Resonance[J]. Measurement, 2015, 73, 55-67.
[18]LEI Yaguo, ZUO Mingjian. Fault Diagnosis of Rotating Machinery Using an Improved HHT Based on EEMD and Sensitive IMFs[J]. Measurement Science and Technology, 2009, 20:125701.
[19]刘永强, 李翠省, 廖英英. 基于EEMD和自相关函数峰态系数的轴承故障诊断方法[J]. 振动与冲击, 2017, 36(2):111-116.
LIU Yongqiang, LI Cuisheng, LIAO Yingying. Bearing Fault Diagnosis Method Based on EEMD and Autocorrelation Function Peak State Coefficient[J]. Journal of Vibration and Shock, 2017, 36(2):111-116.
[20]OSMAN S, WANG W. A Morphological Hilbert-Huang Transform Technique for Bearing Fault Detection[J]. IEEE Transactions on Instrumentation and Measurement, 2016, 65:2646-2656.
[21]DENG Linfei, ZHAO Rongzhen. Fault Feature Extraction of a Rotor System Based on Local Mean Decomposition and Teager Energy Kurtosis[J]. Journal of Mechanical Science and Technology, 2014, 28(4):1161-1169.
[22]LYU Jingxiang, YU Jianbo. Average Combination Difference Morphological Filters for Fault Feature Extraction of Bearing[J]. Mechanical Systems and Signal Processing, 2018, 100:827-845.
[23]ANTONI J. Fast Computation of the Kurtogram for the Detection of Transient Faults[J]. Mechani-cal Systems and Signal Processing, 2007, 21:108-124.
[24]LI Yifan, LIANG Xihui, ZUO Mingjian. Diagonal Slice Spectrum Assisted Optimal Scale Morphological Filter for Rolling Element Bearing Fault Diagnosis[J]. Mechanical Systems and Signal Processing, 2017, 85:146-161.
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