[1]LI Yongbo, XU Minqiang, WANG Rixin, et al. A Fault Diagnosis Scheme for Rolling Bearing Based on Local Mean Decomposition and Improved Multiscale Fuzzy Entropy[J]. Journal of Sound and Vibration, 2016,360:277-299.
[2]赵志宏. 基于振动信号的机械故障特征提取与诊断研究[D]. 北京:北京交通大学,2012.
ZHAO Zhihong. Research on Vibration Signal Based Machinery Fault Feature Extraction and Diagnosis [D]. Beijing: Beijing Jiaotong University, 2012.
[3]钟先友. 旋转机械故障诊断的时频分析方法及其应用研究[D]. 武汉:武汉科技大学, 2014.
ZHONG Xianyou. Research on Time-frequency Analysis Methods and Its Applications to Rotating Machinery Fault Diagnosis[D]. Wuhan:Wuhan University of Science and Technology, 2014.
[4]GILLES J. Empirical Wavelet Transform [J]. IEEE Transactions on Signal Processing, 2013, 61(16): 3999-4010.
[5]黄建,胡晓光,巩玉楠.基于经验模态分解的高压断路器机械故障诊断方法[J]. 中国电机工程学报,2011,31(12):108-113.
HUANG Jian, HU Xiaoguang, GONG Yunan. Machinery Fault Diagnosis of High Voltage Circuit Breaker Based on Empirical Mode Decomposition [J]. Proceedings of the CSEE, 2011,31(12):108-113.
[6]时培明, 李庚, 韩东颖. 基于改进EMD的旋转机械耦合故障诊断方法研究[J].中国机械工程, 2013, 24(17): 2367-2372.
SHI Peiming, LI Geng, HAN Dongying. Study on Coupling Faults of Rotary Machinery Diagnosis Method Based on Improved EMD [J]. China Mechanical Engineering, 2013, 24(17): 2367-2372.
[7]DEERING R, KAISER J F. The Use of a Masking Signal to Improve Empirical Mode Decomposition[C]//Acoustics, Speech, and Signal Processing, 2005. Pennsylvania, 2005: 485-488.
[8]全学海, 丁宣浩, 蒋英春. 基于EMD和概率神经网络的说话人识别[J]. 桂林电子科技大学学报, 2012, 30(2): 108-112.
QUAN Xuehai, DING Xuanhao, JIANG Yingchun. Speaker Recognition Based on EMD and Probabilistic Neural Networks [J]. Journal of Guilin University of Electronic Technology, 2012,30(2): 108-112.
[9]WANG Jinliang, LI Zongjun. Extreme-point Symmetric Mode Decomposition Method for Data Analysis[J]. Advances in Adaptive Data Analysis, 2013,5(3):1350015.
[10]LI Huifeng, WANG Jinliang, LI Zongjun . Application of ESMD Method to Air-sea Flux Investigation[J]. International Journal of Geosciences, 2013, 4(5): 8-11.
[11]王金良, 李宗军. 可用于气候数据分析的ESMD方法[J]. 气候变化研究快报, 2014(3): 1-5.
WANG Jinliang, LI Zongjun . The ESMD Method for Climate Data Analysis[J]. Climate Change Research Letters, 2014(3): 1-5.
[12]包红燕. 基于MEMD和条件熵相空间重构的滚动轴承故障诊断[D]. 秦皇岛:燕山大学, 2014.
BAO Hongyan. Rolling Bearing Fault Diagnosis Based on Masking Empirical Mode Decomposition and Phase Space Reconstruction of Conditional Entroy [D]. Qinhuangdao:Yanshan University, 2014.
[13]CHEN Xianyue, ZHOU Jianzhong, XIAO Han. Fault Diagnosis Based on Comprehensive Geometric Characteristic and Probability Neural Network[J]. Applied Mathematics and Computation, 2014, 230(3) : 542-554.
[14]WANG Changqing, ZHOU Jianzhong, QING Hui. Fault Diagnosis Based on Pulse Coupled Neural Network and Probability Neural Network[J]. Expert Systems with Applications, 2011, 38 (11):14207-14313.
[15]刘凤龙, 宋艺. 基于EMD与PNN的机械故障检测[J]. 计算机应用与软件, 2010, 27(9): 237-239.
LIU Fenglong, SONG Yi. Machinery Fault Diagnosis Based on EMD and PNN[J]. Computer Applications and Software, 2010,27(9): 237-239.
[16]孟宗,胡猛,谷伟明,等. 基于LMD多尺度熵和概率神经网络的滚动轴承故障诊断方法[J]. 中国机械工程, 2016, 27(4): 433-437.
MENG Zong, HU Meng, GU Weiming, et al. Rolling Bearing Fault Diagnosis Method Based on LMD Multi-scale Entropy and Probabilistic Neural Network[J]. China Mechanical Engineering, 2016,27(4): 433-437.
[17]肖韬,袁兴中,唐清华,等. 基于概率神经网络的城市湖泊生态系统健康评价研究[J]. 环境科学学报, 2013, 33(11): 3166-3172.
XIAO Tao, YUAN Xingzhong, TANG Qinghua, et al. Investigation of Health Assessment for Urban Lakes System Based on Probabilistic Neural Networks [J]. Acta Scientiae Circumstantiae, 2013, 33(11): 3166-3172. |