Application of Multifractal Detrended Fluctuation Analysis to Severity Identification of Rolling Bearing Damages
Lin Jinshan1,2;Chen Qian1
1.State Key Laboratory of Mechanics and Control of Mechanical Structures,Nanjing University of Aeronautics and Astronautics, Nanjing,210016
2.Weifang University,Weifang,Shandong,261061
Online:2014-07-10
Published:2014-07-16
Supported by:
Shandong Provincial Natural Science Foundation of China(No. ZR2012EEL07)
Lin Jinshan, Chen Qian. Application of Multifractal Detrended Fluctuation Analysis to Severity Identification of Rolling Bearing Damages[J]. China Mechanical Engineering, 2014, 25(13): 1760-1765.
[1]Randall R B, Antoni J. Rolling Element Bearing Diagnostics—a Tutorial[J]. Mechanical Systems and Signal Processing, 2011, 25(2): 485-520.
[2]Demoura E P,Souto C R,Silva A A,et al. Evaluation of Principal Component Analysis and Neural Network Performance for Bearing Fault Diagnosis from Vibration Signal Processed by RS and DF Analysis[J]. Mechanical Systems and Signal Processing,2011,25(5): 1765-1772.
[3]Lin Jinshan, Chen Qian, Tian Xiange, et al. Fault Diagnosis of Rolling Bearings Using Multifractal Detrended Fluctuation Analysis and Mahalanobis Distance Criterion[C]//Proceedings of the 18th International Conference on Automation & Computing. Leicestershire, UK, 2012:152-157.
[4]郝如江,卢文秀,褚福磊.形态滤波器用于滚动轴承故障信号的特征提取[J]. 中国机械工程,2009,20(2):197-201.
Hao Rujiang, Lu Wenxiu,Chu Fulei. Morphological Filters in Feature Extraction for Rolling Bearing Defect Signals[J]. China Mechanical Engineering, 2009, 20(2): 197-201.
[5]何正嘉,陈进,王太勇,等. 机械故障诊断理论及应用[M].北京:高等教育出版社,2010.
[6]Wang Huaqing,Li Ke,Sun Hao,et al. Feature Extraction Method Based on Pseudo-Wigner-Ville Distribution for Rotational Machinery in Variable Operating Conditions[J].Chinese Journal of Mechanical Engineering,2011,24(4):661-668.
[7]Rafiee J,Rafiee M A,Tse P W. Application of Mother Wavelet Functions for Automatic Gear and Bearing Fault Diagnosis[J]. Expert Systems with Applications,2010, 37(6):4568-4579.
[8]Yu Dejie,Cheng Junsheng,Yang Yu. Fault Diagnosis Approach for Roller Bearings Based on Empirical Mode Decomposition Method and Hilbert Transform[J]. Chinese Journal of Mechanical Engineering,2005,18(2):267-270.
[9]Huang N E,Shen Z,Long S R. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis[J]. Proceedings of the Royal Society of London Series A,1998,454(1971):903-995.
[10]程军圣,张亢,杨宇. 局部均值分解方法及其在滚动轴承故障诊断中的应用[J]. 中国机械工程,2009, 20(22):2711-2717.
Cheng Junsheng, Zhang Kang, Yang Yu. Local Mean Decomposition and Its Application to Roller Bearing Fault Diagnosis[J].China Mechanical Engineering, 2009, 20(22): 2711-2717.
[11]Peng C K,Buldyrev S V,Havlin S,et al. Mosaic Organization of DNA Nucleotides[J]. Physical Review E, 1994, 49(2):1685-1689.
[12]Kantelhardt J W,Zschiegner S A,Koscielny-Bunde E,et al. Multifractal Detrended Fluctuation Analysis of Nonstationary Time Series[J]. Physica A,2002,316(1):87-114.
[13]Zhang Shuqing,Zhao Yuchun,Zhang Liguo,et al. Mechanical Fault Diagnosis Based on Band-phase-randomized Surrogate Data and Multifractal[J]. Chinese Journal of Mechanical Engineering,2011,24(5):885-890.
[14]郝研,王太勇,万剑,等. 基于经验模式分解和广义维数的机械故障诊断[J]. 吉林大学学报(工学版),2012, 42(2):392-396.
Hao Yan,Wang Taiyong,Wan Jian,et al. Mechanical Fault Diagnosis Based on Empirical Mode Decomposition and Generalized Dimension[J]. Journal of Jilin University(Engineering and Technology Edition),2012,42(2):392-396.
[15]Lui Yangqing,Gao Jianmin,Jiang Hongquan,et al. Condition Recognition of Complex Systems Based on Multi-fractal Analysis[C]//Proceedings of IEEE Conference on Annual Reliability and Maintainability Symposium.Lake Buena Vista,New Jersey, 2011:32-37.
[16]唐静远,师奕兵,张伟,等. 非线性模拟电路故障诊断的MF-DFA方法[J]. 计算机辅助设计与图形学学报,2010,22(5):852-857.
Tang Jingyuan,Shi Yibing,Zhang Wei,et al. Nonlinear Analog Circuit Fault Diagnosis Based on MF-DFA Method[J]. Journal of Computer-Aided Design & Computer Graphics,2010,22(5):852-857.
[17]Lin Jinshan, Chen Qian. Fault Diagnosis of Rolling Bearings Based on Multifractal Detrended Fluctuation Analysis and Mahalanobis Distance Criterion[J]. Mechanical Systems and Signal Processing, 2013, 38(2): 515-533.
[18]Mahalanobis P C. On the Generalized Distance in Statistics[J]. Proceedings of the National Institute of Sciences of India,1936,2(1):49-55.
[19]焦李成. 神经网络系统理论[M]. 西安:西安电子科技大学出版社, 1990.
[20]殷震. 基于BP神经网络的电力变压器内部故障诊断方法研究[D]. 天津: 天津大学, 2007.
[21]张学工. 统计学习理论的本质[M]. 北京: 清华大学出版杜, 2000.
[22]Cristianini N, Shawe-Taylor J. 支持向量机导论[M]. 李国正,王猛,曾华军,译. 北京:电子工业出版社,2006.
[23]Sonar R, Deshmukh P R. Multiclass Classification: a Review[J]. International Journal of Computer Science and Mobile Computing, 2014, 3(4): 65-69.
[24]Qian Xiyuan,Gu Gaofeng,Zhou Weixing. Modified Detrended Fluctuation Analysis Based on Empirical Mode Decomposition for the Characterization of Anti-persistent Processes[J]. Physica A,2011,390(23/24):4388-4395.
[25]Moktadir Z,Kraft M,Wensink H. Multifractal Properties of Pyrex and Silicon Surfaces Blasted with Sharp Particles[J]. Physica A,2008,387(8/9):2083-2090.