基于EEMD的高速列车横向减振器故障的排列熵特征分析

doi:10.11896/j.issn.1002-137X.2016.05.058

Abstract

Abstract: To cope with the status monitoring data characteristics of high-speed train bogie’s lateral damper,this paper proposed an analysis approach of fault characteristics combining EEMD and permutation entropy.The approach is used to do complexity analysis for signals under different time measure.Firstly,EEMD is used to decompose lateral damper’sseven signal status with different number of invalid.Then,permutation entropy is used to measure IMF’s complexity.Finally,support vector machine is used to classify the fault conditions.The experimental result shows that the recognition rate of multi-lateral dampers’ fault can reach to 100% at most,proving the permutation entropy’s effectiveness to signal fault analysis of high-speed train lateral damper.

Key words: Ensemble empirical mode decomposition,Permutation entropy,Lateral damper,High-speed train,Support vector machine

WU Zhi-dan, QIN Na and JIN Wei-dong. Permutation Entropy Fault Feature Analysis Based on Ensemble Empirical Mode Decomposition for Lateral Damper of High-speed Train[J].Computer Science, 2016, 43(5): 304-307.

References

[1] Liu Jian-xin,Wang Kai-yun,Feng Quan-bao,et al.Influence of lateral damper on locomotive riding quality[J].Journal of Traffic and Transportation Engineering,2006,6(3):1-4(in Chinese) 刘建新,王开云,封全保,等.横向减振器对机车平稳性能的影响[J].交通运输工程学报,2006,6(3):1-4
[2] Qin Na,Wang Kai-yun,Jin Wei-dong,et al.Fault feature analysis of high-speed train bogie based on empirical mode decomposition entropy[J].Journal of Traffic and Transportation Engineering,2014,4(1):57-64(in Chinese) 秦娜,王开云,金炜东,等.高速列车转向架故障的经验模态熵特征分析[J].交通运输工程学报,2014,4(1):57-64
[3] Wu Z H,Huang N E.Ensemble empirical mode decomposition:a noise-assisted data analysis method[R].Calverton:Center for Ocean-Land-Atmosphere Studies,2009
[4] Wu Z H,Huang N E.A study of characteristics of white noise using the empirical mode decomposition method[C]∥Procee-dings of the Royal Society,Series A:Mathematical,Physical and Engineering Science.London:The Royal society,2004:1597-1611
[5] Yeh J A,Shieh J S,Huang N E.Complementary ensemble enpicical mode decomposition:a novel noise enhanced data analysis method[J].Advances in Adaptive Data Analysis,2010,2(2):135-156
[6] Hong H,Zhu X H,Su W M.Detection of time varying pitch in tonal languages:an approach based on ensemble empirical mode decomposition[J].Zhejiang Univ-Sic C,2012,3(2):139-145
[7] Qin Na,Jin Wei-dong,Huang Jin,et al.Feature extraction of high speed train bogie based on ensemble empirical mode decomposition and sample entropy[J].Journal of Southwest Jiaotong University,2014,9(1):27-32(in Chinese) 秦娜,金炜东,黄进,等.基于 EEMD样本熵的高速列车转向架故障特征提取[J].西南交通大学学报,2014,9(1):27-32
[8] Bandt C,Pompe B.Permutation entropy:a natural complexity measure for time series[J].Physical Review Letters,2002,8(17):174102
[9] Zhao Xiao-lei,Ren Ming-rong,Zhang Ya-ting,et al.Nonlinearanalysis of ECG signal based on permutation entropy[J].Mo-dern Electronic Technology,2010,33(19):90-92(in Chinese) 赵小磊,任明荣,张亚庭,等.基于排列熵的心电信号非线性分析[J].现代电子技术,2010,33(19):90-92
[10] Sun Ke-hui,Tan Guo-qiang,Sheng Li-yuan.Analysis of chaotic pseudo-random sequence complexity based on permutation entropy[J].Computer Engineering and Applications,2008,4(3):47-49(in Chinese) 孙克辉,谈国强,盛利元.基于排列熵算法的混沌伪随机序列复杂性分析[J].计算机工程与应用,2008,4(3):47-49
[11] Feng Fu-zhou,Si Ai-wei,Jiang Peng-cheng.Application in fault prediction of related permutation entropy of wavelet and HMM[J].Journal of Vibration Engineering,2013,6(2):269-276(in Chinese) 冯辅周,司爱威,江鹏程.小波相关排列熵和HMM在故障预测中的应用[J].振动工程学报,2013,6(2):269-276
[12] Feng Fu-zhou,Rao Guo-qiang,Si Ai-wei,et al.Entropy permutation algorithm and its application in the vibration signal detection of mutations[J].Journal of Vibration Engineering,2012,5(2):221-224(in Chinese) 冯辅周,饶国强,司爱威,等.排列熵算法研究及其在振动信号突变检测中的应用[J].振动工程学报,2012,5(2):221-224
[13] He Hui-yan,Sun Yun-qiang,Li Xiao-feng,et al.Frequency ana-lysis of the penetration acceleration signal based on EEMD and Choi-Willians distribution[J].Journal of North University of China(Natural Science),2012,33(5):547-567(in Chinese) 郝慧艳,孙运强,李晓峰,等.基于EEMD和Choi-Willians分布的侵彻加速度信号时频分析[J].中北大学学报(自然科学版),2012,33(5):547-567
[14] Liu Yi-yan,He Shuan-hai,Ju Yong-feng,et al.Trend prediction for a single-degree of freedom structure’s state based on EEMD and SVR[J].Journal of Vibration and Shock,2012,31(5):60-64(in Chinese) 刘义艳,贺栓海,巨永锋,等.基于EEMD和SVR的单自由度结构状态趋势预测[J].振动与冲击,2012,31(5):60-64
[15] Yang J,Zhang Y,Zhu Y.Intelligent fault diagnosis of rolling ele-ment bearing based on SVMs and fractal dimension[J].Mech-anical Systems and Signal Processing,2007,21(5):2012-2024
[16] Liu Yong-bin.Nonlinear signal analysis for rolling bearing condition monitoring and fault diagnosis[D].Hefei:University of Science and Technology of China,2011(in Chinese) 刘永斌.基于非线性信号分析的滚动轴承状态监测诊断研究[D].合肥:中国科学技术大学,2011
[17] Huang Yun-hua,Li Fu,Fu Mao-hai,et al.Influence of lateraldamper place model over metro vehicle on dynamics performance[J].Urban Mass Transit,2010,13(8):39-42(in Chinese) 黄运华,李芾,付茂海,等.横向减振器布置方式对地铁车辆动力学性能的影响[J].城市轨道交通研究,2010,13(8):39-42

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

Permutation Entropy Fault Feature Analysis Based on Ensemble Empirical Mode Decomposition for Lateral Damper of High-speed Train

PDF (PC)

Abstract

Cite this article

share this article

References

Related Articles 0

Metrics

Comments

Recommended 0