Abstract：In order to solve the difficulty in extracting nonlinear fault features, a new feature extraction method based on multiscale entropy and distance evaluation technique is proposed.First, multiscale entropy analysis is performed to extract and characterize detail features over different scales from bearing vibration signals.Second, distance evaluation approach is employed to evaluate the extracted features and select some sensitive features as subsets.The subsets are input into support vector machines for further condition classification and fault identification.Bearing fault diagnosis experiments validate the effectiveness of the proposed method.The experimental results demonstrate that the optimal sensitive feature subsets outperformed the single scale feature, the original feature sets and other random feature subsets in diagnosis accuracy.
［1］王书涛, 李梅梅, 张淑清, 等. 基于多重分形去趋势波动的机械故障诊断新方法［J］. 计量学报, 2012, 33(3): 232-235.
［2］戴桂平. 基于 EMD 近似熵和 DAGSVM 的机械故障诊断［J］. 计量学报, 2010, 31(5): 467-471.
［3］赵志宏,杨绍普. 一种基于样本熵的轴承故障诊断方法［J］. 振动与冲击,2012, 31(6): 136-140,154.
［4］谢平,杜义浩.基于信息熵的裂纹转子动力特征分析与诊断方法［J］.机械工程学报,2009,45 (1):195-199.
［5］Costa M, Goldberger A L, Peng C K. Multiscale Entropy Analysis of Complex Physiologic Time Series ［J］. Physical Review Letters, 2002, 89(6): 1-4.
［6］Lin J L, Liu J Y C, Li C W, et al. Motor Shaft Misalignment Detection Using Multiscale Entropy with Wavelet Denoising［J］. Expert systems with applications, 2010, 37: 7200-7204.
［7］Litak G, Syta A,Rusinek R. Dynamical Changes during Composite Milling: Recurrence and Multiscale Entropy Analysis［J］. Int J Adv Manuf Technol, 2011, 56: 445-453.
［8］Pincus S M. Assessing serial irregularity and its application for health ［J］. Ann N Y Acad Sci, 2002, 954: 245-267.
［9］Yang B S, Han T, An J L. ART-KOHONEN neural network for fault diagnosis of rotating machinery ［J］. Mechanical systems and signal processing, 2004, 18(3): 645-657.
［10］Hsu C, Chang C, Lin C. A practical guide to support vector classification［EB/OL］.http://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf, 2012-9-10.
［11］王冬云, 张文志, 张建刚. 小波包能量谱在滚动轴承故障诊断中的应用［J］. 轴承, 2010, (11): 32-36.
［12］张超, 陈建军, 郭迅. 基于 EMD 能量熵和支持向量机的齿轮故障诊断方法［J］. 振动与冲击, 2010, 29(10): 216-220.
2013, Vol. 34 
