中文摘要：

提出了一种新的时间序列复杂性度量的方法——多尺度模糊熵（multiscale fuzzy entropy,简称MFE）.多尺度模糊熵是基于模糊熵而定义的.模糊熵作为样本熵的改进,是对时间序列复杂性和无规则程度的度量,而多尺度模糊熵则在模糊熵的基础上引入了尺度因子,是对时间序列在不同尺度因子下复杂性的量度.与样本熵、模糊熵和分形维数等其他表征复杂性的非线性动力学方法相比,多尺度模糊熵包含更多时间模式信息.论文首先介绍了模糊熵和多尺度模糊熵的概念,并将其应用于滚动轴承振动信号复杂性的量度,由此提出了一种基于多尺度模糊熵和支持向量机的滚动轴承故障诊断方法.试验数据分析表明,新提出的方法能有效地提取故障特征,实现故障类型的诊断.

英文摘要：

A new method which is referred as multiscale fuzzy entropy （MFE） is introduced for measuring the complexity of time series.Fuzzy entropy is defined to measure the complexity and irregularity of time series,while multiscale entropy which is based on fuzzy entropy is defined to measure the complexity and irregularity of time series in different scale factors.Compared with sample entropy,fuzzy entropy,fractal dimension or other complexity measure methods of nonlinear dynamics,multiscale fuzzy entropy contains more and deeper information of time series.In this paper,the concepts of fuzzy entropy and multiscale fuzzy entropy are introduced firstly,and then they are used to measure the complexity of the rolling bearing vibration signals.Lastly,a new rolling bearing fault diagnosis approach based on multiscale fuzzy entropy and support vector machine （SVM） is put forward.By analysing experimental data,the results show that the proposed method can differentiate the fault categories of rolling bearings effectively.