基于等分符号化序列熵的滚动轴承退化特征提取方法

Method of Extracting Degradation Feature of Rolling Bearing Based on Equalization Symbolic Sequence Entropy

为深入探究岸边集装箱起重机滚动轴承的退化特征,提出一种基于等分符号化序列熵的退化特征提取方法。考虑符号化标准的统一性,该方法以正常状态信号的均方根作为基础,建立统一的基本尺度,同时结合信息熵理论,定量衡量信号符号序列的复杂程度大小。实例分析表明,等分符号序列熵可以准确地衡量非线性时间序列的实际复杂水平,能够敏感地刻画滚动轴承性能退化的全过程,且计算速度快、抗噪能力强,适用于设备在线状态监测与特征分析。

To deeply explore the degradation feature of rolling bearing of quayside container crane,a degradation feature extraction method based on equidistant symbolic sequence entropy is proposed.Considering the unity of symbolization standards,this method is based on the root mean square of normal state signals,establishes a unified basic scale,and combines information entropy theory to quantitatively measure the complexity of signal symbol sequences.Example analysis shows that the equalization symbolic sequence entropy can accurately measure the actual complexity level of nonlinear time series,sensitively depict the entire process of performance degradation of rolling bearings and has fast calculation speed and strong noise resistance.It is suitable for online status monitoring and feature analysis of equipment.