摘要
替代数据法是准确判定时间序列是否具有混沌特征的一种有效方法,该方法不仅能很好地重构原始时间序列的特性,而且能避免直接识别混沌方法的局限性。应用替代数据法,以关联维数作为混沌判据,对故障齿轮信号进行了混沌特性判别。结果表明,齿轮故障信号存在混沌特征,替代数据法能对其进行准确识别。
The surrogate-data technique, an effective method to clearly identify the chaos in time series, can reconstruct the characteristics of the original data while free of the limitations of the positive identification of chaos. In this paper, the correlation dimension is taken as the chaos identification evidence and the method is used to see whether the given fault gear signal has chaos characteristics. The results indicate that there is chaos in the real given fault gear signal and the surrogate data technique can identify chaos exactly.
出处
《武汉科技大学学报》
CAS
2007年第3期268-269,281,共3页
Journal of Wuhan University of Science and Technology
关键词
替代数据法
关联维数
混沌识别
surrogate-data technique
correlation dimension
chaos identification
