小波变换在突变信号识别中的应用  

Application of Wavelet Analysis inSignal Singularity Detection

作　　者：陈志辉[1] 夏虹[2] 邬芝胜[1] 邓礼平[1] 黄伟[1] 彭敏俊[2] 黄华[2] 

机构地区：[1]中国核动力研究设计院核反应堆系统设计技术重点实验室,成都610041 [2]哈尔滨工程大学核科学与技术学院,哈尔滨150001

出　　处：《核动力工程》2013年第2期62-67,共6页Nuclear Power Engineering

摘　　要：小波变换具有识别转动机械振动突变信号的特性。小波变换改进的单子带算法能有效识别第一类突变点,但对于第二类突变点却无法有效识别。进一步的研究发现,单子带改进算法对一些不需要的点作置零运算时,由于没有合理的过渡,使得对置零后的信号再进行傅里叶反变换时带入了许多噪音,造成对第二类突变信号无法有效识别。针对该问题,通过引入过渡函数,提出了进一步完善的单子带重构改进算法,解决了第二类突变信号的识别问题,并应用相关实例——泵刚度突变仿真数据进行分析,验证了方法的有效性。The wavelet transformation can be used to determine the location of mutation of signals. However, further research discovered that the single sub-band algorithm improved from wavelet transformation could recognize the singular signal of the first type effectively, but it could not recognize the singular signal of second type. The reason of resulting this problem is that the improved algorithm did not transfer the signal smoothly. This paper proposed the improved single sub-band reconstruction algorithm, and resolved the issue of recognizing the transient signal of the second type by introducing transition functions. The effectiveness of this method has been proved by related experiments.

关 键 词：小波变换 突变信号 过渡函数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]