基于小波的突变信号识别方法及应用研究  

Mutation Signal Recognition Method Based on Wavelet and Application

作　　者：夏虹[1,2] 陈志辉[2] 邓礼平[2] 黄华 彭敏俊[1] 

机构地区：[1]哈尔滨工程大学核科学与技术学院,黑龙江哈尔滨150001 [2]中国核动力研究设计院核反应堆系统设计技术国家级重点实验室,四川成都610041 [3]中国广东核电有限公司设计公司,广东深圳518031

出　　处：《原子能科学技术》2012年第12期1451-1456,共6页Atomic Energy Science and Technology

基　　金：核反应堆系统设计技术国家级重点实验室基金资助项目(9140C730203)

摘　　要：小波的空间局部性使它能聚焦于信号的局部结构,用来确定信号的突变性位置。但进一步研究发现,小波变换改进的单子带算法虽能有效识别第1类突变点,但对于第2类突变点却无法有效识别,且二进离散小波变换的快速算法还存在频率混淆等问题。通过深入研究提出了引入过渡函数的单子带重构的改进算法,解决了第2类突变信号的准确识别问题,通过相关实验验证了该方法能较好地解决主泵转子刚度突变等信号的有效识别问题。The locality of wavelet makes itself focus on the partial structure of the signal.Therefore,the wavelet transformation can be used to determine the location of mutation of signals such as impulsive noise of machine causing by impulsive vibration.However,further research discovered that the single sub-band algorithm improved from wavelet transformation could recognize the mutation point of the first type effectively,but it could not recognize the mutation of second type,and furthermore,the fast algorithm of binary discrete wavelet transformation has issues such as frequency aliasing.This paper proposed 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 was proved by related experiments.

关 键 词：小波变换 突变信号 频率混淆 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]