机构地区: 南昌大学环境科学与工程学院
出 处: 《南昌大学学报(工科版)》 2005年第3期67-70,共4页
摘 要: 介绍了基于kurtosis最大化准则的自适应Morlet小波分析方法,通过等距改变控制母小波函数时频结构的对应参数得到一系列不同的滤波子小波,对每一个子小波的滤波结果计算其Kurtosis系数,由于该系数对剧变信号尤为敏感,最大值所对应的子小波即为与剧变信号最为接近的子小波。将其应用于处理染噪的周期性脉冲信号,以识别裂纹故障发展的初期征兆。与其它分析方法如离散小波变换和小波降噪进行了比较,结果表明自适应Morlet小波分析方法对于提取噪声中的周期性脉冲是非常有效的。 Introduce an adaptive Morlet wavelet analysis method based on Kurtosis maximization, Achieve a series of daughter wavelet by varying those parameters that influence the time - frequency structure of the mother wavelet, and then calculate the Kurtosis value of each filtering result. Use the daughter wavelet which is corresponding to max Kurtosis to process a periodic impulses signal immersed in noise in order to identify symptom of crack fault. After comparing it with other methods such as DWT and wavelet de -noise, we found that adaptive Morlet wavelet is very effective on extracting periodic impulses from noise.