摘要
对基于免疫系统反面算法机理提出的反面算法进行了改进,给出了一种改进型反面选择算法。根据小波分析和人工免疫系统的原理,提出了一种基于小波变换和免疫系统的故障诊断系统。针对小波分析的特点,将其用来对非稳定信号进行分析,获取信号特征向量作为原始数据,利用改进型反面选择算法对原始数据进行己-非己分析。将此系统应用到汽车差速器故障诊断中,取得了良好的效果。
The negative-selection algorithm proposed which is inspired by the negative-selection mechanism of the immune system is able to detect self-nonself. The algorithm is improved according to the theories of wavelet analysis and artifical immune system, a new efficient fault diagnosis system based on the wavelet transform and immune system is presented. In the system the wavelet transform is used to obtain the eigenvectors. The match algorithm uses these eigenvectors to detect oneself or nonself. This system is successfully used in differential mechanism fault diagnosis and it can identify correctly.
出处
《传感技术学报》
CAS
CSCD
北大核心
2006年第3期645-647,651,共4页
Chinese Journal of Sensors and Actuators
关键词
小波
免疫系统
反面选择算法
差速器
故障诊断
wavelet transform
immune system
negative-selection algorithm
differential mechanism
fault diagnosis
