基于第二代小波及人工免疫的故障诊断  

Fault Diagnosis Based on Second Generation Wavelet and Artificial Immune

作　　者：陶柯[1] 郭俊卿[1] 张帝[2] 

机构地区：[1]沈阳工业大学研究生学院,沈阳110870 [2]沈阳鼓风机集团股份有限公司,沈阳110869

出　　处：《机械工程师》2015年第11期22-23,共2页Mechanical Engineer

摘　　要：针对传统的故障诊断模型无法跟踪故障的动态变化,不能对新型故障进行有效判断的问题,提出了一种有效的故障诊断模式,建立了一种基于第二代小波变换及人工免疫算法的故障诊断模型。该模型是以用第二代小波变换对故障信号降噪为基础,用人工免疫算法对故障信号进行判断处理,与现有的故障类型进行比较,进行故障判断。To solve the problem that the traditional fault dianosis model has no ability of tracking the dynamic changes of the fault and judging the new faults effectively, this paper proposes an effective model of fault diagnosis based on the second generation wavelet and the articicial immune algorithm. This model can reduce the noise of the fault signal based on the second generation wavelet transform and deal with the fault signal using the articial inmune algorithm . It can also distinguish the faults by comparing the fault with the existing faults.

关 键 词：第二代小波变换 人工免疫算法 故障诊断 

分 类 号：TH17[机械工程—机械制造及自动化]