Hilbert-Huang变换及其在大型汽轮机故障诊断中的应用  

Hilbert-Huang Transformation and It's Application to Large Turbine-generator Units Fault Diagnosis

作　　者：唐贵基[1] 王维珍[1] 胡爱军[1] 田丽洁[1] 

机构地区：[1]华北电力大学机械工程学院,河北保定071003

出　　处：《东方电气评论》2005年第4期210-213,共4页Dongfang Electric Review

摘　　要：信号处理技术是大型汽轮机故障诊断的核心,N.E.Huang等人提出了一种新的信号处理方法——经验模态分解方法(EmpiricalModeDecomposition),简称EMD方法。探讨了利用EMD分析方法以及其对应的Hilbert变换在大型汽轮机故障诊断中进行非平稳信号分析的算法和应用,分析了EMD方法在处理的非平稳数据序列方面的优越性。The core of large turbine-generator units fault diagnosis technology is signal processing. A new method for analyzing nonlinear and non-stationary data was put forwarded at length by N. E. Huang, et al. The key part of this method is “the empirical mode decomposition （EMD）”.The algorithm and application of EMD analysis method and its corresponding Hilbert transform used to analyze the non-stationary data in the fault diagnosis of large turbine-generator units are discuesed. At the same time,the superiority of EMD is presented through analyzing a non-stationary data set.

关 键 词：汽轮机组 非平稳信号 经验模态分解 希尔伯特变换 

分 类 号：TK268[动力工程及工程热物理—动力机械及工程]